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Su HL, Lai SJ, Tsai KC, Fung KM, Lung TL, Hsu HM, Wu YC, Liu CH, Lai HX, Lin JH, Tseng TS. Structure-guided identification and characterization of potent inhibitors targeting PhoP and MtrA to combat mycobacteria. Comput Struct Biotechnol J 2024; 23:1477-1488. [PMID: 38623562 PMCID: PMC11016868 DOI: 10.1016/j.csbj.2024.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2023] [Revised: 04/01/2024] [Accepted: 04/01/2024] [Indexed: 04/17/2024] Open
Abstract
Mycobacteria are causative agents of tuberculosis (TB), which is a global health concern. Drug-resistant TB strains are rapidly emerging, thereby necessitating the urgent development of new drugs. Two-component signal transduction systems (TCSs) are signaling pathways involved in the regulation of various bacterial behaviors and responses to environmental stimuli. Applying specific inhibitors of TCSs can disrupt bacterial signaling, growth, and virulence, and can help combat drug-resistant TB. We conducted a comprehensive pharmacophore-based inhibitor screening and biochemical and biophysical examinations to identify, characterize, and validate potential inhibitors targeting the response regulators PhoP and MtrA of mycobacteria. The constructed pharmacophore model Phar-PR-n4 identified effective inhibitors of formation of the PhoP-DNA complex: ST132 (IC50 = 29 ± 1.6 µM) and ST166 (IC50 = 18 ± 1.3 µM). ST166 (KD = 18.4 ± 4.3 μM) and ST132 (KD = 14.5 ± 0.1 μM) strongly targeted PhoP in a slow-on, slow-off manner. The inhibitory potency and binding affinity of ST166 and ST132 for MtrAC were comparable to those of PhoP. Structural analyses and molecular dynamics simulations revealed that ST166 and ST132 mainly interact with the α8-helix and C-terminal β-hairpin of PhoP, with functionally essential residue hotspots for structure-based inhibitor optimization. Moreover, ST166 has in vitro antibacterial activity against Macrobacterium marinum. Thus, ST166, with its characteristic 1,2,5,6-tetrathiocane and terminal sulphonic groups, has excellent potential as a candidate for the development of novel antimicrobial agents to combat pathogenic mycobacteria.
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Affiliation(s)
- Han-Li Su
- Department of Emergency Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City 600, Taiwan
| | - Shu-Jung Lai
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
- Research Center for Cancer Biology, China Medical University, Taichung, Taiwan
| | - Keng-Chang Tsai
- National Research Institute of Chinese Medicine, Ministry of Health and Welfare, Taipei, Taiwan
- Ph.D. Program in Medical Biotechnology, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Kit-Man Fung
- Biomedical Translation Research Center (BioTReC), Academia Sinica, Taipei 11529, Taiwan
| | - Tse-Lin Lung
- Institute of Molecular Biology, National Chung Hsing University, Taichung,Taiwan
| | - Hsing-Mien Hsu
- Institute of Molecular Biology, National Chung Hsing University, Taichung,Taiwan
| | - Yi-Chen Wu
- Institute of Molecular Biology, National Chung Hsing University, Taichung,Taiwan
| | - Ching-Hui Liu
- Institute of Molecular Biology, National Chung Hsing University, Taichung,Taiwan
| | - Hui-Xiang Lai
- Institute of Molecular Biology, National Chung Hsing University, Taichung,Taiwan
| | - Jiun-Han Lin
- Department of Industrial Technology, Ministry of Economic Affairs, Taipei, Taiwan
- Food Industry Research and Development Institute, Hsinchu City, Taiwan
| | - Tien-Sheng Tseng
- Institute of Molecular Biology, National Chung Hsing University, Taichung,Taiwan
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Liu Y, Li C, Li Y, Zhang S, Zhang N, Bian X, Tan S. Ligand-based pharmacophore modelling, structure optimisation, and biological evaluation for the identification of 2-heteroarylthio- N-arylacetamides as novel HSP90 C-terminal inhibitors. J Enzyme Inhib Med Chem 2024; 39:2290912. [PMID: 38083866 DOI: 10.1080/14756366.2023.2290912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 11/29/2023] [Indexed: 12/18/2023] Open
Abstract
Targeting Heat shock protein 90 (HSP90) C-terminus is an important strategy to develop HSP90 inhibitors without inducing heat shock response. The development of C-terminal inhibitors, however, is hampered by a lack of understanding regarding the interaction between the HSP90 C-terminus and the present inhibitors. We collected seven classical and structurally diverse HSP90 C-terminal inhibitors and constructed a ligand-based pharmacophore model. The subsequent virtual screening and structural optimisation led to the identification of 2-heteroarylthio-N-arylacetamides as novel HSP90 C-terminal inhibitors. 9 and 27 exhibited strong antitumour activity in vitro by inhibiting proliferation and inducing apoptosis in multiple cancer cell lines. These compounds disrupted the interaction between HSP90 C-terminus and peptidylprolyl isomerase D, exerting a stronger inhibitory effect than novobiocin. 27 significantly induced the degradation of HSP90 clients without triggering heat shock response. In an in vivo study using 4T1 mice breast cancer models, 9 showed a potent antitumour effect without obvious toxicity.
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Affiliation(s)
- Yajun Liu
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, China
| | - Chenyao Li
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, China
| | - Yajing Li
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, China
| | - Shuming Zhang
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, China
| | - Ning Zhang
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, China
| | - Xiaobo Bian
- Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Shutao Tan
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China
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Deng C, Wang X, Wang T, Liu W, Yuan X, Huang Y, Cao S. Virtual screening and molecular growth guide the design of inhibitors for the influenza virus drug-resistant mutant M2-V27A/S31N. J Biomol Struct Dyn 2024; 42:5253-5267. [PMID: 37424098 DOI: 10.1080/07391102.2023.2233026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 06/09/2023] [Indexed: 07/11/2023]
Abstract
The influenza A virus matrix protein 2 (AM2) protein is a proton-gated, proton-selective ion channel essential for influenza replication that has been identified as an antiviral target. The drug-resistance of the M2-V27A/S31N strain, which has been growing more prevalent in recent years and has the potential to spread globally, prevents current amantadine inhibitors from having the desired impact. In this study, we compiled the most common influenza A virus strains from 2001-2020 from the U.S. National Center for Biotechnology Information database and hypothesized that M2-V27A/S31N would become a common strain. The lead compound ZINC299830590 was screened for M2-V27A/S31N in the ZINC15 database using a pharmacophore model and molecular descriptors. This lead compound was then optimized by molecular growth, which allowed us to identify important amino acid residues and create interactions with them to produce compound 4. Molecular dynamics simulation showed that the complex of compound 4 and M2-V27A/S31N had certain degrees of stability and flexibility. The binding free energy of compound 4 was calculated using the MM/PB(GB)SA method and totaled -106.525 kcal/mol. Finally, physicochemical and pharmacokinetic profiles were predicted using the Absorption, Distribution, Metabolism, Excretion, and Toxicity model, which indicated the good bioavailability of compound 4. These results provide the basis for further in vivo and in vitro studies to demonstrate that compound 4 is a promising drug candidate against M2-V27A/S31N.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Changyong Deng
- Key Laboratory for Green Chemical Process of Ministry of Education, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan, China
| | - Xiaobo Wang
- School of Pharmacy, Xianning Medical College, Hubei University of Science and Technology, Xianning, China
| | - Tangle Wang
- Key Laboratory for Green Chemical Process of Ministry of Education, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan, China
| | - Wei Liu
- Key Laboratory for Green Chemical Process of Ministry of Education, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan, China
| | - Xiaolan Yuan
- Key Laboratory for Green Chemical Process of Ministry of Education, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan, China
| | - Yan Huang
- Key Laboratory for Green Chemical Process of Ministry of Education, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan, China
| | - Shuang Cao
- Key Laboratory for Green Chemical Process of Ministry of Education, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan, China
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4
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Lotfi B, Mebarka O, Khan SU, Htar TT. Pharmacophore-based virtual screening, molecular docking and molecular dynamics studies for the discovery of novel neuraminidase inhibitors. J Biomol Struct Dyn 2024; 42:5308-5320. [PMID: 37334701 DOI: 10.1080/07391102.2023.2225007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
The in silico evaluation of 27 p-aminosalicylic acid derivatives, also referred to as neuraminidase inhibitors was the focus of the current study. To search and predict new potential neuraminidase inhibitors, this study was based on the ligand-based pharmacophore modeling, 3D QSAR, molecular docking, ADMET and MD simulation studies. The data was generated from recently reported inhibitors and divided into two groups, one of these group has 17 compounds for training and the second group has 10 compounds for testing purpose. The generated pharmacophore has known as ADDPR_4 was found statistically significant 3D-QSAR model owing the high trust scores (R2 = 0.974, Q2 = 0.905, RMSE = 0.23). Morever external validation was also employed to evaluate the prediction capacity of the built pharmacophore model (R2pred = 0.905). In addition, in silico ADMET, analyses were employed to evaluate the obtained hits for drug likeness properties. The stability of formed complexes was further evaluated using molecular dynamics. Top two hits showed stable complexes with Neuraminidase based on calculated total binding energy by MM-PBSA.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Bourougaa Lotfi
- Group of Computational and Medicinal Chemistry, LMCE Laboratory, University of Biskra, Biskra, Algeria
| | - Ouassaf Mebarka
- Group of Computational and Medicinal Chemistry, LMCE Laboratory, University of Biskra, Biskra, Algeria
| | - Shafi Ullah Khan
- Product and Process Innovation Department, Qarshi Brands Pvt. Ltd. Hattar Industrial Estate, Haripur, KPK, Pakistan
| | - Thet Thet Htar
- School of Pharmacy, Monash University Malaysia, Jalan Lagoon Selatan, Selangor, Malaysia
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5
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Turgutalp B, Kizil C. Multi-target drugs for Alzheimer's disease. Trends Pharmacol Sci 2024:S0165-6147(24)00097-X. [PMID: 38853102 DOI: 10.1016/j.tips.2024.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Revised: 04/28/2024] [Accepted: 05/09/2024] [Indexed: 06/11/2024]
Abstract
Alzheimer's disease (AD), a leading cause of dementia, increasingly challenges our healthcare systems and society. Traditional therapies aimed at single targets have fallen short owing to the complex, multifactorial nature of AD that necessitates simultaneous targeting of various disease mechanisms for clinical success. Therefore, targeting multiple pathologies at the same time could provide a synergistic therapeutic effect. The identification of new disease targets beyond the classical hallmarks of AD offers a fertile ground for the design of new multi-target drugs (MTDs), and building on existing compounds have the potential to yield in successful disease modifying therapies. This review discusses the evolving landscape of MTDs, focusing on their potential as AD therapeutics. Analysis of past and current trials of compounds with multi-target activity underscores the capacity of MTDs to offer synergistic therapeutic effects, and the flourishing genetic understanding of AD will inform and inspire the development of MTD-based AD therapies.
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Affiliation(s)
- Bengisu Turgutalp
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, Columbia University, 650 West 168th Street, New York, NY 10032, USA; Department of Neurology, Columbia University Irving Medical Center, Columbia University, 710 West 168th Street, New York, NY 10032, USA.
| | - Caghan Kizil
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, Columbia University, 650 West 168th Street, New York, NY 10032, USA; Department of Neurology, Columbia University Irving Medical Center, Columbia University, 710 West 168th Street, New York, NY 10032, USA; Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University Irving Medical Center, Columbia University, 630 West 168th Street, New York, NY, USA.
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6
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Saini RS, Binduhayyim RIH, Gurumurthy V, Alshadidi AAF, Bavabeedu SS, Vyas R, Dermawan D, Naseef PP, Mosaddad SA, Heboyan A. In silico assessment of biocompatibility and toxicity: molecular docking and dynamics simulation of PMMA-based dental materials for interim prosthetic restorations. JOURNAL OF MATERIALS SCIENCE. MATERIALS IN MEDICINE 2024; 35:28. [PMID: 38833196 DOI: 10.1007/s10856-024-06799-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Accepted: 05/09/2024] [Indexed: 06/06/2024]
Abstract
AIM This study aimed to comprehensively assess the biocompatibility and toxicity profiles of poly(methyl methacrylate) (PMMA) and its monomeric unit, methyl methacrylate (MMA), crucial components in dental materials for interim prosthetic restorations. METHODOLOGY Molecular docking was employed to predict the binding affinities, energetics, and steric features of MMA and PMMA with selected receptors involved in bone metabolism and tissue development, including RANKL, Fibronectin, BMP9, NOTCH2, and other related receptors. The HADDOCK standalone version was utilized for docking calculations, employing a Lamarckian genetic algorithm to explore the conformational space of ligand-receptor interactions. Furthermore, molecular dynamics (MD) simulations over 100 nanoseconds were conducted using the GROMACS package to evaluate dynamic actions and structural stability. The LigandScout was utilized for pharmacophore modeling, which employs a shape-based screening approach to identify potential ligand binding sites on protein targets. RESULTS The molecular docking studies elucidated promising interactions between PMMA and MMA with key biomolecular targets relevant to dental applications. MD simulation results provided strong evidence supporting the structural stability of PMMA complexes over time. Pharmacophore modeling highlighted the significance of carbonyl and hydroxyl groups as pharmacophoric features, indicating compounds with favorable biocompatibility profiles. CONCLUSION This study underscores the potential of PMMA in dental applications, emphasizing its structural stability, molecular interactions, and safety considerations. These findings lay a foundation for future advancements in dental biomaterials, guiding the design and optimization of materials for enhanced biocompatibility. Future directions include experimental validation of computational findings and the development of PMMA-based dental materials with improved biocompatibility and clinical performance.
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Affiliation(s)
- Ravinder S Saini
- Department of Dental Technology, COAMS, King Khalid University, Abha, Saudi Arabia
| | | | | | | | - Shashit Shetty Bavabeedu
- Department of Restorative Dentistry, College of Dentistry, King Khalid University, Abha, Saudi Arabia
| | - Rajesh Vyas
- Department of Dental Technology, COAMS, King Khalid University, Abha, Saudi Arabia
| | - Doni Dermawan
- Department of Chemistry, Warsaw University of Technology, Warsaw, Poland
| | | | - Seyed Ali Mosaddad
- Department of Research Analytics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India.
- Student Research Committee, School of Dentistry, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Artak Heboyan
- Department of Research Analytics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India.
- Department of Prosthodontics, Faculty of Stomatology, Yerevan State Medical University after Mkhitar Heratsi, Yerevan, Armenia.
- Department of Prosthodontics, School of Dentistry, Tehran University of Medical Sciences, Tehran, Iran.
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7
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Bhattacharjee A, Kar S, Ojha PK. Unveiling G-protein coupled receptor kinase-5 inhibitors for chronic degenerative diseases: Multilayered prioritization employing explainable machine learning-driven multi-class QSAR, ligand-based pharmacophore and free energy-inspired molecular simulation. Int J Biol Macromol 2024; 269:131784. [PMID: 38697440 DOI: 10.1016/j.ijbiomac.2024.131784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 04/02/2024] [Accepted: 04/21/2024] [Indexed: 05/05/2024]
Abstract
GRK5 holds a pivotal role in cellular signaling pathways, with its overexpression in cardiomyocytes, neuronal cells, and tumor cells strongly associated with various chronic degenerative diseases, which highlights the urgent need for potential inhibitors. In this study, multiclass classification-based QSAR models were developed using diverse machine learning algorithms. These models were built from curated compounds with experimentally derived GRK5 inhibitory activity. Additionally, a pharmacophore model was constructed using active compounds from the dataset. Among the models, the SVM-based approach proved most effective and was initially used to screen DrugBank compounds within the applicability domain. Compounds showing significant GRK5 inhibitory potential underwent evaluation for key pharmacophoric features. Prospective compounds were subjected to molecular docking to assess binding affinity towards GRK5's key active site amino acid residues. Stability at the binding site was analyzed through 200 ns molecular dynamics simulations. MM-GBSA analysis quantified individual free energy components contributing to the total binding energy with respect to binding site residues. Metadynamics analysis, including PCA, FEL, and PDF, provided crucial insights into conformational changes of both apo and holo forms of GRK5 at defined energy states. The study identifies DB02844 (S-Adenosyl-1,8-Diamino-3-Thiooctane) and DB13155 (Esculin) as promising GRK5 inhibitors, warranting further in vitro and in vivo validation studies.
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Affiliation(s)
- Arnab Bhattacharjee
- Drug Discovery and Development Laboratory (DDD Lab), Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India
| | - Supratik Kar
- Chemometrics and Molecular Modeling Laboratory, Department of Chemistry and Physics, Kean University, 1000 Morris Avenue, Union, NJ, 07083, USA
| | - Probir Kumar Ojha
- Drug Discovery and Development Laboratory (DDD Lab), Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India.
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8
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Alsenani F. Unraveling potential neuroprotective mechanisms of herbal medicine for Alzheimer's diseases through comprehensive molecular docking analyses. Saudi J Biol Sci 2024; 31:103998. [PMID: 38681227 PMCID: PMC11053229 DOI: 10.1016/j.sjbs.2024.103998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 04/02/2024] [Accepted: 04/14/2024] [Indexed: 05/01/2024] Open
Abstract
Alzheimer's disease (AD) continues to be a worldwide health concern, demanding innovative therapeutic approaches. This study investigates the neuroprotective potential of herbal compounds by scrutinizing their interactions with Beta-Secretase-1 (BACE1). Through comprehensive molecular docking analyses, three compounds, Masticadienonic acid (ΔG: -9.6 kcal/mol), Hederagenin (ΔG: -9.3 kcal/mol), and Anthocyanins (ΔG: -8.1 kcal/mol), emerge as promising BACE1 ligands, displaying low binding energies and strong affinities. ADME parameter predictions, drug-likeness assessments, and toxicity analyses reveal favorable pharmacokinetic profiles for these compounds. Notably, Masticadienonic Acid exhibits optimal drug-likeness (-3.3736) and negligible toxicity concerns. Hederagenin (drug-likeness: -5.3272) and Anthocyanins (drug-likeness: -6.2041) also demonstrate promising safety profiles. Furthermore, pharmacophore modeling elucidates the compounds' unique interaction landscapes within BACE1's active site. Masticadienonic acid showcases seven hydrophobic interactions and a hydrogen bond acceptor interaction with Thr232. Hederagenin exhibits a specific hydrogen bond acceptor interaction with Trp76, emphasizing its selective binding. Anthocyanins reveal a multifaceted engagement, combining hydrophobic contacts and hydrogen bond interactions with key residues. In conclusion, Masticadienonic acid, Hederagenin, and Anthocyanins stand out as promising candidates for further experimental validation, presenting a synergistic balance of efficacy and safety in combating AD through BACE1 inhibition.
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Affiliation(s)
- Faisal Alsenani
- Department of Pharmaceutical Sciences, College of Pharmacy, Umm Al-Qura University, Makkah 21955, Saudi Arabia
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9
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Shaikh SA, Labhade SR, Kale RR, Pachorkar PY, Meshram RJ, Jain KS, Labhade HS, Boraste DR, More RA, Chobe SS, Ballabh D, Wakchaure SN. Synthesis, Biological and Molecular Docking Studies of Thiazole-Thiadiazole derivatives as potential Anti-Tuberculosis Agents. Chem Biodivers 2024; 21:e202400496. [PMID: 38700369 DOI: 10.1002/cbdv.202400496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 03/31/2024] [Accepted: 04/02/2024] [Indexed: 05/05/2024]
Abstract
Tuberculosis remains a global health threat, with increasing infection rates and mortality despite existing anti-TB drugs. The present work focuses on the research findings regarding the development and evaluation of thiadiazole-linked thiazole derivatives as potential anti-tuberculosis agents. We present the synthesis data and confirm the compound structures using spectroscopic techniques. The current study reports twelve thiazole-thiadiazole compounds (5 a-5 l) for their anti-tuberculosis and related bioactivities. This paper emphasizes compounds 5 g, 5 i, and 5 l, which exhibited promising MIC values, leading to further in silico and interaction analysis. Pharmacophore mapping data included in the present analysis identified tubercular ThyX as potential drug targets. The compounds were evaluated for anti-tubercular activity using standard methods, revealing significant MIC values, particularly compound 5 l, with the best MIC value of 7.1285 μg/ml. Compounds 5 g and 5 i also demonstrated moderate to good MIC values against M. tuberculosis (H37Ra). Structural inspection of the docked poses revealed interactions such as hydrogen bonds, halogen bonds, and interactions containing Pi electron cloud, shedding light on conserved interactions with residues like Arg 95, Cys 43, His 69, and Arg 87 from the tubercular ThyX enzyme.
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Affiliation(s)
- Samin A Shaikh
- Department of Chemistry, Kr. V. N. Naik Shikshan Prasarak Sanstha's Arts, Commerce and Science College, Canada Corner, 422002, Nashik, Maharashtra, India
| | - Shivaji R Labhade
- Department of Chemistry, KTHM College, Gangapur Road, 422002, Nashik, Maharashtra, India
| | - Raju R Kale
- Department of Chemistry, KTHM College, Gangapur Road, 422002, Nashik, Maharashtra, India
| | - Prajakta Y Pachorkar
- Department of Microbiology, KTHM College, Gangapur Road, 422002, Nashik, Maharashtra, India
| | - Rohan J Meshram
- Bioinformatics Centre, Savitribai Phule Pune University, 411007, Pune, Maharashtra, India
| | - Kamlesh S Jain
- Department of Chemistry, Kr. V. N. Naik Shikshan Prasarak Sanstha's Arts, Commerce and Science College, Canada Corner, 422002, Nashik, Maharashtra, India
| | - Hrishikesh S Labhade
- Department of Chemistry, KTHM College, Gangapur Road, 422002, Nashik, Maharashtra, India
| | - Deepak R Boraste
- G. E. Society's, R.N.C Arts, J.D.B Commerce, N.S.C. Science College, Nashik Road, 422101, Nashik, Maharashtra, India
| | - Rahul A More
- Department of Microbiology, Dayanand Science College, 413512, Latur, Maharashtra, India
| | - Santosh S Chobe
- Department of Chemistry, M.G. V's Loknete Vyankatrao Hiray, Arts, Science and Commerce College, Panchavati, 422003, Nashik, Maharashtra, India
| | - Debopriya Ballabh
- Bioinformatics Centre, Savitribai Phule Pune University, 411007, Pune, Maharashtra, India
| | - Satish N Wakchaure
- Department of Synthetic R & D, Delta Finochem Private Limited, Gate No. 350, Village Wadivarhe, Tal-Igatpuri, 422403, Nashik, Maharashtra, India
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10
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Das A, Rajkhowa S, Sinha S, Zaki MEA. Unveiling potential repurposed drug candidates for Plasmodium falciparum through in silico evaluation: A synergy of structure-based approaches, structure prediction, and molecular dynamics simulations. Comput Biol Chem 2024; 110:108048. [PMID: 38471353 DOI: 10.1016/j.compbiolchem.2024.108048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 03/14/2024]
Abstract
The rise of drug resistance in Plasmodium falciparum, rendering current treatments ineffective, has hindered efforts to eliminate malaria. To address this issue, the study employed a combination of Systems Biology approach and a structure-based pharmacophore method to identify a target against P. falciparum. Through text mining, 448 genes were extracted, and it was discovered that plasmepsins, found in the Plasmodium genus, play a crucial role in the parasite's survival. The metabolic pathways of these proteins were determined using the PlasmoDB genomic database and recreated using CellDesigner 4.4.2. To identify a potent target, Plasmepsin V (PF13_0133) was selected and examined for protein-protein interactions (PPIs) using the STRING Database. Topological analysis and global-based methods identified PF13_0133 as having the highest centrality. Moreover, the static protein knockout PPIs demonstrated the essentiality of PF13_0133 in the modeled network. Due to the unavailability of the protein's crystal structure, it was modeled and subjected to a molecular dynamics simulation study. The structure-based pharmacophore modeling utilized the modeled PF13_0133 (PfPMV), generating 10 pharmacophore hypotheses with a library of active and inactive compounds against PfPMV. Through virtual screening, two potential candidates, hesperidin and rutin, were identified as potential drugs which may be repurposed as potential anti-malarial agents.
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Affiliation(s)
- Abhichandan Das
- Centre for Biotechnology and Bioinformatics, Dibrugarh University, Dibrugarh, Assam 786004, India
| | - Sanchaita Rajkhowa
- Centre for Biotechnology and Bioinformatics, Dibrugarh University, Dibrugarh, Assam 786004, India.
| | - Subrata Sinha
- Department of Computational Sciences, Brainware University, Barasat, Kolkata, West Bengal 700125, India
| | - Magdi E A Zaki
- Department of Chemistry, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia
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11
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Chua HM, Moshawih S, Kifli N, Goh HP, Ming LC. Insights into the computer-aided drug design and discovery based on anthraquinone scaffold for cancer treatment: A systematic review. PLoS One 2024; 19:e0301396. [PMID: 38776291 PMCID: PMC11111074 DOI: 10.1371/journal.pone.0301396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 03/14/2024] [Indexed: 05/24/2024] Open
Abstract
BACKGROUND In the search for better anticancer drugs, computer-aided drug design (CADD) techniques play an indispensable role in facilitating the lengthy and costly drug discovery process especially when natural products are involved. Anthraquinone is one of the most widely-recognized natural products with anticancer properties. This review aimed to systematically assess and synthesize evidence on the utilization of CADD techniques centered on the anthraquinone scaffold for cancer treatment. METHODS The conduct and reporting of this review were done in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) 2020 guideline. The protocol was registered in the "International prospective register of systematic reviews" database (PROSPERO: CRD42023432904) and also published recently. The search strategy was designed based on the combination of concept 1 "CADD or virtual screening", concept 2 "anthraquinone" and concept 3 "cancer". The search was executed in PubMed, Scopus, Web of Science and MedRxiv on 30 June 2023. RESULTS Databases searching retrieved a total of 317 records. After deduplication and applying the eligibility criteria, the final review ended up with 32 articles in which 3 articles were found by citation searching. The CADD methods used in the studies were either structure-based alone (69%) or combined with ligand-based methods via parallel (9%) or sequential (22%) approaches. Molecular docking was performed in all studies, with Glide and AutoDock being the most popular commercial and public software used respectively. Protein data bank was used in most studies to retrieve the crystal structure of the targets of interest while the main ligand databases were PubChem and Zinc. The utilization of in-silico techniques has enabled a deeper dive into the structural, biological and pharmacological properties of anthraquinone derivatives, revealing their remarkable anticancer properties in an all-rounded fashion. CONCLUSION By harnessing the power of computational tools and leveraging the natural diversity of anthraquinone compounds, researchers can expedite the development of better drugs to address the unmet medical needs in cancer treatment by improving the treatment outcome for cancer patients.
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Affiliation(s)
- Hui Ming Chua
- PAP Rashidah Sa’adatul Bolkiah Institute of Health Sciences, Universiti Brunei Darussalam, Gadong, Brunei Darussalam
| | - Said Moshawih
- PAP Rashidah Sa’adatul Bolkiah Institute of Health Sciences, Universiti Brunei Darussalam, Gadong, Brunei Darussalam
| | - Nurolaini Kifli
- PAP Rashidah Sa’adatul Bolkiah Institute of Health Sciences, Universiti Brunei Darussalam, Gadong, Brunei Darussalam
| | - Hui Poh Goh
- PAP Rashidah Sa’adatul Bolkiah Institute of Health Sciences, Universiti Brunei Darussalam, Gadong, Brunei Darussalam
| | - Long Chiau Ming
- PAP Rashidah Sa’adatul Bolkiah Institute of Health Sciences, Universiti Brunei Darussalam, Gadong, Brunei Darussalam
- School of Medical and Life Sciences, Sunway University, Bandar Sunway, Malaysia
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12
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de Medeiros WF, Gomes AFT, Aguiar AJFC, de Queiroz JLC, Bezerra IWL, da Silva-Maia JK, Piuvezam G, Morais AHDA. Anti-Obesity Therapeutic Targets Studied In Silico and In Vivo: A Systematic Review. Int J Mol Sci 2024; 25:4699. [PMID: 38731918 PMCID: PMC11083175 DOI: 10.3390/ijms25094699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Revised: 04/12/2024] [Accepted: 04/17/2024] [Indexed: 05/13/2024] Open
Abstract
In the age of information technology and the additional computational search tools and software available, this systematic review aimed to identify potential therapeutic targets for obesity, evaluated in silico and subsequently validated in vivo. The systematic review was initially guided by the research question "What therapeutic targets have been used in in silico analysis for the treatment of obesity?" and structured based on the acronym PECo (P, problem; E, exposure; Co, context). The systematic review protocol was formulated and registered in PROSPERO (CRD42022353808) in accordance with the Preferred Reporting Items Checklist for Systematic Review and Meta-Analysis Protocols (PRISMA-P), and the PRISMA was followed for the systematic review. The studies were selected according to the eligibility criteria, aligned with PECo, in the following databases: PubMed, ScienceDirect, Scopus, Web of Science, BVS, and EMBASE. The search strategy yielded 1142 articles, from which, based on the evaluation criteria, 12 were included in the systematic review. Only seven these articles allowed the identification of both in silico and in vivo reassessed therapeutic targets. Among these targets, five were exclusively experimental, one was exclusively theoretical, and one of the targets presented an experimental portion and a portion obtained by modeling. The predominant methodology used was molecular docking and the most studied target was Human Pancreatic Lipase (HPL) (n = 4). The lack of methodological details resulted in more than 50% of the papers being categorized with an "unclear risk of bias" across eight out of the eleven evaluated criteria. From the current systematic review, it seems evident that integrating in silico methodologies into studies of potential drug targets for the exploration of new therapeutic agents provides an important tool, given the ongoing challenges in controlling obesity.
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Affiliation(s)
- Wendjilla F. de Medeiros
- Nutrition Postgraduate Program, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil; (W.F.d.M.); (A.F.T.G.); (I.W.L.B.); (J.K.d.S.-M.)
| | - Ana Francisca T. Gomes
- Nutrition Postgraduate Program, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil; (W.F.d.M.); (A.F.T.G.); (I.W.L.B.); (J.K.d.S.-M.)
| | - Ana Júlia F. C. Aguiar
- Biochemistry and Molecular Biology Postgraduate Program, Biosciences Center, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil; (A.J.F.C.A.); (J.L.C.d.Q.)
| | - Jaluza Luana C. de Queiroz
- Biochemistry and Molecular Biology Postgraduate Program, Biosciences Center, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil; (A.J.F.C.A.); (J.L.C.d.Q.)
| | - Ingrid Wilza L. Bezerra
- Nutrition Postgraduate Program, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil; (W.F.d.M.); (A.F.T.G.); (I.W.L.B.); (J.K.d.S.-M.)
- Department of Nutrition, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil
| | - Juliana Kelly da Silva-Maia
- Nutrition Postgraduate Program, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil; (W.F.d.M.); (A.F.T.G.); (I.W.L.B.); (J.K.d.S.-M.)
- Department of Nutrition, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil
| | - Grasiela Piuvezam
- Public Health Postgraduate Program, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-400, Brazil;
- Public Health Department, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil
| | - Ana Heloneida de A. Morais
- Nutrition Postgraduate Program, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil; (W.F.d.M.); (A.F.T.G.); (I.W.L.B.); (J.K.d.S.-M.)
- Biochemistry and Molecular Biology Postgraduate Program, Biosciences Center, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil; (A.J.F.C.A.); (J.L.C.d.Q.)
- Department of Nutrition, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil
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13
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Kritsi E, Christodoulou P, Tsiaka T, Georgiadis P, Zervou M. A Computational Approach for the Discovery of Novel DNA Methyltransferase Inhibitors. Curr Issues Mol Biol 2024; 46:3394-3407. [PMID: 38666943 PMCID: PMC11049320 DOI: 10.3390/cimb46040213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/11/2024] [Accepted: 04/13/2024] [Indexed: 04/28/2024] Open
Abstract
Nowadays, the explosion of knowledge in the field of epigenetics has revealed new pathways toward the treatment of multifactorial diseases, rendering the key players of the epigenetic machinery the focus of today's pharmaceutical landscape. Among epigenetic enzymes, DNA methyltransferases (DNMTs) are first studied as inhibition targets for cancer treatment. The increasing clinical interest in DNMTs has led to advanced experimental and computational strategies in the search for novel DNMT inhibitors. Considering the importance of epigenetic targets as a novel and promising pharmaceutical trend, the present study attempted to discover novel inhibitors of natural origin against DNMTs using a combination of structure and ligand-based computational approaches. Particularly, a pharmacophore-based virtual screening was performed, followed by molecular docking and molecular dynamics simulations in order to establish an accurate and robust selection methodology. Our screening protocol prioritized five natural-derived compounds, derivatives of coumarins, flavones, chalcones, benzoic acids, and phenazine, bearing completely diverse chemical scaffolds from FDA-approved "Epi-drugs". Their total DNMT inhibitory activity was evaluated, revealing promising results for the derived hits with an inhibitory activity ranging within 30-45% at 100 µM of the tested compounds.
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Affiliation(s)
- Eftichia Kritsi
- Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vassileos Constantinou Avenue, 11635 Athens, Greece; (P.C.); (T.T.); (P.G.)
| | | | | | | | - Maria Zervou
- Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vassileos Constantinou Avenue, 11635 Athens, Greece; (P.C.); (T.T.); (P.G.)
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14
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Tran XTD, Phan TL, To VT, Tran NVN, Nguyen NNS, Nguyen DNH, Tran NTN, Truong TN. Integration of the Butina algorithm and ensemble learning strategies for the advancement of a pharmacophore ligand-based model: an in silico investigation of apelin agonists. Front Chem 2024; 12:1382319. [PMID: 38690013 PMCID: PMC11058650 DOI: 10.3389/fchem.2024.1382319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 03/18/2024] [Indexed: 05/02/2024] Open
Abstract
Introduction: 3D pharmacophore models describe the ligand's chemical interactions in their bioactive conformation. They offer a simple but sophisticated approach to decipher the chemically encoded ligand information, making them a valuable tool in drug design. Methods: Our research summarized the key studies for applying 3D pharmacophore models in virtual screening for 6,944 compounds of APJ receptor agonists. Recent advances in clustering algorithms and ensemble methods have enabled classical pharmacophore modeling to evolve into more flexible and knowledge-driven techniques. Butina clustering categorizes molecules based on their structural similarity (indicated by the Tanimoto coefficient) to create a structurally diverse training dataset. The learning method combines various individual pharmacophore models into a set of pharmacophore models for pharmacophore space optimization in virtual screening. Results: This approach was evaluated on Apelin datasets and afforded good screening performance, as proven by Receiver Operating Characteristic (AUC score of 0.994 ± 0.007), enrichment factor of (EF1% of 50.07 ± 0.211), Güner-Henry score of 0.956 ± 0.015, and F-measure of 0.911 ± 0.031. Discussion: Although one of the high-scoring models achieved statistically superior results in each dataset (AUC of 0.82; an EF1% of 19.466; GH of 0.131 and F1-score of 0.071), the ensemble learning method including voting and stacking method balanced the shortcomings of each model and passed with close performance measures.
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Affiliation(s)
- Xuan-Truc Dinh Tran
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Tieu-Long Phan
- Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Universität Leipzig, Leipzig, Germany
- Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark
| | - Van-Thinh To
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | | | - Nhu-Ngoc Song Nguyen
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Dong-Nghi Hoang Nguyen
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Ngoc-Tam Nguyen Tran
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Tuyen Ngoc Truong
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
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15
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Zare F, Ataollahi E, Mardaneh P, Sakhteman A, Keshavarz V, Solhjoo A, Emami L. A combination of virtual screening, molecular dynamics simulation, MM/PBSA, ADMET, and DFT calculations to identify a potential DPP4 inhibitor. Sci Rep 2024; 14:7749. [PMID: 38565703 PMCID: PMC10987597 DOI: 10.1038/s41598-024-58485-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 03/29/2024] [Indexed: 04/04/2024] Open
Abstract
DPP4 inhibitors can control glucose homeostasis by increasing the level of GLP-1 incretins hormone due to dipeptidase mimicking. Despite the potent effects of DPP4 inhibitors, these compounds cause unwanted toxicity attributable to their effect on other enzymes. As a result, it seems essential to find novel and DPP4 selective compounds. In this study, we introduce a potent and selective DPP4 inhibitor via structure-based virtual screening, molecular docking, molecular dynamics simulation, MM/PBSA calculations, DFT analysis, and ADMET profile. The screened compounds based on similarity with FDA-approved DPP4 inhibitors were docked towards the DPP4 enzyme. The compound with the highest docking score, ZINC000003015356, was selected. For further considerations, molecular docking studies were performed on selected ligands and FDA-approved drugs for DPP8 and DPP9 enzymes. Molecular dynamics simulation was run during 200 ns and the analysis of RMSD, RMSF, Rg, PCA, and hydrogen bonding were performed. The MD outputs showed stability of the ligand-protein complex compared to available drugs in the market. The total free binding energy obtained for the proposed DPP4 inhibitor was more negative than its co-crystal ligand (N7F). ZINC000003015356 confirmed the role of the five Lipinski rule and also, have low toxicity parameter according to properties. Finally, DFT calculations indicated that this compound is sufficiently soft.
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Affiliation(s)
- Fateme Zare
- Department of Medicinal Chemistry, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Elaheh Ataollahi
- Department of Medicinal Chemistry, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Pegah Mardaneh
- Department of Medicinal Chemistry, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran
- Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Amirhossein Sakhteman
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), 85354, Freising, Germany
| | - Valiollah Keshavarz
- Department of Medicinal Chemistry, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Aida Solhjoo
- Department of Quality Control of Drug Products, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Leila Emami
- Pharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
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16
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Shahab M, de Farias Morais GC, Akash S, Fulco UL, Oliveira JIN, Zheng G, Akter S. A robust computational quest: Discovering potential hits to improve the treatment of pyrazinamide-resistant Mycobacterium tuberculosis. J Cell Mol Med 2024; 28:e18279. [PMID: 38634203 PMCID: PMC11024510 DOI: 10.1111/jcmm.18279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 03/12/2024] [Accepted: 03/18/2024] [Indexed: 04/19/2024] Open
Abstract
The rise of pyrazinamide (PZA)-resistant strains of Mycobacterium tuberculosis (MTB) poses a major challenge to conventional tuberculosis (TB) treatments. PZA, a cornerstone of TB therapy, must be activated by the mycobacterial enzyme pyrazinamidase (PZase) to convert its active form, pyrazinoic acid, which targets the ribosomal protein S1. Resistance, often associated with mutations in the RpsA protein, complicates treatment and highlights a critical gap in the understanding of structural dynamics and mechanisms of resistance, particularly in the context of the G97D mutation. This study utilizes a novel integration of computational techniques, including multiscale biomolecular and molecular dynamics simulations, physicochemical and medicinal chemistry predictions, quantum computations and virtual screening from the ZINC and Chembridge databases, to elucidate the resistance mechanism and identify lead compounds that have the potential to improve treatment outcomes for PZA-resistant MTB, namely ZINC15913786, ZINC20735155, Chem10269711, Chem10279789 and Chem10295790. These computational methods offer a cost-effective, rapid alternative to traditional drug trials by bypassing the need for organic subjects while providing highly accurate insight into the binding sites and efficacy of new drug candidates. The need for rapid and appropriate drug development emphasizes the need for robust computational analysis to justify further validation through in vitro and in vivo experiments.
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Affiliation(s)
- Muhammad Shahab
- State key laboratories of Chemical Resources Engineering Beijing, University of Chemical TechnologyBeijingChina
| | | | - Shopnil Akash
- Department of PharmacyDaffodil International UniversityDhakaBangladesh
| | - Umberto Laino Fulco
- Department of Biophysics and Pharmacology, Bioscience CenterFederal University of Rio Grande do NorteNatalRio Grande do NorteBrazil
| | - Jonas Ivan Nobre Oliveira
- Department of Biophysics and Pharmacology, Bioscience CenterFederal University of Rio Grande do NorteNatalRio Grande do NorteBrazil
| | - Guojun Zheng
- State key laboratories of Chemical Resources Engineering Beijing, University of Chemical TechnologyBeijingChina
| | - Shahina Akter
- Bangladesh Council of Scientific and Industrial ResearchDhakaBangladesh
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17
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Nandi S, Bhaduri S, Das D, Ghosh P, Mandal M, Mitra P. Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence. Mol Pharm 2024; 21:1563-1590. [PMID: 38466810 DOI: 10.1021/acs.molpharmaceut.3c01161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Understanding protein sequence and structure is essential for understanding protein-protein interactions (PPIs), which are essential for many biological processes and diseases. Targeting protein binding hot spots, which regulate signaling and growth, with rational drug design is promising. Rational drug design uses structural data and computational tools to study protein binding sites and protein interfaces to design inhibitors that can change these interactions, thereby potentially leading to therapeutic approaches. Artificial intelligence (AI), such as machine learning (ML) and deep learning (DL), has advanced drug discovery and design by providing computational resources and methods. Quantum chemistry is essential for drug reactivity, toxicology, drug screening, and quantitative structure-activity relationship (QSAR) properties. This review discusses the methodologies and challenges of identifying and characterizing hot spots and binding sites. It also explores the strategies and applications of artificial-intelligence-based rational drug design technologies that target proteins and protein-protein interaction (PPI) binding hot spots. It provides valuable insights for drug design with therapeutic implications. We have also demonstrated the pathological conditions of heat shock protein 27 (HSP27) and matrix metallopoproteinases (MMP2 and MMP9) and designed inhibitors of these proteins using the drug discovery paradigm in a case study on the discovery of drug molecules for cancer treatment. Additionally, the implications of benzothiazole derivatives for anticancer drug design and discovery are deliberated.
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Affiliation(s)
- Suvendu Nandi
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Soumyadeep Bhaduri
- Centre for Computational and Data Sciences, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Debraj Das
- Centre for Computational and Data Sciences, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Priya Ghosh
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Mahitosh Mandal
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Pralay Mitra
- Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
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18
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Tu G, Fu T, Zheng G, Xu B, Gou R, Luo D, Wang P, Xue W. Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives. J Chem Inf Model 2024; 64:1433-1455. [PMID: 38294194 DOI: 10.1021/acs.jcim.3c01736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Solute carrier transporters (SLCs) are a class of important transmembrane proteins that are involved in the transportation of diverse solute ions and small molecules into cells. There are approximately 450 SLCs within the human body, and more than a quarter of them are emerging as attractive therapeutic targets for multiple complex diseases, e.g., depression, cancer, and diabetes. However, only 44 unique transporters (∼9.8% of the SLC superfamily) with 3D structures and specific binding sites have been reported. To design innovative and effective drugs targeting diverse SLCs, there are a number of obstacles that need to be overcome. However, computational chemistry, including physics-based molecular modeling and machine learning- and deep learning-based artificial intelligence (AI), provides an alternative and complementary way to the classical drug discovery approach. Here, we present a comprehensive overview on recent advances and existing challenges of the computational techniques in structure-based drug design of SLCs from three main aspects: (i) characterizing multiple conformations of the proteins during the functional process of transportation, (ii) identifying druggability sites especially the cryptic allosteric ones on the transporters for substrates and drugs binding, and (iii) discovering diverse small molecules or synthetic protein binders targeting the binding sites. This work is expected to provide guidelines for a deep understanding of the structure and function of the SLC superfamily to facilitate rational design of novel modulators of the transporters with the aid of state-of-the-art computational chemistry technologies including artificial intelligence.
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Affiliation(s)
- Gao Tu
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Tingting Fu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | | | - Binbin Xu
- Chengdu Sintanovo Biotechnology Co., Ltd., Chengdu 610200, China
| | - Rongpei Gou
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Ding Luo
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Panpan Wang
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China
| | - Weiwei Xue
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
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19
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Singh S, Yadav S, Cavallo C, Mourya D, Singh I, Kumar V, Shukla S, Shukla P, Chaudhary R, Maurya GP, Müller RLJ, Rohde L, Mishra A, Wolkenhauer O, Gupta S, Tripathi A. Sunset Yellow protects against oxidative damage and exhibits chemoprevention in chemically induced skin cancer model. NPJ Syst Biol Appl 2024; 10:23. [PMID: 38431714 PMCID: PMC10908785 DOI: 10.1038/s41540-024-00349-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 02/09/2024] [Indexed: 03/05/2024] Open
Abstract
Skin cancer and other skin-related inflammatory pathologies are rising due to heightened exposure to environmental pollutants and carcinogens. In this context, natural products and repurposed compounds hold promise as novel therapeutic and preventive agents. Strengthening the skin's antioxidant defense mechanisms is pivotal in neutralizing reactive oxygen species (ROS) and mitigating oxidative stress. Sunset Yellow (SY) exhibits immunomodulatory characteristics, evidenced by its capacity to partially inhibit the secretion of proinflammatory cytokines, regulate immune cell populations, and modulate the activation of lymphocytes. This study aimed to investigate the antioxidant and anti-genotoxic properties of SY using in-silico, in vitro, and physiochemical test systems, and to further explore its potential role in 7,12-dimethylbenz(a) anthracene (DMBA)/ 12-o-tetradecanoylphorbol-13-acetate (TPA)-induced two-stage skin carcinogenesis. In vitro experiments showed that pre-treatment of SY significantly enhanced the cell viability of HaCaT cells when exposed to tertiary-Butyl Hydrogen Peroxide (tBHP). This increase was accompanied by reduced ROS levels, restoration of mitochondrial membrane potential, and notable reduction in DNA damage in (SY + tBHP) treated cells. Mechanistic investigations using DPPH chemical antioxidant activity test and potentiometric titrations confirmed SY's antioxidant properties, with a standard reduction potential (E o ) of 0.211 V. Remarkably, evaluating the effect of topical application of SY in DMBA/TPA-induced two-step skin carcinogenesis model revealed dose-dependent decreases in tumor latency, incidence, yield, and burden over 21-weeks. Furthermore, computational analysis and experimental validations identified GSK3β, KEAP1 and EGFR as putative molecular targets of SY. Collectively, our findings reveal that SY enhances cellular antioxidant defenses, exhibits anti-genotoxic effects, and functions as a promising chemopreventive agent.
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Affiliation(s)
- Saurabh Singh
- Food Toxicology Group, CSIR- Indian Institute of Toxicology Research, 226001, Lucknow, India
- Academy of Scientific and Innovative Research (AcSIR), 201002, Ghaziabad, India
| | - Sarika Yadav
- Food Toxicology Group, CSIR- Indian Institute of Toxicology Research, 226001, Lucknow, India
- Academy of Scientific and Innovative Research (AcSIR), 201002, Ghaziabad, India
| | - Celine Cavallo
- University of Strasbourg, F-67081, Strasbourg, France
- Department of Systems Biology and Bioinformatics, University of Rostock, 18055, Rostock, Germany
| | - Durgesh Mourya
- Academy of Scientific and Innovative Research (AcSIR), 201002, Ghaziabad, India
- Drug and Chemical Toxicology Group (FEST), CSIR- Indian Institute of Toxicology Research, 226001, Lucknow, India
| | - Ishu Singh
- Food Toxicology Group, CSIR- Indian Institute of Toxicology Research, 226001, Lucknow, India
- Academy of Scientific and Innovative Research (AcSIR), 201002, Ghaziabad, India
| | - Vijay Kumar
- Food Toxicology Group, CSIR- Indian Institute of Toxicology Research, 226001, Lucknow, India
- Academy of Scientific and Innovative Research (AcSIR), 201002, Ghaziabad, India
| | - Sachin Shukla
- Food Toxicology Group, CSIR- Indian Institute of Toxicology Research, 226001, Lucknow, India
- Academy of Scientific and Innovative Research (AcSIR), 201002, Ghaziabad, India
| | - Pallavi Shukla
- Division of Microbial Technology, CSIR-National Botanical Research Institute, 226001, Lucknow, India
| | - Romil Chaudhary
- Center for Advanced Studies, Dr APJ Abdul Kalam Technical University, 226031, Lucknow, India
| | - Gyan Prakash Maurya
- Center for Advanced Studies, Dr APJ Abdul Kalam Technical University, 226031, Lucknow, India
| | | | - Lilly Rohde
- Department of Systems Biology and Bioinformatics, University of Rostock, 18055, Rostock, Germany
| | - Aradhana Mishra
- Division of Microbial Technology, CSIR-National Botanical Research Institute, 226001, Lucknow, India
| | - Olaf Wolkenhauer
- Department of Systems Biology and Bioinformatics, University of Rostock, 18055, Rostock, Germany
- Leibniz-Institute for Food Systems Biology at the Technical University of Munich, 85354, Freising, Germany
- Chhattisgarh Swami Vivekananda Technical University, 491107, Bhilai, India
| | - Shailendra Gupta
- Department of Systems Biology and Bioinformatics, University of Rostock, 18055, Rostock, Germany.
- Chhattisgarh Swami Vivekananda Technical University, 491107, Bhilai, India.
| | - Anurag Tripathi
- Food Toxicology Group, CSIR- Indian Institute of Toxicology Research, 226001, Lucknow, India.
- Academy of Scientific and Innovative Research (AcSIR), 201002, Ghaziabad, India.
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Elhadi A, Zhao D, Ali N, Sun F, Zhong S. Multi-method computational evaluation of the inhibitors against leucine-rich repeat kinase 2 G2019S mutant for Parkinson's disease. Mol Divers 2024:10.1007/s11030-024-10808-w. [PMID: 38396210 DOI: 10.1007/s11030-024-10808-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 01/07/2024] [Indexed: 02/25/2024]
Abstract
Leucine-rich repeat kinase 2 G2019S mutant (LRRK2 G2019S) is a potential target for Parkinson's disease therapy. In this work, the computational evaluation of the LRRK2 G2019S inhibitors was conducted via a combined approach which contains a preliminary screening of a large database of compounds via similarity and pharmacophore, a secondary selection via structure-based affinity prediction and molecular docking, and a rescoring treatment for the final selection. MD simulations and MM/GBSA calculations were performed to check the agreement between different prediction methods for these inhibitors. 331 experimental ligands were collected, and 170 were used to build the structure-activity relationship. Eight representative ligand structural models were employed in similarity searching and pharmacophore screening over 14 million compounds. The process for selecting proper molecular descriptors provides a successful sample which can be used as a general strategy in QSAR modelling. The rescoring used in this work presents an alternative useful treatment for ranking and selection.
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Affiliation(s)
- Ahmed Elhadi
- School of Bioengineering, Dalian University of Technology, Dalian, 116024, Liaoning, People's Republic of China
| | - Dan Zhao
- School of Bioengineering, Dalian University of Technology, Dalian, 116024, Liaoning, People's Republic of China
| | - Noman Ali
- School of Bioengineering, Dalian University of Technology, Dalian, 116024, Liaoning, People's Republic of China
| | - Fusheng Sun
- School of Bioengineering, Dalian University of Technology, Dalian, 116024, Liaoning, People's Republic of China
| | - Shijun Zhong
- School of Bioengineering, Dalian University of Technology, Dalian, 116024, Liaoning, People's Republic of China.
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21
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Tripathi T, Singh DB, Tripathi T. Computational resources and chemoinformatics for translational health research. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2024; 139:27-55. [PMID: 38448138 DOI: 10.1016/bs.apcsb.2023.11.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
The integration of computational resources and chemoinformatics has revolutionized translational health research. It has offered a powerful set of tools for accelerating drug discovery. This chapter overviews the computational resources and chemoinformatics methods used in translational health research. The resources and methods can be used to analyze large datasets, identify potential drug candidates, predict drug-target interactions, and optimize treatment regimens. These resources have the potential to transform the drug discovery process and foster personalized medicine research. We discuss insights into their various applications in translational health and emphasize the need for addressing challenges, promoting collaboration, and advancing the field to fully realize the potential of these tools in transforming healthcare.
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Affiliation(s)
- Tripti Tripathi
- Molecular and Structural Biophysics Laboratory, Department of Biochemistry, North-Eastern Hill University, Shillong, India
| | - Dev Bukhsh Singh
- Department of Biotechnology, Siddharth University, Kapilvastu, Siddharth Nagar, India
| | - Timir Tripathi
- Molecular and Structural Biophysics Laboratory, Department of Zoology, North-Eastern Hill University, Shillong, India.
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22
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Aziz S, Waqas M, Naz HF, Halim SA, Jan A, Muhsinah AB, Khan A, Al-Harrasi A. Identification of novel compounds and repurposing of FDA drugs for 1-deoxy-D-xylulose 5-phosphate reductoisomerase enzyme of Plasmodium falciparum to combat malaria resistance. Int J Biol Macromol 2024; 257:128672. [PMID: 38092105 DOI: 10.1016/j.ijbiomac.2023.128672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 11/28/2023] [Accepted: 12/06/2023] [Indexed: 01/27/2024]
Abstract
The rise of Plasmodium falciparum resistance to Artemisinin-based combination therapies (ACTs) is a significant concern in the fight against malaria. This situation calls for the search for novel anti-malarial candidates. 1-deoxy-D-xylulose 5-phosphate reductoisomerase (IspC) is a potential target involved in various cellular processes in P. falciparum (Pf). We screened ∼0.69 billion novel compounds from the ZINC20 library and repurposed ∼1400 FDA drugs using computational drug discovery methods against PfIspC. Following our computational pipeline, we found five novel ZINC20 compounds (Z-2, Z-3, Z-10, Z-13, and Z-14) and three FDA drugs (Aliskiren, Ceftolozane, and Ombitasvir) that showed striking docking energy (ranging from -8.405 to -10.834 kcal/mol), and strong interactions with key binding site residues (Ser269, Ser270, Ser306, Asn311, Lys312, and Met360) of PfIspC. The novel anti-malarial compounds also exhibited favorable pharmacokinetics and physicochemical properties. Furthermore, through molecular dynamics simulation, we observed the stable dynamics of PfIspC-inhibitor complexes and the influence of inhibitor binding on the protein's conformational arrangements. Notably, the binding free energy estimation confirmed high binding affinity (varied from -11.68 to -33.16 kcal/mol) of these compounds for PfIspC. Our findings could contribute to the ongoing efforts in combating malaria and invite experimental-lab researchers for validation.
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Affiliation(s)
- Shahkaar Aziz
- Institute of Biotechnology and Genetic Engineering, The University of Agriculture, Peshawar 25130, Pakistan
| | - Muhammad Waqas
- Department of Biotechnology and Genetic Engineering, Hazara University, Mansehra 21120, Pakistan; Natural and Medical Sciences Research Center, University of Nizwa, Birkat-ul-Mouz, 616 Nizwa, Oman
| | - Hafiza Farah Naz
- Department of Biotechnology, , Quaid-i-Azam University, Islamabad 45320, Pakistan
| | - Sobia Ahsan Halim
- Natural and Medical Sciences Research Center, University of Nizwa, Birkat-ul-Mouz, 616 Nizwa, Oman
| | - Afnan Jan
- Department of Biochemistry, Faculty of Medicine, Umm Al-Qura University, Makkah, Kingdom of Saudi Arabia
| | - Abdullatif Bin Muhsinah
- Department of Pharmacognosy, College of Pharmacy, King Khalid University, Abha 61441, Saudi Arabia
| | - Ajmal Khan
- Natural and Medical Sciences Research Center, University of Nizwa, Birkat-ul-Mouz, 616 Nizwa, Oman.
| | - Ahmed Al-Harrasi
- Natural and Medical Sciences Research Center, University of Nizwa, Birkat-ul-Mouz, 616 Nizwa, Oman.
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23
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Ugrani S. Inhibitor design for TMPRSS2: insights from computational analysis of its backbone hydrogen bonds using a simple descriptor. EUROPEAN BIOPHYSICS JOURNAL : EBJ 2024; 53:27-46. [PMID: 38157015 PMCID: PMC10853362 DOI: 10.1007/s00249-023-01695-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 12/04/2023] [Accepted: 12/07/2023] [Indexed: 01/03/2024]
Abstract
Transmembrane protease serine 2 (TMPRSS2) is an important drug target due to its role in the infection mechanism of coronaviruses including SARS-CoV-2. Current understanding regarding the molecular mechanisms of known inhibitors and insights required for inhibitor design are limited. This study investigates the effect of inhibitor binding on the intramolecular backbone hydrogen bonds (BHBs) of TMPRSS2 using the concept of hydrogen bond wrapping, which is the phenomenon of stabilization of a hydrogen bond in a solvent environment as a result of being surrounded by non-polar groups. A molecular descriptor which quantifies the extent of wrapping around BHBs is introduced for this. First, virtual screening for TMPRSS2 inhibitors is performed by molecular docking using the program DOCK 6 with a Generalized Born surface area (GBSA) scoring function. The docking results are then analyzed using this descriptor and its relationship to the solvent-accessible surface area term ΔGsa of the GBSA score is demonstrated with machine learning regression and principal component analysis. The effect of binding of the inhibitors camostat, nafamostat, and 4-guanidinobenzoic acid (GBA) on the wrapping of important BHBs in TMPRSS2 is also studied using molecular dynamics. For BHBs with a large increase in wrapping groups due to these inhibitors, the radial distribution function of water revealed that certain residues involved in these BHBs, like Gln438, Asp440, and Ser441, undergo preferential desolvation. The findings offer valuable insights into the mechanisms of these inhibitors and may prove useful in the design of new inhibitors.
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Affiliation(s)
- Suraj Ugrani
- Purdue University, West Lafayette, IN, 47907, USA.
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24
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Oselusi SO, Dube P, Odugbemi AI, Akinyede KA, Ilori TL, Egieyeh E, Sibuyi NR, Meyer M, Madiehe AM, Wyckoff GJ, Egieyeh SA. The role and potential of computer-aided drug discovery strategies in the discovery of novel antimicrobials. Comput Biol Med 2024; 169:107927. [PMID: 38184864 DOI: 10.1016/j.compbiomed.2024.107927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 12/25/2023] [Accepted: 01/01/2024] [Indexed: 01/09/2024]
Abstract
Antimicrobial resistance (AMR) has become more of a concern in recent decades, particularly in infections associated with global public health threats. The development of new antibiotics is crucial to ensuring infection control and eradicating AMR. Although drug discovery and development are essential processes in the transformation of a drug candidate from the laboratory to the bedside, they are often very complicated, expensive, and time-consuming. The pharmaceutical sector is continuously innovating strategies to reduce research costs and accelerate the development of new drug candidates. Computer-aided drug discovery (CADD) has emerged as a powerful and promising technology that renews the hope of researchers for the faster identification, design, and development of cheaper, less resource-intensive, and more efficient drug candidates. In this review, we discuss an overview of AMR, the potential, and limitations of CADD in AMR drug discovery, and case studies of the successful application of this technique in the rapid identification of various drug candidates. This review will aid in achieving a better understanding of available CADD techniques in the discovery of novel drug candidates against resistant pathogens and other infectious agents.
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Affiliation(s)
- Samson O Oselusi
- DSI/Mintek Nanotechnology Innovation Centre (NIC), Biolabels Node, Department of Biotechnology, University of the Western Cape, Private Bag X17, Bellville, Cape Town, 7535, South Africa
| | - Phumuzile Dube
- DSI/Mintek Nanotechnology Innovation Centre (NIC), Biolabels Node, Department of Biotechnology, University of the Western Cape, Private Bag X17, Bellville, Cape Town, 7535, South Africa
| | - Adeshina I Odugbemi
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Cape Town, 7535, South Africa
| | - Kolajo A Akinyede
- Department of Science Technology, Biochemistry Unit, The Federal Polytechnic P.M.B.5351, Ado Ekiti, 360231, Nigeria
| | - Tosin L Ilori
- School of Pharmacy, University of the Western Cape, Bellville, Cape Town, 7535, South Africa
| | - Elizabeth Egieyeh
- School of Pharmacy, University of the Western Cape, Bellville, Cape Town, 7535, South Africa
| | - Nicole Rs Sibuyi
- DSI/Mintek Nanotechnology Innovation Centre (NIC), Biolabels Node, Department of Biotechnology, University of the Western Cape, Private Bag X17, Bellville, Cape Town, 7535, South Africa
| | - Mervin Meyer
- DSI/Mintek Nanotechnology Innovation Centre (NIC), Biolabels Node, Department of Biotechnology, University of the Western Cape, Private Bag X17, Bellville, Cape Town, 7535, South Africa
| | - Abram M Madiehe
- DSI/Mintek Nanotechnology Innovation Centre (NIC), Biolabels Node, Department of Biotechnology, University of the Western Cape, Private Bag X17, Bellville, Cape Town, 7535, South Africa
| | - Gerald J Wyckoff
- School of Pharmacy, Division of Pharmacology and Pharmaceutical Sciences, University of Missouri, Kansas City, MO, 64110-2446, United States
| | - Samuel A Egieyeh
- School of Pharmacy, University of the Western Cape, Bellville, Cape Town, 7535, South Africa.
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25
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Chunarkar-Patil P, Kaleem M, Mishra R, Ray S, Ahmad A, Verma D, Bhayye S, Dubey R, Singh HN, Kumar S. Anticancer Drug Discovery Based on Natural Products: From Computational Approaches to Clinical Studies. Biomedicines 2024; 12:201. [PMID: 38255306 PMCID: PMC10813144 DOI: 10.3390/biomedicines12010201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Revised: 01/01/2024] [Accepted: 01/10/2024] [Indexed: 01/24/2024] Open
Abstract
Globally, malignancies cause one out of six mortalities, which is a serious health problem. Cancer therapy has always been challenging, apart from major advances in immunotherapies, stem cell transplantation, targeted therapies, hormonal therapies, precision medicine, and palliative care, and traditional therapies such as surgery, radiation therapy, and chemotherapy. Natural products are integral to the development of innovative anticancer drugs in cancer research, offering the scientific community the possibility of exploring novel natural compounds against cancers. The role of natural products like Vincristine and Vinblastine has been thoroughly implicated in the management of leukemia and Hodgkin's disease. The computational method is the initial key approach in drug discovery, among various approaches. This review investigates the synergy between natural products and computational techniques, and highlights their significance in the drug discovery process. The transition from computational to experimental validation has been highlighted through in vitro and in vivo studies, with examples such as betulinic acid and withaferin A. The path toward therapeutic applications have been demonstrated through clinical studies of compounds such as silvestrol and artemisinin, from preclinical investigations to clinical trials. This article also addresses the challenges and limitations in the development of natural products as potential anti-cancer drugs. Moreover, the integration of deep learning and artificial intelligence with traditional computational drug discovery methods may be useful for enhancing the anticancer potential of natural products.
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Affiliation(s)
- Pritee Chunarkar-Patil
- Department of Bioinformatics, Rajiv Gandhi Institute of IT and Biotechnology, Bharati Vidyapeeth (Deemed to be University), Pune 411046, Maharashtra, India
| | - Mohammed Kaleem
- Department of Pharmacology, Dadasaheb Balpande, College of Pharmacy, Nagpur 440037, Maharashtra, India;
| | - Richa Mishra
- Department of Computer Engineering, Parul University, Ta. Waghodia, Vadodara 391760, Gujarat, India;
| | - Subhasree Ray
- Department of Life Science, Sharda School of Basic Sciences and Research, Greater Noida 201310, Uttar Pradesh, India
| | - Aftab Ahmad
- Health Information Technology Department, The Applied College, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Pharmacovigilance and Medication Safety Unit, Center of Research Excellence for Drug Research and Pharmaceutical Industries, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Devvret Verma
- Department of Biotechnology, Graphic Era (Deemed to be University), Dehradun 248002, Uttarkhand, India;
| | - Sagar Bhayye
- Department of Bioinformatics, Rajiv Gandhi Institute of IT and Biotechnology, Bharati Vidyapeeth (Deemed to be University), Pune 411046, Maharashtra, India
| | - Rajni Dubey
- Division of Cardiology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei 11031, Taiwan
| | - Himanshu Narayan Singh
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Sanjay Kumar
- Biological and Bio-Computational Lab, Department of Life Science, Sharda School of Basic Sciences and Research, Sharda University, Greater Noida 201310, Uttar Pradesh, India
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26
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Rahban M, Joushi S, Bashiri H, Saso L, Sheibani V. Characterization of prevalent tyrosine kinase inhibitors and their challenges in glioblastoma treatment. Front Chem 2024; 11:1325214. [PMID: 38264122 PMCID: PMC10804459 DOI: 10.3389/fchem.2023.1325214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 12/21/2023] [Indexed: 01/25/2024] Open
Abstract
Glioblastoma multiforme (GBM) is a highly aggressive malignant primary tumor in the central nervous system. Despite extensive efforts in radiotherapy, chemotherapy, and neurosurgery, there remains an inadequate level of improvement in treatment outcomes. The development of large-scale genomic and proteomic analysis suggests that GBMs are characterized by transcriptional heterogeneity, which is responsible for therapy resistance. Hence, knowledge about the genetic and epigenetic heterogeneity of GBM is crucial for developing effective treatments for this aggressive form of brain cancer. Tyrosine kinases (TKs) can act as signal transducers, regulate important cellular processes like differentiation, proliferation, apoptosis and metabolism. Therefore, TK inhibitors (TKIs) have been developed to specifically target these kinases. TKIs are categorized into allosteric and non-allosteric inhibitors. Irreversible inhibitors form covalent bonds, which can lead to longer-lasting effects. However, this can also increase the risk of off-target effects and toxicity. The development of TKIs as therapeutics through computer-aided drug design (CADD) and bioinformatic techniques enhance the potential to improve patients' survival rates. Therefore, the continued exploration of TKIs as drug targets is expected to lead to even more effective and specific therapeutics in the future.
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Affiliation(s)
- Mahdie Rahban
- Neuroscience Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran
| | - Sara Joushi
- Neuroscience Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran
| | - Hamideh Bashiri
- Physiology Research Center, Institute of Neuropharmacology, Department of Physiology and Pharmacology, Medical School, Kerman University of Medical Sciences, Kerman, Iran
| | - Luciano Saso
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University, Rome, Italy
| | - Vahid Sheibani
- Neuroscience Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran
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27
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Melancon K, Pliushcheuskaya P, Meiler J, Künze G. Targeting ion channels with ultra-large library screening for hit discovery. Front Mol Neurosci 2024; 16:1336004. [PMID: 38249296 PMCID: PMC10796734 DOI: 10.3389/fnmol.2023.1336004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 12/05/2023] [Indexed: 01/23/2024] Open
Abstract
Ion channels play a crucial role in a variety of physiological and pathological processes, making them attractive targets for drug development in diseases such as diabetes, epilepsy, hypertension, cancer, and chronic pain. Despite the importance of ion channels in drug discovery, the vastness of chemical space and the complexity of ion channels pose significant challenges for identifying drug candidates. The use of in silico methods in drug discovery has dramatically reduced the time and cost of drug development and has the potential to revolutionize the field of medicine. Recent advances in computer hardware and software have enabled the screening of ultra-large compound libraries. Integration of different methods at various scales and dimensions is becoming an inevitable trend in drug development. In this review, we provide an overview of current state-of-the-art computational chemistry methodologies for ultra-large compound library screening and their application to ion channel drug discovery research. We discuss the advantages and limitations of various in silico techniques, including virtual screening, molecular mechanics/dynamics simulations, and machine learning-based approaches. We also highlight several successful applications of computational chemistry methodologies in ion channel drug discovery and provide insights into future directions and challenges in this field.
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Affiliation(s)
- Kortney Melancon
- Department of Chemistry, Vanderbilt University, Nashville, TN, United States
- Center for Structural Biology, Vanderbilt University, Nashville, TN, United States
| | | | - Jens Meiler
- Department of Chemistry, Vanderbilt University, Nashville, TN, United States
- Center for Structural Biology, Vanderbilt University, Nashville, TN, United States
- Medical Faculty, Institute for Drug Discovery, Leipzig University, Leipzig, Germany
- Center for Scalable Data Analytics and Artificial Intelligence, Leipzig University, Leipzig, Germany
| | - Georg Künze
- Medical Faculty, Institute for Drug Discovery, Leipzig University, Leipzig, Germany
- Center for Scalable Data Analytics and Artificial Intelligence, Leipzig University, Leipzig, Germany
- Interdisciplinary Center for Bioinformatics, Leipzig University, Leipzig, Germany
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28
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Singh K, Bhushan B, Singh B. Advances in Drug Discovery and Design using Computer-aided Molecular Modeling. Curr Comput Aided Drug Des 2024; 20:697-710. [PMID: 37711101 DOI: 10.2174/1573409920666230914123005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 08/09/2023] [Accepted: 08/15/2023] [Indexed: 09/16/2023]
Abstract
Computer-aided molecular modeling is a rapidly emerging technology that is being used to accelerate the discovery and design of new drug therapies. It involves the use of computer algorithms and 3D structures of molecules to predict interactions between molecules and their behavior in the body. This has drastically improved the speed and accuracy of drug discovery and design. Additionally, computer-aided molecular modeling has the potential to reduce costs, increase the quality of data, and identify promising targets for drug development. Through the use of sophisticated methods, such as virtual screening, molecular docking, pharmacophore modeling, and quantitative structure-activity relationships, scientists can achieve higher levels of efficacy and safety for new drugs. Moreover, it can be used to understand the activity of known drugs and simplify the process of formulating, optimizing, and predicting the pharmacokinetics of new and existing drugs. In conclusion, computer-aided molecular modeling is an effective tool to rapidly progress drug discovery and design by predicting the interactions between molecules and anticipating the behavior of new drugs in the body.
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Affiliation(s)
- Kuldeep Singh
- Department of Pharmacology, Rajiv Academy for Pharmacy, Mathura Uttar Pradesh, India
| | - Bharat Bhushan
- Department of Pharmacology, Institute of Pharmaceutical Research, GLA University, Mathura Uttar Pradesh, India
| | - Bhoopendra Singh
- Department of Pharmacy, B.S.A. College of Engineering & Technology, Mathura Uttar Pradesh India
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29
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Lavrentaki V, Kousaxidis A, Theodosis-Nobelos P, Papagiouvannis G, Koutsopoulos K, Nicolaou I. Design, synthesis, and pharmacological evaluation of indazole carboxamides of N-substituted pyrrole derivatives as soybean lipoxygenase inhibitors. Mol Divers 2023:10.1007/s11030-023-10775-8. [PMID: 38145424 DOI: 10.1007/s11030-023-10775-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 11/17/2023] [Indexed: 12/26/2023]
Abstract
In this paper, we attempted to develop a novel class of compounds against lipoxygenase, a key enzyme in the biosynthesis of leukotrienes implicated in a series of inflammatory diseases. Given the absence of appropriate human 5-lipoxygenase crystallographic data, solved soybean lipoxygenase-1 and -3 structures were used as a template to generate an accurate pharmacophore model which was further used for virtual screening purposes. Eight compounds (1-8) have been derived from the in-house library consisting of N-substituted pyrroles conjugated with 5- or 6-indazole moieties through a carboxamide linker. This study led to the discovery of hit molecule 8 bearing a naphthyl group with the IC50 value of 22 μM according to soybean lipoxygenase in vitro assay. Isosteric replacement of naphthyl ring with quinoline moieties and reduction of carbonyl carboxamide group resulted in compounds 9-12 and 13, respectively. Compound 12 demonstrated the most promising enzyme inhibition. In addition, compounds 8 and 12 were found to reduce the carrageenan-induced paw edema in vivo by 52.6 and 49.8%, respectively. In view of the encouraging outcomes concerning their notable in vitro and in vivo anti-inflammatory activities, compounds 8 and 12 could be further optimized for the discovery of novel 5-lipoxygenase inhibitors in future. A structure-based 3D pharmacophore model was used in the virtual screening of in-house library to discover novel potential 5-lipoxygenase inhibitors.
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Affiliation(s)
- Vasiliki Lavrentaki
- Department of Pharmaceutical Chemistry, School of Pharmacy, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece
| | - Antonios Kousaxidis
- Department of Pharmaceutical Chemistry, School of Pharmacy, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece
| | | | - Georgios Papagiouvannis
- Department of Pharmacy, School of Health Sciences, Frederick University, 1036, Nicosia, Cyprus
| | | | - Ioannis Nicolaou
- Department of Pharmaceutical Chemistry, School of Pharmacy, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.
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30
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Anggreini P, Kuncoro H, Sumiwi SA, Levita J. Molecular Docking Study of Phytosterols in Lygodium microphyllum Towards SIRT1 and AMPK, the in vitro Brine Shrimp Toxicity Test, and the Phenols and Sterols Levels in the Extract. J Exp Pharmacol 2023; 15:513-527. [PMID: 38148923 PMCID: PMC10751218 DOI: 10.2147/jep.s438435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 12/19/2023] [Indexed: 12/28/2023] Open
Abstract
Background Lygodium microphyllum is a fern plant with various pharmacological activities, and phytosterols were reported contained in the n-hexane and ethyl acetate extract of this plant. Phytosterols are known to inhibit steatosis, oxidative stress, and inflammation. Sirtuin 1 (SIRT1) and adenosine monophosphate-activated protein kinase (AMPK) are the key proteins that control lipogenesis. However, information about L. microphyllum on SIRT1 and AMPK is still lacking. Purpose This study aims to investigate the binding mode of phytosterols in L. microphyllum extract towards AMPK and SIRT1, and the toxicity of the extract against brine shrimp (Artemia salina) larvae, and to determine the phenols and sterols levels in the extract. Methods The molecular docking was performed towards SIRT1 and AMPK using AutoDock v4.2.6, the toxicity of the extract was assayed against brine shrimp (Artemia salina) larvae, and the phytosterols were analyzed by employing a thin layer chromatography densitometry, and the total phenols were by spectrophotometry. Results The molecular docking study revealed that β-sitosterol and stigmasterol could occupy the active allosteric-binding site of SIRT1 and AMPK by binding to important residues similar to the protein's activators. The cold extraction of the plant yields 15.86% w/w. Phytochemical screening revealed the presence of phenols, steroids, flavonoids, alkaloids, and saponins. The total phenols are equivalent to 126 mg gallic acid (GAE)/g dry extract, the total sterols are 954.04 µg/g, and the β-sitosterol level is 283.55 µg/g. The LC50 value of the extract towards A. salina larvae is 203.704 ppm. Conclusion Lygodium microphyllum extract may have the potential to be further explored for its pharmacology activities, particularly in the discovery of plant-based anti-dyslipidemic drug candidates. However, further studies are needed to confirm their roles in alleviating lipid disorders.
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Affiliation(s)
- Putri Anggreini
- Faculty of Pharmacy, Padjadjaran University, Sumedang, 46363, Indonesia
- Faculty of Pharmacy, Mulawarman University, Samarinda, 75119, Indonesia
| | - Hadi Kuncoro
- Faculty of Pharmacy, Mulawarman University, Samarinda, 75119, Indonesia
| | - Sri Adi Sumiwi
- Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Padjadjaran University, Sumedang, 46363, Indonesia
| | - Jutti Levita
- Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Padjadjaran University, Sumedang, 46363, Indonesia
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31
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Faris A, Alnajjar R, Guo J, AL Mughram MH, Aouidate A, Asmari M, Elhallaoui M. Computational 3D Modeling-Based Identification of Inhibitors Targeting Cysteine Covalent Bond Catalysts for JAK3 and CYP3A4 Enzymes in the Treatment of Rheumatoid Arthritis. Molecules 2023; 29:23. [PMID: 38202604 PMCID: PMC10779482 DOI: 10.3390/molecules29010023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/08/2023] [Accepted: 12/14/2023] [Indexed: 01/12/2024] Open
Abstract
This work aimed to find new inhibitors of the CYP3A4 and JAK3 enzymes, which are significant players in autoimmune diseases such as rheumatoid arthritis. Advanced computer-aided drug design techniques, such as pharmacophore and 3D-QSAR modeling, were used. Two strong 3D-QSAR models were created, and their predictive power was validated by the strong correlation (R2 values > 80%) between the predicted and experimental activity. With an ROC value of 0.9, a pharmacophore model grounded in the DHRRR hypothesis likewise demonstrated strong predictive ability. Eight possible inhibitors were found, and six new inhibitors were designed in silico using these computational models. The pharmacokinetic and safety characteristics of these candidates were thoroughly assessed. The possible interactions between the inhibitors and the target enzymes were made clear via molecular docking. Furthermore, MM/GBSA computations and molecular dynamics simulations offered insightful information about the stability of the binding between inhibitors and CYP3A4 or JAK3. Through the integration of various computational approaches, this study successfully identified potential inhibitor candidates for additional investigation and efficiently screened compounds. The findings contribute to our knowledge of enzyme-inhibitor interactions and may help us create more effective treatments for autoimmune conditions like rheumatoid arthritis.
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Affiliation(s)
- Abdelmoujoud Faris
- LIMAS, Department of Chemical Sciences, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco;
| | - Radwan Alnajjar
- Department of Chemistry, Faculty of Science, University of Benghazi, Benghazi 16063, Libya;
- PharmD, Faculty of Pharmacy, Libyan International Medical University, Benghazi 16063, Libya
- Department of Chemistry, University of Cape Town, Rondebosch 7701, South Africa
| | - Jingjing Guo
- Centre in Artificial Intelligence-Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao 999078, China;
| | - Mohammed H. AL Mughram
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Khalid University, Abha 61421, Saudi Arabia; (M.H.A.M.); (M.A.)
| | - Adnane Aouidate
- Laboratory of Organic Chemistry and Physical Chemistry, Team of Molecular Modeling, Materials and Environment, Faculty of Sciences, University Ibn Zohr, Agadir 80060, Morocco;
| | - Mufarreh Asmari
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Khalid University, Abha 61421, Saudi Arabia; (M.H.A.M.); (M.A.)
| | - Menana Elhallaoui
- LIMAS, Department of Chemical Sciences, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco;
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Yamkela M, Sitobo Z, Makhoba XH. In Silico Analysis of SARS-CoV-2 Non-Structural Proteins Reveals an Interaction with the Host's Heat Shock Proteins That May Contribute to Viral Replications and Development. Curr Issues Mol Biol 2023; 45:10225-10247. [PMID: 38132484 PMCID: PMC10742040 DOI: 10.3390/cimb45120638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/15/2023] [Accepted: 11/23/2023] [Indexed: 12/23/2023] Open
Abstract
The non-structural protein 2 (NSP2) is an RNA-binding protein involved in coronavirus genome replication, and it often decreases human immune response to promote viral invasion and development. It is believed that the NSP2 associates itself with polyamines and heat shock proteins inside the host cell to proceed with viral development. This study aimed to investigate how the SARS-CoV-2 virus' key non-structural proteins (NSP2) utilize polyamines and heat shock proteins using a molecular docking approach and molecular dynamics (MD). ClusPro and HADDOCK servers were used for the docking and Discovery Studio, chimera, and PyMOL were used for analysis. Docking of the heat shock proteins 40 (HSP40), 70 (HSP70), and 90 (HSP90) with SARS-CoV-2 NSP2 resulted in 32, 28, and 19 interactions, respectively. Molecular dynamics revealed Arg458, Asn508, Met297, Arg301, and Trp417 as active residues, and pharmacophore modeling indicated ZINC395648, ZINC01150525, and ZINC85324008 from the zinc database as possible inhibitors for this NSP2.
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Affiliation(s)
- Mthembu Yamkela
- Department of Microbiology and Biochemistry, University of Fort Hare, Alice Campus, Alice 5700, South Africa; (M.Y.); (Z.S.)
| | - Zingisa Sitobo
- Department of Microbiology and Biochemistry, University of Fort Hare, Alice Campus, Alice 5700, South Africa; (M.Y.); (Z.S.)
| | - Xolani H. Makhoba
- Department of Life and Consumer Sciences, College of Agriculture and Environmental Sciences, University of South Africa (UNISA), Florida Campus, Roodepoort 1709, South Africa
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Khairullina V, Martynova Y. Quantitative Structure-Activity Relationship in the Series of 5-Ethyluridine, N2-Guanine, and 6-Oxopurine Derivatives with Pronounced Anti-Herpetic Activity. Molecules 2023; 28:7715. [PMID: 38067446 PMCID: PMC10708366 DOI: 10.3390/molecules28237715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 11/10/2023] [Accepted: 11/13/2023] [Indexed: 12/18/2023] Open
Abstract
A quantitative analysis of the relationship between the structure and inhibitory activity against the herpes simplex virus thymidine kinase (HSV-TK) was performed for the series of 5-ethyluridine, N2-guanine, and 6-oxopurines derivatives with pronounced anti-herpetic activity (IC50 = 0.09 ÷ 160,000 μmol/L) using the GUSAR 2019 software. On the basis of the MNA and QNA descriptors and whole-molecule descriptors using the self-consistent regression, 12 statistically significant consensus models for predicting numerical pIC50 values were constructed. These models demonstrated high predictive accuracy for the training and test sets. Molecular fragments of HSV-1 and HSV-2 TK inhibitors that enhance or diminish the anti-herpetic activity are considered. Virtual screening of the ChEMBL database using the developed QSAR models revealed 42 new effective HSV-1 and HSV-2 TK inhibitors. These compounds are promising for further research. The obtained data open up new opportunities for developing novel effective inhibitors of TK.
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Affiliation(s)
- Veronika Khairullina
- Institute of Chemistry and Defence in Emergency Situations, Ufa University of Science and Technology, 50076 Ufa, Russia;
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Najmi A, Alam MS, Thangavel N, Taha MME, Meraya AM, Albratty M, Alhazmi HA, Ahsan W, Haque A, Azam F. Synthesis, molecular docking, and in vivo antidiabetic evaluation of new benzylidene-2,4-thiazolidinediones as partial PPAR-γ agonists. Sci Rep 2023; 13:19869. [PMID: 37963936 PMCID: PMC10645977 DOI: 10.1038/s41598-023-47157-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 11/09/2023] [Indexed: 11/16/2023] Open
Abstract
Peroxisome proliferator-activated receptor-γ (PPAR-γ) partial agonists or antagonists, also termed as selective PPAR-γ modulators, are more beneficial than full agonists because they can avoid the adverse effects associated with PPAR-γ full agonists, such as weight gain and congestive heart disorders, while retaining the antidiabetic efficiency. In this study, we designed and synthesized new benzylidene-thiazolidine-2,4-diones while keeping the acidic thiazolidinedione (TZD) ring at the center, which is in contrast with the typical pharmacophore of PPAR-γ agonists. Five compounds (5a-e) were designed and synthesized in moderate to good yields and were characterized using spectral techniques. The in vivo antidiabetic efficacy of the synthesized compounds was assessed on streptozotocin-induced diabetic mice using standard protocols, and their effect on weight gain was also studied. Molecular docking and molecular dynamics (MD) simulation studies were performed to investigate the binding interactions of the title compounds with the PPAR-γ receptor and to establish their binding mechanism. Antidiabetic activity results revealed that compounds 5d and 5e possess promising antidiabetic activity comparable with the standard drug rosiglitazone. No compound showed considerable effect on the body weight of animals after 21 days of administration, and the findings showed statistical difference (p < 0.05 to p < 0.0001) among the diabetic control and standard drug rosiglitazone groups. In molecular docking study, compounds 5c and 5d exhibited higher binding energies (- 10.1 and - 10.0 kcal/mol, respectively) than the native ligand, non-thiazolidinedione PPAR-γ partial agonist (nTZDpa) (- 9.8 kcal/mol). MD simulation further authenticated the stability of compound 5c-PPAR-γ complex over the 150 ns duration. The RMSD, RMSF, rGyr, SASA, and binding interactions of compound 5c-PPAR-γ complex were comparable to those of native ligand nTZDpa-PPAR-γ complex, suggesting that the title compounds have the potential to be developed as partial PPAR-γ agonists.
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Affiliation(s)
- Asim Najmi
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, P. Box No. 114, Jazan, Saudi Arabia.
| | - Md Shamsher Alam
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, P. Box No. 114, Jazan, Saudi Arabia
| | - Neelaveni Thangavel
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, P. Box No. 114, Jazan, Saudi Arabia
| | - Manal M E Taha
- Substance Abuse and Toxicology Research Centre, Jazan University, P. Box No. 114, Jazan, Saudi Arabia
| | - Abdulkarim M Meraya
- Pharmacy Practice Research Unit, Department of Clinical Pharmacy, College of Pharmacy, Jazan University, Jazan, Saudi Arabia
| | - Mohammed Albratty
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, P. Box No. 114, Jazan, Saudi Arabia
| | - Hassan A Alhazmi
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, P. Box No. 114, Jazan, Saudi Arabia
- Substance Abuse and Toxicology Research Centre, Jazan University, P. Box No. 114, Jazan, Saudi Arabia
- Medical Research Center, Jazan University, Jazan, Saudi Arabia
| | - Waquar Ahsan
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, P. Box No. 114, Jazan, Saudi Arabia
| | - Anzarul Haque
- Department of Pharmaceutics, Buraydah College of Dentistry and Pharmacy, P.O Box 31717, Buraydah, Al-Qassim, Saudi Arabia
| | - Faizul Azam
- Department of Pharmaceutical Chemistry and Pharmacognosy, Unaizah College of Pharmacy, Qassim University, Unaizah, Saudi Arabia
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Jiang W, Chen J, Zhang P, Zheng N, Ma L, Zhang Y, Zhang H. Repurposing Drugs for Inhibition against ALDH2 via a 2D/3D Ligand-Based Similarity Search and Molecular Simulation. Molecules 2023; 28:7325. [PMID: 37959744 PMCID: PMC10650273 DOI: 10.3390/molecules28217325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/22/2023] [Accepted: 10/27/2023] [Indexed: 11/15/2023] Open
Abstract
Aldehyde dehydrogenase-2 (ALDH2) is a crucial enzyme participating in intracellular aldehyde metabolism and is acknowledged as a potential therapeutic target for the treatment of alcohol use disorder and other addictive behaviors. Using previously reported ALDH2 inhibitors of Daidzin, CVT-10216, and CHEMBL114083 as reference molecules, here we perform a ligand-based virtual screening of world-approved drugs via 2D/3D similarity search methods, followed by the assessments of molecular docking, toxicity prediction, molecular simulation, and the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) analysis. The 2D molecular fingerprinting of ECFP4 and FCFP4 and 3D molecule-shape-based USRCAT methods show good performances in selecting compounds with a strong binding behavior with ALDH2. Three compounds of Zeaxanthin (q = 0), Troglitazone (q = 0), and Sequinavir (q = +1 e) are singled out as potential inhibitors; Zeaxanthin can only be hit via USRCAT. These drugs displayed a stronger binding strength compared to the reported potent inhibitor CVT-10216. Sarizotan (q = +1 e) and Netarsudil (q = 0/+1 e) displayed a strong binding strength with ALDH2 as well, whereas they displayed a shallow penetration into the substrate-binding tunnel of ALDH2 and could not fully occupy it. This likely left a space for substrate binding, and thus they were not ideal inhibitors. The MM-PBSA results indicate that the selected negatively charged compounds from the similarity search and Vina scoring are thermodynamically unfavorable, mainly due to electrostatic repulsion with the receptor (q = -6 e for ALDH2). The electrostatic attraction with positively charged compounds, however, yielded very strong binding results with ALDH2. These findings reveal a deficiency in the modeling of electrostatic interactions (in particular, between charged moieties) in the virtual screening via the 2D/3D similarity search and molecular docking with the Vina scoring system.
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Affiliation(s)
| | | | | | | | | | | | - Haiyang Zhang
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing100083, China
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Rana N, Patel D, Parmar M, Mukherjee N, Jha PC, Manhas A. Targeting allosteric binding site in methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) to identify natural product inhibitors via structure-based computational approach. Sci Rep 2023; 13:18090. [PMID: 37872243 PMCID: PMC10593809 DOI: 10.1038/s41598-023-45175-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 10/17/2023] [Indexed: 10/25/2023] Open
Abstract
Cancer has been viewed as one of the deadliest diseases worldwide. Among various types of cancer, breast cancer is the most common type of cancer in women. Methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) is a promising druggable target and is overexpressed in cancerous cells, like, breast cancer. We conducted structure-based modeling on the allosteric site of the enzyme. Targeting the allosteric site avoids the problem of drug resistance. Pharmacophore modeling, molecular docking, HYDE assessment, drug-likeness, ADMET predictions, simulations, and free-energy calculations were performed. The RMSD, RMSF, RoG, SASA, and Hydrogen-bonding studies showed that seven candidates displayed stable behaviour. As per the literature, average superimposed simulated structures revealed a similar protein conformational change in the αE'-βf' loop, causing its displacement away from the allosteric site. The MM-PBSA showed tight binding of six compounds with the allosteric pocket. The effect of inhibitors interacting in the allosteric site causes a decrease in the binding energy of J49 (active-site inhibitor), suggesting the effect of allosteric binding. The PCA and FEL analysis revealed the significance of the docked compounds in the stable behaviour of the complexes. The outcome can contribute to the development of potential natural products with drug-like properties that can inhibit the MTHFD2 enzyme.
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Affiliation(s)
- Nisarg Rana
- Department of Chemistry, School of Energy Technology, Pandit Deendayal Energy University, Gandhinagar, 382426, India
| | - Dhaval Patel
- Department of Industrial Biotechnology, Gujarat Biotechnology University, Gandhinagar, India
| | - Meet Parmar
- Department of Industrial Biotechnology, Gujarat Biotechnology University, Gandhinagar, India
| | - Nandini Mukherjee
- Department of Chemistry, School of Energy Technology, Pandit Deendayal Energy University, Gandhinagar, 382426, India
| | - Prakash C Jha
- School of Applied Material Sciences, Central University of Gujarat, Gandhinagar, 382030, India
| | - Anu Manhas
- Department of Chemistry, School of Energy Technology, Pandit Deendayal Energy University, Gandhinagar, 382426, India.
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37
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Touati I, Abdalla M, Boulaamane Y, Al-Hoshani N, Alouffi A, Britel MR, Maurady A. Identification of novel dual acting ligands targeting the adenosine A2A and serotonin 5-HT1A receptors. J Biomol Struct Dyn 2023:1-16. [PMID: 37850444 DOI: 10.1080/07391102.2023.2270753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 10/07/2023] [Indexed: 10/19/2023]
Abstract
GPCRs are a family of transmembrane receptors that are profoundly linked to various neurological disorders, among which is Parkinson's disease (PD). PD is the second most ubiquitous neurological disorder after Alzheimer's disease, characterized by the depletion of dopamine in the central nervous system due to the impairment of dopaminergic neurons, leading to involuntary movements or dyskinesia. The current standard of care for PD is Levodopa, a dopamine precursor, yet the chronic use of this agent can exacerbate motor symptoms. Recent studies have investigated the effects of combining A2AR antagonist and 5-HT1A agonist on dyskinesia and motor complications in animal models of PD. It has been proved that the drug combination has significantly improved involuntary movements while maintaining motor activity, highlighting as a result new lines of therapy for PD treatments, through the regulation of both receptors. Using a combination of ligand-based pharmacophore modelling, virtual screening, and molecular dynamics simulation, this study intends on identifying potential dual-target compounds from IBScreen. Results showed that the selected models displayed good enrichment metrics with a near perfect receiver operator characteristic (ROC) and Area under the accumulation curve (AUAC) values, signifying that the models are both specific and sensitive. Molecular docking and ADMET analysis revealed that STOCK2N-00171 could be potentially active against A2AR and 5-HT1A. Post-MD analysis confirmed that the ligand exhibits a stable behavior throughout the simulation while maintaining crucial interactions. These results imply that STOCK2N-00171 can serve as a blueprint for the design of novel and effective dual-acting ligands targeting A2AR and 5-HT1A.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Iman Touati
- Laboratory of Innovative Technologies, National School of Applied Sciences of Tangier, Abdelmalek Essaadi University, Tetouan, Morocco
| | - Mohnad Abdalla
- Pediatric Research Institute, Children's Hospital Affiliated to Shandong University, Jinan, Shandong, China
| | - Yassir Boulaamane
- Laboratory of Innovative Technologies, National School of Applied Sciences of Tangier, Abdelmalek Essaadi University, Tetouan, Morocco
| | - Nawal Al-Hoshani
- Department of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
| | - Abdulaziz Alouffi
- King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Mohammed Reda Britel
- Laboratory of Innovative Technologies, National School of Applied Sciences of Tangier, Abdelmalek Essaadi University, Tetouan, Morocco
| | - Amal Maurady
- Laboratory of Innovative Technologies, National School of Applied Sciences of Tangier, Abdelmalek Essaadi University, Tetouan, Morocco
- Faculty of Sciences and Techniques of Tangier, Abdelmalek Essaadi University, Tetouan, Morocco
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38
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Vales S, Kryukova J, Chandra S, Smagurauskaite G, Payne M, Clark CJ, Hafner K, Mburu P, Denisov S, Davies G, Outeiral C, Deane CM, Morris GM, Bhattacharya S. Discovery and pharmacophoric characterization of chemokine network inhibitors using phage-display, saturation mutagenesis and computational modelling. Nat Commun 2023; 14:5763. [PMID: 37717048 PMCID: PMC10505172 DOI: 10.1038/s41467-023-41488-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 09/06/2023] [Indexed: 09/18/2023] Open
Abstract
CC and CXC-chemokines are the primary drivers of chemotaxis in inflammation, but chemokine network redundancy thwarts pharmacological intervention. Tick evasins promiscuously bind CC and CXC-chemokines, overcoming redundancy. Here we show that short peptides that promiscuously bind both chemokine classes can be identified from evasins by phage-display screening performed with multiple chemokines in parallel. We identify two conserved motifs within these peptides and show using saturation-mutagenesis phage-display and chemotaxis studies of an exemplar peptide that an anionic patch in the first motif and hydrophobic, aromatic and cysteine residues in the second are functionally necessary. AlphaFold2-Multimer modelling suggests that the peptide occludes distinct receptor-binding regions in CC and in CXC-chemokines, with the first and second motifs contributing ionic and hydrophobic interactions respectively. Our results indicate that peptides with broad-spectrum anti-chemokine activity and therapeutic potential may be identified from evasins, and the pharmacophore characterised by phage display, saturation mutagenesis and computational modelling.
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Affiliation(s)
- Serena Vales
- Wellcome Centre for Human Genetics and RDM Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Jhanna Kryukova
- Wellcome Centre for Human Genetics and RDM Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Soumyanetra Chandra
- Wellcome Centre for Human Genetics and RDM Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Gintare Smagurauskaite
- Wellcome Centre for Human Genetics and RDM Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Megan Payne
- Wellcome Centre for Human Genetics and RDM Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Charlie J Clark
- Wellcome Centre for Human Genetics and RDM Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Katrin Hafner
- Wellcome Centre for Human Genetics and RDM Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Philomena Mburu
- Wellcome Centre for Human Genetics and RDM Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Stepan Denisov
- Wellcome Centre for Human Genetics and RDM Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Graham Davies
- Wellcome Centre for Human Genetics and RDM Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Carlos Outeiral
- Department of Statistics, University of Oxford, 24-29 St Giles, Oxford, OX1 3LB, UK
| | - Charlotte M Deane
- Department of Statistics, University of Oxford, 24-29 St Giles, Oxford, OX1 3LB, UK
| | - Garrett M Morris
- Department of Statistics, University of Oxford, 24-29 St Giles, Oxford, OX1 3LB, UK
| | - Shoumo Bhattacharya
- Wellcome Centre for Human Genetics and RDM Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK.
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Li L, Liu S, Wang B, Liu F, Xu S, Li P, Chen Y. An Updated Review on Developing Small Molecule Kinase Inhibitors Using Computer-Aided Drug Design Approaches. Int J Mol Sci 2023; 24:13953. [PMID: 37762253 PMCID: PMC10530957 DOI: 10.3390/ijms241813953] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 08/31/2023] [Accepted: 09/07/2023] [Indexed: 09/29/2023] Open
Abstract
Small molecule kinase inhibitors (SMKIs) are of heightened interest in the field of drug research and development. There are 79 (as of July 2023) small molecule kinase inhibitors that have been approved by the FDA and hundreds of kinase inhibitor candidates in clinical trials that have shed light on the treatment of some major diseases. As an important strategy in drug design, computer-aided drug design (CADD) plays an indispensable role in the discovery of SMKIs. CADD methods such as docking, molecular dynamic, quantum mechanics/molecular mechanics, pharmacophore, virtual screening, and quantitative structure-activity relationship have been applied to the design and optimization of small molecule kinase inhibitors. In this review, we provide an overview of recent advances in CADD and SMKIs and the application of CADD in the discovery of SMKIs.
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Affiliation(s)
- Linwei Li
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China; (L.L.); (S.L.); (B.W.); (F.L.); (S.X.)
- Jiangsu Province Engineering Research Center of Eco-Cultivation and High-Value Utilization of Chines Medicinal Materials, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
| | - Songtao Liu
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China; (L.L.); (S.L.); (B.W.); (F.L.); (S.X.)
- Jiangsu Province Engineering Research Center of Eco-Cultivation and High-Value Utilization of Chines Medicinal Materials, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
- Key Laboratory of Pesticide, College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, China
| | - Bi Wang
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China; (L.L.); (S.L.); (B.W.); (F.L.); (S.X.)
- Jiangsu Province Engineering Research Center of Eco-Cultivation and High-Value Utilization of Chines Medicinal Materials, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
| | - Fei Liu
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China; (L.L.); (S.L.); (B.W.); (F.L.); (S.X.)
- Jiangsu Province Engineering Research Center of Eco-Cultivation and High-Value Utilization of Chines Medicinal Materials, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
| | - Shu Xu
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China; (L.L.); (S.L.); (B.W.); (F.L.); (S.X.)
- Jiangsu Province Engineering Research Center of Eco-Cultivation and High-Value Utilization of Chines Medicinal Materials, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
| | - Pirui Li
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China; (L.L.); (S.L.); (B.W.); (F.L.); (S.X.)
- Jiangsu Province Engineering Research Center of Eco-Cultivation and High-Value Utilization of Chines Medicinal Materials, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
| | - Yu Chen
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China; (L.L.); (S.L.); (B.W.); (F.L.); (S.X.)
- Jiangsu Province Engineering Research Center of Eco-Cultivation and High-Value Utilization of Chines Medicinal Materials, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
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40
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Pojtanadithee P, Hengphasatporn K, Suroengrit A, Boonyasuppayakorn S, Wilasluck P, Deetanya P, Wangkanont K, Sukanadi IP, Chavasiri W, Wolschann P, Langer T, Shigeta Y, Maitarad P, Sanachai K, Rungrotmongkol T. Identification of Promising Sulfonamide Chalcones as Inhibitors of SARS-CoV-2 3CL pro through Structure-Based Virtual Screening and Experimental Approaches. J Chem Inf Model 2023; 63:5244-5258. [PMID: 37581276 DOI: 10.1021/acs.jcim.3c00663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2023]
Abstract
3CLpro is a viable target for developing antiviral therapies against the coronavirus. With the urgent need to find new possible inhibitors, a structure-based virtual screening approach was developed. This study recognized 75 pharmacologically bioactive compounds from our in-house library of 1052 natural product-based compounds that satisfied drug-likeness criteria and exhibited good bioavailability and membrane permeability. Among these compounds, three promising sulfonamide chalcones were identified by combined theoretical and experimental approaches, with SWC423 being the most suitable representative compound due to its competitive inhibition and low cytotoxicity in Vero E6 cells (EC50 = 0.89 ± 0.32 μM; CC50 = 25.54 ± 1.38 μM; SI = 28.70). The binding and stability of SWC423 in the 3CLpro active site were investigated through all-atom molecular dynamics simulation and fragment molecular orbital calculation, indicating its potential as a 3CLpro inhibitor for further SARS-CoV-2 therapeutic research. These findings suggested that inhibiting 3CLpro with a sulfonamide chalcone such as SWC423 may pave the effective way for developing COVID-19 treatments.
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Affiliation(s)
- Piyatida Pojtanadithee
- Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok 10330, Thailand
| | - Kowit Hengphasatporn
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
| | - Aphinya Suroengrit
- Center of Excellence in Applied Medical Virology, Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Siwaporn Boonyasuppayakorn
- Center of Excellence in Applied Medical Virology, Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Patcharin Wilasluck
- Center of Excellence for Molecular Biology and Genomics of Shrimp, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
- Center of Excellence for Molecular Crop, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Peerapon Deetanya
- Center of Excellence for Molecular Biology and Genomics of Shrimp, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
- Center of Excellence for Molecular Crop, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Kittikhun Wangkanont
- Center of Excellence for Molecular Biology and Genomics of Shrimp, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
- Center of Excellence for Molecular Crop, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - I Putu Sukanadi
- Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Warinthorn Chavasiri
- Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Peter Wolschann
- Department of Pharmaceutical Chemistry, Faculty of Chemistry, University of Vienna, Vienna 1090, Austria
- Institute of Theoretical Chemistry, University of Vienna, Vienna 1090, Austria
| | - Thierry Langer
- Department of Pharmaceutical Chemistry, Faculty of Chemistry, University of Vienna, Vienna 1090, Austria
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
| | - Phornphimon Maitarad
- Research Center of Nano Science and Technology, Department of Chemistry, College of Science, Shanghai University, Shanghai 200444, P. R. China
| | - Kamonpan Sanachai
- Department of Biochemistry, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Thanyada Rungrotmongkol
- Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok 10330, Thailand
- Center of Excellence in Structural and Computational Biology, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
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Ma W, Zhang W, Le Y, Shi X, Xu Q, Xiao Y, Dou Y, Wang X, Zhou W, Peng W, Zhang H, Huang B. Using macromolecular electron densities to improve the enrichment of active compounds in virtual screening. Commun Chem 2023; 6:173. [PMID: 37608192 PMCID: PMC10444862 DOI: 10.1038/s42004-023-00984-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 08/15/2023] [Indexed: 08/24/2023] Open
Abstract
The quest for effective virtual screening algorithms is hindered by the scarcity of training data, calling for innovative approaches. This study presents the use of experimental electron density (ED) data for improving active compound enrichment in virtual screening, supported by ED's ability to reflect the time-averaged behavior of ligands and solvents in the binding pocket. Experimental ED-based grid matching score (ExptGMS) was developed to score compounds by measuring the degree of matching between their binding conformations and a series of multi-resolution experimental ED grids. The efficiency of ExptGMS was validated using both in silico tests with the Directory of Useful Decoys-Enhanced dataset and wet-lab tests on Covid-19 3CLpro-inhibitors. ExptGMS improved the active compound enrichment in top-ranked molecules by approximately 20%. Furthermore, ExptGMS identified four active inhibitors of 3CLpro, with the most effective showing an IC50 value of 1.9 µM. We also developed an online database containing experimental ED grids for over 17,000 proteins to facilitate the use of ExptGMS for academic users.
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Affiliation(s)
- Wenzhi Ma
- Beijing StoneWise Technology Co Ltd., Haidian Street #15, Haidian District, 100080, Beijing, China
| | - Wei Zhang
- State Key Laboratory of Respiratory Disease, First Affiliated Hospital of Guangzhou Medical University, 510182, Guangzhou, China
- Innovation Center for Pathogen Research, Guangzhou Laboratory, 510320, Guangzhou, China
| | - Yuan Le
- Beijing StoneWise Technology Co Ltd., Haidian Street #15, Haidian District, 100080, Beijing, China
| | - Xiaoxuan Shi
- Beijing StoneWise Technology Co Ltd., Haidian Street #15, Haidian District, 100080, Beijing, China
| | - Qingbo Xu
- Beijing StoneWise Technology Co Ltd., Haidian Street #15, Haidian District, 100080, Beijing, China
| | - Yang Xiao
- Beijing StoneWise Technology Co Ltd., Haidian Street #15, Haidian District, 100080, Beijing, China
| | - Yueying Dou
- Beijing StoneWise Technology Co Ltd., Haidian Street #15, Haidian District, 100080, Beijing, China
| | - Xiaoman Wang
- Beijing StoneWise Technology Co Ltd., Haidian Street #15, Haidian District, 100080, Beijing, China
| | - Wenbiao Zhou
- Beijing StoneWise Technology Co Ltd., Haidian Street #15, Haidian District, 100080, Beijing, China
| | - Wei Peng
- State Key Laboratory of Respiratory Disease, First Affiliated Hospital of Guangzhou Medical University, 510182, Guangzhou, China
- Innovation Center for Pathogen Research, Guangzhou Laboratory, 510320, Guangzhou, China
| | - Hongbo Zhang
- Beijing StoneWise Technology Co Ltd., Haidian Street #15, Haidian District, 100080, Beijing, China.
| | - Bo Huang
- Beijing StoneWise Technology Co Ltd., Haidian Street #15, Haidian District, 100080, Beijing, China.
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Saha S, Ghosh M. Computational exploration of natural compounds targeting Staphylococcus aureus: inhibiting AgrA promoter binding for antimicrobial intervention. J Biomol Struct Dyn 2023:1-12. [PMID: 37578046 DOI: 10.1080/07391102.2023.2246566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 07/30/2023] [Indexed: 08/15/2023]
Abstract
Staphylococcus aureus is a highly virulent nosocomial pathogen that poses a significant threat to individuals exposed to healthcare settings. Due to its sophisticated machinery for producing virulence factors, S. aureus can cause severe and potentially fatal infections in humans. This study focuses on the response regulator AgrA, which plays a crucial role in regulating the production of virulence factors in S. aureus. The objective is to identify natural compounds that can inhibit the binding of AgrA to its promoter site, thus inhibiting the expression of virulence genes. To achieve this, a pharmacophore model was generated using known drugs and applied to screen the ZINC natural product database. The resulting compounds were subjected to molecular docking-based virtual screening against the C-terminal DNA binding domain of AgrA. Three compounds, namely ZINC000077269178, ZINC000051012304, and ZINC000004266026, were shortlisted based on their strong affinity for key residues involved in DNA binding and transcription initiation. Subsequently, the unbound and ligand-bound complexes were subjected to a 200 ns molecular dynamics simulation to assess their conformational stability. Various analyses, including RMSD, RMSF, Rg, SASA, Principal Component Analysis, and Gibbs free energy landscape, were conducted on the simulation trajectory. The RMSD profile indicated similar fluctuations in both bound and unbound structures, while the Rg profile demonstrated the compactness of the protein without any unfolding during the simulation. Furthermore, Principal component analysis revealed that ligand binding reduced the overall atomic motion of the protein whereas free energy landscape suggested the energy variations obtained in complexes.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Subhadip Saha
- Department of Biotechnology, National Institute of Technology Durgapur, Durgapur, India
| | - Monidipa Ghosh
- Department of Biotechnology, National Institute of Technology Durgapur, Durgapur, India
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Faris A, Ibrahim IM, Al kamaly O, Saleh A, Elhallaoui M. Computer-Aided Drug Design of Novel Derivatives of 2-Amino-7,9-dihydro-8H-purin-8-one as Potent Pan-Janus JAK3 Inhibitors. Molecules 2023; 28:5914. [PMID: 37570884 PMCID: PMC10473238 DOI: 10.3390/molecules28155914] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 07/28/2023] [Accepted: 07/31/2023] [Indexed: 08/13/2023] Open
Abstract
Rheumatoid arthritis (RA) remains one of the most prevalent autoimmune diseases worldwide. Janus kinase 3 (JAK3) is an essential enzyme for treating autoimmune diseases, including RA. Molecular modeling techniques play a crucial role in the search for new drugs by reducing time delays. In this study, the 3D-QSAR approach is employed to predict new JAK3 inhibitors. Two robust models, both field-based with R2 = 0.93, R = 0.96, and Q2 = 87, and atom-based with R2 = 0.94, R = 0.97, and Q2 = 86, yielded good results by identifying groups that may readily direct their interaction. A reliable pharmacophore model, DHRRR1, was provided in this work to enable the clear characterization of chemical features, leading to the design of 13 inhibitors with their pIC50 values. The DHRRR1 model yielded a validation result with a ROC value of 0.87. Five promising inhibitors were selected for further study based on an ADMET analysis of their pharmacokinetic properties and covalent docking (CovDock). Compared to the FDA-approved drug tofacitinib, the pharmaceutical features, binding affinity and stability of the inhibitors were analyzed through CovDock, 300 ns molecular dynamics simulations, free energy binding calculations and ADMET predictions. The results show that the inhibitors have strong binding affinity, stability and favorable pharmaceutical properties. The newly predicted molecules, as JAK3 inhibitors for the treatment of RA, are promising candidates for use as drugs.
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Affiliation(s)
- Abdelmoujoud Faris
- LIMAS, Department of Chemical Sciences, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco;
| | - Ibrahim M. Ibrahim
- Biophysics Department, Faculty of Science, Cairo University, Cairo 12613, Egypt;
| | - Omkulthom Al kamaly
- Department of Pharmaceutical Sciences, College of Pharmacy, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia; (O.A.k.); (A.S.)
| | - Asmaa Saleh
- Department of Pharmaceutical Sciences, College of Pharmacy, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia; (O.A.k.); (A.S.)
| | - Menana Elhallaoui
- LIMAS, Department of Chemical Sciences, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco;
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Ramasamy M, Vetrivel A, Venugopal S, Murugesan R. Identification of inhibitors for Agr quorum sensing system of Staphylococcus aureus by machine learning, pharmacophore modeling, and molecular dynamics approaches. J Mol Model 2023; 29:258. [PMID: 37468720 DOI: 10.1007/s00894-023-05647-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 07/03/2023] [Indexed: 07/21/2023]
Abstract
CONTEXT Staphylococcus aureus is a highly pathogenic organism that is the most common cause of postoperative complications as well as severe infections like bacteremia and infective endocarditis. By mediating the formation of biofilms and the expression of virulent genes, the quorum sensing (QS) mechanism is a major contributor to the development of these diseases. By hindering its QS network, an innovative approach to avoiding this bacterial infection is taken. Targeting the AgrA of the Agr system serves as beneficial in holding the top position in the QS system cascade. METHODS Using known AgrA inhibitors, the machine learning algorithms (artificial neural network, naïve Bayes, random forest, and support vector machine) and pharmacophore model were developed. The potential lead compounds were screened against the Zinc and COCONUT databases using the best pharmacophore hypothesis. The hits were then subjected second screening process using the best machine learning model. The predicted active compounds were then reranked based on the docking score. The stability of AgrA-lead compounds was studied using molecular dynamics approaches, and an ADME profile was also carried out. Five lead compounds, namely, CNP02386963,4,5-trihydroxy-2-[({7,13,14-trihydroxy-3,10-dioxo-2,9-dioxatetracyclo[6.6.2.04,16.011,15]hexadeca-1(14),4,6,8(16),11(15),12-hexaen-6-yl}oxy)methyl]benzoic acid, CNP0129274 4-(dimethylamino)-1,5,6,10,12,12a-hexahydroxy-6-methyl-3,11-dioxo-3,4,4a,5,5a,6,11,12a-octahydrotetracene-2-carboxamide, CNP0242717 3-Hydroxyasebotin, CNP0361624 3,4,5-trihydroxy-6-[(2,4,5,6,7-pentahydroxy-1-oxooctan-3-yl)oxy]oxane-2-carboxylic acid, and CNP0285058 2-{[4,5-dihydroxy-6-(hydroxymethyl)-3-[(3,4,5-trihydroxy-6-methyloxan-2-yl)oxy]oxan-2-yl]oxy}-2-(4-hydroxyphenyl)acetonitrile were obtained using the two-step virtual screening process. The molecular dynamics study revealed that the CNP0238696 was found to be stable in the binding pocket of AgrA. ADME profiles show that this compound has two Lipinski violations and low bioavailability. Further studies should be performed to assess the anti-biofilm activity of the lead compound in vitro.
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Affiliation(s)
- Monica Ramasamy
- Department of Biochemistry, Biotechnology, and Bioinformatics, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
| | - Aishwarya Vetrivel
- Department of Biochemistry, Biotechnology, and Bioinformatics, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
| | - Sharulatha Venugopal
- Department of Chemistry, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
| | - Rajeswari Murugesan
- Department of Biochemistry, Biotechnology, and Bioinformatics, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India.
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Yang J, Qiu M, Lu T, Yang S, Yu J, Lin J, Ma H, Guo Z, Chen Z, Han X, Zhang D. Discovery and verification of bitter components in Panax notoginseng based on the integrated strategy of pharmacophore model, system separation and bitter tracing technology. Food Chem 2023; 428:136716. [PMID: 37413835 DOI: 10.1016/j.foodchem.2023.136716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Revised: 06/14/2023] [Accepted: 06/22/2023] [Indexed: 07/08/2023]
Abstract
Panax notoginseng is a world-renowned tonic herb, which has been used as a characteristic food in Southwest China for hundreds of years. However, the taste of Panax notoginseng is extremely bitter and serious after tasting, and its bitter components are unknown. This manuscript proposes a new strategy for discovering bitter components of Panax notoginseng based on the integrated analysis of pharmacophore model, system separation and bitter tracing technology. Firstly, 16 potential bitter components were obtained by UPLC-Q-Orbitrap HRMS combined with virtual screening, most of which were saponins.Then, the bitter components were further separated by system component separation and 5 potential bitter components were obtained. Finally, the main contributors of bitterness in Panax notoginseng were verified to be Ginsenoside Rg1, Ginsenoside Rb1 and Ginsenoside Rd by components knock-in and fNIRS. In general, this paper is the first literature report on the relatively systematic study of bitter components in Panax notoginseng.
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Affiliation(s)
- Jing Yang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, PR China
| | - Min Qiu
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, PR China
| | - Tai Lu
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, PR China
| | - Shangdong Yang
- Department of Psychology, Jiangxi University of Traditional Chinese Medicine, Nanchang 330004, PR China
| | - Ji Yu
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, PR China
| | - Junzhi Lin
- TCM Regulating Metabolic Diseases Key Laboratory of Sichuan Province, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu 610072, PR China
| | - Hongyan Ma
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, PR China
| | - Zhiping Guo
- Sichuan Houde Pharmaceutical Technology Co. Ltd., Chengdu 610041, PR China
| | - Zhencai Chen
- Department of Psychology, Jiangxi University of Traditional Chinese Medicine, Nanchang 330004, PR China.
| | - Xue Han
- Chengdu Medical College, Chengdu 610500, PR China.
| | - Dingkun Zhang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, PR China; Tianfu TCM Innovation Harbour, Chengdu University of Traditional Chinese Medicine, Pengzhou 611900, PR China.
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Marsili G, Acchioni C, Remoli AL, Amatore D, Sgarbanti R, De Angelis M, Orsatti R, Acchioni M, Astolfi A, Iraci N, Puzelli S, Facchini M, Perrotti E, Cecchetti V, Sabatini S, Superti F, Agamennone M, Barreca ML, Hiscott J, Nencioni L, Sgarbanti M. Identification of Anti-Influenza A Compounds Inhibiting the Viral Non-Structural Protein 1 (NS1) Using a Type I Interferon-Driven Screening Strategy. Int J Mol Sci 2023; 24:10495. [PMID: 37445672 DOI: 10.3390/ijms241310495] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 06/18/2023] [Accepted: 06/19/2023] [Indexed: 07/15/2023] Open
Abstract
There is an urgent need to identify efficient antiviral compounds to combat existing and emerging RNA virus infections, particularly those related to seasonal and pandemic influenza outbreaks. While inhibitors of the influenza viral integral membrane proton channel protein (M2), neuraminidase (NA), and cap-dependent endonuclease are available, circulating influenza viruses acquire resistance over time. Thus, the need for the development of additional anti-influenza drugs with novel mechanisms of action exists. In the present study, a cell-based screening assay and a small molecule library were used to screen for activities that antagonized influenza A non-structural protein 1 (NS1), a highly conserved, multifunctional accessory protein that inhibits the type I interferon response against influenza. Two potential anti-influenza agents, compounds 157 and 164, were identified with anti-NS1 activity, resulting in the reduction of A/PR/8/34(H1N1) influenza A virus replication and the restoration of IFN-β expression in human lung epithelial A549 cells. A 3D pharmacophore modeling study of the active compounds provided a glimpse of the structural motifs that may contribute to anti-influenza virus activity. This screening approach is amenable to a broader analysis of small molecule compounds to inhibit other viral targets.
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Affiliation(s)
- Giulia Marsili
- Department of Infectious Diseases, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Chiara Acchioni
- Department of Infectious Diseases, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Anna Lisa Remoli
- Department of Infectious Diseases, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Donatella Amatore
- Department of Public Health and Infectious Diseases, Laboratory Affiliated to Istituto Pasteur Italia-Fondazione Cenci Bolognetti, Sapienza University, 00185 Rome, Italy
| | - Rossella Sgarbanti
- Department of Public Health and Infectious Diseases, Laboratory Affiliated to Istituto Pasteur Italia-Fondazione Cenci Bolognetti, Sapienza University, 00185 Rome, Italy
| | - Marta De Angelis
- Department of Public Health and Infectious Diseases, Laboratory Affiliated to Istituto Pasteur Italia-Fondazione Cenci Bolognetti, Sapienza University, 00185 Rome, Italy
- Laboratory of Virology, Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, Italy
| | - Roberto Orsatti
- Department of Infectious Diseases, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Marta Acchioni
- Department of Infectious Diseases, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Andrea Astolfi
- Department of Pharmaceutical Sciences, Università degli Studi di Perugia, Via del Liceo 1, 06123 Perugia, Italy
| | - Nunzio Iraci
- Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, Viale Ferdinando Stagno d'Alcontres 31, 98166 Messina, Italy
| | - Simona Puzelli
- Department of Infectious Diseases, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Marzia Facchini
- Department of Infectious Diseases, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Edvige Perrotti
- Department of Infectious Diseases, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Violetta Cecchetti
- Department of Pharmaceutical Sciences, Università degli Studi di Perugia, Via del Liceo 1, 06123 Perugia, Italy
| | - Stefano Sabatini
- Department of Pharmaceutical Sciences, Università degli Studi di Perugia, Via del Liceo 1, 06123 Perugia, Italy
| | - Fabiana Superti
- National Centre for Innovative Technologies in Public Health, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Mariangela Agamennone
- Department of Pharmacy, University "G. d'Annunzio" of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti, Italy
| | - Maria Letizia Barreca
- Department of Pharmaceutical Sciences, Università degli Studi di Perugia, Via del Liceo 1, 06123 Perugia, Italy
| | - John Hiscott
- Istituto Pasteur Italia, Fondazione Cenci Bolognetti, Viale Regina Elena 291, 00161 Rome, Italy
| | - Lucia Nencioni
- Department of Public Health and Infectious Diseases, Laboratory Affiliated to Istituto Pasteur Italia-Fondazione Cenci Bolognetti, Sapienza University, 00185 Rome, Italy
| | - Marco Sgarbanti
- Department of Infectious Diseases, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
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Shehzadi K, Saba A, Yu M, Liang J. Structure-Based Drug Design of RdRp Inhibitors against SARS-CoV-2. Top Curr Chem (Cham) 2023; 381:22. [PMID: 37318607 DOI: 10.1007/s41061-023-00432-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 05/15/2023] [Indexed: 06/16/2023]
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a worldwide pandemic since 2019, spreading rapidly and posing a significant threat to human health and life. With over 6 billion confirmed cases of the virus, the need for effective therapeutic drugs has become more urgent than ever before. RNA-dependent RNA polymerase (RdRp) is crucial in viral replication and transcription, catalysing viral RNA synthesis and serving as a promising therapeutic target for developing antiviral drugs. In this article, we explore the inhibition of RdRp as a potential treatment for viral diseases, analysing the structural information of RdRp in virus proliferation and summarizing the reported inhibitors' pharmacophore features and structure-activity relationship profiles. We hope that the information provided by this review will aid in structure-based drug design and aid in the global fight against SARS-CoV-2 infection.
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Affiliation(s)
- Kiran Shehzadi
- Key Laboratory of Medical Molecule Science and Pharmaceutical Engineering, Ministry of Industry and Information Technology, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing, 10081, China
| | - Afsheen Saba
- Key Laboratory of Medical Molecule Science and Pharmaceutical Engineering, Ministry of Industry and Information Technology, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing, 10081, China
| | - Mingjia Yu
- Key Laboratory of Medical Molecule Science and Pharmaceutical Engineering, Ministry of Industry and Information Technology, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing, 10081, China.
| | - Jianhua Liang
- Key Laboratory of Medical Molecule Science and Pharmaceutical Engineering, Ministry of Industry and Information Technology, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing, 10081, China.
- Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing, 314019, China.
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Pliushcheuskaya P, Künze G. Recent Advances in Computer-Aided Structure-Based Drug Design on Ion Channels. Int J Mol Sci 2023; 24:ijms24119226. [PMID: 37298178 DOI: 10.3390/ijms24119226] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 05/16/2023] [Accepted: 05/22/2023] [Indexed: 06/12/2023] Open
Abstract
Ion channels play important roles in fundamental biological processes, such as electric signaling in cells, muscle contraction, hormone secretion, and regulation of the immune response. Targeting ion channels with drugs represents a treatment option for neurological and cardiovascular diseases, muscular degradation disorders, and pathologies related to disturbed pain sensation. While there are more than 300 different ion channels in the human organism, drugs have been developed only for some of them and currently available drugs lack selectivity. Computational approaches are an indispensable tool for drug discovery and can speed up, especially, the early development stages of lead identification and optimization. The number of molecular structures of ion channels has considerably increased over the last ten years, providing new opportunities for structure-based drug development. This review summarizes important knowledge about ion channel classification, structure, mechanisms, and pathology with the main focus on recent developments in the field of computer-aided, structure-based drug design on ion channels. We highlight studies that link structural data with modeling and chemoinformatic approaches for the identification and characterization of new molecules targeting ion channels. These approaches hold great potential to advance research on ion channel drugs in the future.
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Affiliation(s)
- Palina Pliushcheuskaya
- Institute for Drug Discovery, Medical Faculty, University of Leipzig, Brüderstr. 34, D-04103 Leipzig, Germany
| | - Georg Künze
- Institute for Drug Discovery, Medical Faculty, University of Leipzig, Brüderstr. 34, D-04103 Leipzig, Germany
- Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstr. 16-18, D-04107 Leipzig, Germany
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Liu X, Yan W, Wang S, Lu M, Yang H, Chai X, Shi H, Zhang Y, Jia Q. Discovery of selective HDAC6 inhibitors based on a multi-layer virtual screening strategy. Comput Biol Med 2023; 160:107036. [PMID: 37196455 DOI: 10.1016/j.compbiomed.2023.107036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 04/30/2023] [Accepted: 05/11/2023] [Indexed: 05/19/2023]
Abstract
The abnormal enhancement of histone deacetylase 6 (HDAC6) has been demonstrated to be closely related to the occurrence and development of various malignant tumors, attracting extensive attention as a promising target for cancer therapy. Currently, only limited selective HDAC6 inhibitors have entered clinical trials, making the rapid discovery of selective HDAC6 inhibitors with safety profiles particularly urgent. In this study, a multi-layer virtual screening workflow was established, and the representative compounds screened were biologically evaluated in combination with enzyme inhibitory and anti-tumor cell proliferation experiments. The experimental results showed that the screened compounds L-25, L-32, L-45 and L-81 exhibited nanomolar inhibitory activity against HDAC6, and exerted a certain degree of anti-proliferative activities against tumor cells, especially the cytotoxicity of L-45 to A375 (IC50 = 11.23 ± 1.27 μM) and the cytotoxicity of L-81 against HCT-116 (IC50 = 12.25 ± 1.13 μM). Additionally, the molecular mechanisms underlying the subtype selective inhibitory activities of the selected compounds were further elucidated using computational approaches, and the hotspot residues on HDAC6 contributing to the ligands' binding were identified. In summary, this study established a multi-layer screening scheme to quickly and effectively screen out hit compounds with enzyme inhibitory activity and anti-tumor cell proliferation, providing novel scaffolds for the subsequent anti-tumor drug design based on HDAC6 target.
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Affiliation(s)
- Xingang Liu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China; The Key Laboratory of Neural and Vascular Biology, Ministry of Education, Hebei Medical University, Shijiazhuang, 050017, China; Key Laboratory of Innovative Drug Research and Evaluation of Hebei Province, Shijiazhuang, 050017, China
| | - Wenying Yan
- Department of Clinical Pharmacy, The Third Hospital of Hebei Medical University, Shijiazhuang, 050051, China
| | - Songsong Wang
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China; The Key Laboratory of Neural and Vascular Biology, Ministry of Education, Hebei Medical University, Shijiazhuang, 050017, China; Key Laboratory of Innovative Drug Research and Evaluation of Hebei Province, Shijiazhuang, 050017, China
| | - Ming Lu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China; Department of Pharmacy, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, China
| | - Hao Yang
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Xu Chai
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - He Shi
- The Fourth Hospital of Shijiazhuang, Shijiazhuang Obstetrics and Gynecology Hospital, Shijiazhuang, 050000, China.
| | - Yang Zhang
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China; The Key Laboratory of Neural and Vascular Biology, Ministry of Education, Hebei Medical University, Shijiazhuang, 050017, China; Key Laboratory of Innovative Drug Research and Evaluation of Hebei Province, Shijiazhuang, 050017, China.
| | - Qingzhong Jia
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China; The Key Laboratory of Neural and Vascular Biology, Ministry of Education, Hebei Medical University, Shijiazhuang, 050017, China; Key Laboratory of Innovative Drug Research and Evaluation of Hebei Province, Shijiazhuang, 050017, China.
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50
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Zhu J, Sun D, Li X, Jia L, Cai Y, Chen Y, Jin J, Yu L. Developing new PI3Kγ inhibitors by combining pharmacophore modeling, molecular dynamic simulation, molecular docking, fragment-based drug design, and virtual screening. Comput Biol Chem 2023; 104:107879. [PMID: 37182359 DOI: 10.1016/j.compbiolchem.2023.107879] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 05/06/2023] [Accepted: 05/06/2023] [Indexed: 05/16/2023]
Abstract
Since dysregulation of the phosphatidylinositol 3-kinase gamma (PI3Kγ) signaling pathway is associated with the pathogenesis of cancer, inflammation, and autoimmunity, PI3Kγ has emerged as an attractive target for drug development. IPI-549 is the only selective PI3Kγ inhibitor that has advanced to clinical trials, thus, IPI-549 could serve as a promising template for designing novel PI3Kγ inhibitors. In this present study, a modeling strategy consisting of common feature pharmacophore modeling, receptor-ligand pharmacophore modeling, and molecular dynamics simulation was utilized to identify the key pharmacodynamic characteristic elements of the target compound and the key residue information of the PI3Kγ interaction with the inhibitors. Then, 10 molecules were designed based on the structure-activity relationships, and some of them exhibited satisfactory predicted binding affinities to PI3Kγ. Finally, a hierarchical multistage virtual screening method, involving the developed common feature and receptor-ligand pharmacophore model and molecular docking, was constructed for screening the potential PI3Kγ inhibitors. Overall, we hope these findings would provide some guidance for the development of novel PI3Kγ inhibitors.
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Affiliation(s)
- Jingyu Zhu
- School of Life Sciences and Health Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China.
| | - Dan Sun
- School of Life Sciences and Health Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Xintong Li
- School of Life Sciences and Health Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Lei Jia
- School of Life Sciences and Health Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Yanfei Cai
- School of Life Sciences and Health Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Yun Chen
- School of Life Sciences and Health Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Jian Jin
- School of Life Sciences and Health Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Li Yu
- School of Inspection and Testing Certification, Changzhou Vocational Institute of Engineering, Changzhou 213164, Jiangsu, China.
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