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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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Ancajas CMF, Oyedele AS, Butt CM, Walker AS. Advances, opportunities, and challenges in methods for interrogating the structure activity relationships of natural products. Nat Prod Rep 2024. [PMID: 38912779 DOI: 10.1039/d4np00009a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/25/2024]
Abstract
Time span in literature: 1985-early 2024Natural products play a key role in drug discovery, both as a direct source of drugs and as a starting point for the development of synthetic compounds. Most natural products are not suitable to be used as drugs without further modification due to insufficient activity or poor pharmacokinetic properties. Choosing what modifications to make requires an understanding of the compound's structure-activity relationships. Use of structure-activity relationships is commonplace and essential in medicinal chemistry campaigns applied to human-designed synthetic compounds. Structure-activity relationships have also been used to improve the properties of natural products, but several challenges still limit these efforts. Here, we review methods for studying the structure-activity relationships of natural products and their limitations. Specifically, we will discuss how synthesis, including total synthesis, late-stage derivatization, chemoenzymatic synthetic pathways, and engineering and genome mining of biosynthetic pathways can be used to produce natural product analogs and discuss the challenges of each of these approaches. Finally, we will discuss computational methods including machine learning methods for analyzing the relationship between biosynthetic genes and product activity, computer aided drug design techniques, and interpretable artificial intelligence approaches towards elucidating structure-activity relationships from models trained to predict bioactivity from chemical structure. Our focus will be on these latter topics as their applications for natural products have not been extensively reviewed. We suggest that these methods are all complementary to each other, and that only collaborative efforts using a combination of these techniques will result in a full understanding of the structure-activity relationships of natural products.
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Affiliation(s)
| | | | - Caitlin M Butt
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA.
| | - Allison S Walker
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA.
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
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Pathak Y, Camps I, Yadav M, Mishra A, Upadhyay J, Tripathi V. Lumacaftor as a potential repurposed drug in targeting breast cancer stem cells: insights from in silico study. J Mol Model 2024; 30:227. [PMID: 38913211 DOI: 10.1007/s00894-024-05990-5] [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: 09/27/2023] [Accepted: 05/21/2024] [Indexed: 06/25/2024]
Abstract
CONTEXT Breast cancer stem cells (BCSCs) are a small subset of cells within breast tumors with characteristics similar to normal stem cells. Despite advancements in chemotherapy and targeted therapy for breast cancer, the prognosis for breast cancer patients has remained poor due to drug resistance, reoccurrence, and metastasis. Growing evidence suggests that deregulation of the self-renewal pathways, like the Wnt signaling pathway mediated by β-catenin, plays a crucial role in the survival of breast cancer stem cells. Targeting the Wnt signaling pathway in breast cancer stem cells offers a promising avenue for developing effective therapeutic strategies targeting these cells, potentially leading to improved patient outcomes and reduced tumor recurrence. METHODS For this purpose, we have screened a 1615 FDA-approved drug library against our target protein, β-catenin, which is involved in the Wnt signaling pathway using molecular docking analysis, molecular dynamics (MD) simulations, and molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculations. RESULTS Molecular docking studies showed that the Lumacaftor- β-catenin complex had the lowest docking score of - 8.7 kcal/mol towards β-catenin protein than the reference inhibitor. Molecular dynamic simulations and MM/PBSA calculations were also performed for the Lumacaftor-β-catenin complex to establish the stability of the interactions involved. Considering its promising attributes and encouraging results, Lumacaftor holds significant potential as a novel therapeutic option to target BCSCs. This study opens avenues for further investigation and may pave the way for developing therapeutic potential in breast cancer treatment. Further confirmation is warranted through in vitro and clinical studies to validate the findings of this study.
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Affiliation(s)
- Yamini Pathak
- School of Biotechnology, Gautam Buddha University, Greater Noida, 201310, India
| | - Ihosvany Camps
- Laboratório de Modelagem Computacional - LaModel, Instituto de Ciências Exatas - ICEx. Universidade Federal de Alfenas - UNIFAL-MG, Alfenas, Minas Gerais, Brazil
- High Performance & Quantum Computing Labs, Waterloo, Canada
| | - Manju Yadav
- Institute of Nuclear Medicine and Allied Sciences, DRDO, Delhi, India
| | - Amaresh Mishra
- School of Biotechnology, Gautam Buddha University, Greater Noida, 201310, India
| | - Jyoti Upadhyay
- School of Biotechnology, Gautam Buddha University, Greater Noida, 201310, India
| | - Vishwas Tripathi
- School of Biotechnology, Gautam Buddha University, Greater Noida, 201310, India.
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Thai QM, Nguyen TH, Phung HTT, Pham MQ, Pham NKT, Horng JT, Ngo ST. MedChemExpress compounds prevent neuraminidase N1 via physics- and knowledge-based methods. RSC Adv 2024; 14:18950-18956. [PMID: 38873542 PMCID: PMC11167619 DOI: 10.1039/d4ra02661f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 06/07/2024] [Indexed: 06/15/2024] Open
Abstract
Influenza A viruses spread out worldwide, causing several global concerns. Hence, discovering neuraminidase inhibitors to prevent the influenza A virus is of great interest. In this work, a machine learning model was employed to evaluate the ligand-binding affinity of ca. 10 000 compounds from the MedChemExpress (MCE) database for inhibiting neuraminidase. Atomistic simulations, including molecular docking and molecular dynamics simulations, then confirmed the ligand-binding affinity. Furthermore, we clarified the physical insights into the binding process of ligands to neuraminidase. It was found that five compounds, including micronomicin, didesmethyl cariprazine, argatroban, Kgp-IN-1, and AY 9944, are able to inhibit neuraminidase N1 of the influenza A virus. Ten residues, including Glu119, Asp151, Arg152, Trp179, Gln228, Glu277, Glu278, Arg293, Asn295, and Tyr402, may be very important in controlling the ligand-binding process to N1.
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Affiliation(s)
- Quynh Mai Thai
- Laboratory of Biophysics, Institute for Advanced Study in Technology, Ton Duc Thang University Ho Chi Minh City Vietnam
- Faculty of Pharmacy, Ton Duc Thang University Ho Chi Minh City Vietnam
| | - Trung Hai Nguyen
- Laboratory of Biophysics, Institute for Advanced Study in Technology, Ton Duc Thang University Ho Chi Minh City Vietnam
- Faculty of Pharmacy, Ton Duc Thang University Ho Chi Minh City Vietnam
| | | | - Minh Quan Pham
- Institute of Natural Products Chemistry, Vietnam Academy of Science and Technology Hanoi Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology Hanoi Vietnam
| | - Nguyen Kim Tuyen Pham
- Faculty of Environment, Sai Gon University 273 An Duong Vuong, Ward 3, District 5 Ho Chi Minh City Vietnam
| | - Jim-Tong Horng
- Department of Biochemistry and Molecular Biology, College of Medicine, Chang Gung University Kweishan Taoyuan Taiwan
| | - Son Tung Ngo
- Laboratory of Biophysics, Institute for Advanced Study in Technology, Ton Duc Thang University Ho Chi Minh City Vietnam
- Faculty of Pharmacy, Ton Duc Thang University Ho Chi Minh City Vietnam
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Hayat M, Gao T, Cao Y, Rafiq M, Zhuo L, Li YZ. Identification of Prospective Ebola Virus VP35 and VP40 Protein Inhibitors from Myxobacterial Natural Products. Biomolecules 2024; 14:660. [PMID: 38927063 PMCID: PMC11201620 DOI: 10.3390/biom14060660] [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: 05/09/2024] [Revised: 06/01/2024] [Accepted: 06/03/2024] [Indexed: 06/28/2024] Open
Abstract
The Ebola virus (EBOV) is a lethal pathogen causing hemorrhagic fever syndrome which remains a global health challenge. In the EBOV, two multifunctional proteins, VP35 and VP40, have significant roles in replication, virion assembly, and budding from the cell and have been identified as druggable targets. In this study, we employed in silico methods comprising molecular docking, molecular dynamic simulations, and pharmacological properties to identify prospective drugs for inhibiting VP35 and VP40 proteins from the myxobacterial bioactive natural product repertoire. Cystobactamid 934-2, Cystobactamid 919-1, and Cittilin A bound firmly to VP35. Meanwhile, 2-Hydroxysorangiadenosine, Enhypyrazinone B, and Sorangiadenosine showed strong binding to the matrix protein VP40. Molecular dynamic simulations revealed that, among these compounds, Cystobactamid 919-1 and 2-Hydroxysorangiadenosine had stable interactions with their respective targets. Similarly, molecular mechanics Poisson-Boltzmann surface area (MMPBSA) calculations indicated close-fitting receptor binding with VP35 or VP40. These two compounds also exhibited good pharmacological properties. In conclusion, we identified Cystobactamid 919-1 and 2-Hydroxysorangiadenosine as potential ligands for EBOV that target VP35 and VP40 proteins. These findings signify an essential step in vitro and in vivo to validate their potential for EBOV inhibition.
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Affiliation(s)
- Muhammad Hayat
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao 266237, China; (M.H.); (T.G.); (Y.C.); (Y.-Z.L.)
| | - Tian Gao
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao 266237, China; (M.H.); (T.G.); (Y.C.); (Y.-Z.L.)
| | - Ying Cao
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao 266237, China; (M.H.); (T.G.); (Y.C.); (Y.-Z.L.)
| | - Muhammad Rafiq
- Department of Microbiology, Faculty of Life Sciences and Informatics, Balochistan University of IT, Engineering and Management Sciences, Quetta 87100, Pakistan
| | - Li Zhuo
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao 266237, China; (M.H.); (T.G.); (Y.C.); (Y.-Z.L.)
- Shenzhen Research Institute, Shandong University, Shenzhen 518057, China
- Suzhou Research Institute, Shandong University, Suzhou 215123, China
| | - Yue-Zhong Li
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao 266237, China; (M.H.); (T.G.); (Y.C.); (Y.-Z.L.)
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Wu YC, Lai HX, Li JM, Fung KM, Tseng TS. Discovery of a potent inhibitor, D-132, targeting AsfvPolX, via protein-DNA complex-guided pharmacophore screening and in vitro molecular characterizations. Virus Res 2024; 344:199359. [PMID: 38521505 PMCID: PMC10995865 DOI: 10.1016/j.virusres.2024.199359] [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: 01/15/2024] [Revised: 03/15/2024] [Accepted: 03/17/2024] [Indexed: 03/25/2024]
Abstract
The heightened transmissibility and capacity of African swine fever virus (ASFV) induce fatal diseases in domestic pigs and wild boars, posing significant economic repercussions and global threats. Despite extensive research efforts, the development of potent vaccines or treatments for ASFV remains a persistent challenge. Recently, inhibiting the AsfvPolX, a key DNA repair enzyme, emerges as a feasible strategy to disrupt viral replication and control ASFV infections. In this study, a comprehensive approach involving pharmacophore-based inhibitor screening, coupled with biochemical and biophysical analyses, were implemented to identify, characterize, and validate potential inhibitors targeting AsfvPolX. The constructed pharmacophore model, Phar-PolX-S, demonstrated efficacy in identifying a potent inhibitor, D-132 (IC50 = 2.8 ± 0.2 µM), disrupting the formation of the AsfvPolX-DNA complex. Notably, D-132 exhibited strong binding to AsfvPolX (KD = 6.9 ± 2.2 µM) through a slow-on-fast-off binding mechanism. Employing molecular modeling, it was elucidated that D-132 predominantly binds in-between the palm and finger domains of AsfvPolX, with crucial residues (R42, N48, Q98, E100, F102, and F116) identified as hotspots for structure-based inhibitor optimization. Distinctively characterized by a 1,2,5,6-tetrathiocane with modifications at the 3 and 8 positions involving ethanesulfonates, D-132 holds considerable promise as a lead compound for the development of innovative agents to combat ASFV infections.
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Affiliation(s)
- Yi-Chen Wu
- Institute of Molecular Biology, National Chung Hsing University, Taichung, 40202, Taiwan
| | - Hui-Xiang Lai
- Institute of Molecular Biology, National Chung Hsing University, Taichung, 40202, Taiwan
| | - Ji-Min Li
- Institute of Precision Medicine, College of Medicine, National Sun Yat-sen University, Kaohsiung, 80424, Taiwan; Center of Excellence for Metabolic Associated Fatty Liver Disease, National Sun Yat-sen University, Kaohsiung, 80424, Taiwan
| | - Kit-Man Fung
- Biomedical Translation Research Center (BioTReC), Academia Sinica, Taipei, 11529, Taiwan
| | - Tien-Sheng Tseng
- Institute of Molecular Biology, National Chung Hsing University, Taichung, 40202, Taiwan.
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Chakravorty A, Hussain A, Cervantes LF, Lai TT, Brooks CL. Exploring the Limits of the Generalized CHARMM and AMBER Force Fields through Predictions of Hydration Free Energy of Small Molecules. J Chem Inf Model 2024; 64:4089-4101. [PMID: 38717640 PMCID: PMC11275216 DOI: 10.1021/acs.jcim.4c00126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/28/2024]
Abstract
Accurate force field parameters, potential energy functions, and receptor-ligand models are essential for modeling the solvation and binding of drug-like molecules to a receptor. A large and ever-growing chemical space of medicinally relevant scaffolds has also required these factors, especially force field parameters, to be highly transferable. Generalized force fields such as the CHARMM General Force Field (CGenFF) and the generalized AMBER force field (GAFF) have accomplished this feat along with other contemporaneous ones like OPLS. Here, we analyze the limits in the parametrization of drug-like small molecules by CGenFF and GAFF in terms of the various functional groups represented within them. Specifically, we link the presence of specific functional groups to the error in the absolute hydration free energy of over 600 small molecules, predicted by alchemical free energy methods implemented in the CHARMM program. Our investigation reveals that molecules with (i) a nitro group in CGenFF and GAFF are, respectively, over- or undersolubilized in aqueous medium, (ii) amine groups are undersolubilized more so in CGenFF than in GAFF, and (iii) carboxyl groups are more oversolubilized in GAFF than in CGenFF. We present our analyses of the potential factors underlying these trends. We also showcase the use of a machine-learning-based approach combined with the SHapley Additive exPlanations framework to attribute these trends to specific functional groups, which can be easily adopted to explore the limits of other general force fields.
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Affiliation(s)
- Arghya Chakravorty
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Azam Hussain
- Department of Macromolecular Science and Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Luis F Cervantes
- Department of Medicinal Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Thanh T Lai
- Biophysics Program, Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Charles L Brooks
- Department of Medicinal Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
- Biophysics Program, Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
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Elrashedy A, Nayel M, Salama A, Salama MM, Hasan ME. Bioinformatics approach for structure modeling, vaccine design, and molecular docking of Brucella candidate proteins BvrR, OMP25, and OMP31. Sci Rep 2024; 14:11951. [PMID: 38789443 PMCID: PMC11126717 DOI: 10.1038/s41598-024-61991-7] [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: 12/12/2023] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
Brucellosis is a zoonotic disease with significant economic and healthcare costs. Despite the eradication efforts, the disease persists. Vaccines prevent disease in animals while antibiotics cure humans with limitations. This study aims to design vaccines and drugs for brucellosis in animals and humans, using protein modeling, epitope prediction, and molecular docking of the target proteins (BvrR, OMP25, and OMP31). Tertiary structure models of three target proteins were constructed and assessed using RMSD, TM-score, C-score, Z-score, and ERRAT. The best models selected from AlphaFold and I-TASSER due to their superior performance according to CASP 12 - CASP 15 were chosen for further analysis. The motif analysis of best models using MotifFinder revealed two, five, and five protein binding motifs, however, the Motif Scan identified seven, six, and eight Post-Translational Modification sites (PTMs) in the BvrR, OMP25, and OMP31 proteins, respectively. Dominant B cell epitopes were predicted at (44-63, 85-93, 126-137, 193-205, and 208-237), (26-46, 52-71, 98-114, 142-155, and 183-200), and (29-45, 58-82, 119-142, 177-198, and 222-251) for the three target proteins. Additionally, cytotoxic T lymphocyte epitopes were detected at (173-181, 189-197, and 202-210), (61-69, 91-99, 159-167, and 181-189), and (3-11, 24-32, 167-175, and 216-224), while T helper lymphocyte epitopes were displayed at (39-53, 57-65, 150-158, 163-171), (79-87, 95-108, 115-123, 128-142, and 189-197), and (39-47, 109-123, 216-224, and 245-253), for the respective target protein. Furthermore, structure-based virtual screening of the ZINC and DrugBank databases using the docking MOE program was followed by ADMET analysis. The best five compounds of the ZINC database revealed docking scores ranged from (- 16.8744 to - 15.1922), (- 16.0424 to - 14.1645), and (- 14.7566 to - 13.3222) for the BvrR, OMP25, and OMP31, respectively. These compounds had good ADMET parameters and no cytotoxicity, while DrugBank compounds didn't meet Lipinski's rule criteria. Therefore, the five selected compounds from the ZINC20 databases may fulfill the pharmacokinetics and could be considered lead molecules for potentially inhibiting Brucella's proteins.
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Affiliation(s)
- Alyaa Elrashedy
- Department of Animal Medicine and Infectious Diseases (Infectious Diseases), Faculty of Veterinary Medicine, University of Sadat City, Sadat City, Egypt.
| | - Mohamed Nayel
- Department of Animal Medicine and Infectious Diseases (Infectious Diseases), Faculty of Veterinary Medicine, University of Sadat City, Sadat City, Egypt
| | - Akram Salama
- Department of Animal Medicine and Infectious Diseases (Infectious Diseases), Faculty of Veterinary Medicine, University of Sadat City, Sadat City, Egypt
| | - Mohammed M Salama
- Physics Department, Medical Biophysics Division, Faculty of Science, Helwan University, Cairo, Egypt
| | - Mohamed E Hasan
- Bioinformatics Department, Genetic Engineering and Biotechnology Research Institute, University of Sadat City, Sadat City, Egypt
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Sulaimany S, Farahmandi K, Mafakheri A. Computational prediction of new therapeutic effects of probiotics. Sci Rep 2024; 14:11932. [PMID: 38789535 PMCID: PMC11126595 DOI: 10.1038/s41598-024-62796-4] [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: 12/12/2023] [Accepted: 05/21/2024] [Indexed: 05/26/2024] Open
Abstract
Probiotics are living microorganisms that provide health benefits to their hosts, potentially aiding in the treatment or prevention of various diseases, including diarrhea, irritable bowel syndrome, ulcerative colitis, and Crohn's disease. Motivated by successful applications of link prediction in medical and biological networks, we applied link prediction to the probiotic-disease network to identify unreported relations. Using data from the Probio database and International Classification of Diseases-10th Revision (ICD-10) resources, we constructed a bipartite graph focused on the relationship between probiotics and diseases. We applied customized link prediction algorithms for this bipartite network, including common neighbors, Jaccard coefficient, and Adamic/Adar ranking formulas. We evaluated the results using Area under the Curve (AUC) and precision metrics. Our analysis revealed that common neighbors outperformed the other methods, with an AUC of 0.96 and precision of 0.6, indicating that basic formulas can predict at least six out of ten probable relations correctly. To support our findings, we conducted an exact search of the top 20 predictions and found six confirming papers on Google Scholar and Science Direct. Evidence suggests that Lactobacillus jensenii may provide prophylactic and therapeutic benefits for gastrointestinal diseases and that Lactobacillus acidophilus may have potential activity against urologic and female genital illnesses. Further investigation of other predictions through additional preclinical and clinical studies is recommended. Future research may focus on deploying more powerful link prediction algorithms to achieve better and more accurate results.
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Affiliation(s)
- Sadegh Sulaimany
- Social and Biological Network Analysis Laboratory (SBNA), Department of Computer Engineering, University of Kurdistan, Sanandaj, Iran.
| | - Kajal Farahmandi
- Department of Industrial and Environmental Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran
| | - Aso Mafakheri
- Social and Biological Network Analysis Laboratory (SBNA), Department of Computer Engineering, University of Kurdistan, Sanandaj, Iran
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Hassanie H, Penteado AB, de Almeida LC, Calil RL, da Silva Emery F, Costa-Lotufo LV, Trossini GHG. SETDB1 as a cancer target: challenges and perspectives in drug design. RSC Med Chem 2024; 15:1424-1451. [PMID: 38799223 PMCID: PMC11113007 DOI: 10.1039/d3md00366c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 03/16/2024] [Indexed: 05/29/2024] Open
Abstract
Genome stability is governed by chromatin structural dynamics, which modify DNA accessibility under the influence of intra- and inter-nucleosomal contacts, histone post-translational modifications (PTMs) and variations, besides the activity of ATP-dependent chromatin remodelers. These are the main ways by which chromatin dynamics are regulated and connected to nuclear processes, which when dysregulated can frequently be associated with most malignancies. Recently, functional crosstalk between histone modifications and chromatin remodeling has emerged as a critical regulatory method of transcriptional regulation during cell destiny choice. Therefore, improving therapeutic outcomes for patients by focusing on epigenetic targets dysregulated in malignancies should help prevent cancer cells from developing resistance to anticancer treatments. For this reason, SET domain bifurcated histone lysine methyltransferase 1 (SETDB1) has gained a lot of attention recently as a cancer target. SETDB1 is a histone lysine methyltransferase that plays an important role in marking euchromatic and heterochromatic regions. Hence, it promotes the silencing of tumor suppressor genes and contributes to carcinogenesis. Some studies revealed that SETDB1 was overexpressed in various human cancer types, which enhanced tumor growth and metastasis. Thus, SETDB1 appears to be an attractive epigenetic target for new cancer treatments. In this review, we have discussed the effects of its overexpression on the progression of tumors and the development of inhibitor drugs that specifically target this enzyme.
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Affiliation(s)
- Haifa Hassanie
- School of Pharmaceutical Sciences, University of São Paulo Brazil
| | | | | | | | - Flávio da Silva Emery
- School of Pharmaceutical Sciences of the Ribeirão Preto, University of São Paulo Brazil
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11
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Mandal P, Pradhan SM, Mathew AA, Benny S, Kumar S, Unni AR, S K K. Exploring the effects of vasoactive constituents in large cardamom: implications for the anti-hypertensive effect via eNOS coupling pathway - an in-vitro study in rat endothelial cells. Nat Prod Res 2024:1-7. [PMID: 38742417 DOI: 10.1080/14786419.2024.2351534] [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: 12/13/2023] [Accepted: 04/30/2024] [Indexed: 05/16/2024]
Abstract
Endothelial dysfunction, linked to reduced eNOS expression and nitric oxide (NO) availability, contributes to cardiovascular diseases (CVDs). Large cardamom exhibits antihypertensive effects by augmenting NO levels and antioxidant activity. To decipher its mechanisms, selected constituents were docked with eNOS-associated target genes such as GTP cyclohydrolase I (GTPCH-1) and (dihydrofolate reductase [DHFR]). Endothelial damage induced by L-NAME and fructose was countered by assessing nitric oxide metabolites (NOx), tetrahydrobipterin (BH4 levels), GCH-I expression and super oxide dismutase (SOD) activity after constituent incubation. Cyanidin-3-O-glucoside and petunidin-3-O-glucoside notably restored impaired vascular markers in both models. These phytoconstituents are likely to activate GCH-BH4-eNOS pathways, upregulating SOD and NO expression, maintaining endothelial integrity. Large cardamom's antihypertensive effects may stem from these components, synergistically enhancing endothelial NO release via the eNOS pathway.
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Affiliation(s)
- Pronay Mandal
- Department of Pharmacology, Amrita School of Pharmacy, Kochi, India
| | | | | | - Sonu Benny
- Department of Pharmaceutical Chemistry, Amrita School of Pharmacy, Kochi, India
| | - Sunil Kumar
- Department of Pharmaceutical Chemistry, Amrita School of Pharmacy, Kochi, India
| | - Ashok R Unni
- Central Lab Animal Facility, Amrita Institute of Medical Sciences, Kochi, India
| | - Kanthlal S K
- Department of Pharmacology, Amrita School of Pharmacy, Kochi, India
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12
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Chandraghatgi R, Ji HF, Rosen GL, Sokhansanj BA. Streamlining Computational Fragment-Based Drug Discovery through Evolutionary Optimization Informed by Ligand-Based Virtual Prescreening. J Chem Inf Model 2024; 64:3826-3840. [PMID: 38696451 PMCID: PMC11197033 DOI: 10.1021/acs.jcim.4c00234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 04/18/2024] [Accepted: 04/19/2024] [Indexed: 05/04/2024]
Abstract
Recent advances in computational methods provide the promise of dramatically accelerating drug discovery. While mathematical modeling and machine learning have become vital in predicting drug-target interactions and properties, there is untapped potential in computational drug discovery due to the vast and complex chemical space. This paper builds on our recently published computational fragment-based drug discovery (FBDD) method called fragment databases from screened ligand drug discovery (FDSL-DD). FDSL-DD uses in silico screening to identify ligands from a vast library, fragmenting them while attaching specific attributes based on predicted binding affinity and interaction with the target subdomain. In this paper, we further propose a two-stage optimization method that utilizes the information from prescreening to optimize computational ligand synthesis. We hypothesize that using prescreening information for optimization shrinks the search space and focuses on promising regions, thereby improving the optimization for candidate ligands. The first optimization stage assembles these fragments into larger compounds using genetic algorithms, followed by a second stage of iterative refinement to produce compounds with enhanced bioactivity. To demonstrate broad applicability, the methodology is demonstrated on three diverse protein targets found in human solid cancers, bacterial antimicrobial resistance, and the SARS-CoV-2 virus. Combined, the proposed FDSL-DD and a two-stage optimization approach yield high-affinity ligand candidates more efficiently than other state-of-the-art computational FBDD methods. We further show that a multiobjective optimization method accounting for drug-likeness can still produce potential candidate ligands with a high binding affinity. Overall, the results demonstrate that integrating detailed chemical information with a constrained search framework can markedly optimize the initial drug discovery process, offering a more precise and efficient route to developing new therapeutics.
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Affiliation(s)
- Rohan Chandraghatgi
- Department
of Biology, Drexel University, Philadelphia, Pennsylvania 19104, United States
| | - Hai-Feng Ji
- Department
of Chemistry, Drexel University, Philadelphia, Pennsylvania 19104, United States
| | - Gail L. Rosen
- Department
of Electrical & Computer Engineering, Drexel University, Philadelphia, Pennsylvania 19104, United States
| | - Bahrad A. Sokhansanj
- Department
of Electrical & Computer Engineering, Drexel University, Philadelphia, Pennsylvania 19104, United States
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13
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Chen Y, Chen Z, Zhu Y, Wen Y, Zhao C, Mu W. Recent Progress in Human Milk Oligosaccharides and Its Antiviral Efficacy. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:7607-7617. [PMID: 38563422 DOI: 10.1021/acs.jafc.3c09460] [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: 04/04/2024]
Abstract
Gastrointestinal (GI)-associated viruses, including rotavirus (RV), norovirus (NV), and enterovirus, usually invade host cells, transmit, and mutate their genetic information, resulting in influenza-like symptoms, acute gastroenteritis, encephalitis, or even death. The unique structures of human milk oligosaccharides (HMOs) enable them to shape the gut microbial diversity and endogenous immune system of human infants. Growing evidence suggests that HMOs can enhance host resistance to GI-associated viruses but without a systematic summary to review the mechanism. The present review examines the lactose- and neutral-core HMOs and their antiviral effects in the host. The potential negative impacts of enterovirus 71 (EV-A71) and other GI viruses on children are extensive and include neurological sequelae, neurodevelopmental retardation, and cognitive decline. However, the differences in the binding affinity of HMOs for GI viruses are vast. Hence, elucidating the mechanisms and positive effects of HMOs against different viruses may facilitate the development of novel HMO derived oligosaccharides.
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Affiliation(s)
- Yihan Chen
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China
| | - Zhengxin Chen
- College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Yingying Zhu
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China
| | - Yuxi Wen
- College of Marine Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
- Department of Analytical and Food Chemistry, Faculty of Sciences, Universidade de Vigo, 32004 Ourense Spain
| | - Chao Zhao
- College of Marine Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Wanmeng Mu
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China
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14
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Xie J, Chen S, Lei J, Yang Y. DiffDec: Structure-Aware Scaffold Decoration with an End-to-End Diffusion Model. J Chem Inf Model 2024; 64:2554-2564. [PMID: 38267393 DOI: 10.1021/acs.jcim.3c01466] [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: 01/26/2024]
Abstract
In molecular optimization, one popular way is R-group decoration on molecular scaffolds, and many efforts have been made to generate R-groups based on deep generative models. However, these methods mostly use information on known binding ligands, without fully utilizing target structure information. In this study, we proposed a new method, DiffDec, to involve 3D pocket constraints by a modified diffusion technique for optimizing molecules through molecular scaffold decoration. For end-to-end generation of R-groups with different sizes, we designed a novel fake atom mechanism. DiffDec was shown to be able to generate structure-aware R-groups with realistic geometric substructures by the analysis of bond angles and dihedral angles and simultaneously generate multiple R-groups for one scaffold on different growth anchors. The growth anchors could be provided by users or automatically determined by our model. DiffDec achieved R-group recovery rates of 69.67% and 45.34% in the single and multiple R-group decoration tasks, respectively, and these values were significantly higher than competing methods (37.33% and 26.85%). According to the molecular docking study, our decorated molecules obtained a better average binding affinity than baseline methods. The docking pose analysis revealed that DiffDec could decorate scaffolds with R-groups that exhibited improved binding affinities and more favorable interactions with the pocket. These results demonstrated the potential and applicability of DiffDec in real-world scaffold decoration for molecular optimization.
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Affiliation(s)
- Junjie Xie
- School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China
- AixplorerBio Inc., Jiaxing 314031, China
| | - Sheng Chen
- School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China
- AixplorerBio Inc., Jiaxing 314031, China
| | - Jinping Lei
- School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou 510006, China
| | - Yuedong Yang
- School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China
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15
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Yang W, Wang Y, Han D, Tang W, Sun L. Recent advances in application of computer-aided drug design in anti-COVID-19 Virials Drug Discovery. Biomed Pharmacother 2024; 173:116423. [PMID: 38493593 DOI: 10.1016/j.biopha.2024.116423] [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: 12/08/2023] [Revised: 03/05/2024] [Accepted: 03/08/2024] [Indexed: 03/19/2024] Open
Abstract
Corona Virus Disease 2019 (COVID-19) is a global pandemic epidemic caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), which poses a serious threat to human health worldwide and results in significant economic losses. With the continuous emergence of new virus strains, small molecule drugs remain the most effective treatment for COVID-19. The traditional drug development process usually requires several years; however, the development of computer-aided drug design (CADD) offers the opportunity to develop innovative drugs quickly and efficiently. The literature review describes the general process of CADD, the viral proteins that play essential roles in the life cycle of SARS-CoV-2 and can serve as therapeutic targets, and examples of drug screening of viral target proteins by applying CADD methods. Finally, the potential of CADD in COVID-19 therapy, the deficiency, and the possible future development direction are discussed.
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Affiliation(s)
- Weiying Yang
- Department of Emergency Medicine, First Hospital of Jilin University, Changchun 130021, China
| | - Ye Wang
- School of Life Sciences, Jilin University, Changchun 130012, China
| | - Dongfeng Han
- Department of Emergency Medicine, First Hospital of Jilin University, Changchun 130021, China
| | - Wenjing Tang
- Department of Emergency Medicine, First Hospital of Jilin University, Changchun 130021, China
| | - Lichao Sun
- Department of Emergency Medicine, First Hospital of Jilin University, Changchun 130021, China.
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16
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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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17
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Nguyen TH, Thai QM, Pham MQ, Minh PTH, Phung HTT. Machine learning combines atomistic simulations to predict SARS-CoV-2 Mpro inhibitors from natural compounds. Mol Divers 2024; 28:553-561. [PMID: 36823394 PMCID: PMC9950021 DOI: 10.1007/s11030-023-10601-1] [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: 11/02/2022] [Accepted: 01/04/2023] [Indexed: 02/25/2023]
Abstract
To date, the COVID-19 pandemic has still been infectious around the world, continuously causing social and economic damage on a global scale. One of the most important therapeutic targets for the treatment of COVID-19 is the main protease (Mpro) of SARS-CoV-2. In this study, we combined machine-learning (ML) model with atomistic simulations to computationally search for highly promising SARS-CoV-2 Mpro inhibitors from the representative natural compounds of the National Cancer Institute (NCI) Database. First, the trained ML model was used to scan the library quickly and reliably for possible Mpro inhibitors. The ML output was then confirmed using atomistic simulations integrating molecular docking and molecular dynamic simulations with the linear interaction energy scheme. The results turned out to show that there was evidently good agreement between ML and atomistic simulations. Ten substances were proposed to be able to inhibit SARS-CoV-2 Mpro. Seven of them have high-nanomolar affinity and are very potential inhibitors. The strategy has been proven to be reliable and appropriate for fast prediction of SARS-CoV-2 Mpro inhibitors, benefiting for new emerging SARS-CoV-2 variants in the future accordingly.
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Affiliation(s)
- Trung Hai Nguyen
- Laboratory of Theoretical and Computational Biophysics, Advanced Institute of Materials Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Quynh Mai Thai
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Minh Quan Pham
- Institute of Natural Products Chemistry, Vietnam Academy of Science and Technology, Hanoi, Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Pham Thi Hong Minh
- Institute of Natural Products Chemistry, Vietnam Academy of Science and Technology, Hanoi, Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Huong Thi Thu Phung
- NTT Hi-Tech Institute, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam
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18
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Ye Q, Lin R, Chen Z, Li J, Zheng C. Isolation, Identification and Chemical Modification of Bufadienolides from Bufo melanostictus Schneider and Their Cytotoxic Activities against Prostate Cancer Cells. Molecules 2024; 29:1571. [PMID: 38611850 PMCID: PMC11013645 DOI: 10.3390/molecules29071571] [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: 01/03/2024] [Revised: 03/10/2024] [Accepted: 03/29/2024] [Indexed: 04/14/2024] Open
Abstract
The traditional Chinese medicine toad venom (Venenum bufonis) has been extensively used to treat various diseases, including cancers, in China and other Southeast Asian countries. The major constituents of toad venom, e.g., bufadienolides and alkaloids, exhibit broad-spectrum pharmacological effects in cancers. Herein, two new bufadienolides (1 and 2), along with eleven known compounds (3-13) were successfully isolated from Bufo melanostictus Schneider. Their structures were elucidated by extensive spectroscopic data and X-ray diffraction analysis. Furthermore, four lactam derivatives were synthesized through the transformation of bufadienolides lactones. The inhibitory effects of these compounds against human prostate cancer cell lines PC-3 and DU145 were evaluated. The outcomes indicated a notable trend, with a substantial subset displaying nanomolar range IC50 values against PC-3 and DU145 cells, underscoring their pronounced cytotoxicity. Moreover, a noteworthy distinction surfaces, wherein lactones consistently outperformed their lactam counterparts, further validating their heightened potency for the treatment of prostate cancer. This study contributes significant preclinical evidence substantiating the therapeutic viability of bufadienolides and toad venom as intervention strategies for prostate cancer.
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Affiliation(s)
- Qingmei Ye
- Key Laboratory of Tropical Medicinal Resource Chemistry of Ministry of Education, Key Laboratory of Tropical Medicinal Plant Chemistry of Hainan Province, College of Chemistry and Chemical Engineering, Hainan Normal University, Haikou 571158, China;
- Hainan General Hospital & Hainan Affiliated Hospital of Hainan Medical University, Haikou 570311, China
| | - Rong Lin
- Hubei Province Key Laboratory of Traditional Chinese Medicine Resource and Chemistry, Department of Pharmacy, Hubei University of Chinese Medicine, Wuhan 430065, China;
| | - Zeping Chen
- Institute of Traditional Chinese Medicine and Natural Products, College of Pharmacy, Jinan University, Guangzhou 510632, China;
| | - Juan Li
- Hubei Province Key Laboratory of Traditional Chinese Medicine Resource and Chemistry, Department of Pharmacy, Hubei University of Chinese Medicine, Wuhan 430065, China;
| | - Caijuan Zheng
- Key Laboratory of Tropical Medicinal Resource Chemistry of Ministry of Education, Key Laboratory of Tropical Medicinal Plant Chemistry of Hainan Province, College of Chemistry and Chemical Engineering, Hainan Normal University, Haikou 571158, China;
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19
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Huang H, Dickhaut J, Weisel M, Mao L, Rankl N, Takeda H, Stam LF, Peacock QM, Höffken HW. Discovery and biological characterization of a novel mesoionic insecticide fenmezoditiaz. PEST MANAGEMENT SCIENCE 2024. [PMID: 38554053 DOI: 10.1002/ps.8108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/25/2024] [Accepted: 03/27/2024] [Indexed: 04/01/2024]
Abstract
BACKGROUND Many piercing-sucking insects have developed resistance or cross-resistance to many insecticides targeting insect neural nicotinic acetylcholine receptor (nAChR). Here we are aiming to present the discovery of a novel mesoionic insecticide, fenmezoditiaz, by BASF through structure-based drug design (SBDD) approaches. It has recently been added to the Insecticide Resistance Action Committee mode of classification (IRAC 4E). It is being developed for plant protection against piercing-sucking pests, especially rice hopper complex. RESULTS The soluble acetylcholine binding protein (AChBP) from the sea slug Aplysia californica was modified using site-directed mutagenesis and based on putative aphid nAChR subunit sequences to create soluble insect-like AChBPs. Among them, insect-like β1 AChBP and native aphid membrane preparation showed the highest correlated biochemical affinity toward structurally diverse ligands. This mutant AChBP was used to understand how insect nAChRs structurally interact with mesoionics, which was then utilized to design novel mesoionics including fenmezoditiaz. It is an excellent systemic insecticide with diverse application methods and has a broad insecticidal spectrum, especially against piercing/sucking insects. It lacks cross-resistance for neonicotinoid resistant plant hoppers. Field-collected brown plant hopper populations from Asian countries showed high susceptibility. CONCLUSIONS Fenmezoditiaz is a systemic insecticide with a broad spectrum, lack of cross-resistance and it could be an additional tool for integrated pest management and insecticide resistance management, especially for the rice hopper complex. © 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
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Affiliation(s)
- Huazhang Huang
- BASF Corporation, Global Insecticide Discovery/ Early Biology, Research Triangle Park, Research Triangle Park, NC, USA
| | - Joachim Dickhaut
- BASF SE, Global Insecticide Discovery/ Chemistry at Ludwigshafen, Ludwigshafen am Rhein, Germany
| | - Martin Weisel
- BASF SE, Molecular Modeling & Drug Discovery, Ludwigshafen, Germany
| | - Lixin Mao
- BASF Corporation, Global Insecticide Discovery/ Early Biology, Research Triangle Park, Research Triangle Park, NC, USA
| | - Nancy Rankl
- BASF Corporation, Global Insecticide Discovery/ Early Biology, Research Triangle Park, Research Triangle Park, NC, USA
| | - Haruka Takeda
- Agricultural Solutions, AgSolution Farm Naruto, BASF Japan Ltd, Naruto Sanmu-shi Chiba, Japan
| | - Lynn F Stam
- BASF Corporation, Global Insecticide Discovery/ Early Biology, Research Triangle Park, Research Triangle Park, NC, USA
| | - Quinn M Peacock
- BASF Corporation, Global Insecticide Discovery/ Early Biology, Research Triangle Park, Research Triangle Park, NC, USA
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20
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Zhang C, Xie L, Lu X, Mao R, Xu L, Xu X. Developing an Improved Cycle Architecture for AI-Based Generation of New Structures Aimed at Drug Discovery. Molecules 2024; 29:1499. [PMID: 38611779 PMCID: PMC11013495 DOI: 10.3390/molecules29071499] [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: 01/25/2024] [Revised: 03/18/2024] [Accepted: 03/21/2024] [Indexed: 04/14/2024] Open
Abstract
Drug discovery involves a crucial step of optimizing molecules with the desired structural groups. In the domain of computer-aided drug discovery, deep learning has emerged as a prominent technique in molecular modeling. Deep generative models, based on deep learning, play a crucial role in generating novel molecules when optimizing molecules. However, many existing molecular generative models have limitations as they solely process input information in a forward way. To overcome this limitation, we propose an improved generative model called BD-CycleGAN, which incorporates BiLSTM (bidirectional long short-term memory) and Mol-CycleGAN (molecular cycle generative adversarial network) to preserve the information of molecular input. To evaluate the proposed model, we assess its performance by analyzing the structural distribution and evaluation matrices of generated molecules in the process of structural transformation. The results demonstrate that the BD-CycleGAN model achieves a higher success rate and exhibits increased diversity in molecular generation. Furthermore, we demonstrate its application in molecular docking, where it successfully increases the docking score for the generated molecules. The proposed BD-CycleGAN architecture harnesses the power of deep learning to facilitate the generation of molecules with desired structural features, thus offering promising advancements in the field of drug discovery processes.
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Affiliation(s)
| | | | | | | | - Lei Xu
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China; (C.Z.); (L.X.); (X.L.); (R.M.)
| | - Xiaojun Xu
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China; (C.Z.); (L.X.); (X.L.); (R.M.)
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21
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Siddiqui AJ, Jamal A, Zafar M, Jahan S. Identification of TBK1 inhibitors against breast cancer using a computational approach supported by machine learning. Front Pharmacol 2024; 15:1342392. [PMID: 38567349 PMCID: PMC10985244 DOI: 10.3389/fphar.2024.1342392] [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: 11/21/2023] [Accepted: 03/07/2024] [Indexed: 04/04/2024] Open
Abstract
Introduction: The cytosolic Ser/Thr kinase TBK1 is of utmost importance in facilitating signals that facilitate tumor migration and growth. TBK1-related signaling plays important role in tumor progression, and there is need to work on new methods and workflows to identify new molecules for potential treatments for TBK1-affecting oncologies such as breast cancer. Methods: Here, we propose the machine learning assisted computational drug discovery approach to identify TBK1 inhibitors. Through our computational ML-integrated approach, we identified four novel inhibitors that could be used as new hit molecules for TBK1 inhibition. Results and Discussion: All these four molecules displayed solvent based free energy values of -48.78, -47.56, -46.78 and -45.47 Kcal/mol and glide docking score of -10.4, -9.84, -10.03, -10.06 Kcal/mol respectively. The molecules displayed highly stable RMSD plots, hydrogen bond patterns and MMPBSA score close to or higher than BX795 molecule. In future, all these compounds can be further refined or validated by in vitro as well as in vivo activity. Also, we have found two novel groups that have the potential to be utilized in a fragment-based design strategy for the discovery and development of novel inhibitors targeting TBK1. Our method for identifying small molecule inhibitors can be used to make fundamental advances in drug design methods for the TBK1 protein which will further help to reduce breast cancer incidence.
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Affiliation(s)
- Arif Jamal Siddiqui
- Department of Biology, College of Science, University of Ha’il, Ha’il, Saudi Arabia
| | - Arshad Jamal
- Department of Biology, College of Science, University of Ha’il, Ha’il, Saudi Arabia
| | - Mubashir Zafar
- Department of Family and Community Medicine, College of Medicine, University of Ha’il, Ha’il, Saudi Arabia
| | - Sadaf Jahan
- Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Majmaah University, Al Majmaah, Saudi Arabia
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22
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Selvaraj C, Pedone E, Lee JK, Singh SK. Editorial: Molecular level atomistic and structural insights on biological macromolecules, inhibition, and dynamics studies. Front Mol Biosci 2024; 11:1362215. [PMID: 38516195 PMCID: PMC10955358 DOI: 10.3389/fmolb.2024.1362215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 02/19/2024] [Indexed: 03/23/2024] Open
Affiliation(s)
- Chandrabose Selvaraj
- Computational and Structural Research in Drug Discovery Lab (CSRDD), Center for Global Health Research, Saveetha Medical College, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India
| | - Emilia Pedone
- Institute of Biostructures and Bioimaging, CNR, Naples, Italy
| | - Jung-Kul Lee
- Department of Chemical Engineering, Konkuk University, Seoul, Republic of Korea
| | - Sanjeev Kumar Singh
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
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23
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Filipić B, Ušjak D, Rambaher MH, Oljacic S, Milenković MT. Evaluation of novel compounds as anti-bacterial or anti-virulence agents. Front Cell Infect Microbiol 2024; 14:1370062. [PMID: 38510964 PMCID: PMC10951914 DOI: 10.3389/fcimb.2024.1370062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 02/21/2024] [Indexed: 03/22/2024] Open
Abstract
Antimicrobial resistance is a global threat, leading to an alarming increase in the prevalence of bacterial infections that can no longer be treated with available antibiotics. The World Health Organization estimates that by 2050 up to 10 million deaths per year could be associated with antimicrobial resistance, which would equal the annual number of cancer deaths worldwide. To overcome this emerging crisis, novel anti-bacterial compounds are urgently needed. There are two possible approaches in the fight against bacterial infections: a) targeting structures within bacterial cells, similar to existing antibiotics; and/or b) targeting virulence factors rather than bacterial growth. Here, for the first time, we provide a comprehensive overview of the key steps in the evaluation of potential new anti-bacterial and/or anti-virulence compounds. The methods described in this review include: a) in silico methods for the evaluation of novel compounds; b) anti-bacterial assays (MIC, MBC, Time-kill); b) anti-virulence assays (anti-biofilm, anti-quorum sensing, anti-adhesion); and c) evaluation of safety aspects (cytotoxicity assay and Ames test). Overall, we provide a detailed description of the methods that are an essential tool for chemists, computational chemists, microbiologists, and toxicologists in the evaluation of potential novel antimicrobial compounds. These methods are cost-effective and have high predictive value. They are widely used in preclinical studies to identify new molecular candidates, for further investigation in animal and human trials.
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Affiliation(s)
- Brankica Filipić
- Department of Microbiology and Immunology, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
| | - Dušan Ušjak
- Laboratory for Molecular Biology, Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
| | - Martina Hrast Rambaher
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Ljubljana, Ljubljana, Slovenia
| | - Slavica Oljacic
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
| | - Marina T. Milenković
- Department of Microbiology and Immunology, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
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24
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Altharawi A, Alqahatani SM, Alanazi MM, Tahir Ul Qamar M. Unveiling MurE ligase potential inhibitors for treating multi-drug resistant Acinetobacter baumannii. J Biomol Struct Dyn 2024; 42:2358-2368. [PMID: 37099644 DOI: 10.1080/07391102.2023.2204499] [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: 03/03/2023] [Accepted: 04/14/2023] [Indexed: 04/28/2023]
Abstract
Acinetobacter baumannii is an opportunistic pathogen with ability to cause serious infection such as bacteremia, ventilator associated pneumonia, and wound infections. As strains of A. baumannii are resistant to almost all clinically used antibiotics and with the emergence of carbapenems resistant phenotypes warrants the search for novel antibiotics. Considering this, herein, a series of computer aided drug designing approach was utilized to search novel chemical scaffolds that bind stronger to MurE ligase enzyme of A. baumannii, which is involved peptidoglycan synthesis. The work identified LAS_22461675, LAS_34000090 and LAS_51177972 compounds as promising binding molecules with MurE enzyme having binding energy score of -10.5 kcal/mol, -9.3 kcal/mol and -8.6 kcal/mol, respectively. The compounds were found to achieve docked inside the MurE substrate binding pocket and established close distance chemical interactions. The interaction energies were dominated by van der Waals and less contributions were seen from hydrogen bonding energy. The dynamic simulation assay predicted the complexes stable with no major global and local changes noticed. The docked stability was also validated by MM/PBSA and MM/GBSA binding free energy methods. The net MM/GBSA binding free energy of LAS_22461675 complex, LAS_34000090 complex and LAS_51177972 complex is -26.25 kcal/mol, -27.23 kcal/mol and -29.64 kcal/mol, respectively. Similarly in case of MM-PBSA, the net energy value was in following order; LAS_22461675 complex (-27.67 kcal/mol), LAS_34000090 complex (-29.94 kcal/mol) and LAS_51177972 complex (-27.32 kcal/mol). The AMBER entropy and WaterSwap methods also confirmed stable complexes formation. Further, molecular features of the compounds were determined that predicted compounds to have good druglike properties and pharmacokinetic favorable. The study concluded the compounds to good candidates to be tested by in vivo and in vitro experimental assays.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Ali Altharawi
- Department of Pharmaceutical Chemistry, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Safar M Alqahatani
- Department of Pharmaceutical Chemistry, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Mohammed M Alanazi
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Muhammad Tahir Ul Qamar
- Department of Bioinformatics and Biotechnology, Government College University Faisalabad (GCUF), Pakistan
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25
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Thai QM, Phung HTT, Pham NQA, Horng JT, Tran PT, Tung NT, Ngo ST. Natural compounds inhibit Monkeypox virus methyltransferase VP39 in silico studies. J Biomol Struct Dyn 2024:1-9. [PMID: 38419271 DOI: 10.1080/07391102.2024.2321509] [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: 09/30/2023] [Accepted: 02/15/2024] [Indexed: 03/02/2024]
Abstract
VP39, an essential 2'-O-RNA methyltransferase enzyme discovered in Monkeypox virus (MPXV), plays a vital role in viral RNA replication and transcription. Inhibition of the enzyme may prevent viral replication. In this context, using a combination of molecular docking and molecular dynamics (MDs) simulations, the inhibitory ability of NCI Diversity Set VII natural compounds to VP39 protein was investigated. It should be noted that the computed binding free energy of ligand via molecular docking and linear interaction energy (LIE) approaches are in good agreement with the corresponding experiments with coefficients of R = 0.72 and 0.75, respectively. NSC 319990, NSC 196515 and NSC 376254 compounds were demonstrated that can inhibit MPVX methyltransferase VP39 protein with the similar affinity compared to available inhibitor sinefungin. Moreover, nine residues involving Gln39, Gly68, Gly72, Asp95, Arg97, Val116, Asp138, Arg140 and Asn156 may be argued that they play an important role in binding process of inhibitors to VP39.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Quynh Mai Thai
- Laboratory of Biophysics, Institute for Advanced Study in Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Huong T T Phung
- NTT Hi-Tech Institute, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam
| | - Ngoc Quynh Anh Pham
- Graduate Institute of Biomedical Sciences, Chang Gung University, Taoyuan, ROC
| | - Jim-Tong Horng
- Graduate Institute of Biomedical Sciences, Chang Gung University, Taoyuan, ROC
| | - Phuong-Thao Tran
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, Hanoi, Vietnam
| | - Nguyen Thanh Tung
- Institute of Materials Science, Vietnam Academy of Science and Technology, Hanoi, Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Son Tung Ngo
- Laboratory of Biophysics, Institute for Advanced Study in Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
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Alawam AS, M Alneghery L, Alwethaynani MS, Alamri MA. A hierarchical approach towards identification of novel inhibitors against L, D-transpeptidase YcbB as an anti-bacterial therapeutic target. J Biomol Struct Dyn 2024:1-11. [PMID: 38411016 DOI: 10.1080/07391102.2024.2322619] [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: 10/22/2023] [Accepted: 02/16/2024] [Indexed: 02/28/2024]
Abstract
The bacterial cell wall, being a vital component for cell viability, is regarded as a promising drug target. The L, D-Transpeptidase YcbB enzyme has been implicated for a significant role in cell wall polymers cross linking during typhoid toxin release, β-lactam resistance and outer membrane defect rescue. These observations have been recorded in different bacterial pathogens such as Salmonella Typhimurium, Citrobacter rodentium, and Salmonella typhi. In this work, we have shown structure based virtual screening of diverse natural and synthetic drug libraries against the enzyme and revealed three compounds as LAS_32135590, LAS_34036730 and LAS-51380924. These compounds showed highly stable energies and the findings are very competitive with the control molecule ((1RG or (4 R,5S)-3-({(3S,5S)-5-[(3-carboxyphenyl)carbamoyl]pyrrolidin-3-yl}sulfanyl)-5-[(1S,2R)-1-formyl-2-hydroxypropyl]-4-methyl-4,5-dihydro-1H-pyrrole-2-carboxylic acid or ertapenem)) used. Compared to control (which has binding energy score of -11.63 kcal/mol), the compounds showed better binding energy. The binding energy score of LAS_32135590, LAS_34036730 and LAS-51380924 is -12.63 kcal/mol, -12.22 kcal/mol and -12.10 kcal/mol, respectively. Further, the docked snapshot of the lead compounds and control were investigated for stability under time dependent dynamics environment. All the three leads complex and control system showed significant equilibrium (mean RMSD < 3 Å) both in term of intermolecular docked conformation and binding interactions network. Further validation on the complex's stability was acquired from the end-state MMPB/GBSA analysis that observed greater contribution from van der Waals forces and electrostatic energy while less contribution was noticed from solvation part. The compounds were also showed good drug-likeness and are non-toxic and non-mutagenic. In short, the compounds can be used in experimental testing's and might be subjected to structure modification to get better results.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Abdullah S Alawam
- Department of Biology, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia
| | - Lina M Alneghery
- Department of Biology, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia
| | - Maher S Alwethaynani
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Shaqra University, Al-Quwayiyah, Saudi Arabia
| | - Mubarak A Alamri
- Department of Pharmaceutical Chemistry, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
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27
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Barbhuiya T, Beard S, Shah ET, Mason S, Bolderson E, O’Byrne K, Guddat LW, Richard DJ, Adams MN, Gandhi NS. Targeting the hSSB1-INTS3 Interface: A Computational Screening Driven Approach to Identify Potential Modulators. ACS OMEGA 2024; 9:8362-8373. [PMID: 38405517 PMCID: PMC10882649 DOI: 10.1021/acsomega.3c09267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 01/20/2024] [Accepted: 01/25/2024] [Indexed: 02/27/2024]
Abstract
Human single-stranded DNA binding protein 1 (hSSB1) forms a heterotrimeric complex, known as a sensor of single-stranded DNA binding protein 1 (SOSS1), in conjunction with integrator complex subunit 3 (INTS3) and C9ORF80. This sensory protein plays an important role in homologous recombination repair of double-strand breaks in DNA to efficiently recruit other repair proteins at the damaged sites. Previous studies have identified elevated hSSB1-mediated DNA repair activities in various cancers, highlighting its potential as an anticancer target. While prior efforts have focused on inhibiting hSSB1 by targeting its DNA binding domain, this study seeks to explore the inhibition of the hSSB1 function by disrupting its interaction with the key partner protein INTS3 in the SOSS1 complex. The investigative strategy entails a molecular docking-based screening of a specific compound library against the three-dimensional structure of INTS3 at the hSSB1 binding interface. Subsequent assessments involve in vitro analyses of protein-protein interaction (PPI) disruption and cellular effects through co-immunoprecipitation and immunofluorescence assays, respectively. Moreover, the study includes an evaluation of the structural stability of ligands at the INTS3 hot-spot site using molecular dynamics simulations. The results indicate a potential in vitro disruption of the INTS3-hSSB1 interaction by three of the tested compounds obtained from the virtual screening with one impacting the recruitment of hSSB1 and INTS3 to chromatin following DNA damage. To our knowledge, our results identify the first set of drug-like compounds that functionally target INTS3-hSSB1 interaction, and this provides the basis for further biophysical investigations that should help to speed up PPI inhibitor discovery.
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Affiliation(s)
- Tabassum
Khair Barbhuiya
- Centre
for Genomics and Personalised Health, and School of Chemistry and
Physics, Faculty of Science, Queensland
University of Technology, 2 George Street, Brisbane, QLD 4000, Australia
- Cancer
and Ageing Research Program, Woolloongabba, QLD 4102, Australia
| | - Sam Beard
- Cancer
and Ageing Research Program, Woolloongabba, QLD 4102, Australia
- Centre
for Genomics and Personalised Health, and School of Biomedical Sciences,
Faculty of Health, Queensland University
of Technology, Kelvin Grove, QLD 4059, Australia
| | - Esha T. Shah
- Cancer
and Ageing Research Program, Woolloongabba, QLD 4102, Australia
- Centre
for Genomics and Personalised Health, and School of Biomedical Sciences,
Faculty of Health, Queensland University
of Technology, Kelvin Grove, QLD 4059, Australia
| | - Steven Mason
- School
of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Emma Bolderson
- Cancer
and Ageing Research Program, Woolloongabba, QLD 4102, Australia
- Centre
for Genomics and Personalised Health, and School of Biomedical Sciences,
Faculty of Health, Queensland University
of Technology, Kelvin Grove, QLD 4059, Australia
| | - Ken O’Byrne
- Cancer
and Ageing Research Program, Woolloongabba, QLD 4102, Australia
- Centre
for Genomics and Personalised Health, and School of Biomedical Sciences,
Faculty of Health, Queensland University
of Technology, Kelvin Grove, QLD 4059, Australia
| | - Luke W. Guddat
- School
of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Derek J. Richard
- Cancer
and Ageing Research Program, Woolloongabba, QLD 4102, Australia
- Centre
for Genomics and Personalised Health, and School of Biomedical Sciences,
Faculty of Health, Queensland University
of Technology, Kelvin Grove, QLD 4059, Australia
| | - Mark N. Adams
- Cancer
and Ageing Research Program, Woolloongabba, QLD 4102, Australia
- Centre
for Genomics and Personalised Health, and School of Biomedical Sciences,
Faculty of Health, Queensland University
of Technology, Kelvin Grove, QLD 4059, Australia
| | - Neha S. Gandhi
- Centre
for Genomics and Personalised Health, and School of Chemistry and
Physics, Faculty of Science, Queensland
University of Technology, 2 George Street, Brisbane, QLD 4000, Australia
- Cancer
and Ageing Research Program, Woolloongabba, QLD 4102, Australia
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28
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Parveen S, Shehzadi S, Shafiq N, Rashid M, Naz S, Mehmood T, Riaz R, S Almaary K, Nafidi HA, Bourhia M. A discovery of potent kaempferol derivatives as multi-target medicines against diabetes as well as bacterial infections: an in silico approach. J Biomol Struct Dyn 2024:1-23. [PMID: 38334277 DOI: 10.1080/07391102.2024.2308773] [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: 09/25/2023] [Accepted: 01/14/2024] [Indexed: 02/10/2024]
Abstract
Flavonoids demonstrate beneficial effects on human health because flavonoids contain important biological properties. Kaempferol is a flavonol, type of flavonoid found in eatable plants and in plants usually employed in ancient drugs (Moringa oleifera, Tilia spp., fern genus spp. and gingko etc.). Some medicinal studies have shown that the use of foods full of kaempferol decreases the risk of many (cancer, vascular) diseases. All the data of 50 kaempferol derivatives were collected from PubChem database. Through Schrödinger software, 3D-QSAR study was performed for 50 compounds by using method of field base. Conformer of kaempferol derivatives was docked against anti-diabetic, anti-microbial co-crystal structures and protein. To monitor the best anti-diabetic and antibacterial agent, particular kaempferol derivatives were downloaded from PubChem database. Virtual screening by molecular docking provided four lead compounds with four different proteins. These hit compounds were found to be potent inhibitor for diabetic enzymes alpha-amylase and DPP IV and had the potential to suppress DNA gyrase and dihydrofolate reductase synthesis. Molecular dynamic simulation of docked complexes evaluates the value of root mean square fluctuation by iMOD server. Kaempferol 3-O-alpha-L-(2, 3-di-Z-p-coumaroyl) rhamnoside (42) compound used as anti-diabetic and kaempferol 3-O-gentiobioside (3) as antibacterial with good results can be used for drug discovery.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Shagufta Parveen
- Synthetic and Natural Product Drug Discovery Laboratory, Department of Chemistry, Government College Women University, Faisalabad, Pakistan
| | - Saman Shehzadi
- Synthetic and Natural Product Drug Discovery Laboratory, Department of Chemistry, Government College Women University, Faisalabad, Pakistan
| | - Nusrat Shafiq
- Synthetic and Natural Product Drug Discovery Laboratory, Department of Chemistry, Government College Women University, Faisalabad, Pakistan
| | - Maryam Rashid
- Synthetic and Natural Product Drug Discovery Laboratory, Department of Chemistry, Government College Women University, Faisalabad, Pakistan
| | - Sadaf Naz
- Department of Chemistry, The University of Lahore, Lahore, Pakistan
| | - Tahir Mehmood
- Centre for Applied Molecular Biology (CAMB), University of the Punjab, Punjab, Pakistan
| | - Rabia Riaz
- Synthetic and Natural Product Drug Discovery Laboratory, Department of Chemistry, Government College Women University, Faisalabad, Pakistan
| | - Khalid S Almaary
- Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Hiba-Allah Nafidi
- Department of Food Science, Faculty of Agricultural and Food Sciences, Laval University, Quebec, QC, Canada
| | - Mohammed Bourhia
- Department of Chemistry and Biochemistry, Faculty of Medicine and Pharmacy, Ibn Zohr University, Laayoune, Morocco
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29
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Nath M, Bhowmik D, Saha S, Nandi R, Kumar D. Identification of potential inhibitor against Leishmania donovani mitochondrial DNA primase through in-silico and in vitro drug repurposing approaches. Sci Rep 2024; 14:3246. [PMID: 38332162 PMCID: PMC10853515 DOI: 10.1038/s41598-024-53316-5] [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: 10/07/2023] [Accepted: 01/30/2024] [Indexed: 02/10/2024] Open
Abstract
Leishmania donovani is the causal organism of leishmaniasis with critical health implications affecting about 12 million people around the globe. Due to less efficacy, adverse side effects, and resistance, the available therapeutic molecules fail to control leishmaniasis. The mitochondrial primase of Leishmania donovani (LdmtPRI1) is a vital cog in the DNA replication mechanism, as the enzyme initiates the replication of the mitochondrial genome of Leishmania donovani. Hence, we target this protein as a probable drug target against leishmaniasis. The de-novo approach enabled computational prediction of the three-dimensional structure of LdmtPRI1, and its active sites were identified. Ligands from commercially available drug compounds were selected and docked against LdmtPRI1. The compounds were chosen for pharmacokinetic study and molecular dynamics simulation based on their binding energies and protein interactions. The LdmtPRI1 gene was cloned, overexpressed, and purified, and a primase activity assay was performed. The selected compounds were verified experimentally by the parasite and primase inhibition assay. Capecitabine was observed to be effective against the promastigote form of Leishmania donovani, as well as inhibiting primase activity. This study's findings suggest capecitabine might be a potential anti-leishmanial drug candidate after adequate further studies.
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Affiliation(s)
- Mitul Nath
- Department of Microbiology, Assam University, Silchar, Assam, 788011, India
| | - Deep Bhowmik
- Department of Microbiology, Assam University, Silchar, Assam, 788011, India
| | - Satabdi Saha
- Department of Microbiology, Assam University, Silchar, Assam, 788011, India
| | - Rajat Nandi
- Department of Microbiology, Assam University, Silchar, Assam, 788011, India
| | - Diwakar Kumar
- Department of Microbiology, Assam University, Silchar, Assam, 788011, India.
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30
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Zheng J, Chen S, Song M, Liu B, Ma S, Wang S, Wang Q, Ding Q, Xia Q, Zhu K, Wang H. Discovery of adjuvants with antibacterial potentiation activity against carbapenemase-producing Enterobacterales based on in silico virtual screening. Int J Antimicrob Agents 2024; 63:107076. [PMID: 38159889 DOI: 10.1016/j.ijantimicag.2023.107076] [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: 06/30/2023] [Revised: 12/04/2023] [Accepted: 12/21/2023] [Indexed: 01/03/2024]
Abstract
Bacterial multi-drug resistance has become a concern worldwide, especially after the emergence of carbapenemases. Adjuvants with antibacterial potentiation activity can resensitise drug-resistant strains to carbapenems. However, only a few adjuvants with antibacterial potentiation activity are currently available in clinical practice. Here, we first docked the library containing more than 30,000 small molecules to carbapenemases including Klebsiella pneumoniae carbapenemase 2 (KPC-2) and New Delhi metallo-β-lactamase-5 (NDM-5), through in silico virtual screening to obtain lead compounds against carbapenemase-producing Enterobacterales. Meanwhile, the in vitro antibacterial potentiation assays revealed that ibandronate, azacytidine, ribostamycin sulfate and cidofovir exhibited synergistic or additive activity in the presence of meropenem, with good biocompatibility based on red blood cell hemolysis and cell viability tests. Furthermore, the combination of meropenem and azacytidine showed high efficacy in a mouse sepsis model infected with an NDM-5-producing clinical strain, with a 100% survival rate, decreased bacterial burden and alleviated pathological deterioration. These results suggest that the virtual screening is a promising strategy to identify new antibiotic adjuvants targeting carbapenemase-producing Enterobacterales.
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Affiliation(s)
- Ji Zheng
- Institute of Medical Technology, Peking University Health Science Center, Beijing, China; Department of Clinical Laboratory, Peking University People's Hospital, Beijing, China
| | - Shang Chen
- National Key Laboratory of Veterinary Public Health and Safety, College of Veterinary Medicine, China Agricultural University, Beijing, China; State Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China
| | - Meirong Song
- National Key Laboratory of Veterinary Public Health and Safety, College of Veterinary Medicine, China Agricultural University, Beijing, China
| | - Binkai Liu
- Key Laboratory of Radiopharmaceuticals, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing, China
| | - Shuai Ma
- Institute of Medical Technology, Peking University Health Science Center, Beijing, China; Department of Clinical Laboratory, Peking University People's Hospital, Beijing, China
| | - Shuyi Wang
- Institute of Medical Technology, Peking University Health Science Center, Beijing, China; Department of Clinical Laboratory, Peking University People's Hospital, Beijing, China
| | - Qi Wang
- Department of Clinical Laboratory, Peking University People's Hospital, Beijing, China
| | - Qi Ding
- Department of Clinical Laboratory, Peking University People's Hospital, Beijing, China
| | - Qing Xia
- State Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China
| | - Kui Zhu
- National Key Laboratory of Veterinary Public Health and Safety, College of Veterinary Medicine, China Agricultural University, Beijing, China
| | - Hui Wang
- Institute of Medical Technology, Peking University Health Science Center, Beijing, China; Department of Clinical Laboratory, Peking University People's Hospital, Beijing, China.
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31
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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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32
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Bhattacharya K, Mahato S, Deka S, Chanu NR, Shrivastava AK, Khanal P. Netting into the Sophoretin pool: An approach to trace GSTP1 inhibitors for reversing chemoresistance. Comput Biol Chem 2024; 108:107981. [PMID: 37976621 DOI: 10.1016/j.compbiolchem.2023.107981] [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: 09/27/2023] [Revised: 11/04/2023] [Accepted: 11/05/2023] [Indexed: 11/19/2023]
Abstract
Chemoresistance, a significant challenge in cancer treatment, is often associated with the cellular glutathione-related detoxification system. The GSTP1 isoenzyme (glutathione S-transferases) plays a critical role in the cytoplasmic inactivation of anticancer drugs. This suggests the identification of GSTP1 inhibitors to combat chemoresistance. We screened Sophoretin (also called quercetin) derivatives for molecular properties, pharmacokinetics, and toxicity profiles. Following that, we conducted molecular docking and simulations between selected derivatives and GSTP1. The best-docked complex, GSTP1-quercetin 7-O-β-D-glucoside, exhibited a binding affinity of -8.1 kcal/mol, with no predicted toxicity and good pharmacokinetic properties. Molecular dynamics simulations confirmed the stability of this complex. Quercetin 7-O-β-D-glucoside shows promise as a lead candidate for addressing chemoresistance in cancer patients, although further experimental studies are needed to validate its efficacy and therapeutic potential.
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Affiliation(s)
- Kunal Bhattacharya
- Pratiksha Institute of Pharmaceutical Sciences, Guwahati, Assam 781026, India; Royal School of Pharmacy, The Assam Royal Global University, Assam 781035, India.
| | - Shikha Mahato
- Pratiksha Institute of Pharmaceutical Sciences, Guwahati, Assam 781026, India
| | - Satyendra Deka
- Pratiksha Institute of Pharmaceutical Sciences, Guwahati, Assam 781026, India
| | - Nongmaithem Randhoni Chanu
- Pratiksha Institute of Pharmaceutical Sciences, Guwahati, Assam 781026, India; Faculty of Pharmaceutical Science, Assam Downtown University, Assam, India
| | - Amit Kumar Shrivastava
- Department of Oriental Pharmacy and Wonkwang-Oriental Medicine Research Institute, Wonkwang University, Iksan 570-749, Republic of Korea
| | - Pukar Khanal
- Department of Pharmacology and Toxicology, KLE College of Pharmacy, Belagavi, KLE Academy of Higher Education and Research (KAHER), Belagavi 590010, India.
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33
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Thi HV, Hoang TN, Le NQK, Chu DT. Application of data science and bioinformatics in RNA therapeutics. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2024; 203:83-97. [PMID: 38360007 DOI: 10.1016/bs.pmbts.2023.12.019] [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: 02/17/2024]
Abstract
Nowadays, information technology (IT) has been holding a significant role in daily life worldwide. The trajectory of data science and bioinformatics promises pioneering personalized therapies, reshaping medical landscapes and patient care. For RNA therapy to reach more patients, a comprehensive understanding of the application of data science and bioinformatics to this therapy is essential. Thus, this chapter has summarized the application of data science and bioinformatics in RNA therapeutics. Data science applications in RNA therapy, such as data integration and analytics, machine learning, and drug development, have been discussed. In addition, aspects of bioinformatics such as RNA design and evaluation, drug delivery system simulation, and databases for personalized medicine have also been covered in this chapter. These insights have shed light on existing evidence and opened potential future directions. From there, scientists can elevate RNA-based therapeutics into an era of tailored treatments and revolutionary healthcare.
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Affiliation(s)
- Hue Vu Thi
- Center for Biomedicine and Community Health, International School, Vietnam National University, Hanoi, Vietnam; Faculty of Applied Sciences, International School, Vietnam National University, Hanoi, Vietnam
| | - Thanh-Nhat Hoang
- Center for Biomedicine and Community Health, International School, Vietnam National University, Hanoi, Vietnam
| | - Nguyen Quoc Khanh Le
- Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; AIBioMed Research Group, Taipei Medical University, Taipei, Taiwan
| | - Dinh-Toi Chu
- Center for Biomedicine and Community Health, International School, Vietnam National University, Hanoi, Vietnam; Faculty of Applied Sciences, International School, Vietnam National University, Hanoi, Vietnam.
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Sharma T, Mondal T, Khan S, Churqui MP, Nyström K, Thombare K, Baig MH, Dong JJ. Identifying novel inhibitors targeting Exportin-1 for the potential treatment of COVID-19. Arch Microbiol 2024; 206:69. [PMID: 38240823 DOI: 10.1007/s00203-023-03761-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: 10/17/2023] [Revised: 11/09/2023] [Accepted: 11/19/2023] [Indexed: 01/23/2024]
Abstract
The nuclear export protein 1 (XPO1) mediates the nucleocytoplasmic transport of proteins and ribonucleic acids (RNAs) and plays a prominent role in maintaining cellular homeostasis. XPO1 has emerged as a promising therapeutic approach to interfere with the lifecycle of many viruses. In our earlier study, we proved the inhibition of XPO1 as a therapeutic strategy for managing SARS-COV-2 and its variants. In this study, we have utilized pharmacophore-assisted computational methods to identify prominent XPO1 inhibitors. After several layers of screening, a few molecules were shortlisted for further experimental validation on the in vitro SARS-CoV-2 cell infection model. It was observed that these compounds reduced spike positivity, suggesting inhibition of SARS-COV-2 infection. The outcome of this study could be considered further for developing novel antiviral therapeutic strategies against SARS-CoV-2.
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Affiliation(s)
- Tanuj Sharma
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Gangnam-gu, Seoul, 06273, Republic of Korea
| | - Tanmoy Mondal
- Department of Laboratory Medicine, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden
- Department of Clinical Chemistry, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Sajid Khan
- Department of Biochemistry, Aligarh Muslim University, Aligarh, India
| | - Marianela Patzi Churqui
- Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, 41345, Gothenburg, Sweden
| | - Kristina Nyström
- Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, 41345, Gothenburg, Sweden
| | - Ketan Thombare
- Department of Laboratory Medicine, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden
- Department of Clinical Chemistry, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Mohammad Hassan Baig
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Gangnam-gu, Seoul, 06273, Republic of Korea.
| | - Jae-June Dong
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Gangnam-gu, Seoul, 06273, Republic of Korea.
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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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Chen C, Zhang B, Tu J, Peng Y, Zhou Y, Yang X, Yu Q, Tan X. Discovery of 4-aminophenylacetamide derivatives as intestine-specific farnesoid X receptor antagonists for the potential treatment of nonalcoholic steatohepatitis. Eur J Med Chem 2024; 264:115992. [PMID: 38043493 DOI: 10.1016/j.ejmech.2023.115992] [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: 09/20/2023] [Revised: 11/21/2023] [Accepted: 11/21/2023] [Indexed: 12/05/2023]
Abstract
Farnesoid X receptor (FXR) plays a key role in bile acid homeostasis, inflammation, fibrosis, lipid and glucose metabolism and is emerging as a promising therapeutic target for nonalcoholic steatohepatitis (NASH). Emerging evidence suggested that intestine-specific FXR antagonists exhibited remarkable metabolic improvements and slowed NASH progression. In this study, we discovered several potent FXR antagonists using a multistage ligand- and structure-based virtual screening approach. Notably, compound V023-9340, which possesses a 4-aminophenylacetamide scaffold, emerged as the most potent FXR antagonist with an IC50 value of 4.27 μM. In vivo, V023-9340 demonstrated selective accumulation in the intestine, substantially ameliorating high-fat diet (HFD)-induced NASH in mice by mitigating hepatic steatosis and inflammation. Mechanistic studies revealed that V023-9340 strongly inhibited intestinal FXR while concurrently feedback-activated hepatic FXR. Further structure-activity relationship optimization employing V023-9340 has resulted in the synthesis of a more efficacious compound V02-8 with an IC50 value of 0.89 μM, which exhibited a 4.8-fold increase in FXR antagonistic activity compared to V023-9340. In summary, 4-aminophenylacetamide derivative V023-9340 represented a novel intestine-specific FXR antagonist and showed improved effects against HFD-induced NASH in mice, which may serve as a promising lead in discovering potential therapeutic drugs for NASH treatment.
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Affiliation(s)
- Cong Chen
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China
| | - Bing Zhang
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China
| | - Jiaojiao Tu
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China
| | - Yanfen Peng
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China
| | - Yihuan Zhou
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China
| | - Xinping Yang
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China
| | - Qiming Yu
- Guangxi Key Laboratory of Environmental Exposure Omics and Life Cycle Health, College of Public Health, Guilin Medical University, Guilin 541199, China.
| | - Xiangduan Tan
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China.
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Khalaf MNA, Soliman THA, Mohamed SS. PLM-GAN: A Large-Scale Protein Loop Modeling Using pix2pix GAN. ACS OMEGA 2024; 9:437-446. [PMID: 38222545 PMCID: PMC10785670 DOI: 10.1021/acsomega.3c05863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 11/01/2023] [Accepted: 11/22/2023] [Indexed: 01/16/2024]
Abstract
Revealing the tertiary structure of proteins holds huge significance as it unveils their vital properties and functions. These intricate three-dimensional configurations comprise diverse interactions including ionic, hydrophobic, and disulfide forces. In certain instances, these structures exhibit missing regions, necessitating the reconstruction of specific segments, thereby resulting in challenges in protein design, which encompasses loop modeling, circular permutation, and interface prediction. To address this problem, we present two pioneering models: pix2pix generative adversarial network (GAN) and PLM-GAN. The pix2pix GAN model is adept at generating and inpainting distance matrices of protein structures, whereas the PLM-GAN model incorporates residual blocks into the U-Net network of the GAN, building upon the foundation of the pix2pix GAN model. To bolster the models' performance, we introduce a novel loss function named the "missing to real regions loss" (LMTR) within the GAN framework. Additionally, we introduce a distinctive approach of pairing two different distance matrices: one representing the native protein structure and the other representing the same structure with a missing region that undergoes changes in each successive epoch. Moreover, we extend the reconstruction of missing regions, encompassing up to 30 amino acids and increase the protein length by 128 amino acids. The evaluation of our pix2pix GAN and PLM-GAN models on a random selection of natural proteins (4ZCB, 3FJB, and 2REZ) demonstrated promising experimental results. Our models constitute significant contributions to addressing intricate challenges in protein structure design. These contributions hold immense potential to propel advancements in protein-protein interactions, drug design, and further innovations in protein engineering. Data, code, trained models, examples, and measurements are available on https://github.com/mena01/PLM-GAN-A-Large-Scale-Protein-Loop-Modeling-Using-pix2pix-GAN_.
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Affiliation(s)
- Mena Nagy A Khalaf
- Information System Department, Faculty of Computer and Information, Assiut University, Assiut 71515, Egypt
| | - Taysir Hassan A Soliman
- Information System Department, Faculty of Computer and Information, Assiut University, Assiut 71515, Egypt
| | - Sara Salah Mohamed
- Information System Department, Faculty of Computer and Information, Assiut University, Assiut 71515, Egypt
- Mathematics and Computer Science Department, Faculty of Science, New Valley University, New Valley 71511, Egypt
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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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Martin RL, Heifetz A, Bodkin MJ, Townsend-Nicholson A. High-Throughput Structure-Based Drug Design (HT-SBDD) Using Drug Docking, Fragment Molecular Orbital Calculations, and Molecular Dynamic Techniques. Methods Mol Biol 2024; 2716:293-306. [PMID: 37702945 DOI: 10.1007/978-1-0716-3449-3_13] [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: 09/14/2023]
Abstract
Structure-based drug design (SBDD) is rapidly evolving to be a fundamental tool for faster and more cost-effective methods of lead drug discovery. SBDD aims to offer a computational replacement to traditional high-throughput screening (HTS) methods of drug discovery. This "virtual screening" technique utilizes the structural data of a target protein in conjunction with large databases of potential drug candidates and then applies a range of different computational techniques to determine which potential candidates are likely to bind with high affinity and efficacy. It is proposed that high-throughput SBDD (HT-SBDD) will significantly enrich the success rate of HTS methods, which currently fluctuates around ~1%. In this chapter, we focus on the theory and utility of high-throughput drug docking, fragment molecular orbital calculations, and molecular dynamics techniques. We also offer a comparative review of the benefits and limitations of traditional methods against more recent SBDD advances. As HT-SBDD is computationally intensive, we will also cover the important role high-performance computing (HPC) clusters play in the future of computational drug discovery.
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Affiliation(s)
- Reuben L Martin
- Research Department of Structural & Molecular Biology, Division of Biosciences, University College London, London, UK.
- Evotec (UK) Ltd., Abingdon, Oxfordshire, UK.
| | | | | | - Andrea Townsend-Nicholson
- Research Department of Structural & Molecular Biology, Division of Biosciences, University College London, London, UK
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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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Jangid K, Devi B, Sahoo A, Kumar V, Dwivedi AR, Thareja S, Kumar R, Kumar V. Virtual screening and molecular dynamics simulation approach for the identification of potential multi-target directed ligands for the treatment of Alzheimer's disease. J Biomol Struct Dyn 2024; 42:509-527. [PMID: 37114423 DOI: 10.1080/07391102.2023.2201838] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 03/15/2023] [Indexed: 04/29/2023]
Abstract
Alzheimer's disease (AD) is a multifactorial neurological disorder characterized by memory loss and cognitive impairment. The currently available single-targeting drugs have miserably failed in the treatment of AD, and multi-target directed ligands (MTDLs) are being explored as an alternative treatment strategy. Cholinesterase and monoamine oxidase enzymes are reported to play a crucial role in the pathology of AD, and multipotent ligands targeting these two enzymes simultaneously are under various phases of design and development. Recent studies have revealed that computational approaches are robust and trusted tools for identifying novel therapeutics. The current research work is focused on the development of potential multi-target directed ligands that simultaneously inhibit acetylcholinesterase (AChE) and monoamine oxidase B (MAO-B) enzymes employing a structure-based virtual screening (SBVS) approach. The ASINEX database was screened after applying pan assay interference and drug-likeness filter to identify novel molecules using three docking precision criteria; High Throughput Virtual Screening (HTVS), Standard Precision (SP), and Extra Precision (XP). Additionally, binding free energy calculations, ADME, and molecular dynamic simulations were employed to get structural insights into the mechanism of protein-ligand binding and pharmacokinetic properties. Three lead molecules viz. AOP19078710, BAS00314308 and BDD26909696 were successfully identified with binding scores of -10.565, -10.543 & -8.066 kcal/mol against AChE and -11.019, -12.357 & -10.068 kcal/mol against MAO-B, better score as compared to the standard inhibitors. In the near future, these molecules will be synthesized and evaluated through in vitro and in vivo assays for their inhibition potential against AChE and MAO-B enzymes.
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Affiliation(s)
- Kailash Jangid
- Laboratory of Organic and Medicinal Chemistry, Department of Chemistry, Central University of Punjab, Bathinda, Punjab, India
- Department of Pharmaceutical Sciences and Natural Products, Central University of Punjab, Bathinda, Punjab, India
| | - Bharti Devi
- Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology, BHU, Varanasi, Uttar Pradesh, India
| | - Ashrulochan Sahoo
- Department of Pharmaceutical Sciences and Natural Products, Central University of Punjab, Bathinda, Punjab, India
| | - Vijay Kumar
- Laboratory of Organic and Medicinal Chemistry, Department of Chemistry, Central University of Punjab, Bathinda, Punjab, India
| | - Ashish Ranjan Dwivedi
- Department of Medicinal Chemistry, Gitam School of Pharmacy Hyderabad, Hyderabad, Telangana, India
| | - Suresh Thareja
- Department of Pharmaceutical Sciences and Natural Products, Central University of Punjab, Bathinda, Punjab, India
| | - Rajnish Kumar
- Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology, BHU, Varanasi, Uttar Pradesh, India
| | - Vinod Kumar
- Laboratory of Organic and Medicinal Chemistry, Department of Chemistry, Central University of Punjab, Bathinda, Punjab, India
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Thakur A, Sharma B, Parashar A, Sharma V, Kumar A, Mehta V. 2D-QSAR, molecular docking and MD simulation based virtual screening of the herbal molecules against Alzheimer's disorder: an approach to predict CNS activity. J Biomol Struct Dyn 2024; 42:148-162. [PMID: 36970779 DOI: 10.1080/07391102.2023.2192805] [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: 10/10/2022] [Accepted: 03/10/2023] [Indexed: 03/29/2023]
Abstract
Acetylcholinesterase (AChE) is one of the key enzyme targets that have been used clinically for the management of Alzheimer's Disorder (AD). Numerous reports in the literature predict and demonstrate in-vitro, and in-silico anticholinergic activity of herbal molecules, however, majority of them failed to find clinical application. To address these issues, we developed a 2D-QSAR model that could efficiently predict the AChE inhibitory activity of herbal molecules along with predicting their potential to cross the blood-brain-barrier (BBB) to exert their beneficial effects during AD. Virtual screening of the herbal molecules was performed and amentoflavone, asiaticoside, astaxanthin, bahouside, biapigenin, glycyrrhizin, hyperforin, hypericin, and tocopherol were predicted as the most promising herbal molecules for inhibiting AChE. Results were validated through molecular docking, atomistic molecular dynamics simulations and Molecular mechanics-Poisson Boltzmann surface area (MM-PBSA) studies against human AChE (PDB ID: 4EY7). To determine whether or not these molecules can cross BBB to inhibit AChE within the central nervous system (CNS) for being beneficial for the management of AD, we determined a CNS Multi-parameter Optimization (MPO) score, which was found in the range of 1 to 3.76. Overall, the best results were observed for amentoflavone and our results demonstrated a PIC50 value of 7.377 nM, molecular docking score of -11.5 kcal/mol, and CNS MPO score of 3.76. In conclusion, we successfully developed a reliable and efficient 2D-QSAR model and predicted amentoflavone to be the most promising molecule that could inhibit human AChE enzyme within the CNS and could prove beneficial for the management of AD.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Aman Thakur
- DCO, Govt. of Rajasthan, Bharatpur, Rajasthan, India
| | - Bhanu Sharma
- Structural Bioinformatics Lab, CSIR-Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur, Himachal Pradesh, India
- Biotechnology Division, CSIR-IHBT, Palampur, Himachal Pradesh, India
- Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Arun Parashar
- School of Pharmaceutical Sciences, Shoolini University of Biotechnology and Management Sciences, Solan, Himachal Pradesh, India
| | - Vivek Sharma
- Department of Pharmacology, Govt. College of Pharmacy, Shimla, Himachal Pradesh, India
| | - Ajay Kumar
- Institute of Pharmaceutical Sciences, Kurukshetra University, Kurukshetra, Haryana, India
| | - Vineet Mehta
- Department of Pharmacology, Govt. College of Pharmacy, Shimla, Himachal Pradesh, India
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Kaur A, Sharma K, Sharma N, Aggarwal G. An Insight into the Repurposing of Phytoconstituents obtained from Delhi's Aravalli Biodiversity Park as Antifungal Agents. Infect Disord Drug Targets 2024; 24:e020224226666. [PMID: 38305295 DOI: 10.2174/0118715265282411240119061441] [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: 09/15/2023] [Revised: 12/04/2023] [Accepted: 12/11/2023] [Indexed: 02/03/2024]
Abstract
The global prevalence of fungal infections is alarming in both the pre- and post- COVID period. Due to a limited number of antifungal drugs, there are hurdles in treatment strategies for fungal infections due to toxic potential, drug interactions, and the development of fungal resistance. All the antifungal targets (existing and newer) and pipeline molecules showing promise against these targets are reviewed. The objective was to predict or repurpose phyto-based antifungal compounds based on a dual target inhibition approach (Sterol-14-α- demethylase and HSP-90) using a case study. In pursuit of repurposing the phytochemicals as antifungal agents, a team of researchers visited Aravalli Biodiversity Park (ABP), Delhi, India, to collect information on available medicinal plants. From 45 plants, a total of 1149 ligands were collected, and virtual screening was performed using Schrodinger Suite 2016 software to get 83 hits against both the target proteins: Sterol-14-α-demethylase and HSP-90. After analysis of docking results, ligands were selected based on their interaction against both the target proteins and comparison with respective standard ligands (fluconazole and ganetespib). We have selected Isocarthamidin, Quercetin and Boeravinone B based on their docking score and binding interaction against the HSP-90 (Docking Score -9.65, -9.22 and -9.21, respectively) and 14-α-demethylase (Docking Score -9.19, -10.76 and -9.74 respectively). The docking protocol was validated and MM/GBSA studies depicted better stability of selected three ligands (Isocarthamidin, Quercetin, Boeravinone B) complex as compared to standard complex. Further, MD simulation studies were performed using the Desmond (67) software package version 2018-4. All the findings are presented as a case study for the prediction of dual targets for the repurposing of certain phytochemicals as antifungal agents.
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Affiliation(s)
- Amanpreet Kaur
- Delhi Pharmaceutical Sciences and Research University, M.B. Road, Sector III, Pushp Vihar, New Delhi, 110017, India
| | - Kalicharan Sharma
- Delhi Pharmaceutical Sciences and Research University, M.B. Road, Sector III, Pushp Vihar, New Delhi, 110017, India
| | - Neetika Sharma
- Delhi Pharmaceutical Sciences and Research University, M.B. Road, Sector III, Pushp Vihar, New Delhi, 110017, India
| | - Geeta Aggarwal
- Delhi Pharmaceutical Sciences and Research University, M.B. Road, Sector III, Pushp Vihar, New Delhi, 110017, India
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Zaib S, Rana N, Ali HS, Hussain N, Areeba, Ogaly HA, Al-Zahrani FAM, Khan I. Discovery of druggable potent inhibitors of serine proteases and farnesoid X receptor by ligand-based virtual screening to obstruct SARS-CoV-2. Int J Biol Macromol 2023; 253:127379. [PMID: 37838109 DOI: 10.1016/j.ijbiomac.2023.127379] [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] [Received: 05/08/2023] [Revised: 09/12/2023] [Accepted: 10/09/2023] [Indexed: 10/16/2023]
Abstract
The coronavirus, a subfamily of the coronavirinae family, is an RNA virus with over 40 variations that can infect humans, non-human mammals and birds. There are seven types of human coronaviruses, including SARS-CoV-2, is responsible for the recent COVID-19 pandemic. The current study is focused on the identification of drug molecules for the treatment of COVID-19 by targeting human proteases like transmembrane serine protease 2 (TMPRSS2), furin, cathepsin B, and a nuclear receptor named farnesoid X receptor (FXR). TMPRSS2 and furin help in cleaving the spike protein of the SARS-CoV-2 virus, while cathepsin B plays a critical role in the entry and pathogenesis. FXR, on the other hand, regulates the expression of ACE2, and its inhibition can reduce SARS-CoV-2 infection. By inhibiting these four protein targets with non-toxic inhibitors, the entry of the infectious agent into host cells and its pathogenesis can be obstructed. We have used the BioSolveIT suite for pharmacophore-based computational drug designing. A total of 1611 ligands from the ligand library were docked with the target proteins to obtain potent inhibitors on the basis of pharmacophore. Following the ADMET analysis and protein ligand interactions, potent and druggable inhibitors of the target proteins were obtained. Additionally, toxic substructures and the less toxic route of administration of the most potent inhibitors in rodents were also determined computationally. Compounds namely N-(diaminomethylene)-2-((3-((1R,3R)-3-(2-(methoxy(methyl)amino)-2-oxoethyl)cyclopentyl)propyl)amino)-2-oxoethan-1-aminium (26), (1R,3R)-3-(((2-ammonioethyl)ammonio)methyl)-1-((4-propyl-1H-imidazol-2-yl)methyl)piperidin-1-ium (29) and (1R,3R)-3-(((2-ammonioethyl)ammonio)methyl)-1-((1-propyl-1H-pyrazol-4-yl)methyl)piperidin-1-ium (30) were found as the potent inhibitors of TMPRSS2, whereas, 1-(1-(1-(1H-tetrazol-1-yl)cyclopropane-1‑carbonyl)piperidin-4-yl)azepan-2-one (6), (2R)-4-methyl-1-oxo-1-((7R,11S)-4-oxo-6,7,8,9,10,11-hexahydro-4H-7,11-methanopyrido[1,2-a]azocin-9-yl)pentan-2-aminium (12), 4-((1-(3-(3,5-dimethylisoxazol-4-yl)propanoyl)piperidin-4-yl)methyl)morpholin-4-ium (13), 1-(4,6-dimethylpyrimidin-2-yl)-N-(3-oxocyclohex-1-en-1-yl)piperidine-4-carboxamide (14), 1-(4-(1,5-dimethyl-1H-1,2,4-triazol-3-yl)piperidin-1-yl)-3-(3,5-dimethylisoxazol-4-yl)propan-1-one (25) and N,N-dimethyl-4-oxo-4-((1S,5R)-8-oxo-5,6-dihydro-1H-1,5-methanopyrido[1,2-a][1,5]diazocin-3(2H,4H,8H)-yl)butanamide (31) inhibited the FXR preferentially. In case of cathepsin B, N-((5-benzoylthiophen-2-yl)methyl)-2-hydrazineyl-2-oxoacetamide (2) and N-([2,2'-bifuran]-5-ylmethyl)-2-hydrazineyl-2-oxoacetamide (7) were identified as the most druggable inhibitors whereas 1-amino-2,7-diethyl-3,8-dioxo-6-(p-tolyl)-2,3,7,8-tetrahydro-2,7-naphthyridine-4‑carbonitrile (5) and (R)-6-amino-2-(2,3-dihydroxypropyl)-1H-benzo[de]isoquinoline-1,3(2H)-dione (20) were active against furin.
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Affiliation(s)
- Sumera Zaib
- Department of Basic and Applied Chemistry, Faculty of Science and Technology, University of Central Punjab, Lahore 54590, Pakistan.
| | - Nehal Rana
- Department of Basic and Applied Chemistry, Faculty of Science and Technology, University of Central Punjab, Lahore 54590, Pakistan
| | - Hafiz Saqib Ali
- INEOS Oxford Institute for Antimicrobial Research and Chemistry Research Laboratory, Department of Chemistry, University of Oxford, 12 Mansfield Road, Oxford OX1 3TA, United Kingdom
| | - Nadia Hussain
- Department of Pharmaceutical Sciences, College of Pharmacy, Al Ain University, Al Ain, P.O. Box 64141, United Arab Emirates; AAU Health and Biomedical Research Center, Al Ain University, Abu Dhabi, P.O. Box 144534, United Arab Emirates
| | - Areeba
- Department of Basic and Applied Chemistry, Faculty of Science and Technology, University of Central Punjab, Lahore 54590, Pakistan
| | - Hanan A Ogaly
- Chemistry Department, College of Science, King Khalid University, Abha 61421, Saudi Arabia
| | - Fatimah A M Al-Zahrani
- Chemistry Department, College of Science, King Khalid University, Abha 61421, Saudi Arabia
| | - Imtiaz Khan
- Department of Chemistry and Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester M1 7DN, United Kingdom.
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Tayal S, Singh V, Bhatnagar S. 3D-QSAR and ADMET studies of morpholino-pyrimidine inhibitors of DprE1 from Mycobacterium tuberculosis. J Biomol Struct Dyn 2023:1-20. [PMID: 38112325 DOI: 10.1080/07391102.2023.2294496] [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: 07/18/2023] [Accepted: 12/01/2023] [Indexed: 12/21/2023]
Abstract
DprE1 is involved in the synthesis of Mycobacterium tuberculosis cell wall and is a potent drug target for Tuberculosis (TB) treatment. The structure and dynamics of the loops L-I and L-II flanking the inhibitor binding site was studied using molecular dynamics (MD) simulation and MMPBSA in Amber v18. Docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) of 55 Morpholino-pyrimidine (MP) inhibitors was carried out using Autodock v1.2.0 and Forge v10. ADMET analysis was done using SwissADME and pkCSM. All MP inhibitors docked in the DprE1 binding pocket, making contacts with L-II residues. MD studies showed that L-I and L-II unfold in the absence of the inhibitor but fold stably structure with reduced protein motions in the presence of MP-38, the highest affinity inhibitor. This was confirmed by k-means clustering and secondary structure analysis. L-II residues, L317, F320 and R325 contributed most towards the MMPBSA binding free energy of MP-38. A robust field-based 3D-QSAR model showed values of r2train = 0.982, r2test = 0.702 and q2 = 0.516. The MP inhibitor field points were broadly divided into negative electrostatics near the A, B rings and hydrophobic electrostatics near the D, E rings. Addition of negative groups at methanone position and ring B as well as addition of hydrophobic and bulky groups at ring E will improve activity. Highly active compounds 47, 49 and 50 of MP series exhibited highly favourable drug-like properties. SAR and ADMET insights attained from this model will help in the development of active DprE1 inhibitors in future.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Sonali Tayal
- Computational and Structural Biology Laboratory, Department of Biological Sciences and Engineering, Netaji Subhas University of Technology, Dwarka, New Delhi, India
| | - Vasundhara Singh
- Computational and Structural Biology Laboratory, Department of Biological Sciences and Engineering, Netaji Subhas University of Technology, Dwarka, New Delhi, India
| | - Sonika Bhatnagar
- Computational and Structural Biology Laboratory, Department of Biological Sciences and Engineering, Netaji Subhas University of Technology, Dwarka, New Delhi, India
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46
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Chowdhury R, Bhuia MS, Rakib AI, Hasan R, Coutinho HDM, Araújo IM, de Menezes IRA, Islam MT. Assessment of Quercetin Antiemetic Properties: In Vivo and In Silico Investigations on Receptor Binding Affinity and Synergistic Effects. PLANTS (BASEL, SWITZERLAND) 2023; 12:4189. [PMID: 38140516 PMCID: PMC10747098 DOI: 10.3390/plants12244189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 12/01/2023] [Accepted: 12/15/2023] [Indexed: 12/24/2023]
Abstract
Quercetin (QUA), a flavonoid compound, is ubiquitously found in plants and has demonstrated a diverse range of biological activities. The primary objective of the current study is to assess the potential antiemetic properties of QUA using an in vivo and in silico approach. In this experiment, 4-day-old chicks were purchased to induce emesis by orally administering copper sulfate pentahydrate (CuSO4·5H2O) at a dose of 50 mg/kg (orally). Domperidone (DOM) (6 mg/kg), Hyoscine (HYS) (21 mg/kg), and Ondansetron (OND) (5 mg/kg) were treated as positive controls (PCs), and distilled water and a trace amount of Tween 80 mixture was employed as a negative control (NC). QUA was given orally at two distinct doses (25 and 50 mg/kg). Additionally, QUA (50 mg/kg) and PCs were administered separately or in combination to assess their antagonistic or synergistic effects on the chicks. The binding affinity of QUA and referral ligands towards the serotonin receptor (5HT3), dopamine receptors (D2 and D3), and muscarinic acetylcholine receptors (M1-M5) were estimated, and ligand-receptor interactions were visualized through various computational tools. In vivo findings indicate that QUA (25 and 50 mg/kg) has a significant effect on reducing the number of retches (16.50 ± 4.65 and 10.00 ± 4.19 times) and increasing the chick latency period (59.25 ± 4.75 and 94.25 ± 4.01 s), respectively. Additionally, QUA (50 mg/kg) in combination with Domperidone and Ondansetron exhibited superior antiemetic effects, reducing the number of retches and increasing the onset of emesis-inducing time. Furthermore, it is worth noting that QUA exhibited the strongest binding affinity against the D2 receptor with a value of -9.7 kcal/mol through the formation of hydrogen and hydrophobic bonds. In summary, the study found that QUA exhibited antiemetic activity in chicks, potentially by interacting with the D2 receptor pathway.
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Affiliation(s)
- Raihan Chowdhury
- Department of Pharmacy, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh; (R.C.); (M.S.B.); (A.I.R.); (R.H.)
| | - Md. Shimul Bhuia
- Department of Pharmacy, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh; (R.C.); (M.S.B.); (A.I.R.); (R.H.)
| | - Asraful Islam Rakib
- Department of Pharmacy, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh; (R.C.); (M.S.B.); (A.I.R.); (R.H.)
| | - Rubel Hasan
- Department of Pharmacy, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh; (R.C.); (M.S.B.); (A.I.R.); (R.H.)
| | | | - Isaac Moura Araújo
- Department of Biological Chemistry, Regional University of Cariri—URCA, Crato 63105-000, Brazil; (H.D.M.C.); (I.M.A.)
| | - Irwin Rose Alencar de Menezes
- Department of Biological Chemistry, Regional University of Cariri—URCA, Crato 63105-000, Brazil; (H.D.M.C.); (I.M.A.)
| | - Muhammad Torequl Islam
- Department of Pharmacy, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh; (R.C.); (M.S.B.); (A.I.R.); (R.H.)
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47
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Gu M, Sun S, You Q, Wang L. Forward or Backward: Lessons Learned from Small Molecule Drugs Approved by FDA from 2012 to 2022. Molecules 2023; 28:7941. [PMID: 38138431 PMCID: PMC10745639 DOI: 10.3390/molecules28247941] [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: 10/23/2023] [Revised: 11/22/2023] [Accepted: 11/28/2023] [Indexed: 12/24/2023] Open
Abstract
At every juncture in history, the design and identification of new drugs pose significant challenges. To gain valuable insights for future drug development, we conducted a detailed analysis of New Molecular Entitiy (NME) approved by the Food and Drug Administration (FDA) from 2012 to 2022 and focused on the analysis of first-in-class (FIC) small-molecules from a perspective of a medicinal chemist. We compared the change of numbers between all the FDA-approved NMEs and FIC, which could be more visual to analyze the changing trend of FIC. To get a more visual change of molecular physical properties, we computed the annual average trends in molecular weight for FIC across various therapeutic fields. Furthermore, we consolidated essential information into three comprehensive databases, which covered the indications, canonical SMILES, structural formula, research and development (R&D) institutions, molecular weight, calculated LogP (CLogP), and route of administration on all the small-molecule pharmaceutical. Through the analysis of the database of 11 years of approvals, we forecast the development trend of NME approval in the future.
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Affiliation(s)
- Mingxiao Gu
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Design and Optimization, China Pharmaceutical University, Nanjing 210009, China
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Sudan Sun
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Design and Optimization, China Pharmaceutical University, Nanjing 210009, China
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Qidong You
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Design and Optimization, China Pharmaceutical University, Nanjing 210009, China
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Lei Wang
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Design and Optimization, China Pharmaceutical University, Nanjing 210009, China
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
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48
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Alzain AA, Elbadwi FA, Mukhtar RM, Shoaib TH, Abdelmoniem N, Miski SF, Ghazawi KF, Alsulaimany M, Mohamed SGA, Ainousah BE, Hussein HGA, Mohamed GA, Ibrahim SRM. Design of new Mcl-1 inhibitors for cancer using fragments hybridization, molecular docking, and molecular dynamics studies. J Biomol Struct Dyn 2023:1-13. [PMID: 37962580 DOI: 10.1080/07391102.2023.2281637] [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: 08/09/2023] [Accepted: 11/04/2023] [Indexed: 11/15/2023]
Abstract
Apoptosis is a critical process that regulates cell survival and death and plays an essential role in cancer development. The Bcl-2 protein family, including myeloid leukemia 1 (Mcl-1), is a key regulator of the intrinsic apoptosis pathway, and its overexpression in many human cancers has prompted efforts to develop Mcl-1 inhibitors as potential anticancer agents. In this study, we aimed to design new Mcl-1 inhibitors using various computational techniques. First, we used the Mcl-1 receptor-ligand complex to build an e-pharmacophore hypothesis and screened a library of 567,000 fragments from the Enamine database. We obtained 410 fragments and used them to design 92,384 novel compounds, which we then docked into the Mcl-1 binding cavity using HTVS, SP, and XP docking modes of Glide. To assess their suitability as drug candidates, we conducted MM-GBSA calculations and ADME prediction, leading to the identification of 10 compounds with excellent binding affinity and favorable pharmacokinetic properties. To further investigate the interaction strength, we performed molecular dynamics simulations on the top three Mcl-1 receptor-ligand complexes to study their interaction stability. Overall, our findings suggest that these compounds have promising potential as anticancer agents, pending further experimental validation such as Mcl-1 apoptosis Assay. By combining experimental methods with various in silico approaches, these techniques prove to be invaluable for identifying novel drug candidates with distinct therapeutic applications using fragment-based drug design. This methodology has the potential to expedite the drug discovery process while also reducing its costs.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Abdulrahim A Alzain
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani, Sudan
| | - Fatima A Elbadwi
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani, Sudan
| | - Rua M Mukhtar
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani, Sudan
| | - Tagyedeen H Shoaib
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani, Sudan
| | - Nihal Abdelmoniem
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani, Sudan
| | - Samar F Miski
- Department of Pharmacology and Toxicology, College of Pharmacy, Taibah University, Al-Madinah Al-Munawwarah, Saudi Arabia
| | - Kholoud F Ghazawi
- Pharmacy Practice Department, College of Pharmacy, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Marwa Alsulaimany
- Department of Pharmacognosy & Pharmaceutical Chemistry, College of Pharmacy, Taibah University, Medina, Saudi Arabia
| | | | - Bayan E Ainousah
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Hazem G A Hussein
- Preparatory Year Program, Batterjee Medical College, Jeddah, Saudi Arabia
| | - Gamal A Mohamed
- Department of Natural Products and Alternative Medicine, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Sabrin R M Ibrahim
- Preparatory Year Program, Department of Chemistry, Batterjee Medical College, Jeddah, Saudi Arabia
- Department of Pharmacognosy, Faculty of Pharmacy, Assiut University, Assiut, Egypt
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49
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Bugnon M, Goullieux M, Röhrig UF, Perez MAS, Daina A, Michielin O, Zoete V. SwissParam 2023: A Modern Web-Based Tool for Efficient Small Molecule Parametrization. J Chem Inf Model 2023; 63:6469-6475. [PMID: 37853543 PMCID: PMC10649791 DOI: 10.1021/acs.jcim.3c01053] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Indexed: 10/20/2023]
Abstract
Most steps of drug discovery are now routinely supported and accelerated by computer-aided drug design tools. Among them, structure-based approaches use the three-dimensional structure of the targeted biomacromolecule as a major source of information. When it comes to calculating the interactions of small molecules with proteins using the equations of molecular mechanics, topologies, atom typing, and force field parameters are required. However, generating parameters for small molecules remains challenging due to the large number of existing chemical groups. The SwissParam web tool was first released in 2011 with the aim of generating parameters and topologies for small molecules based on the Merck molecular force field (MMFF) while being compatible with the CHARMM22/27 force field. Here, we present an updated version of SwissParam, providing various new features, including the possibility to setup covalent ligands. Molecules can now be imported from different file formats or via a molecular sketcher. The MMFF-based approach has been updated to provide parameters and topologies compatible with the CHARMM36 force field. An option was added to generate small molecule parametrizations following the CHARMM General Force Field via the multipurpose atom-typer for CHARMM (MATCH) approach. Additionally, SwissParam now generates information on probable alternative tautomers and protonation states of the query molecule so that the user can consider all microspecies relevant to its compound. The new version of SwissParam is freely available at www.swissparam.ch and can also be accessed through a newly implemented command-line interface.
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Affiliation(s)
- Marine Bugnon
- Molecular
Modeling Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | - Mathilde Goullieux
- Molecular
Modeling Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | - Ute F. Röhrig
- Molecular
Modeling Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | - Marta A. S. Perez
- Molecular
Modeling Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | - Antoine Daina
- Molecular
Modeling Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | - Olivier Michielin
- Molecular
Modeling Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
- Department
of Oncology, Geneva University Hospital
(HUG), CH-1205 Genève, Switzerland
| | - Vincent Zoete
- Molecular
Modeling Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
- Department
of Oncology UNIL-CHUV, Ludwig Institute for Cancer Research, Lausanne Branch, University of Lausanne (UNIL), CH-1015 Lausanne, Switzerland
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50
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Ahmed AH, Jassim TS, Ali RW, Hameed AR, Alfalki AM. Systemic computational investigation to identify potential inhibitors against cancer by targeting P21-activated kinase 4 and D(CGATCG). J Biomol Struct Dyn 2023; 41:9356-9365. [PMID: 36326467 DOI: 10.1080/07391102.2022.2141894] [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: 08/22/2022] [Accepted: 10/24/2022] [Indexed: 11/06/2022]
Abstract
Cancer accounts for more than 10 million deaths in the year 2020. Development of drugs that specifically target cancer signaling pathways and proteins attain significant importance in the recent past. The p21-activated kinase 4 enzyme, which plays diverse functions in cancer and is reported in elevated expression makes this enzyme an attractive anti-cancer drug target. Similarly, cancer cells' DNA could also serve as a good platform for anti-cancer drug development. Herein, a robust in silico framework is designed to virtually screen multiple drug libraries from diverse sources to identify potential binders of the mentioned cancer targets. The virtual screening process identified three compounds (BAS_01059603, ASN_10027856, and ASN_06916672) as best docked molecules with a binding energy score of ≤ -10 kcal/mol for p21-activated kinase 4 and ≤ -6 kcal/mol for D(CGATCG). In the docking analysis, the filtered compounds revealed stable binding to the same site to which controls bind in X-ray structures. The binding interactions of the compounds with receptors are dominated by van der Waals interactions. The average root mean square deviation (rmsd) value for p21-activated kinase 4 systems is noticed at ∼2 Å, while for D(CGATCG), the average rmsd is 2.7 Å. The MMGB/PBSA interpreted ASN_12674021 to show strong intermolecular binding energy compared to the other two systems and control in both receptors. Moreover, the entropy energy contribution is less than the mean binding energy. In short, the compounds are showing promising binding to the biomolecules and therefore must be evaluated for anti-cancer activity in experimental studies.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Ameen Haider Ahmed
- Department of Medical Laboratory Technique, Al Salam University College, Baghdad, Iraq
| | - Tabarak Sabah Jassim
- Department of Medical Laboratory Technique, Dijlah University College, Baghdad University, Baghdad, Iraq
| | - Rusul Waleed Ali
- Department of Medical Laboratory Technique, Dijlah University College, Baghdad University, Baghdad, Iraq
| | - Alaa R Hameed
- Department of Medical Laboratory Techniques, School of Life Sciences, Dijlah University College, Baghdad, Iraq
| | - Ali Mamoon Alfalki
- College of Health Professions, University of New England, Biddeford, ME, USA
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