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Jørgensen FK, Delcey MG, Hedegård ED. Perspective: multi-configurational methods in bio-inorganic chemistry. Phys Chem Chem Phys 2024. [PMID: 38868993 DOI: 10.1039/d4cp01297f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2024]
Abstract
Transition metal ions play crucial roles in the structure and function of numerous proteins, contributing to essential biological processes such as catalysis, electron transfer, and oxygen binding. However, accurately modeling the electronic structure and properties of metalloproteins poses significant challenges due to the complex nature of their electronic configurations and strong correlation effects. Multiconfigurational quantum chemistry methods are, in principle, the most appropriate tools for addressing these challenges, offering the capability to capture the inherent multi-reference character and strong electron correlation present in bio-inorganic systems. Yet their computational cost has long hindered wider adoption, making methods such as density functional theory (DFT) the method of choice. However, advancements over the past decade have substantially alleviated this limitation, rendering multiconfigurational quantum chemistry methods more accessible and applicable to a wider range of bio-inorganic systems. In this perspective, we discuss some of these developments and how they have already been used to answer some of the most important questions in bio-inorganic chemistry. We also comment on ongoing developments in the field and how the future of the field may evolve.
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Affiliation(s)
- Frederik K Jørgensen
- Department of Physics, Chemistry, and Pharmacy, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark.
| | - Mickaël G Delcey
- Department of Chemistry, Lund University, Naturvetarvägen 14, 221 00 Lund, Sweden
| | - Erik D Hedegård
- Department of Physics, Chemistry, and Pharmacy, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark.
- Department of Chemistry, Lund University, Naturvetarvägen 14, 221 00 Lund, Sweden
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2
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Bhatt R, Koes DR, Durrant JD. CENsible: Interpretable Insights into Small-Molecule Binding with Context Explanation Networks. J Chem Inf Model 2024. [PMID: 38847393 DOI: 10.1021/acs.jcim.4c00825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
We present a novel and interpretable approach for assessing small-molecule binding using context explanation networks. Given the specific structure of a protein/ligand complex, our CENsible scoring function uses a deep convolutional neural network to predict the contributions of precalculated terms to the overall binding affinity. We show that CENsible can effectively distinguish active vs inactive compounds for many systems. Its primary benefit over related machine-learning scoring functions, however, is that it retains interpretability, allowing researchers to identify the contribution of each precalculated term to the final affinity prediction, with implications for subsequent lead optimization.
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Affiliation(s)
- Roshni Bhatt
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States
| | - David Ryan Koes
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States
| | - Jacob D Durrant
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States
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3
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Tian T, Li S, Zhang Z, Chen L, Zou Z, Zhao D, Zeng J. Benchmarking compound activity prediction for real-world drug discovery applications. Commun Chem 2024; 7:127. [PMID: 38834746 DOI: 10.1038/s42004-024-01204-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 05/16/2024] [Indexed: 06/06/2024] Open
Abstract
Identifying active compounds for target proteins is fundamental in early drug discovery. Recently, data-driven computational methods have demonstrated promising potential in predicting compound activities. However, there lacks a well-designed benchmark to comprehensively evaluate these methods from a practical perspective. To fill this gap, we propose a Compound Activity benchmark for Real-world Applications (CARA). Through carefully distinguishing assay types, designing train-test splitting schemes and selecting evaluation metrics, CARA can consider the biased distribution of current real-world compound activity data and avoid overestimation of model performances. We observed that although current models can make successful predictions for certain proportions of assays, their performances varied across different assays. In addition, evaluation of several few-shot training strategies demonstrated different performances related to task types. Overall, we provide a high-quality dataset for developing and evaluating compound activity prediction models, and the analyses in this work may inspire better applications of data-driven models in drug discovery.
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Affiliation(s)
- Tingzhong Tian
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China
| | - Shuya Li
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China
| | - Ziting Zhang
- Department of Automation, Tsinghua University, Beijing, China
- MOE Key Laboratory of Bioinformatics, Tsinghua University, Beijing, China
| | - Lin Chen
- Silexon AI Technology Co., Ltd., Nanjing, Jiangsu Province, China
| | - Ziheng Zou
- Silexon AI Technology Co., Ltd., Nanjing, Jiangsu Province, China
| | - Dan Zhao
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China.
| | - Jianyang Zeng
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China.
- School of Engineering, Westlake University, Hangzhou, Zhejiang Province, China.
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4
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Milon TI, Wang Y, Fontenot RL, Khajouie P, Villinger F, Raghavan V, Xu W. Development of a novel representation of drug 3D structures and enhancement of the TSR-based method for probing drug and target interactions. Comput Biol Chem 2024; 112:108117. [PMID: 38852360 DOI: 10.1016/j.compbiolchem.2024.108117] [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: 03/05/2024] [Revised: 05/13/2024] [Accepted: 05/31/2024] [Indexed: 06/11/2024]
Abstract
Understanding the mechanisms underlying interactions between drugs and target proteins is critical for drug discovery. In our earlier studies, we introduced the Triangular Spatial Relationship (TSR)-based algorithm, which enables the representation of a protein's 3D structure as a vector of integers (TSR keys). These TSR keys correspond to substructures of the 3D structure of a protein and are computed based on the triangles constructed by all possible triples of Cα atoms within the protein. In this study, we report on a new TSR-based algorithm for probing drug and target interactions. Specifically, we have extended the previous algorithm in three novel directions: TSR keys for representing the 3D structure of a drug or a ligand, cross TSR keys between drugs and their targets and intra-residual TSR keys for phosphorylated amino acids. The outcomes illustrate the key contributions as follows: (i) The TSR-based method, which uses the TSR keys as features, is unique in its capability to interpret hierarchical relationships of drugs as well as drug - target complexes using common and specific TSR keys. (ii) The method can distinguish not only the binding sites from the rest of the protein structures, but also the binding sites of primary targets from those of off-targets. (iii) The method has the potential to correlate the 3D structures of drugs with their functions. (iv) Representation of 3D structures by TSR keys has its unique advantage in terms of ease of making searching for similar substructures across structure datasets easier. In summary, this study presents a novel computational methodology, with significant advantages, for providing insights into the mechanism underlying drug and target interactions.
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Affiliation(s)
- Tarikul I Milon
- Department of Chemistry, University of Louisiana at Lafayette, P.O. Box 44370, Lafayette, LA 70504, USA
| | - Yuhong Wang
- National Center for Advancing Translational Sciences, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Ryan L Fontenot
- Department of Chemistry, University of Louisiana at Lafayette, P.O. Box 44370, Lafayette, LA 70504, USA
| | - Poorya Khajouie
- Department of Chemistry, University of Louisiana at Lafayette, P.O. Box 44370, Lafayette, LA 70504, USA; The Center for Advanced Computer Studies, University of Louisiana at Lafayette, LA 70504, USA
| | - Francois Villinger
- Department of Biology, University of Louisiana at Lafayette, New Iberia, LA 70560, USA
| | - Vijay Raghavan
- The Center for Advanced Computer Studies, University of Louisiana at Lafayette, LA 70504, USA
| | - Wu Xu
- Department of Chemistry, University of Louisiana at Lafayette, P.O. Box 44370, Lafayette, LA 70504, USA.
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5
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Islam MT, Aktaruzzaman M, Saif A, Akter A, Bhat MA, Hossain MM, Alam SMN, Rayhan R, Rehman S, Yaseen M, Raihan MO. In Silico-Based Identification of Natural Inhibitors from Traditionally Used Medicinal Plants that can Inhibit Dengue Infection. Mol Biotechnol 2024:10.1007/s12033-024-01204-8. [PMID: 38834897 DOI: 10.1007/s12033-024-01204-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Accepted: 05/15/2024] [Indexed: 06/06/2024]
Abstract
Dengue fever (DF) is an endemic disease that has become a public health concern around the globe. The NS3 protease-helicase enzyme is an important target for the development of antiviral drugs against DENV (dengue virus) due to its impact on viral replication. Inhibition of the activity of the NS3 protease-helicase enzyme complex significantly inhibits the infection associated with DENV. Unfortunately, there are no scientifically approved antiviral drugs for its prevention. However, this study has been developed to find natural bioactive molecules that can block the activity of the NS3 protease-helicase enzyme complex associated with DENV infection through molecular docking, MM-GBSA (molecular mechanics-generalized born surface area), and molecular dynamics (MD) simulations. Three hundred forty-two (342) compounds selected from twenty traditional medicinal plants were retrieved and screened against the NS3 protease-helicase protein by molecular docking and MM-GBSA studies, where the top six phytochemicals have been identified based on binding affinities. The six compounds were then subjected to pharmacokinetics and toxicity analysis, and we conducted molecular dynamics simulations on three protein-ligand complexes to validate their stability. Through computational analysis, this study revealed the potential of the two selected natural bioactive inhibitors (CID-440015 and CID-7424) as novel anti-dengue agents.
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Affiliation(s)
- Md Tarikul Islam
- Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, 7408, Bangladesh
| | - Md Aktaruzzaman
- Department of Pharmacy, Faculty of Biological Science and Technology, Jashore University of Science and Technology, Jashore, 7408, Bangladesh
| | - Ahmed Saif
- Department of Pharmacy, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Ayesha Akter
- Department of Biotechnology and Genetic Engineering, Faculty of Science, Noakhali Science and Technology University, Noakhali, Bangladesh
| | - Mashooq Ahmad Bhat
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Mirza Mahfuj Hossain
- Department of Computer Science and Engineering, Faculty of Engineering and Technology, Jashore University of Science and Technology, Jashore, 7408, Bangladesh
| | - S M Nur Alam
- Department of Chemical Engineering, Faculty of Engineering and Technology, Jashore University of Science and Technology, Jashore, 7408, Bangladesh
| | - Rifat Rayhan
- Department of Biomedical Engineering, Jashore University of Science and Technology, Jashore, 7408, Bangladesh
| | - Saira Rehman
- Faculty of Pharmaceutical Sciences, Pharmacognosy Department, Lahore University of Biological and Applied Sciences, Lahore, Punjab, Pakistan
| | - Muhammad Yaseen
- Institute of Chemical Sciences, University of Swat, Charbagh, 19130, Swat, Pakistan.
| | - Md Obayed Raihan
- Department of Pharmaceutical Sciences, College of Health Sciences and Pharmacy, Chicago State University, Chicago, IL, USA.
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6
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Herbst C, Endres S, Würz R, Sotriffer C. Assessment of fragment docking and scoring with the endothiapepsin model system. Arch Pharm (Weinheim) 2024; 357:e2400061. [PMID: 38631672 DOI: 10.1002/ardp.202400061] [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: 01/23/2024] [Revised: 03/23/2024] [Accepted: 04/01/2024] [Indexed: 04/19/2024]
Abstract
Fragment-based screening has become indispensable in drug discovery. Yet, the weak binding affinities of these small molecules still represent a challenge for the reliable detection of fragment hits. The extent of this issue was illustrated in the literature for the aspartic protease endothiapepsin: When seven biochemical and biophysical in vitro screening methods were applied to screen a library of 361 fragments, very poor overlap was observed between the hit fragments identified by the individual approaches, resulting in high levels of false positive and/or false negative results depending on the mutually compared methods. Here, the reported in vitro findings are juxtaposed with the results from in silico docking and scoring approaches. The docking programs GOLD and Glide were considered with the scoring functions ASP, ChemScore, ChemPLP, GoldScore, DSXCSD, and GlideScore. First, the ranking power and scoring power were assessed for the named scoring functions. Second, the capability of reproducing the crystallized fragment binding modes was tested in a structure-based redocking approach. The redocking success notably depended on the ligand efficiency of the considered fragments. Third, a blinded virtual screening approach was employed to evaluate whether in silico screening can compete with in vitro methods in the enrichment of fragment databases.
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Affiliation(s)
- Carina Herbst
- Institute of Pharmacy and Food Chemistry, Julius-Maximilians-Universität, Würzburg, Germany
| | - Sara Endres
- Institute of Pharmacy and Food Chemistry, Julius-Maximilians-Universität, Würzburg, Germany
| | - Rebecca Würz
- Institute of Pharmacy and Food Chemistry, Julius-Maximilians-Universität, Würzburg, Germany
| | - Christoph Sotriffer
- Institute of Pharmacy and Food Chemistry, Julius-Maximilians-Universität, Würzburg, Germany
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7
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Yatoo GN, Bhat BA, Zubaid-Ul-Khazir, Asif M, Bhat SA, Gulzar F, Rashied F, Wani AH, Ahmed I, Zargar SM, Mir MA, Banday JA. Network pharmacology and experimental insights into STAT3 inhibition by novel isoxazole derivatives of piperic acid in triple negative breast cancer. Fitoterapia 2024; 175:105927. [PMID: 38548028 DOI: 10.1016/j.fitote.2024.105927] [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: 12/04/2023] [Revised: 03/23/2024] [Accepted: 03/24/2024] [Indexed: 04/01/2024]
Abstract
STAT3 is a crucial member within a family of seven essential transcription factors. Elevated STAT3 levels have been identified in various cancer types, notably in breast cancer (BC). Consequently, inhibiting STAT3 is recognized as a promising and effective strategy for therapeutic intervention against breast cancer. We herein synthesize a library of isoxazole (PAIs) from piperic acid [2E, 4E)-5-(2H-1,3-Benzodioxol-5-yl) penta-2,4-dienoic acid] on treatment with propargyl bromide followed by oxime under prescribed reaction conditions. Piperic acid was obtained by hydrolysis of piperine extracted from Piper nigrum. First, we checked the binding potential of isoxazole derivatives with breast cancer target proteins by network pharmacology, molecular docking, molecular dynamic (MD) simulation and cytotoxicity analysis as potential anti-breast cancer (BC) agents. The multi-source databases were used to identify possible targets for isoxazole derivatives. A network of protein-protein interactions (PPIs) was generated by obtaining 877 target genes that overlapped gene symbols associated with isoxazole derivatives and BC. Molecular docking and MD modelling demonstrated a strong affinity between isoxazole derivatives and essential target genes. Further, the cell viability studies of isoxazole derivatives on the human breast carcinoma cell lines showed toxicity in all breast cancer cell lines. In summary, our study indicated that the isoxazole derivative showed the significant anticancer activity. The results highlight the prospective utility of isoxazole derivatives as new drug candidates for anticancer chemotherapy, suggesting route for the continued exploration and development of drugs suitable for clinical applications.
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Affiliation(s)
- G N Yatoo
- Department of Chemistry, National Institute of Technology Srinagar, J & K, India.
| | - Basharat A Bhat
- Department of Bio-Resources, Amar Singh College Campus, Cluster University Srinagar, J&K, India
| | - Zubaid-Ul-Khazir
- Department of Chemistry, National Institute of Technology Srinagar, J & K, India
| | - Mohammad Asif
- Department of Chemistry, National Institute of Technology Srinagar, J & K, India
| | - Sajad A Bhat
- Department of Chemistry, National Institute of Technology Srinagar, J & K, India
| | - Farhana Gulzar
- Department of Chemistry, National Institute of Technology Srinagar, J & K, India
| | - Fehmida Rashied
- Department of Chemistry, National Institute of Technology Srinagar, J & K, India
| | - Abdul Haleem Wani
- Department of Chemistry, National Institute of Technology Srinagar, J & K, India; Department of Chemistry, Sri Pratap College Campus, Cluster University Srinagar, J&K, India
| | - Ishfaq Ahmed
- Department of Chemistry, National Institute of Technology Srinagar, J & K, India
| | - Sajad Majeed Zargar
- Proteomics Laboratory, Division of Plant Biotechnology, SKUAST-K, Shalimar, J&K, India
| | - Mushtaq A Mir
- Department of Clinical Laboratory Sciences, College of Applied Medical Science, King Khalid University, Abha, Saudi Arabia
| | - Javid A Banday
- Department of Chemistry, National Institute of Technology Srinagar, J & K, India.
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Bassani D, Parrott NJ, Manevski N, Zhang JD. Another string to your bow: machine learning prediction of the pharmacokinetic properties of small molecules. Expert Opin Drug Discov 2024; 19:683-698. [PMID: 38727016 DOI: 10.1080/17460441.2024.2348157] [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] [Accepted: 04/23/2024] [Indexed: 05/22/2024]
Abstract
INTRODUCTION Prediction of pharmacokinetic (PK) properties is crucial for drug discovery and development. Machine-learning (ML) models, which use statistical pattern recognition to learn correlations between input features (such as chemical structures) and target variables (such as PK parameters), are being increasingly used for this purpose. To embed ML models for PK prediction into workflows and to guide future development, a solid understanding of their applicability, advantages, limitations, and synergies with other approaches is necessary. AREAS COVERED This narrative review discusses the design and application of ML models to predict PK parameters of small molecules, especially in light of established approaches including in vitro-in vivo extrapolation (IVIVE) and physiologically based pharmacokinetic (PBPK) models. The authors illustrate scenarios in which the three approaches are used and emphasize how they enhance and complement each other. In particular, they highlight achievements, the state of the art and potentials of applying machine learning for PK prediction through a comphrehensive literature review. EXPERT OPINION ML models, when carefully crafted, regularly updated, and appropriately used, empower users to prioritize molecules with favorable PK properties. Informed practitioners can leverage these models to improve the efficiency of drug discovery and development process.
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Affiliation(s)
- Davide Bassani
- Pharmaceutical Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Neil John Parrott
- Pharmaceutical Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Nenad Manevski
- Pharmaceutical Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Jitao David Zhang
- Pharmaceutical Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
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Chen R, Wang Y, Shen Z, Ye C, Guo Y, Lu Y, Ding J, Dong X, Xu D, Zheng X. Discovery of potent CSK inhibitors through integrated virtual screening and molecular dynamic simulation. Arch Pharm (Weinheim) 2024:e2400066. [PMID: 38809025 DOI: 10.1002/ardp.202400066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 04/23/2024] [Accepted: 05/08/2024] [Indexed: 05/30/2024]
Abstract
Oncogenic overexpression or activation of C-terminal Src kinase (CSK) has been shown to play an important role in triple-negative breast cancer (TNBC) progression, including tumor initiation, growth, metastasis, drug resistance. This revelation has pivoted the focus toward CSK as a potential target for novel treatments. However, until now, there are few inhibitors designed to target the CSK protein. Responding to this, our research has implemented a comprehensive virtual screening protocol. By integrating energy-based screening methods with AI-driven scoring functions, such as Attentive FP, and employing rigorous rescoring methods like Glide docking and molecular mechanics generalized Born surface area (MM/GBSA), we have systematically sought out inhibitors of CSK. This approach led to the discovery of a compound with a potent CSK inhibitory activity, reflected by an IC50 value of 1.6 nM under a homogeneous time-resolved fluorescence (HTRF) bioassay. Subsequently, molecule 2 exhibits strong growth inhibition of MD anderson - metastatic breast (MDA-MB) -231, Hs578T, and SUM159 cells, showing a level of growth inhibition comparable to that observed with dasatinib. Treatment with molecule 2 also induced significant G1 phase accumulation and cell apoptosis. Furthermore, we have explored the explicit binding interactions of the compound with CSK using molecular dynamics simulations, providing valuable insights into its mechanism of action.
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Affiliation(s)
- Roufen Chen
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, China
- Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Yuchen Wang
- Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Zheyuan Shen
- Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Chenyi Ye
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, China
| | - Yu Guo
- Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Yan Lu
- Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jianjun Ding
- School of Food Science and Technology, Jiangnan University, Wuxi, China
| | - Xiaowu Dong
- Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
- Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Donghang Xu
- Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaoli Zheng
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, China
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10
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Champion C, Hünenberger PH, Riniker S. Multistate Method to Efficiently Account for Tautomerism and Protonation in Alchemical Free-Energy Calculations. J Chem Theory Comput 2024; 20:4350-4362. [PMID: 38742760 PMCID: PMC11137823 DOI: 10.1021/acs.jctc.4c00370] [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: 03/22/2024] [Revised: 04/25/2024] [Accepted: 04/29/2024] [Indexed: 05/16/2024]
Abstract
The majority of drug-like molecules contain at least one ionizable group, and many common drug scaffolds are subject to tautomeric equilibria. Thus, these compounds are found in a mixture of protonation and/or tautomeric states at physiological pH. Intrinsically, standard classical molecular dynamics (MD) simulations cannot describe such equilibria between states, which negatively impacts the prediction of key molecular properties in silico. Following the formalism described by de Oliveira and co-workers (J. Chem. Theory Comput. 2019, 15, 424-435) to consider the influence of all states on the binding process based on alchemical free-energy calculations, we demonstrate in this work that the multistate method replica-exchange enveloping distribution sampling (RE-EDS) is well suited to describe molecules with multiple protonation and/or tautomeric states in a single simulation. We apply our methodology to a series of eight inhibitors of factor Xa with two protonation states and a series of eight inhibitors of glycogen synthase kinase 3β (GSK3β) with two tautomeric states. In particular, we show that given a sufficient phase-space overlap between the states, RE-EDS is computationally more efficient than standard pairwise free-energy methods.
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Affiliation(s)
- Candide Champion
- Department of Chemistry and Applied
Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Philippe H. Hünenberger
- Department of Chemistry and Applied
Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Sereina Riniker
- Department of Chemistry and Applied
Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
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11
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Goles M, Daza A, Cabas-Mora G, Sarmiento-Varón L, Sepúlveda-Yañez J, Anvari-Kazemabad H, Davari MD, Uribe-Paredes R, Olivera-Nappa Á, Navarrete MA, Medina-Ortiz D. Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides. Brief Bioinform 2024; 25:bbae275. [PMID: 38856172 PMCID: PMC11163380 DOI: 10.1093/bib/bbae275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 04/23/2024] [Accepted: 06/04/2024] [Indexed: 06/11/2024] Open
Abstract
With their diverse biological activities, peptides are promising candidates for therapeutic applications, showing antimicrobial, antitumour and hormonal signalling capabilities. Despite their advantages, therapeutic peptides face challenges such as short half-life, limited oral bioavailability and susceptibility to plasma degradation. The rise of computational tools and artificial intelligence (AI) in peptide research has spurred the development of advanced methodologies and databases that are pivotal in the exploration of these complex macromolecules. This perspective delves into integrating AI in peptide development, encompassing classifier methods, predictive systems and the avant-garde design facilitated by deep-generative models like generative adversarial networks and variational autoencoders. There are still challenges, such as the need for processing optimization and careful validation of predictive models. This work outlines traditional strategies for machine learning model construction and training techniques and proposes a comprehensive AI-assisted peptide design and validation pipeline. The evolving landscape of peptide design using AI is emphasized, showcasing the practicality of these methods in expediting the development and discovery of novel peptides within the context of peptide-based drug discovery.
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Affiliation(s)
- Montserrat Goles
- Departamento de Ingeniería en Computación, Universidad de Magallanes, Av. Pdte. Manuel Bulnes 01855, 6210427, Punta Arenas, Chile
- Departamento de Ingeniería Química, Biotecnología y Materiales, Universidad de Chile, Beauchef 851, 8370456, Santiago, Chile
| | - Anamaría Daza
- Centre for Biotechnology and Bioengineering, CeBiB, Universidad de Chile, Beauchef 851, 8370456, Santiago, Chile
| | - Gabriel Cabas-Mora
- Departamento de Ingeniería en Computación, Universidad de Magallanes, Av. Pdte. Manuel Bulnes 01855, 6210427, Punta Arenas, Chile
| | - Lindybeth Sarmiento-Varón
- Centro Asistencial de Docencia e Investigación, CADI, Universidad de Magallanes, Av. Los Flamencos 01364, 6210005, Punta Arenas, Chile
| | - Julieta Sepúlveda-Yañez
- Facultad de Ciencias de la Salud, Universidad de Magallanes, Av. Pdte. Manuel Bulnes 01855, 6210427, Punta Arenas, Chile
| | - Hoda Anvari-Kazemabad
- Departamento de Ingeniería en Computación, Universidad de Magallanes, Av. Pdte. Manuel Bulnes 01855, 6210427, Punta Arenas, Chile
| | - Mehdi D Davari
- Department of Bioorganic Chemistry, Leibniz Institute of Plant Biochemistry, Weinberg 3, 06120, Halle, Germany
| | - Roberto Uribe-Paredes
- Departamento de Ingeniería en Computación, Universidad de Magallanes, Av. Pdte. Manuel Bulnes 01855, 6210427, Punta Arenas, Chile
| | - Álvaro Olivera-Nappa
- Centre for Biotechnology and Bioengineering, CeBiB, Universidad de Chile, Beauchef 851, 8370456, Santiago, Chile
| | - Marcelo A Navarrete
- Centro Asistencial de Docencia e Investigación, CADI, Universidad de Magallanes, Av. Los Flamencos 01364, 6210005, Punta Arenas, Chile
- Escuela de Medicina, Universidad de Magallanes, Av. Pdte. Manuel Bulnes 01855, 6210427, Punta Arenas, Chile
| | - David Medina-Ortiz
- Departamento de Ingeniería en Computación, Universidad de Magallanes, Av. Pdte. Manuel Bulnes 01855, 6210427, Punta Arenas, Chile
- Centre for Biotechnology and Bioengineering, CeBiB, Universidad de Chile, Beauchef 851, 8370456, Santiago, Chile
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12
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Kochnev Y, Ahmed M, Maldonado AM, Durrant JD. MolModa: accessible and secure molecular docking in a web browser. Nucleic Acids Res 2024:gkae406. [PMID: 38783339 DOI: 10.1093/nar/gkae406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/14/2024] [Accepted: 05/01/2024] [Indexed: 05/25/2024] Open
Abstract
Molecular docking advances early-stage drug discovery by predicting the geometries and affinities of small-molecule compounds bound to drug-target receptors, predictions that researchers can leverage in prioritizing drug candidates for experimental testing. Unfortunately, existing docking tools often suffer from poor usability, data security, and maintainability, limiting broader adoption. Additionally, the complexity of the docking process, which requires users to execute a series of specialized steps, often poses a substantial barrier for non-expert users. Here, we introduce MolModa, a secure, accessible environment where users can perform molecular docking entirely in their web browsers. We provide two case studies that illustrate how MolModa provides valuable biological insights. We further compare MolModa to other docking tools to highlight its strengths and limitations. MolModa is available free of charge for academic and commercial use, without login or registration, at https://durrantlab.com/molmoda.
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Affiliation(s)
- Yuri Kochnev
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mayar Ahmed
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alex M Maldonado
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jacob D Durrant
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
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13
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Yasir M, Park J, Chun W. Discovery of Novel Aldose Reductase Inhibitors via the Integration of Ligand-Based and Structure-Based Virtual Screening with Experimental Validation. ACS OMEGA 2024; 9:20338-20349. [PMID: 38737046 PMCID: PMC11079907 DOI: 10.1021/acsomega.4c00820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 04/15/2024] [Accepted: 04/18/2024] [Indexed: 05/14/2024]
Abstract
Aldose reductase plays a central role in diabetes mellitus (DM) associated complications by converting glucose to sorbitol, resulting in a harmful increase of reactive oxygen species (ROS) in various tissues, such as the heart, vasculature, neurons, eyes, and kidneys. We employed a comprehensive approach, integrating both ligand- and structure-based virtual screening followed by experimental validation. Initially, candidate compounds were extracted from extensive drug and chemical libraries using the DeepChem's GraphConvMol algorithm, leveraging its capacity for robust molecular feature representation. Subsequent refinement employed molecular docking and molecular dynamics (MD) simulations, which are crucial for understanding compound-receptor interactions and dynamic behavior in a simulated physiological environment. Finally, the candidate compounds were subjected to experimental validation of their biological activity using an aldose reductase inhibitor screening kit. The comprehensive approach led to the identification of a promising compound, demonstrating significant potential as an aldose reductase inhibitor. This comprehensive approach not only yields a potential therapeutic intervention for DM-related complications but also establishes an integrated protocol for drug development, setting a new benchmark in the field.
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Affiliation(s)
- Muhammad Yasir
- Department of Pharmacology, Kangwon National University School of Medicine, Chuncheon 24341, Republic of Korea
| | - Jinyoung Park
- Department of Pharmacology, Kangwon National University School of Medicine, Chuncheon 24341, Republic of Korea
| | - Wanjoo Chun
- Department of Pharmacology, Kangwon National University School of Medicine, Chuncheon 24341, Republic of Korea
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14
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Sheikh HK, Ortiz CJC, Arshad T, Padrón JM, Khan H. Advancements in steroidal Pt(II) & Pt(IV) derivatives for targeted chemotherapy (2000-2023). Eur J Med Chem 2024; 271:116438. [PMID: 38685141 DOI: 10.1016/j.ejmech.2024.116438] [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: 01/10/2024] [Revised: 04/08/2024] [Accepted: 04/18/2024] [Indexed: 05/02/2024]
Abstract
One of the key strategies in chemotherapy involves crosslinking the DNA strands of cancer cells to impede their replication, with platinum (Pt) coordination compounds being a prominent class and cisplatin being its major representative. Steroidal ligands tethered to DNA interactive Pt core act as drug carriers for targeted therapy. While crosslinking of nuclear or mitochondrial DNA strands using coordination complexes has been studied for years, there remains a lack of comprehensive reviews addressing the advancements made in steroidal-Pt derivatives. This review specifically focuses on advancements made in steroid-tethered structural derivatives of Pt(II) or prodrug Pt(IV) for targeted chemotherapy, synthesized between 2000 and 2023. This period was deliberately chosen due to the widespread use of computational techniques for more accurate structure-based drug-design in last two decades. This review discusses the strategy behind tethering steroidal ligands such as testosterone, estrogen, bile acids, and cholesterol to the central DNA interactive Pt core through specific linker groups. The steroidal ligands function as drug delivery vehicles of DNA interactive Pt core and bind with their respective target receptors or proteins that are often overexpressed in cancer cells, thus enabling targeted delivery of Pt moiety to interact with DNA. We discussed structural features such as the location of the linker group on the steroid, the mono, bi, and tridentate configuration of the chelating arm in coordination with Pt, and the rigidity and flexibility of the linker group. The comparative in vitro, in vivo activities, and relative binding affinities of the designed compounds against standard Pt drugs are also discussed. We also provided a critique of observed trends and shortcomings. Our review will provide insights into future molecular designing of targeted DNA crosslinkers and their structural optimization to achieve desired drug properties. From this analysis, we proposed further research directions leading to the future of targeted chemotherapy.
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Affiliation(s)
- Hamdullah Khadim Sheikh
- Instituto Universitario de Bio-Orgánica Antonio González, Universidad de La Laguna, Spain; Faculty of Pharmacy, University of Karachi, Pakistan
| | | | | | - José M Padrón
- Instituto Universitario de Bio-Orgánica Antonio González, Universidad de La Laguna, Spain
| | - Haroon Khan
- Department of Pharmacy, Abdul Wali Khan University Mardan, Mardan, 23200, Pakistan.
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15
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Medina-Franco JL, López-López E. What is the plausibility that all drugs will be designed by computers by the end of the decade? Expert Opin Drug Discov 2024; 19:507-510. [PMID: 38501288 DOI: 10.1080/17460441.2024.2331734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Accepted: 03/13/2024] [Indexed: 03/20/2024]
Affiliation(s)
- José L Medina-Franco
- DIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, Mexico, Mexico
| | - Edgar López-López
- DIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, Mexico, Mexico
- Department of Chemistry and Graduate Program in Pharmacology, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico, Mexico
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16
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Mousavi H, Rimaz M, Zeynizadeh B. Practical Three-Component Regioselective Synthesis of Drug-Like 3-Aryl(or heteroaryl)-5,6-dihydrobenzo[ h]cinnolines as Potential Non-Covalent Multi-Targeting Inhibitors To Combat Neurodegenerative Diseases. ACS Chem Neurosci 2024; 15:1828-1881. [PMID: 38647433 DOI: 10.1021/acschemneuro.4c00055] [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: 04/25/2024] Open
Abstract
Neurodegenerative diseases (NDs) are one of the prominent health challenges facing contemporary society, and many efforts have been made to overcome and (or) control it. In this research paper, we described a practical one-pot two-step three-component reaction between 3,4-dihydronaphthalen-1(2H)-one (1), aryl(or heteroaryl)glyoxal monohydrates (2a-h), and hydrazine monohydrate (NH2NH2•H2O) for the regioselective preparation of some 3-aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnoline derivatives (3a-h). After synthesis and characterization of the mentioned cinnolines (3a-h), the in silico multi-targeting inhibitory properties of these heterocyclic scaffolds have been investigated upon various Homo sapiens-type enzymes, including hMAO-A, hMAO-B, hAChE, hBChE, hBACE-1, hBACE-2, hNQO-1, hNQO-2, hnNOS, hiNOS, hPARP-1, hPARP-2, hLRRK-2(G2019S), hGSK-3β, hp38α MAPK, hJNK-3, hOGA, hNMDA receptor, hnSMase-2, hIDO-1, hCOMT, hLIMK-1, hLIMK-2, hRIPK-1, hUCH-L1, hPARK-7, and hDHODH, which have confirmed their functions and roles in the neurodegenerative diseases (NDs), based on molecular docking studies, and the obtained results were compared with a wide range of approved drugs and well-known (with IC50, EC50, etc.) compounds. In addition, in silico ADMET prediction analysis was performed to examine the prospective drug properties of the synthesized heterocyclic compounds (3a-h). The obtained results from the molecular docking studies and ADMET-related data demonstrated that these series of 3-aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnolines (3a-h), especially hit ones, can really be turned into the potent core of new drugs for the treatment of neurodegenerative diseases (NDs), and/or due to the having some reactionable locations, they are able to have further organic reactions (such as cross-coupling reactions), and expansion of these compounds (for example, with using other types of aryl(or heteroaryl)glyoxal monohydrates) makes a new avenue for designing novel and efficient drugs for this purpose.
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Affiliation(s)
- Hossein Mousavi
- Department of Organic Chemistry, Faculty of Chemistry, Urmia University, Urmia 5756151818, Iran
| | - Mehdi Rimaz
- Department of Chemistry, Payame Noor University, P.O. Box 19395-3697, Tehran 19395-3697, Iran
| | - Behzad Zeynizadeh
- Department of Organic Chemistry, Faculty of Chemistry, Urmia University, Urmia 5756151818, Iran
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17
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Shaimardanov AR, Shulga DA, Palyulin VA. Do electrostatic interactions make a difference in physics-based AutoDock4 scoring function? J Comput Chem 2024. [PMID: 38661234 DOI: 10.1002/jcc.27373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 03/21/2024] [Accepted: 03/25/2024] [Indexed: 04/26/2024]
Abstract
Physics-based scoring function AutoDock4 is one of the most successfully applied tools in the area of structure-based drug design. However, current scoring functions are still far from being perfect. In a recent work highlighting the strengths and deficiencies of current scoring functions, we discovered that the residual error of ΔGbind predictions made by AutoDock4 is highly correlated to the presence of formally charged fragments in a ligand. In this work, we study how the use of the high-quality atomic charges, applied for contemporary force fields calculation, affects the quality of the experimental ΔGbind prediction by means of AutoDock4. We initially expected that the previously found discrepancy could be attributed to the Gasteiger charges used within AutoDock4. We show that AutoDock4 is, surprisingly, not sensitive to the charges used, and the use of QC-derived atomic charges does not lead to any statistical improvements. We also briefly discuss the role of the explicit empirical hydrogen bond term along with the electrostatic term.
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Affiliation(s)
- Arslan R Shaimardanov
- Department of Chemistry, Lomonosov Moscow State University, Moscow, Russian Federation
| | - Dmitry A Shulga
- Department of Chemistry, Lomonosov Moscow State University, Moscow, Russian Federation
| | - Vladimir A Palyulin
- Department of Chemistry, Lomonosov Moscow State University, Moscow, Russian Federation
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18
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Mushtaq A, Asif R, Humayun WA, Naseer MM. Novel isatin-triazole based thiosemicarbazones as potential anticancer agents: synthesis, DFT and molecular docking studies. RSC Adv 2024; 14:14051-14067. [PMID: 38686286 PMCID: PMC11057040 DOI: 10.1039/d4ra01937g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 04/23/2024] [Indexed: 05/02/2024] Open
Abstract
Thiosemicarbazones of isatin have been found to exhibit versatile bioactivities. In this study, two distinct types of isatin-triazole hybrids 3a and 3b were accessed via copper-catalyzed azide-alkyne cycloaddition reaction (CuAAC), together with their mono and bis-thiosemicarbazone derivatives 4a-h and 5a-h. In addition to the characterization by physical, spectral and analytical data, a DFT study was carried out to obtain the optimized geometries of all thiosemicarbazones. The global reactivity values showed that among the synthesized derivatives, 4c, 4g and 5c having nitro substituents are the most soft compounds, with compound 5c having the highest electronegativity and electrophilicity index values among the synthesized series, thus possessing strong binding ability with biomolecules. Molecular docking studies were performed to explore the inhibitory ability of the selected compounds against the active sites of the anticancer protein of phosphoinositide 3-kinase (PI3K). Among the synthesized derivatives, 4-nitro substituted bisthiosemicarbazone 5c showed the highest binding energy of -10.3 kcal mol-1. These findings demonstrated that compound 5c could be used as a favored anticancer scaffold via the mechanism of inhibition against the PI3K signaling pathways.
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Affiliation(s)
- Alia Mushtaq
- Department of Chemistry, Quaid-i-Azam University Islamabad 45320 Pakistan
| | - Rabbia Asif
- Department of Chemistry, Quaid-i-Azam University Islamabad 45320 Pakistan
| | - Waqar Ahmed Humayun
- Department of Medical Oncology & Radiotherapy, King Edward Medical University Lahore 54000 Pakistan
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19
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Liu Y, Li Q, Shao C, She Y, Zhou H, Guo Y, An H, Wang T, Yang J, Wan H. Exploring the Potential Mechanisms of Guanxinshutong Capsules in Treating Pathological Cardiac Hypertrophy based on Network Pharmacology, Computer-Aided Drug Design, and Animal Experiments. ACS OMEGA 2024; 9:18083-18098. [PMID: 38680308 PMCID: PMC11044149 DOI: 10.1021/acsomega.3c10009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 02/15/2024] [Accepted: 03/08/2024] [Indexed: 05/01/2024]
Abstract
Cardiovascular diseases (CVDs) are significant causes of morbidity and mortality worldwide, and pathological cardiac hypertrophy (PCH) is an essential predictor of many heart diseases. Guanxinshutong capsule (GXST) is a Chinese patent medicine widely used in the clinical treatment of CVD, In our previous research, we identified 111 compounds of GXST. In order to reveal the potential molecular mechanisms by which GXST treats PCH, this study employed network pharmacology methods to screen for the active ingredients of GXST in treating PCH and predicted the potential targets. The results identified 26 active ingredients of GXST and 110 potential targets for PCH. Through a protein-protein interaction (PPI) network, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, we confirmed AKT1, MAPK1, and MAPK3 as the core proteins in GXST treatment of PCH, thus establishing the PI3K/AKT and MAPK signaling pathways as the significant mechanisms of GXST in treating PCH. The results of molecular docking (MD) demonstrate that flavonoid naringenin and diterpenoid tanshinone iia have the highest binding affinity with the core protein. Before performing molecular dynamics simulations (MDSs), the geometric structure of naringenin and tanshinone iia was optimized using density functional theory (DFT) at the B97-3c level, and RESP2 atomic charge calculations were carried out at the B3LYP-D3(BJ)/def2-TZVP level. Further MDS results demonstrated that in the human body environment, the complex of naringenin and tanshinone iii with core proteins exhibited high stability, flexibility, and low binding free energy. Additionally, naringenin and tanshinone iia showed favorable absorption, distribution, metabolism, excretion, and toxicity (ADMET) characteristics and passed the drug similarity (DS) assessment. Ultrasound cardiograms and cardiac morphometric measurements in animal experiments demonstrate that GXST can improve the PCH induced by isoproterenol (ISO). Protein immunoblotting results indicate that GXST increases the expression of P-eNOS and eNOS by activating the PI3K/AKT signaling pathway and the MAPK signaling pathway, further elucidating the mechanism of action of GXST in treating PCH. This study contributes to the elucidation of the key ingredients and molecular mechanisms of GXST in treating PCH.
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Affiliation(s)
- Yuanfeng Liu
- College
of Life Science, Zhejiang Chinese Medical
University, Hangzhou, Zhejiang 310053, China
| | - Qixiang Li
- College
of Basic Medical Sciences, Zhejiang Chinese
Medical University, Hangzhou, Zhejiang 310053, China
| | - Chongyu Shao
- College
of Basic Medical Sciences, Zhejiang Chinese
Medical University, Hangzhou, Zhejiang 310053, China
- Key
Laboratory of TCM Encephalopathy of Zhejiang Province, No.548, Hangzhou, Zhejiang 310053, China
| | - Yong She
- College
of Life Science, Zhejiang Chinese Medical
University, Hangzhou, Zhejiang 310053, China
| | - Huifen Zhou
- College
of Basic Medical Sciences, Zhejiang Chinese
Medical University, Hangzhou, Zhejiang 310053, China
- Key
Laboratory of TCM Encephalopathy of Zhejiang Province, No.548, Hangzhou, Zhejiang 310053, China
| | - Yan Guo
- Hangzhou
TCM Hospital Affiliated to Zhejiang Chinese Medical University Hangzhou, Zhejiang 310053, China
| | - Huiyan An
- College
of Life Science, Zhejiang Chinese Medical
University, Hangzhou, Zhejiang 310053, China
| | - Ting Wang
- College
of Basic Medical Sciences, Zhejiang Chinese
Medical University, Hangzhou, Zhejiang 310053, China
| | - Jiehong Yang
- College
of Basic Medical Sciences, Zhejiang Chinese
Medical University, Hangzhou, Zhejiang 310053, China
- Key
Laboratory of TCM Encephalopathy of Zhejiang Province, No.548, Hangzhou, Zhejiang 310053, China
| | - Haitong Wan
- College
of Basic Medical Sciences, Zhejiang Chinese
Medical University, Hangzhou, Zhejiang 310053, China
- Key
Laboratory of TCM Encephalopathy of Zhejiang Province, No.548, Hangzhou, Zhejiang 310053, China
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20
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Oliveira PF, Guedes RC, Falcao AO. Inferring molecular inhibition potency with AlphaFold predicted structures. Sci Rep 2024; 14:8252. [PMID: 38589418 PMCID: PMC11001998 DOI: 10.1038/s41598-024-58394-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: 12/03/2023] [Accepted: 03/28/2024] [Indexed: 04/10/2024] Open
Abstract
Even though in silico drug ligand-based methods have been successful in predicting interactions with known target proteins, they struggle with new, unassessed targets. To address this challenge, we propose an approach that integrates structural data from AlphaFold 2 predicted protein structures into machine learning models. Our method extracts 3D structural protein fingerprints and combines them with ligand structural data to train a single machine learning model. This model captures the relationship between ligand properties and the unique structural features of various target proteins, enabling predictions for never before tested molecules and protein targets. To assess our model, we used a dataset of 144 Human G-protein Coupled Receptors (GPCRs) with over 140,000 measured inhibition constants (Ki) values. Results strongly suggest that our approach performs as well as state-of-the-art ligand-based methods. In a second modeling approach that used 129 targets for training and a separate test set of 15 different protein targets, our model correctly predicted interactions for 73% of targets, with explained variances exceeding 0.50 in 22% of cases. Our findings further verified that the usage of experimentally determined protein structures produced models that were statistically indistinct from the Alphafold synthetic structures. This study presents a proteo-chemometric drug screening approach that uses a simple and scalable method for extracting protein structural information for usage in machine learning models capable of predicting protein-molecule interactions even for orphan targets.
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Affiliation(s)
- Pedro F Oliveira
- Lasige, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal
| | - Rita C Guedes
- Research Institute for Medicines (iMed.ULisboa), Faculdade de Farmácia, Universidade de Lisboa, Av. Prof. Gama Pinto, 1649-003 Lisboa, Portugal
| | - Andre O Falcao
- Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, 1749-016, Lisboa, Portugal.
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21
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Waseem T, Rajput TA, Mushtaq MS, Babar MM, Rajadas J. Computational biology approaches for drug repurposing. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2024; 205:91-109. [PMID: 38789189 DOI: 10.1016/bs.pmbts.2024.03.018] [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: 05/26/2024]
Abstract
The drug discovery and development (DDD) process greatly relies on the data available in various forms to generate hypotheses for novel drug design. The complex and heterogeneous nature of biological data makes it difficult to utilize or gather meaningful information as such. Computational biology techniques have provided us with opportunities to better understand biological systems through refining and organizing large amounts of data into actionable and systematic purviews. The drug repurposing approach has been utilized to overcome the expansive time periods and costs associated with traditional drug development. It deals with discovering new uses of already approved drugs that have an established safety and efficacy profile, thereby, requiring them to go through fewer development phases. Thus, drug repurposing through computational biology provides a systematic approach to drug development and overcomes the constraints of traditional processes. The current chapter covers the basics, approaches and tools of computational biology that can be employed to effectively develop repurposing profile of already approved drug molecules.
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Affiliation(s)
- Tanya Waseem
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan
| | - Tausif Ahmed Rajput
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan
| | | | - Mustafeez Mujtaba Babar
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan; Advanced Drug Delivery and Regenerative Biomaterials Laboratory, Cardiovascular Institute and Pulmonary and Critical Care Medicine, Stanford University School of Medicine, Stanford University, Palo Alto, CA, United States.
| | - Jayakumar Rajadas
- Advanced Drug Delivery and Regenerative Biomaterials Laboratory, Cardiovascular Institute and Pulmonary and Critical Care Medicine, Stanford University School of Medicine, Stanford University, Palo Alto, CA, United States
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22
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Ramya S, Manivannan HP, Veeraraghavan VP, Francis AP. In Silico Analysis of Selective Bioactive Compounds from Acronychia Pedunculata as a Potential Inhibitor of HER2 in Colorectal Cancer. JOURNAL OF PHARMACY AND BIOALLIED SCIENCES 2024; 16:S1281-S1286. [PMID: 38882725 PMCID: PMC11174219 DOI: 10.4103/jpbs.jpbs_570_23] [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: 08/12/2023] [Revised: 11/01/2023] [Accepted: 11/17/2023] [Indexed: 06/18/2024] Open
Abstract
Colorectal cancer (CRC) is a pervasive malignancy that stands as a prominent contributor to global cancer-related mortality. Among the numerous causative factors, the overexpression of human epidermal growth factor receptor 2 (HER2) is notably linked to CRC progression. Acronychia (A.) pedunculata has a longstanding history in folk medicine due to its multifaceted medicinal attributes. This study aimed to assess the potential of specific bioactive compounds derived from A. pedunculata for their inhibition of HER2 in CRC, utilizing in silico analysis. The compounds were systematically evaluated through a series of computational analyses. Drug-likeness assessment, pharmacokinetic evaluation, and toxicity analysis were conducted. Molecular docking studies were performed to investigate binding affinities with the HER2 target. Additionally, bioavailability radar analysis was employed to predict oral bioavailability, while molecular target prediction provided insights into potential protein interactions. All 12 compounds demonstrated favorable drug-likeness properties and adherence to Lipinski's rule of five, indicative of the potential for good oral bioavailability. Four compounds were found to have no toxicological endpoints. Molecular docking revealed two compounds, namely caryophylla-4 (14), 8 (15)-dien-5alpha-ol and (-)-globulol, which showed promising binding affinities between several compounds and HER2. From this study, two leads were identified from A. pedunculata. Further experimental studies are required to validate the action of leads.
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Affiliation(s)
- S Ramya
- Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India
| | - Hema P Manivannan
- Department of Biochemistry, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India
| | - Vishnu P Veeraraghavan
- Department of Biochemistry, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India
| | - Arul P Francis
- Department of Biochemistry, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India
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23
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Shaaban MM, Teleb M, Ragab HM, Singh M, Elwakil BH, A Heikal L, Sriram D, Mahran MA. The first-in-class pyrazole-based dual InhA-VEGFR inhibitors towards integrated antitubercular host-directed therapy. Bioorg Chem 2024; 145:107179. [PMID: 38367430 DOI: 10.1016/j.bioorg.2024.107179] [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: 12/14/2023] [Revised: 01/22/2024] [Accepted: 02/02/2024] [Indexed: 02/19/2024]
Abstract
Several facets of the host response to tuberculosis have been tapped for clinical investigation, especially targeting angiogenesis mediated by VEGF signaling from infected macrophages. Herein, we rationalized combining the antiangiogenic effects of VEGFR-2 blockade with direct antitubercular InhA inhibition in single hybrid dual inhibitors as advantageous alternatives to the multidrug regimens. Inspired by expanded triclosans, the ether ligation of triclosan was replaced by rationalized linkers to assemble the VEGFR-2 inhibitors thematic scaffold. Accordingly, new series of 3-(p-chlorophenyl)-1-phenylpyrazole derivatives tethered to substituted ureas and their isosteres were synthesized, evaluated against Mycobacterium tuberculosis virulent cell line H37Rv, and assessed for their InhA inhibitory activities. The urea derivatives 8d and 8g exhibited the most promising antitubercular activity (MIC = 6.25 µg/mL) surpassing triclosan (MIC = 20 µg/mL) with potential InhA inhibition, thus identified as the study hits. Interestingly, both compounds inhibited VEGFR-2 at nanomolar IC50 (15.27 and 24.12 nM, respectively). Docking and molecular dynamics simulations presumed that 8d and 8g could bind to their molecular targets InhA and VEGFR-2 posing essential stable interactions shared by the reference inhibitors triclosan and sorafenib. Finally, practical LogP, Lipinski's parameters and in silico ADMET calculations highlighted their drug-likeness as novel leads in the arsenal against TB.
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Affiliation(s)
- Marwa M Shaaban
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Alexandria University, Alexandria 21521, Egypt
| | - Mohamed Teleb
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Alexandria University, Alexandria 21521, Egypt.
| | - Hanan M Ragab
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Alexandria University, Alexandria 21521, Egypt
| | - Monica Singh
- Tuberculosis Drug Discovery Laboratory, Pharmacy Group, Birla Institute of Technology and Science-Pilani, Hyderabad Campus, Hyderabad 500 0078, India
| | - Bassma H Elwakil
- Department of Medical Laboratory Technology, Faculty of Applied Health Sciences Technology, Pharos University in Alexandria, Alexandria, Egypt
| | - Lamia A Heikal
- Department of Pharmaceutics, Faculty of Pharmacy, Alexandria University, Alexandria 21521, Egypt
| | - D Sriram
- Tuberculosis Drug Discovery Laboratory, Pharmacy Group, Birla Institute of Technology and Science-Pilani, Hyderabad Campus, Hyderabad 500 0078, India
| | - Mona A Mahran
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Alexandria University, Alexandria 21521, Egypt
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Liu L, Yang L, Cao S, Gao Z, Yang B, Zhang G, Zhu R, Wu D. CyclicPepedia: a knowledge base of natural and synthetic cyclic peptides. Brief Bioinform 2024; 25:bbae190. [PMID: 38678388 PMCID: PMC11056021 DOI: 10.1093/bib/bbae190] [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: 11/27/2023] [Revised: 02/28/2024] [Accepted: 04/09/2024] [Indexed: 04/30/2024] Open
Abstract
Cyclic peptides offer a range of notable advantages, including potent antibacterial properties, high binding affinity and specificity to target molecules, and minimal toxicity, making them highly promising candidates for drug development. However, a comprehensive database that consolidates both synthetically derived and naturally occurring cyclic peptides is conspicuously absent. To address this void, we introduce CyclicPepedia (https://www.biosino.org/iMAC/cyclicpepedia/), a pioneering database that encompasses 8744 known cyclic peptides. This repository, structured as a composite knowledge network, offers a wealth of information encompassing various aspects of cyclic peptides, such as cyclic peptides' sources, categorizations, structural characteristics, pharmacokinetic profiles, physicochemical properties, patented drug applications, and a collection of crucial publications. Supported by a user-friendly knowledge retrieval system and calculation tools specifically designed for cyclic peptides, CyclicPepedia will be able to facilitate advancements in cyclic peptide drug development.
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Affiliation(s)
- Lei Liu
- Department of Gastroenterology, Shanghai Tenth People's Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200072, P. R. China
| | - Liu Yang
- National Center, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, P. R. China
| | - Suqi Cao
- National Center, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, P. R. China
| | - Zhigang Gao
- Department of General Surgery, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, P. R. China
| | - Bin Yang
- Shanghai Southgene Technology Co., Ltd., Shanghai 201203, China
| | - Guoqing Zhang
- National Genomics Data Center & Bio-Med Big Data Center, Chinese Academy of Sciences Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, P. R. China
| | - Ruixin Zhu
- Department of Gastroenterology, Shanghai Tenth People's Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200072, P. R. China
| | - Dingfeng Wu
- National Center, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, P. R. China
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25
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Velásquez-López Y, Ruiz-Escudero A, Arrasate S, González-Díaz H. Implementation of IFPTML Computational Models in Drug Discovery Against Flaviviridae Family. J Chem Inf Model 2024; 64:1841-1852. [PMID: 38466369 DOI: 10.1021/acs.jcim.3c01796] [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: 03/13/2024]
Abstract
The Flaviviridae family consists of single-stranded positive-sense RNA viruses, which contains the genera Flavivirus, Hepacivirus, Pegivirus, and Pestivirus. Currently, there is an outbreak of viral diseases caused by this family affecting millions of people worldwide, leading to significant morbidity and mortality rates. Advances in computational chemistry have greatly facilitated the discovery of novel drugs and treatments for diseases associated with this family. Chemoinformatic techniques, such as the perturbation theory machine learning method, have played a crucial role in developing new approaches based on ML models that can effectively aid drug discovery. The IFPTML models have shown its capability to handle, classify, and process large data sets with high specificity. The results obtained from different models indicates that this methodology is proficient in processing the data, resulting in a reduction of the false positive rate by 4.25%, along with an accuracy of 83% and reliability of 92%. These values suggest that the model can serve as a computational tool in assisting drug discovery efforts and the development of new treatments against Flaviviridae family diseases.
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Affiliation(s)
- Yendrek Velásquez-López
- Departamento de Química Orgánica e Inorgánica, Facultad de Ciencia y Tecnología, Universidad del País Vasco/Euskal Herriko Unibertsitatea UPV/EHU. Apdo. 644. 48080 Bilbao (Spain)
- Bio-Cheminformatics Research Group, Universidad de Las Américas, Quito 170504, (Ecuador)
| | - Andrea Ruiz-Escudero
- Department of Pharmacology, University of the Basque Country UPV/EHU, 48940 Leioa, (Spain)
- IKERDATA S.L., ZITEK, University of Basque Country UPV/EHU, Rectorate Building, 48940 Leioa, Spain
| | - Sonia Arrasate
- Departamento de Química Orgánica e Inorgánica, Facultad de Ciencia y Tecnología, Universidad del País Vasco/Euskal Herriko Unibertsitatea UPV/EHU. Apdo. 644. 48080 Bilbao (Spain)
| | - Humberto González-Díaz
- Departamento de Química Orgánica e Inorgánica, Facultad de Ciencia y Tecnología, Universidad del País Vasco/Euskal Herriko Unibertsitatea UPV/EHU. Apdo. 644. 48080 Bilbao (Spain)
- BIOFISIKA, Basque Center for Biophysics CSIC-UPV/EHU, 48940 Bilbao (Spain)
- IKERBASQUE, Basque Foundation for Science, 48011 Bilbao (Spain)
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26
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Jangra J, Bajad NG, Singh R, Kumar A, Singh SK. Identification of novel potential cathepsin-B inhibitors through pharmacophore-based virtual screening, molecular docking, and dynamics simulation studies for the treatment of Alzheimer's disease. Mol Divers 2024:10.1007/s11030-024-10821-z. [PMID: 38517648 DOI: 10.1007/s11030-024-10821-z] [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: 11/28/2023] [Accepted: 02/03/2024] [Indexed: 03/24/2024]
Abstract
Cathepsin B is a cysteine protease lysosomal enzyme involved in several physiological functions. Overexpression of the enzyme enhances its proteolytic activity and causes the breakdown of amyloid precursor protein (APP) into neurotoxic amyloid β (Aβ), a characteristic hallmark of Alzheimer's disease (AD). Therefore, inhibition of the enzyme is a crucial therapeutic aspect for treating the disease. Combined structure and ligand-based drug design strategies were employed in the current study to identify the novel potential cathepsin B inhibitors. Five different pharmacophore models were developed and used for the screening of the ZINC-15 database. The obtained hits were analyzed for the presence of duplicates, interfering PAINS moieties, and structural similarities based on Tanimoto's coefficient. The molecular docking study was performed to screen hits with better target binding affinity. The top seven hits were selected and were further evaluated based on their predicted ADME properties. The resulting best hits, ZINC827855702, ZINC123282431, and ZINC95386847, were finally subjected to molecular dynamics simulation studies to determine the stability of the protein-ligand complex during the run. ZINC123282431 was obtained as the virtual lead compound for cathepsin B inhibition and may be a promising novel anti-Alzheimer agent.
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Affiliation(s)
- Jatin Jangra
- Pharmaceutical Chemistry Research Laboratory-I, Department of Pharmaceutical Engineering & Technology, Indian Institute of Technology (Banaras Hindu University), Varanasi, 221005, India
| | - Nilesh Gajanan Bajad
- Pharmaceutical Chemistry Research Laboratory-I, Department of Pharmaceutical Engineering & Technology, Indian Institute of Technology (Banaras Hindu University), Varanasi, 221005, India
| | - Ravi Singh
- Pharmaceutical Chemistry Research Laboratory-I, Department of Pharmaceutical Engineering & Technology, Indian Institute of Technology (Banaras Hindu University), Varanasi, 221005, India
| | - Ashok Kumar
- Pharmaceutical Chemistry Research Laboratory-I, Department of Pharmaceutical Engineering & Technology, Indian Institute of Technology (Banaras Hindu University), Varanasi, 221005, India
| | - Sushil Kumar Singh
- Pharmaceutical Chemistry Research Laboratory-I, Department of Pharmaceutical Engineering & Technology, Indian Institute of Technology (Banaras Hindu University), Varanasi, 221005, India.
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27
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Onisuru O, Achilonu I. Describing the ligandin properties of Plasmodium falciparum and vivax glutathione transferase towards bromosulfophthalein from empirical and computational modelling viewpoints. J Biomol Struct Dyn 2024:1-16. [PMID: 38506165 DOI: 10.1080/07391102.2024.2329291] [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: 12/14/2023] [Accepted: 03/06/2024] [Indexed: 03/21/2024]
Abstract
Research has spotlighted glutathione transferase (GST) as a promising target for antimalarial drug development due to its pivotal role in cellular processes, including metabolizing toxins and managing oxidative stress. This interest arises from GST's potential to combat multidrug resistance in existing antimalarial drugs. Plasmodium falciparum GST (PfGST) and Plasmodium vivax GST (PvGST) are key targets; inhibiting them not only disrupt detoxification but also reduce their antioxidant capacity, a critical feature for potent antimalarials. Bromosulfophthalein (BSP), a clinical liver function dye, emerged as a potent cytosolic GST inhibitor. This study explored BSP's inhibitory properties on PfGST and PvGST, showcasing its binding capabilities through empirical and computational analyses. The study revealed BSP's ability to significantly inhibit GST activity, altering the proteins' structures and stability. Specifically, BSP binding induced spectral changes and impacted the proteins' thermal stability, reducing their melting temperatures. Computational simulations highlighted BSP's strong binding to PfGST and PvGST at their dimer interface, stabilized by various interactions, including hydrogen bonds and van der Waals forces. Notably, BSP's binding altered the proteins' compactness and conformational dynamics, suggesting a potential non-competitive, allosteric inhibition mechanism. This study provided novel insights into BSP's candidacy as an antimalarial drug by targeting PfGST and PvGST. Its ability to disrupt crucial functions of these enzymes' positions BSP as a promising candidate for further drug development in combating malariaCommunicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Olalekan Onisuru
- Protein Structure-Function and Research Unit, School of Molecular and Cell Biology, Faculty of Science, University of the Witwatersrand, Braamfontein, Johannesburg, South Africa
| | - Ikechukwu Achilonu
- Protein Structure-Function and Research Unit, School of Molecular and Cell Biology, Faculty of Science, University of the Witwatersrand, Braamfontein, Johannesburg, South Africa
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28
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Wu Z, Chen S, Wang Y, Li F, Xu H, Li M, Zeng Y, Wu Z, Gao Y. Current perspectives and trend of computer-aided drug design: a review and bibliometric analysis. Int J Surg 2024; 110:01279778-990000000-01229. [PMID: 38502850 PMCID: PMC11175770 DOI: 10.1097/js9.0000000000001289] [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: 11/08/2023] [Accepted: 02/22/2024] [Indexed: 03/21/2024]
Abstract
AIM Computer-aided drug design (CADD) is a drug design technique for computing ligand‒receptor interactions and is involved in various stages of drug development. To better grasp the frontiers and hotspots of CADD, we conducted a review analysis through bibliometrics. METHODS A systematic review of studies published between 2000 and July 20, 2023 was conducted following the PRISMA guidelines. Literature on CADD was selected from the Web of Science Core Collection. General information, publications, output trends, countries/regions, institutions, journals, keywords, and influential authors were visually analysed using software such as Excel, VOSviewer, RStudio, and CiteSpace. RESULTS A total of 2,031 publications were included. These publications primarily originated from 99 countries or regions, led by the U.S. and China. Among the contributors, MacKerell AD had the highest number of articles and greatest influence. The Journal of Medicinal Chemistry was the most cited journal, whereas the Journal of Chemical Information and Modeling had the highest number of publications. CONCLUSIONS Influential authors in the field were identified. Current research shows active collaboration between countries, institutions, and companies. CADD technologies such as homology modelling, pharmacophore modelling, quantitative conformational relationships, molecular docking, molecular dynamics simulation, binding free energy prediction, and high-throughput virtual screening can effectively improve the efficiency of new drug discovery. Artificial intelligence-assisted drug design and screening based on CADD represent key topics direction for future development. Furthermore, this paper will be helpful for better understanding the frontiers and hotspots of CADD.
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Affiliation(s)
- Zhenhui Wu
- School of Pharmacy, Jiangxi University of Chinese Medicine
- School of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang
- Beijing Institute of Radiation Medicine, Academy of Military Sciences, Beijing, People’s Republic of China
| | - Shupeng Chen
- School of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang
| | - Yihao Wang
- Beijing Institute of Radiation Medicine, Academy of Military Sciences, Beijing, People’s Republic of China
| | - Fangyang Li
- Beijing Institute of Radiation Medicine, Academy of Military Sciences, Beijing, People’s Republic of China
| | - Huanhua Xu
- School of Pharmacy, Jiangxi University of Chinese Medicine
| | - Maoxing Li
- Beijing Institute of Radiation Medicine, Academy of Military Sciences, Beijing, People’s Republic of China
| | - Yingjian Zeng
- School of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang
| | - Zhenfeng Wu
- School of Pharmacy, Jiangxi University of Chinese Medicine
| | - Yue Gao
- School of Pharmacy, Jiangxi University of Chinese Medicine
- Beijing Institute of Radiation Medicine, Academy of Military Sciences, Beijing, People’s Republic of China
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29
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Du B, Ru J, Zhan Z, Lin C, Liu Y, Mao W, Zhang J. Insight into small-molecule inhibitors targeting extracellular nucleotide pyrophosphatase/phosphodiesterase1 for potential multiple human diseases. Eur J Med Chem 2024; 268:116286. [PMID: 38432057 DOI: 10.1016/j.ejmech.2024.116286] [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: 12/31/2023] [Revised: 02/06/2024] [Accepted: 02/24/2024] [Indexed: 03/05/2024]
Abstract
Extracellular nucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) has been identified as a type II transmembrane glycoprotein. It plays a crucial role in various biological processes, such as bone mineralization, cancer cell proliferation, and immune regulation. Consequently, ENPP1 has garnered attention as a promising target for pharmacological interventions. Despite its potential, the development of clinical-stage ENPP1 inhibitors for solid tumors, diabetes, and silent rickets remains limited. However, there are encouraging findings from preclinical trials involving small molecules exhibiting favorable therapeutic effects and safety profiles. This perspective aims to shed light on the structural properties, biological functions and the relationship between ENPP1 and diseases. Additionally, it focuses on the structure-activity relationship of ENPP1 inhibitors, with the intention of guiding the future development of new and effective ENPP1 inhibitors.
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Affiliation(s)
- Baochan Du
- Department of Neurology, Neuro-system and Multimorbidity Laboratory and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China; Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Jinxiao Ru
- Department of Neurology, Neuro-system and Multimorbidity Laboratory and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China; Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Zixuan Zhan
- Department of Neurology, Neuro-system and Multimorbidity Laboratory and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Congcong Lin
- Department of Medicinal Chemistry and Natural Medicine Chemistry, College of Pharmacy, Harbin Medical University, Harbin, 150081, China
| | - Yang Liu
- Department of Medical Oncology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, 233004, China
| | - Wuyu Mao
- Department of Neurology, Neuro-system and Multimorbidity Laboratory and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
| | - Jifa Zhang
- Department of Neurology, Neuro-system and Multimorbidity Laboratory and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China; Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China.
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30
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Lin C, Mazor Y, Reppert M. Feeling the Strain: Quantifying Ligand Deformation in Photosynthesis. J Phys Chem B 2024; 128:2266-2280. [PMID: 38442033 DOI: 10.1021/acs.jpcb.3c06488] [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: 03/07/2024]
Abstract
Structural distortion of protein-bound ligands can play a critical role in enzyme function by tuning the electronic and chemical properties of the ligand molecule. However, quantifying these effects is difficult due to the limited resolution of protein structures and the difficulty of generating accurate structural restraints for nonprotein ligands. Here, we seek to quantify these effects through a statistical analysis of ligand distortion in chlorophyll proteins (CP), where ring deformation is thought to play a role in energy and electron transfer. To assess the accuracy of ring-deformation estimates from available structural data, we take advantage of the C2 symmetry of photosystem II (PSII), comparing ring-deformation estimates for equivalent sites both within and between 113 distinct X-ray and cryogenic electron microscopy PSII structures. Significantly, we find that several deformation modes exhibit considerable variability in predictions, even for equivalent monomers, down to a 2 Å resolution, to an extent that probably prevents their utilization in optical calculations. We further find that refinement restraints play a critical role in determining deformation values to resolution as low as 2 Å. However, for those modes that are well-resolved in the structural data, ring deformation in PSII is strongly conserved across all species tested from cyanobacteria to algae. These results highlight both the opportunities and limitations inherent in structure-based analyses of the bioenergetic and optical properties of CPs and other protein-ligand complexes.
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Affiliation(s)
- Chientzu Lin
- Department of Chemistry, Purdue University, West Lafayette, Indiana 47920, United States
| | - Yuval Mazor
- School of Molecular Sciences, The Biodesign Institute, Arizona State University, Tempe, Arizona 85281, United States
| | - Mike Reppert
- Department of Chemistry, Purdue University, West Lafayette, Indiana 47920, United States
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31
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Tu G, Fu T, Zheng G, Xu B, Gou R, Luo D, Wang P, Xue W. Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives. J Chem Inf Model 2024; 64:1433-1455. [PMID: 38294194 DOI: 10.1021/acs.jcim.3c01736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Solute carrier transporters (SLCs) are a class of important transmembrane proteins that are involved in the transportation of diverse solute ions and small molecules into cells. There are approximately 450 SLCs within the human body, and more than a quarter of them are emerging as attractive therapeutic targets for multiple complex diseases, e.g., depression, cancer, and diabetes. However, only 44 unique transporters (∼9.8% of the SLC superfamily) with 3D structures and specific binding sites have been reported. To design innovative and effective drugs targeting diverse SLCs, there are a number of obstacles that need to be overcome. However, computational chemistry, including physics-based molecular modeling and machine learning- and deep learning-based artificial intelligence (AI), provides an alternative and complementary way to the classical drug discovery approach. Here, we present a comprehensive overview on recent advances and existing challenges of the computational techniques in structure-based drug design of SLCs from three main aspects: (i) characterizing multiple conformations of the proteins during the functional process of transportation, (ii) identifying druggability sites especially the cryptic allosteric ones on the transporters for substrates and drugs binding, and (iii) discovering diverse small molecules or synthetic protein binders targeting the binding sites. This work is expected to provide guidelines for a deep understanding of the structure and function of the SLC superfamily to facilitate rational design of novel modulators of the transporters with the aid of state-of-the-art computational chemistry technologies including artificial intelligence.
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Affiliation(s)
- Gao Tu
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Tingting Fu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | | | - Binbin Xu
- Chengdu Sintanovo Biotechnology Co., Ltd., Chengdu 610200, China
| | - Rongpei Gou
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Ding Luo
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Panpan Wang
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China
| | - Weiwei Xue
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
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32
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Cebi E, Lee J, Subramani VK, Bak N, Oh C, Kim KK. Cryo-electron microscopy-based drug design. Front Mol Biosci 2024; 11:1342179. [PMID: 38501110 PMCID: PMC10945328 DOI: 10.3389/fmolb.2024.1342179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 01/31/2024] [Indexed: 03/20/2024] Open
Abstract
Structure-based drug design (SBDD) has gained popularity owing to its ability to develop more potent drugs compared to conventional drug-discovery methods. The success of SBDD relies heavily on obtaining the three-dimensional structures of drug targets. X-ray crystallography is the primary method used for solving structures and aiding the SBDD workflow; however, it is not suitable for all targets. With the resolution revolution, enabling routine high-resolution reconstruction of structures, cryogenic electron microscopy (cryo-EM) has emerged as a promising alternative and has attracted increasing attention in SBDD. Cryo-EM offers various advantages over X-ray crystallography and can potentially replace X-ray crystallography in SBDD. To fully utilize cryo-EM in drug discovery, understanding the strengths and weaknesses of this technique and noting the key advancements in the field are crucial. This review provides an overview of the general workflow of cryo-EM in SBDD and highlights technical innovations that enable its application in drug design. Furthermore, the most recent achievements in the cryo-EM methodology for drug discovery are discussed, demonstrating the potential of this technique for advancing drug development. By understanding the capabilities and advancements of cryo-EM, researchers can leverage the benefits of designing more effective drugs. This review concludes with a discussion of the future perspectives of cryo-EM-based SBDD, emphasizing the role of this technique in driving innovations in drug discovery and development. The integration of cryo-EM into the drug design process holds great promise for accelerating the discovery of new and improved therapeutic agents to combat various diseases.
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Affiliation(s)
| | | | | | | | - Changsuk Oh
- Department of Precision Medicine, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea
| | - Kyeong Kyu Kim
- Department of Precision Medicine, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea
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33
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R D, S W, D P D, R S. Cracking a cancer code DNA methylation in epigenetic modification: an in-silico approach on efficacy assessment of Sri Lanka-oriented nutraceuticals. J Biomol Struct Dyn 2024:1-21. [PMID: 38425013 DOI: 10.1080/07391102.2024.2321235] [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: 08/02/2023] [Accepted: 02/14/2024] [Indexed: 03/02/2024]
Abstract
DNA methyltransferase (DNMTs) are essential epigenetic modifiers that play a critical role in gene regulation. These enzymes add a methyl group to cytosine's 5'-carbon, specifically within CpG dinucleotides, using S-adenosyl-L-methionine. Abnormal overexpression of DNMTs can alter the gene expression patterns and contribute to cancer development in the human body. Therefore, the inhibition of DNMT is a promising therapeutic approach to cancer treatment. This study was aimed to identify potential nutraceutical inhibitors from the Sri Lanka Flora database using computational methods, which provided an atomic-level description of the drug binding site and examined the interactions between nutraceuticals and amino acids of the DNMT enzyme. A series of nutraceuticals from Sri Lanka-oriented plants were selected and evaluated to assess their inhibitory effects on DNMT using absorption, distribution, metabolism, excretion and toxicity analysis, virtual screening, molecular docking, molecular dynamics simulation and trajectory analysis. Azacitidine, a DNMT inhibitor approved by the US Food and Drug Administration, was selected as a reference inhibitor. The complexes with more negative binding energies were selected and further assessed for their potency. Seven molecules were identified from 200 nutraceuticals, demonstrating significantly negative binding energies against the DNMT enzyme. Various trajectory analyses were conducted to investigate the stability of the DNMT enzyme. The results indicated that petchicine (NP#0003), ouregidione (NP#0011) and azacitidine increased the stability of the DNMT enzyme. Consequently, these two nutraceuticals showed inhibitory efficacies similar to azacitidine, making them potential candidates for therapeutic interventions targeting DNMT enzyme-related cancers. Additional bioassay testing is recommended to confirm the efficacies of these nutraceuticals and explore their applicability in clinical treatments.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Dushanan R
- Department of Chemistry, Faculty of Natural Sciences, The Open University of Sri Lanka, Nawala, Sri Lanka
| | - Weerasinghe S
- Department of Chemistry, Faculty of Science, University of Colombo, Colombo, Sri Lanka
| | - Dissanayake D P
- Department of Chemistry, Faculty of Science, University of Colombo, Colombo, Sri Lanka
| | - Senthilnithy R
- Department of Chemistry, Faculty of Natural Sciences, The Open University of Sri Lanka, Nawala, Sri Lanka
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Draper MR, Waterman A, Dannatt JE, Patel P. Integrating multiscale and machine learning approaches towards the SAMPL9 log P challenge. Phys Chem Chem Phys 2024; 26:7907-7919. [PMID: 38376855 PMCID: PMC10938873 DOI: 10.1039/d3cp04140a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
The partition coefficient (log P) is an important physicochemical property that provides information regarding a molecule's pharmacokinetics, toxicity, and bioavailability. Methods to accurately predict the partition coefficient have the potential to accelerate drug design. In an effort to test current methods and explore new computational techniques, the statistical assessment of the modeling of proteins and ligands (SAMPL) has established a blind prediction challenge. The ninth iteration challenge was to predict the toluene-water partition coefficient (log Ptol/w) of sixteen drug molecules. Herein, three approaches are reported broadly under the categories of quantum mechanics (QM), molecular mechanics (MM), and data-driven machine learning (ML). The three blind submissions yield mean unsigned errors (MUE) ranging from 1.53-2.93 log Ptol/w units. The MUEs were reduced to 1.00 log Ptol/w for the QM methods. While MM and ML methods outperformed DFT approaches for challenge molecules with fewer rotational degrees of freedom, they suffered for the larger molecules in this dataset. Overall, DFT functionals paired with a triple-ζ basis set were the simplest and most effective tool to obtain quantitatively accurate partition coefficients.
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Affiliation(s)
- Michael R Draper
- Chemistry Department, University of Dallas, Irving, Texas, 75062, USA.
| | - Asa Waterman
- Chemistry Department, University of Dallas, Irving, Texas, 75062, USA.
| | | | - Prajay Patel
- Chemistry Department, University of Dallas, Irving, Texas, 75062, USA.
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35
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Borges PHO, Ferreira SB, Silva FP. Recent Advances on Targeting Proteases for Antiviral Development. Viruses 2024; 16:366. [PMID: 38543732 PMCID: PMC10976044 DOI: 10.3390/v16030366] [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: 01/19/2024] [Revised: 02/21/2024] [Accepted: 02/24/2024] [Indexed: 05/23/2024] Open
Abstract
Viral proteases are an important target for drug development, since they can modulate vital pathways in viral replication, maturation, assembly and cell entry. With the (re)appearance of several new viruses responsible for causing diseases in humans, like the West Nile virus (WNV) and the recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), understanding the mechanisms behind blocking viral protease's function is pivotal for the development of new antiviral drugs and therapeutical strategies. Apart from directly inhibiting the target protease, usually by targeting its active site, several new pathways have been explored to impair its activity, such as inducing protein aggregation, targeting allosteric sites or by inducing protein degradation by cellular proteasomes, which can be extremely valuable when considering the emerging drug-resistant strains. In this review, we aim to discuss the recent advances on a broad range of viral proteases inhibitors, therapies and molecular approaches for protein inactivation or degradation, giving an insight on different possible strategies against this important class of antiviral target.
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Affiliation(s)
- Pedro Henrique Oliveira Borges
- Laboratory of Organic Synthesis and Biological Prospecting, Chemistry Institute, Federal University of Rio de Janeiro, Rio de Janeiro 21941-909, Brazil;
- Laboratory of Experimental and Computational Biochemistry of Drugs, Oswaldo Cruz Institute, Fiocruz, Rio de Janeiro 21040-900, Brazil
| | - Sabrina Baptista Ferreira
- Laboratory of Organic Synthesis and Biological Prospecting, Chemistry Institute, Federal University of Rio de Janeiro, Rio de Janeiro 21941-909, Brazil;
| | - Floriano Paes Silva
- Laboratory of Experimental and Computational Biochemistry of Drugs, Oswaldo Cruz Institute, Fiocruz, Rio de Janeiro 21040-900, Brazil
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Uddin MJ, Niloy SI, Aktaruzzaman M, Talukder MEK, Rahman MM, Imon RR, Uddin AFMS, Amin MZ. Neuropharmacological assessment and identification of possible lead compound (apomorphine) from Hygrophila spinosa through in-vivo and in-silico approaches. J Biomol Struct Dyn 2024:1-16. [PMID: 38385482 DOI: 10.1080/07391102.2024.2317974] [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: 08/23/2023] [Accepted: 02/07/2024] [Indexed: 02/23/2024]
Abstract
The aim of this research is to examine possible neurological activity of methanol, ethyl acetate, and aqueous extracts of Hygrophila spinosa and identify possible lead compounds through in silico analysis. In vivo, neuropharmacological activity was evaluated by using four distinct neuropharmacological assessment assays. Previously reported GC-MS data and earlier literature were utilized to identify the phytochemicals present in Hygrophila spinosa. Computational studies notably molecular docking and molecular dynamic simulations were conducted with responsible receptors to assess the stability of the best interacting compound. Pharmacokinetics properties like absorption, distribution, metabolism, excretion, and toxicity were considered to evaluate the drug likeliness properties of the identified compounds. All the in vivo results support the notion that different extracts (methanol, ethyl acetate, and aqueous) of Hygrophila spinosa have significant (*p = 0.05) sedative-hypnotic, anxiolytic, and anti-depressant activity. Among all the extracts, specifically methanol extracts of Hygrophila spinosa (MHS 400 mg/kg.b.w.) showed better sedative, anxiolytic and antidepressant activity than aqueous and ethyl acetate extracts. In silico molecular docking analysis revealed that among 53 compounds 7 compounds showed good binding affinities and one compound, namely apomorphine (CID: 6005), surprisingly showed promising binding affinity to all the receptors . An analysis of molecular dynamics simulations confirmed that apomorphine (CID: 6005) had a high level of stability at the protein binding site. Evidence suggests that Hygrophila spinosa has significant sedative, anxiolytic, and antidepressant activity. In silico analysis revealed that a particular compound (apomorphine) is responsible for this action. Further research is required in order to establish apomorphine as a drug for anxiety, depression, and sleep disorders.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Mohammad Jashim Uddin
- Department of Pharmacy, Faculty of Biological Science and Technology, Jashore University of Science and Technology, Jashore, Bangladesh
- Laboratory of Clinical Pharmacy and Pharmacology. Department of Pharmacy, Jashore University of Science and Technology, Jashore, Bangladesh
- Laboratory of Pharmaceutical Technology, Department of Pharmacy, Jashore University of Science and Technology, Jashore, Bangladesh
| | | | - Md Aktaruzzaman
- Department of Pharmacy, Faculty of Biological Science and Technology, Jashore University of Science and Technology, Jashore, Bangladesh
- Laboratory of Clinical Pharmacy and Pharmacology. Department of Pharmacy, Jashore University of Science and Technology, Jashore, Bangladesh
- Laboratory of Pharmaceutical Technology, Department of Pharmacy, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Md Enamul Kabir Talukder
- Molecular and Cellular Biology Laboratory, Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Md Mashiar Rahman
- Molecular and Cellular Biology Laboratory, Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Raihan Rahman Imon
- Molecular and Cellular Biology Laboratory, Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - A F M Shahab Uddin
- Department of Computer Science and Engineering, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Md Ziaul Amin
- Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
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Mondal I, Halder AK, Pattanayak N, Mandal SK, Cordeiro MNDS. Shaping the Future of Obesity Treatment: In Silico Multi-Modeling of IP6K1 Inhibitors for Obesity and Metabolic Dysfunction. Pharmaceuticals (Basel) 2024; 17:263. [PMID: 38399478 PMCID: PMC10891520 DOI: 10.3390/ph17020263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 02/14/2024] [Accepted: 02/16/2024] [Indexed: 02/25/2024] Open
Abstract
Recent research has uncovered a promising approach to addressing the growing global health concern of obesity and related disorders. The inhibition of inositol hexakisphosphate kinase 1 (IP6K1) has emerged as a potential therapeutic strategy. This study employs multiple ligand-based in silico modeling techniques to investigate the structural requirements for benzisoxazole derivatives as IP6K1 inhibitors. Firstly, we developed linear 2D Quantitative Structure-Activity Relationship (2D-QSAR) models to ensure both their mechanistic interpretability and predictive accuracy. Then, ligand-based pharmacophore modeling was performed to identify the essential features responsible for the compounds' high activity. To gain insights into the 3D requirements for enhanced potency against the IP6K1 enzyme, we employed multiple alignment techniques to set up 3D-QSAR models. Given the absence of an available X-ray crystal structure for IP6K1, a reliable homology model for the enzyme was developed and structurally validated in order to perform structure-based analyses on the selected dataset compounds. Finally, molecular dynamic simulations, using the docked poses of these compounds, provided further insights. Our findings consistently supported the mechanistic interpretations derived from both ligand-based and structure-based analyses. This study offers valuable guidance on the design of novel IP6K1 inhibitors. Importantly, our work exclusively relies on non-commercial software packages, ensuring accessibility for reproducing the reported models.
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Affiliation(s)
- Ismail Mondal
- Dr. B. C. Roy College of Pharmacy and Allied Health Sciences, Dr. Meghnad Saha Sarani, Bidhannagar, Durgapur 713206, India; (I.M.); (A.K.H.); (N.P.); (S.K.M.)
| | - Amit Kumar Halder
- Dr. B. C. Roy College of Pharmacy and Allied Health Sciences, Dr. Meghnad Saha Sarani, Bidhannagar, Durgapur 713206, India; (I.M.); (A.K.H.); (N.P.); (S.K.M.)
- LAQV@REQUIMTE, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal
| | - Nirupam Pattanayak
- Dr. B. C. Roy College of Pharmacy and Allied Health Sciences, Dr. Meghnad Saha Sarani, Bidhannagar, Durgapur 713206, India; (I.M.); (A.K.H.); (N.P.); (S.K.M.)
| | - Sudip Kumar Mandal
- Dr. B. C. Roy College of Pharmacy and Allied Health Sciences, Dr. Meghnad Saha Sarani, Bidhannagar, Durgapur 713206, India; (I.M.); (A.K.H.); (N.P.); (S.K.M.)
| | - Maria Natalia D. S. Cordeiro
- LAQV@REQUIMTE, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal
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Zhou N, Zheng C, Tan H, Luo L. Identification of PLK1-PBD Inhibitors from the Library of Marine Natural Products: 3D QSAR Pharmacophore, ADMET, Scaffold Hopping, Molecular Docking, and Molecular Dynamics Study. Mar Drugs 2024; 22:83. [PMID: 38393054 PMCID: PMC10890274 DOI: 10.3390/md22020083] [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: 12/30/2023] [Revised: 02/03/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
PLK1 is found to be highly expressed in various types of cancers, but the development of inhibitors for it has been slow. Most inhibitors are still in clinical stages, and many lack the necessary selectivity and anti-tumor effects. This study aimed to create new inhibitors for the PLK1-PBD by focusing on the PBD binding domain, which has the potential for greater selectivity. A 3D QSAR model was developed using a dataset of 112 compounds to evaluate 500 molecules. ADMET prediction was then used to select three molecules with strong drug-like characteristics. Scaffold hopping was employed to reconstruct 98 new compounds with improved drug-like properties and increased activity. Molecular docking was used to compare the efficient compound abbapolin, confirming the high-activity status of [(14S)-14-hydroxy-14-(pyridin-2-yl)tetradecyl]ammonium,[(14S)-15-(2-furyl)-14-hydroxypentadecyl]ammonium and [(14S)-14-hydroxy-14-phenyltetradecyl]ammonium. Molecular dynamics simulations and MMPBSA were conducted to evaluate the stability of the compounds in the presence of proteins. An in-depth analysis of [(14S)-15-(2-furyl)-14-hydroxypentadecyl]ammonium and [(14S)-14-hydroxy-14-phenyltetradecyl]ammonium identified them as potential candidates for PLK1 inhibitors.
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Affiliation(s)
- Nan Zhou
- The First Clinical College, Guangdong Medical University, Zhanjiang 524023, China; (N.Z.); (C.Z.); (H.T.)
| | - Chuangze Zheng
- The First Clinical College, Guangdong Medical University, Zhanjiang 524023, China; (N.Z.); (C.Z.); (H.T.)
| | - Huiting Tan
- The First Clinical College, Guangdong Medical University, Zhanjiang 524023, China; (N.Z.); (C.Z.); (H.T.)
| | - Lianxiang Luo
- The Marine Biomedical Research Institute, School of Ocean and Tropical Medicine, Guangdong Medical University, Zhanjiang 524023, China
- The Marine Biomedical Research Institute of Guangdong Zhanjiang, Zhanjiang 524023, China
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Azevedo PHRDA, Peçanha BRDB, Flores-Junior LAP, Alves TF, Dias LRS, Muri EMF, Lima CHDS. In silico drug repurposing by combining machine learning classification model and molecular dynamics to identify a potential OGT inhibitor. J Biomol Struct Dyn 2024; 42:1417-1428. [PMID: 37054524 DOI: 10.1080/07391102.2023.2199868] [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: 10/20/2022] [Accepted: 04/01/2023] [Indexed: 04/15/2023]
Abstract
O-linked N-acetylglucosamine (O-GlcNAc) is a unique intracellular post-translational glycosylation at the hydroxyl group of serine or threonine residues in nuclear, cytoplasmic and mitochondrial proteins. The enzyme O-GlcNAc transferase (OGT) is responsible for adding GlcNAc, and anomalies in this process can lead to the development of diseases associated with metabolic imbalance, such as diabetes and cancer. Repurposing approved drugs can be an attractive tool to discover new targets reducing time and costs in the drug design. This work focuses on drug repurposing to OGT targets by virtual screening of FDA-approved drugs through consensus machine learning (ML) models from an imbalanced dataset. We developed a classification model using docking scores and ligand descriptors. The SMOTE approach to resampling the dataset showed excellent statistical values in five of the seven ML algorithms to create models from the training set, with sensitivity, specificity and accuracy over 90% and Matthew's correlation coefficient greater than 0.8. The pose analysis obtained by molecular docking showed only H-bond interaction with the OGT C-Cat domain. The molecular dynamics simulation showed the lack of H-bond interactions with the C- and N-catalytic domains allowed the drug to exit the binding site. Our results showed that the non-steroidal anti-inflammatory celecoxib could be a potentially OGT inhibitor.
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Affiliation(s)
| | | | | | - Tatiana Fialho Alves
- Laboratório de Química Medicinal, Faculdade de Farmácia, Universidade Federal Fluminense, Niterói, RJ, Brazil
| | - Luiza Rosaria Sousa Dias
- Laboratório de Química Medicinal, Faculdade de Farmácia, Universidade Federal Fluminense, Niterói, RJ, Brazil
| | - Estela Maris Freitas Muri
- Laboratório de Química Medicinal, Faculdade de Farmácia, Universidade Federal Fluminense, Niterói, RJ, Brazil
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40
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Adebayo GP, Oduselu GO, Aderohunmu DV, Klika KD, Olasehinde GI, Ajani OO, Adebiyi E. Structure-based design, and development of amidinyl, amidoximyl and hydroxamic acid based organic molecules as novel antimalarial drug candidates. ARAB J CHEM 2024; 17:105573. [PMID: 38283036 PMCID: PMC10810238 DOI: 10.1016/j.arabjc.2023.105573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2024] Open
Abstract
Malaria remains a significant global health concern causing numerous fatalities and the emergence of antimalarial drug resistance highlights the urgent need for novel therapeutic options with innovative mechanisms of action and targets. This study aimed to design potential inhibitors of Plasmodium falciparum 6-pyruvoyltetrahydropterin synthase (PfPTPS), synthesize them, and experimentally validate their efficacy as antimalarial agents. A structure-based approach was employed to design a series of novel derivatives, including amidinyl, amidoximyl and hydroxamic acid analogs (1c, 1d, 2b, and 3b), with a focus on their ability to bind to the Zn2+ present in the active site of PfPTPS. The syntheses of these compounds were accomplished through various multi-step synthetic pathways and their structural identities were confirmed using 1H and 13C NMR spectra, mass spectra, and elemental analysis. The compounds were screened for their antiplasmodial activity against the NF54 strain of P. falciparum and in vitro cytotoxicity testing was performed using L-6 cells. The in vivo acute toxicity of the compounds was evaluated in mice. Docking studies of the compounds with the 3D structure of PfPTPS revealed their strong binding affinities, with compound 3b exhibiting notable metal-acceptor interaction with the Zn2+ in the protein binding pocket thereby positioning it as a lead compound for PfPTPS inhibition. The in vitro antiplasmodial studies revealed moderate efficacies against the Pf NF54 strain, particularly compounds 1d and 3b which displayed IC50 < 0.2 μM. No significant cytotoxicity was noted on the L-6 rat cell line. Moreover, in vivo studies suggested that compound 3b exhibited both safety and efficacy in treating rodent malaria. The identified lead compound in this study represents a possible candidate for antimalarial drug development and can be further explored in the search for alternative antifolate drugs to combat the malaria menace.
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Affiliation(s)
- Glory P. Adebayo
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria
- Biological Sciences Department, Covenant University, Ota, Nigeria
| | - Gbolahan O. Oduselu
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria
| | | | - Karel D. Klika
- NMR Structural Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Grace I. Olasehinde
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria
- Biological Sciences Department, Covenant University, Ota, Nigeria
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota 112233, Nigeria
| | - Olayinka O. Ajani
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota 112233, Nigeria
- Department of Chemistry, Covenant University, Covenant University, Km 10 Idiroko Road, P.M.B. 1023 Ota, Ogun State, Nigeria
| | - Ezekiel Adebiyi
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota 112233, Nigeria
- Department of Computer and Information Sciences, Covenant University, Ota, Nigeria
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
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41
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Ugrani S. Inhibitor design for TMPRSS2: insights from computational analysis of its backbone hydrogen bonds using a simple descriptor. EUROPEAN BIOPHYSICS JOURNAL : EBJ 2024; 53:27-46. [PMID: 38157015 PMCID: PMC10853362 DOI: 10.1007/s00249-023-01695-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 12/04/2023] [Accepted: 12/07/2023] [Indexed: 01/03/2024]
Abstract
Transmembrane protease serine 2 (TMPRSS2) is an important drug target due to its role in the infection mechanism of coronaviruses including SARS-CoV-2. Current understanding regarding the molecular mechanisms of known inhibitors and insights required for inhibitor design are limited. This study investigates the effect of inhibitor binding on the intramolecular backbone hydrogen bonds (BHBs) of TMPRSS2 using the concept of hydrogen bond wrapping, which is the phenomenon of stabilization of a hydrogen bond in a solvent environment as a result of being surrounded by non-polar groups. A molecular descriptor which quantifies the extent of wrapping around BHBs is introduced for this. First, virtual screening for TMPRSS2 inhibitors is performed by molecular docking using the program DOCK 6 with a Generalized Born surface area (GBSA) scoring function. The docking results are then analyzed using this descriptor and its relationship to the solvent-accessible surface area term ΔGsa of the GBSA score is demonstrated with machine learning regression and principal component analysis. The effect of binding of the inhibitors camostat, nafamostat, and 4-guanidinobenzoic acid (GBA) on the wrapping of important BHBs in TMPRSS2 is also studied using molecular dynamics. For BHBs with a large increase in wrapping groups due to these inhibitors, the radial distribution function of water revealed that certain residues involved in these BHBs, like Gln438, Asp440, and Ser441, undergo preferential desolvation. The findings offer valuable insights into the mechanisms of these inhibitors and may prove useful in the design of new inhibitors.
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Affiliation(s)
- Suraj Ugrani
- Purdue University, West Lafayette, IN, 47907, USA.
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42
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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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Li H, Sun X, Cui W, Xu M, Dong J, Ekundayo BE, Ni D, Rao Z, Guo L, Stahlberg H, Yuan S, Vogel H. Computational drug development for membrane protein targets. Nat Biotechnol 2024; 42:229-242. [PMID: 38361054 DOI: 10.1038/s41587-023-01987-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 09/13/2023] [Indexed: 02/17/2024]
Abstract
The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learning structure-based design and the evaluation of big data. Recent protein structure predictions based on machine learning tools have delivered surprisingly reliable results for water-soluble and membrane proteins but have limitations for development of drugs that target membrane proteins. Structural transitions of membrane proteins have a central role during transmembrane signaling and are often influenced by therapeutic compounds. Resolving the structural and functional basis of dynamic transmembrane signaling networks, especially within the native membrane or cellular environment, remains a central challenge for drug development. Tackling this challenge will require an interplay between experimental and computational tools, such as super-resolution optical microscopy for quantification of the molecular interactions of cellular signaling networks and their modulation by potential drugs, cryo-electron microscopy for determination of the structural transitions of proteins in native cell membranes and entire cells, and computational tools for data analysis and prediction of the structure and function of cellular signaling networks, as well as generation of promising drug candidates.
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Affiliation(s)
- Haijian Li
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
| | - Xiaolin Sun
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
| | - Wenqiang Cui
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Marc Xu
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Junlin Dong
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Babatunde Edukpe Ekundayo
- Laboratory of Biological Electron Microscopy, IPHYS, SB, EPFL and Department of Fundamental Microbiology, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Dongchun Ni
- Laboratory of Biological Electron Microscopy, IPHYS, SB, EPFL and Department of Fundamental Microbiology, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Zhili Rao
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
| | - Liwei Guo
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
| | - Henning Stahlberg
- Laboratory of Biological Electron Microscopy, IPHYS, SB, EPFL and Department of Fundamental Microbiology, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.
| | - Shuguang Yuan
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China.
| | - Horst Vogel
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China.
- Institut des Sciences et Ingénierie Chimiques (ISIC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
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Yssartier T, Liu L, Pardoue S, Le Questel JY, Guérard F, Montavon G, Galland N. In vivo stability of 211At-radiopharmaceuticals: on the impact of halogen bond formation. RSC Med Chem 2024; 15:223-233. [PMID: 38283213 PMCID: PMC10809332 DOI: 10.1039/d3md00579h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 11/22/2023] [Indexed: 01/30/2024] Open
Abstract
211At, when coupled to a targeting agent, is one of the most promising radionuclides for therapeutic applications. The main labelling approach consists in the formation of astatoaryl compounds, which often show a lack of in vivo stability. The hypothesis that halogen bond (XB) interactions with protein functional groups initiate a deastatination mechanism is investigated through radiochemical experiments and DFT modelling. Several descriptors agree on the known mechanism of iodoaryl substrates dehalogenation by iodothyronine deiodinases, supporting the higher in vivo dehalogenation of N-succinimidyl 3-[211At]astatobenzoate (SAB) conjugates in comparison with their iodinated counterparts. The guanidinium group in 3-[211At]astato-4-guanidinomethylbenzoate (SAGMB) prevents the formation of At-mediated XBs with the selenocysteine active site in iodothyronine deiodinases. The initial step of At-aryl bond dissociation is inhibited, elucidating the better in vivo stability of SAGMB conjugates compared with those of SAB. The impact of astatine's ability to form XB interactions on radiopharmaceutical degradation may not be limited to the case of aryl radiolabeling.
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Affiliation(s)
- Thibault Yssartier
- CNRS, CEISAM UMR 6230, Nantes Université F-44000 Nantes France
- CNRS, SUBATECH UMR 6457, IMT Atlantique F-44307 Nantes France
| | - Lu Liu
- CNRS, IPHC UMR 7178, Université de Strasbourg F-67037 Strasbourg France
| | - Sylvain Pardoue
- CNRS, SUBATECH UMR 6457, IMT Atlantique F-44307 Nantes France
| | | | - François Guérard
- Inserm UMR 1307, CNRS UMR 6075, CRCI2NA, Nantes Université, Université d'Angers F-44000 Nantes France
| | - Gilles Montavon
- CNRS, SUBATECH UMR 6457, IMT Atlantique F-44307 Nantes France
| | - Nicolas Galland
- CNRS, CEISAM UMR 6230, Nantes Université F-44000 Nantes France
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45
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Cai H, Shen C, Jian T, Zhang X, Chen T, Han X, Yang Z, Dang W, Hsieh CY, Kang Y, Pan P, Ji X, Song J, Hou T, Deng Y. CarsiDock: a deep learning paradigm for accurate protein-ligand docking and screening based on large-scale pre-training. Chem Sci 2024; 15:1449-1471. [PMID: 38274053 PMCID: PMC10806797 DOI: 10.1039/d3sc05552c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/18/2023] [Indexed: 01/27/2024] Open
Abstract
The expertise accumulated in deep neural network-based structure prediction has been widely transferred to the field of protein-ligand binding pose prediction, thus leading to the emergence of a variety of deep learning-guided docking models for predicting protein-ligand binding poses without relying on heavy sampling. However, their prediction accuracy and applicability are still far from satisfactory, partially due to the lack of protein-ligand binding complex data. To this end, we create a large-scale complex dataset containing ∼9 M protein-ligand docking complexes for pre-training, and propose CarsiDock, the first deep learning-guided docking approach that leverages pre-training of millions of predicted protein-ligand complexes. CarsiDock contains two main stages, i.e., a deep learning model for the prediction of protein-ligand atomic distance matrices, and a translation, rotation and torsion-guided geometry optimization procedure to reconstruct the matrices into a credible binding pose. The pre-training and multiple innovative architectural designs facilitate the dramatically improved docking accuracy of our approach over the baselines in terms of multiple docking scenarios, thereby contributing to its outstanding early recognition performance in several retrospective virtual screening campaigns. Further explorations demonstrate that CarsiDock can not only guarantee the topological reliability of the binding poses but also successfully reproduce the crucial interactions in crystalized structures, highlighting its superior applicability.
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Affiliation(s)
- Heng Cai
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
| | - Chao Shen
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Tianye Jian
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
| | - Xujun Zhang
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Tong Chen
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
| | - Xiaoqi Han
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
| | - Zhuo Yang
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
| | - Wei Dang
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
| | - Chang-Yu Hsieh
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Yu Kang
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Peichen Pan
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Xiangyang Ji
- Department of Automation, Tsinghua University Beijing 100084 China
| | - Jianfei Song
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
| | - Tingjun Hou
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Yafeng Deng
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
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46
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Sinha P, Yadav AK. Repurposing integrase inhibitors against human T-lymphotropic virus type-1: a computational approach. J Biomol Struct Dyn 2024:1-12. [PMID: 38234060 DOI: 10.1080/07391102.2024.2304681] [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: 08/10/2023] [Accepted: 01/07/2024] [Indexed: 01/19/2024]
Abstract
Adult T-cell Lymphoma (ATL) is caused by the delta retrovirus family member known as Human T-cell Leukaemia Type I (HTLV-1). Due to the unavailability of any cure, the study gained motivation to identify some repurposed drugs against the virus. A quick and accurate method of screening licensed medications for finding a treatment for HTLV-1 is by cheminformatics drug repurposing in order to analyze a dataset of FDA approved integrase antivirals against HTLV-1 infection. To determine how the antiviral medications interacted with the important residues in the HTLV-1 integrase active regions, molecular docking modeling was used. The steady behavior of the ligands inside the active region was then confirmed by molecular dynamics for the probable receptor-drug complexes. Cabotegravir, Raltegravir and Elvitegravir had the best docking scores with the target, indicating that they can tightly bind to the HTLV-1 integrase. Moreover, MD simulation revealed that the Cabotegravir-HTLV-1, Raltegravir-HTLV-1 and Elvitegravir-HTLV-1 interactions were stable. It is obvious that more testing of these medicines in both clinical trials and experimental tests is necessary to demonstrate their efficacy against HTLV-1 infection.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Prashasti Sinha
- Department of Physics, School of Physical & Decision Science, Babasaheb Bhimrao Ambedkar University, Lucknow, India
| | - Anil Kumar Yadav
- Department of Physics, School of Physical & Decision Science, Babasaheb Bhimrao Ambedkar University, Lucknow, India
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47
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Dangat Y, Freindorf M, Kraka E. Mechanistic Insights into S-Depalmitolyse Activity of Cln5 Protein Linked to Neurodegeneration and Batten Disease: A QM/MM Study. J Am Chem Soc 2024; 146:145-158. [PMID: 38055807 DOI: 10.1021/jacs.3c06397] [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: 12/08/2023]
Abstract
Ceroid lipofuscinosis neuronal protein 5 (Cln5) is encoded by the CLN5 gene. The genetic variants of this gene are associated with the CLN5 form of Batten disease. Recently, the first crystal structure of Cln5 was reported. Cln5 shows cysteine palmitoyl thioesterase S-depalmitoylation activity, which was explored via fluorescent emission spectroscopy utilizing the fluorescent probe DDP-5. In this work, the mechanism of the reaction between Cln5 and DDP-5 was studied computationally by applying a QM/MM methodology at the ωB97X-D/6-31G(d,p):AMBER level. The results of our study clearly demonstrate the critical role of the catalytic triad Cys280-His166-Glu183 in S-depalmitoylation activity. This is evidenced through a comparison of the pathways catalyzed by the Cys280-His166-Glu183 triad and those with only Cys280 involved. The computed reaction barriers are in agreement with the catalytic efficiency. The calculated Gibb's free-energy profile suggests that S-depalmitoylation is a rate-limiting step compared to the preceding S-palmitoylation, with barriers of 26.1 and 25.3 kcal/mol, respectively. The energetics were complemented by monitoring the fluctuations in the electron density distribution through NBO charges and bond strength alterations via local mode stretching force constants during the catalytic pathways. This comprehensive protocol led to a more holistic picture of the reaction mechanism at the atomic level. It forms the foundation for future studies on the effects of gene mutations on both the S-palmitoylation and S-depalmitoylation steps, providing valuable data for the further development of enzyme replacement therapy, which is currently the only FDA-approved therapy for childhood neurodegenerative diseases, including Batten disease.
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Affiliation(s)
- Yuvraj Dangat
- Department of Chemistry, Southern Methodist University, 3215 Daniel Avenue, Dallas, Texas 75275-0314, United States
| | - Marek Freindorf
- Department of Chemistry, Southern Methodist University, 3215 Daniel Avenue, Dallas, Texas 75275-0314, United States
| | - Elfi Kraka
- Department of Chemistry, Southern Methodist University, 3215 Daniel Avenue, Dallas, Texas 75275-0314, United States
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48
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Zari A, Kurdi LAF, Jaber FA, Alghamdi KMS, Zari TA, Bahieldin A, Hakeem KR, Alnahdi HS, Edris S, Ashraf GM. Investigation and drug design for novel molecules from natural products as inhibitors for controlling multiple myeloma disease using in-silico tools. J Biomol Struct Dyn 2024:1-16. [PMID: 38173181 DOI: 10.1080/07391102.2023.2300409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 10/02/2023] [Indexed: 01/05/2024]
Abstract
Multiple myeloma (MM) is a disease that causes plasma cell growth in the bone marrow and immune globulin buildup in blood and urine. Despite recent advances in MM therapy, many still die due to its high mortality rate. A study using computational simulations analyzed 100 natural ingredients from the SANC database to determine if they inhibited the IgH domain, a known cause of multiple myeloma. Natural component Diospyrin inhibited the IgH enzyme with the best binding energy of -10.3 kcal/mol and three carbon-hydrogen bonds, followed by Parviflorone F complex with a binding energy of -10.1 kcal/mol and two conventional-hydrogen bonds. As a result, the Molecular Dynamic simulation was used to test the stability of the two complexes. During the simulation, the Diospyrin molecule dissociated from the protein at roughly 67.5 ns, whereas the Parviflorone F molecule stayed attached to the protein throughout. The latter was the subject of the investigation. The analysis of the production run data revealed that the Parviflorone F molecule exhibits a variety of conformations within the binding pocket while keeping a relatively constant distance from the protein's center of mass. The analysis of the production run data revealed that the Parviflorone F molecule exhibited a variety of conformations within the binding pocket while keeping a relatively constant distance from the protein's center of mass. The root mean square deviation (RMSD) plots for both the protein and complex showed a stable and steady average value of 4.4 Å for the first 82 nanoseconds of manufacture. As a result, the average value increased to 8.3 Å. Furthermore, the components of the binding free energy, as computed by MM-GBSA, revealed that the mean binding energy of the Parviflorone F molecule was -23.88 kcal/mol. Finally, after analyzing all of the examination data, Parviflorone F was identified as a powerful inhibitor of the IgH domain and hence of the MM disease, which requires further in-vivo conformation.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Ali Zari
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
- Princess Dr. Najla Bint Saud Al-Saud Center for Excellence Research in Biotechnology, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Lina A F Kurdi
- Department of Biology, College of Science, University of Jeddah, Jeddah, Saudi Arabia
| | - Fatima A Jaber
- Department of Biology, College of Science, University of Jeddah, Jeddah, Saudi Arabia
| | - Khalid M S Alghamdi
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Talal A Zari
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ahmed Bahieldin
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
- Princess Dr. Najla Bint Saud Al-Saud Center for Excellence Research in Biotechnology, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Genetics, Faculty of Agriculture, Ain Shams University, Cairo, Egypt
| | - Khalid Rehman Hakeem
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
- Princess Dr. Najla Bint Saud Al-Saud Center for Excellence Research in Biotechnology, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Public Health, Daffodil International University, Dhaka, Bangladesh
| | - Hanan S Alnahdi
- Department of Biochemistry, College of Science, University of Jeddah, Saudi Arabia
| | - Sherif Edris
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
- Princess Dr. Najla Bint Saud Al-Saud Center for Excellence Research in Biotechnology, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Genetics, Faculty of Agriculture, Ain Shams University, Cairo, Egypt
- Al Borg Medical Laboratories, Jeddah, Saudi Arabia
| | - Ghulam Md Ashraf
- Department of Medical Laboratory Sciences, College of Health Sciences and Research Institute for Medical and Health Sciences, University of Sharjah, Sharjah, United Arab Emirates
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49
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Nejabat M, Hadizadeh F, Nejabat M, Rajabi O. Novel hits for autosomal dominated polycystic kidney disease (ADPKD) targeting derived by in silico screening on ZINC-15 natural product database. J Biomol Struct Dyn 2024; 42:885-902. [PMID: 37029756 DOI: 10.1080/07391102.2023.2196700] [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: 11/19/2022] [Accepted: 03/22/2023] [Indexed: 04/09/2023]
Abstract
Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic kidney disorder that leads to growth cysts in the kidney, ultimately resulting in loss of function. Currently, no effective drug therapy can be safely used in the clinic. So, looking for effective therapeutic drugs is urgent for treating ADPKD. Our natural product library was prepared based on the ZINC-15 database. Lipinski's rule of five, drug-likeness, and toxicity screening of the designed library were evaluated. Swiss model online server was used for modeling of GANAB target. Finally, docking-based screening against ADPKD targets was done by MOE 2019 software. The top 14 favorable druglike and non-toxic hits were selected for docking studies. Our results showed that compound-10 (ZINC 6073947) as a sesquiterpene coumarin had more negative binding interaction into the active site of PPARG, OXSR1, GANAB, AVPR2, and PC2 with docking scores of -8.22, -7.52, -6.98, -6.61 and -6.05 kcal/mol, respectively, in comparison to Curcumin, as a natural product that is now in phase 4 clinical trial in ADPKD disease, with an affinity of -8.03, -6.42, -6.82, -5.84 and -5.10 kcal/mol, respectively. Furthermore, seven sesquiterpene coumarins similar to compound 10 were generated and docked. Farnesiferol B (16), compared to compound-10, showed binding affinity of -8.16, -6.4, -7.46, -6.92, and -6.11 kcal/mol against the above targets, respectively. Molecular dynamics, which was done on the compound-10 and 16 (Farnesiferol B) in complex with PPARG, GANAB, and AVPR2, showed more negative binding free-energy than Pioglitazone, Miglitol, and Tolvaptan as FDA-approved drugs for each target, respectively.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Mojgan Nejabat
- Department of Medicinal Chemistry, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Farzin Hadizadeh
- Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Masoud Nejabat
- Department of Medicinal Chemistry, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Omid Rajabi
- Department of Pharmaceutical and Food Control, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran
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50
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Rawat S, Subramaniam K, Subramanian SK, Subbarayan S, Dhanabalan S, Chidambaram SKM, Stalin B, Roy A, Nagaprasad N, Aruna M, Tesfaye JL, Badassa B, Krishnaraj R. Drug Repositioning Using Computer-aided Drug Design (CADD). Curr Pharm Biotechnol 2024; 25:301-312. [PMID: 37605405 DOI: 10.2174/1389201024666230821103601] [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: 10/27/2022] [Revised: 03/03/2023] [Accepted: 03/20/2023] [Indexed: 08/23/2023]
Abstract
Drug repositioning is a method of using authorized drugs for other unusually complex diseases. Compared to new drug development, this method is fast, low in cost, and effective. Through the use of outstanding bioinformatics tools, such as computer-aided drug design (CADD), computer strategies play a vital role in the re-transformation of drugs. The use of CADD's special strategy for target-based drug reuse is the most promising method, and its realization rate is high. In this review article, we have particularly focused on understanding the various technologies of CADD and the use of computer-aided drug design for target-based drug reuse, taking COVID-19 and cancer as examples. Finally, it is concluded that CADD technology is accelerating the development of repurposed drugs due to its many advantages, and there are many facts to prove that the new ligand-targeting strategy is a beneficial method and that it will gain momentum with the development of technology.
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Affiliation(s)
- Sona Rawat
- School of Life Sciences, Jaipur National University, Jaipur-302017, India
| | - Kanmani Subramaniam
- Department of Civil Engineering, KPR Institute of Engineering and Technology, Coimbatore-641407, Tamil Nadu, India
| | - Selva Kumar Subramanian
- Department of Sciences, Amrita School of Engineering, Coimbatore - 641112, Tamil Nadu, India
| | - Saravanan Subbarayan
- Department of Civil Engineering, National Institute of Technology, Trichy-620015, Tamil Nadu, India
| | - Subramanian Dhanabalan
- Department of Mechanical Engineering, M. Kumarasamy College of Engineering, Karur - 639113, Tamil Nadu, India
| | | | - Balasubramaniam Stalin
- Department of Mechanical Engineering, Anna University, Regional Campus Madurai, Madurai - 625 019, Tamil Nadu, India
| | - Arpita Roy
- Department of Biotechnology, School of Engineering & Technology, Sharda University, Greater Noida 201310, India
| | - Nagaraj Nagaprasad
- Department of Mechanical Engineering, ULTRA College of Engineering and Technology, Madurai - 625104, Tamilnadu, India
| | - Mahalingam Aruna
- College of Engineering and Computing, Al Ghurair University, Academic City, Dubai, UAE
| | - Jule Leta Tesfaye
- Dambi Dollo University, College of Natural and Computational Science, Department of Physics, Ethiopia
- Centre for Excellence-Indigenous Knowledge, Innovative Technology Transfer and Entrepreneurship, Dambi Dollo University, Dambi Dollo, Ethiopia
- Ministry of innovation and technology, Ethiopia
| | - Bayissa Badassa
- Department of Mechanical Engineering, Dambi Dollo University, Dambi Dollo, Ethiopia
| | - Ramaswamy Krishnaraj
- Centre for Excellence-Indigenous Knowledge, Innovative Technology Transfer and Entrepreneurship, Dambi Dollo University, Dambi Dollo, Ethiopia
- Ministry of innovation and technology, Ethiopia
- Department of Mechanical Engineering, Dambi Dollo University, Dambi Dollo, Ethiopia
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