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Sanches IH, Braga RC, Alves VM, Andrade CH. Enhancing hERG Risk Assessment with Interpretable Classificatory and Regression Models. Chem Res Toxicol 2024; 37:910-922. [PMID: 38781421 PMCID: PMC11187631 DOI: 10.1021/acs.chemrestox.3c00400] [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: 12/15/2023] [Revised: 04/22/2024] [Accepted: 05/14/2024] [Indexed: 05/25/2024]
Abstract
The human Ether-à-go-go-Related Gene (hERG) is a transmembrane protein that regulates cardiac action potential, and its inhibition can induce a potentially deadly cardiac syndrome. In vitro tests help identify hERG blockers at early stages; however, the high cost motivates searching for alternative, cost-effective methods. The primary goal of this study was to enhance the Pred-hERG tool for predicting hERG blockage. To achieve this, we developed new QSAR models that incorporated additional data, updated existing classificatory and multiclassificatory models, and introduced new regression models. Notably, we integrated SHAP (SHapley Additive exPlanations) values to offer a visual interpretation of these models. Utilizing the latest data from ChEMBL v30, encompassing over 14,364 compounds with hERG data, our binary and multiclassification models outperformed both the previous iteration of Pred-hERG and all publicly available models. Notably, the new version of our tool introduces a regression model for predicting hERG activity (pIC50). The optimal model demonstrated an R2 of 0.61 and an RMSE of 0.48, surpassing the only available regression model in the literature. Pred-hERG 5.0 now offers users a swift, reliable, and user-friendly platform for the early assessment of chemically induced cardiotoxicity through hERG blockage. The tool provides versatile outcomes, including (i) classificatory predictions of hERG blockage with prediction reliability, (ii) multiclassificatory predictions of hERG blockage with reliability, (iii) regression predictions with estimated pIC50 values, and (iv) probability maps illustrating the contribution of chemical fragments for each prediction. Furthermore, we implemented explainable AI analysis (XAI) to visualize SHAP values, providing insights into the contribution of each feature to binary classification predictions. A consensus prediction calculated based on the predictions of the three developed models is also present to assist the user's decision-making process. Pred-hERG 5.0 has been designed to be user-friendly, making it accessible to users without computational or programming expertise. The tool is freely available at http://predherg.labmol.com.br.
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Affiliation(s)
- Igor H. Sanches
- Laboratory
for Molecular Modeling and Drug Design (LabMol), Faculty of Pharmacy, Universidade Federal de Goiás, Goiânia, GO 74690-900, Brazil
- Center
for Excellence in Artificial Intelligence (CEIA), Institute of Informatics, Universidade Federal de Goiás, Goiânia, GO 74690-900, Brazil
- Center
for the Research and Advancement in Fragments and Molecular Targets
(CRAFT), School of Pharmaceutical Sciences at Ribeirao Preto, University of São Paulo, Ribeirão Preto, SP 05508-220, Brazil
| | | | - Vinicius M. Alves
- University
of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Carolina Horta Andrade
- Laboratory
for Molecular Modeling and Drug Design (LabMol), Faculty of Pharmacy, Universidade Federal de Goiás, Goiânia, GO 74690-900, Brazil
- Center
for Excellence in Artificial Intelligence (CEIA), Institute of Informatics, Universidade Federal de Goiás, Goiânia, GO 74690-900, Brazil
- Center
for the Research and Advancement in Fragments and Molecular Targets
(CRAFT), School of Pharmaceutical Sciences at Ribeirao Preto, University of São Paulo, Ribeirão Preto, SP 05508-220, Brazil
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Tran QH, Nguyen QT, Tran TTN, Tran TD, Le MT, Trinh DTT, Tran VT, Tran VH, Thai KM. Identification of small molecules as potential inhibitors of interleukin 6: a multi-computational investigation. Mol Divers 2023; 27:2315-2330. [PMID: 36319930 PMCID: PMC9628397 DOI: 10.1007/s11030-022-10558-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 10/26/2022] [Indexed: 11/07/2022]
Abstract
IL(interleukin)-6 is a multifunctional cytokine crucial for immunological, hematopoiesis, inflammation, and bone metabolism. Strikingly, IL-6 has been shown to significantly contribute to the initiation of cytokine storm-an acute systemic inflammatory syndrome in Covid-19 patients. Recent study has showed that blocking the IL-6 signaling pathway with an anti-IL-6 receptor monoclonal antibody (mAb) can reduce the severity of COVID-19 symptoms and enhance patient survival. However, the mAb has several drawbacks, such as high cost, potential immunogenicity, and invasive administration due to the large-molecule protein product. Instead, these issues could be mitigated using small molecule IL-6 inhibitors, but none are currently available. This study aimed to discover IL-6 inhibitors based on the PPI with a novel camelid Fab fragment, namely 68F2, in a crystal protein complex structure (PDB ID: 4ZS7). The pharmacophore models and molecular docking were used to screen compounds from DrugBank databases. The oral bioavailability of the top 24 ligands from the screening was predicted by the SwissAMDE tool. Subsequently, the selected molecules from docking and MD simulation illustrated a promising binding affinity in the formation of stable complexes at the active binding pocket of IL-6. Binding energies using the MM-PBSA technique were applied to the top 4 hit compounds. The result indicated that DB08402 and DB12903 could form strong interactions and build stable protein-ligand complexes with IL-6. These potential compounds may serve as a basis for further developing small molecule IL-6 inhibitors in the future.
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Affiliation(s)
- Que-Huong Tran
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang St., Dist. 1, Ho Chi Minh City, 700000 Vietnam
- Department of Pharmaceutical Chemistry Da, Nang University of Medical Technology and Pharmacy, Da Nang, 500000 Vietnam
| | - Quoc-Thai Nguyen
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang St., Dist. 1, Ho Chi Minh City, 700000 Vietnam
| | - Thi-Thuy Nga Tran
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang St., Dist. 1, Ho Chi Minh City, 700000 Vietnam
- Department of Pharmaceutical Chemistry Da, Nang University of Medical Technology and Pharmacy, Da Nang, 500000 Vietnam
| | - Thanh-Dao Tran
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang St., Dist. 1, Ho Chi Minh City, 700000 Vietnam
| | - Minh-Tri Le
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang St., Dist. 1, Ho Chi Minh City, 700000 Vietnam
- School of Medicine, Vietnam National University Ho Chi Minh City, Linh Trung Ward., Thu Duc Dist., Ho Chi Minh City, 700000 Vietnam
| | - Dieu-Thuong Thi Trinh
- Faculty of Traditional Medicine, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, 100000 Vietnam
| | - Van-Thanh Tran
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang St., Dist. 1, Ho Chi Minh City, 700000 Vietnam
| | - Viet-Hung Tran
- Institute of Drug Quality Control Ho Chi Minh City, Ho Chi Minh City, 100000 Vietnam
| | - Khac-Minh Thai
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang St., Dist. 1, Ho Chi Minh City, 700000 Vietnam
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Tran QH, Cao HN, Nguyen DN, Tran TTN, Le MT, Nguyen QT, Tran VT, Tran VH, Thai KM. Targeting Olokizumab-Interleukin 6 interaction interface to discover novel IL-6 inhibitors. J Biomol Struct Dyn 2023; 41:14003-14015. [PMID: 36995131 DOI: 10.1080/07391102.2023.2193990] [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: 10/05/2022] [Accepted: 01/29/2023] [Indexed: 03/31/2023]
Abstract
The IL-6/IL-6R or IL-6/GP130 protein-protein interactions play a significant role in controlling the development of chronic inflammatory diseases, such as rheumatoid arthritis, Castleman disease, psoriasis, and, most recently, COVID-19. Modulating or antagonizing protein-protein interactions of IL6 binding to its receptors by oral drugs promises similar efficacy to biological therapy in patients, namely monoclonal antibodies. In this study, we used a crystal structure of the Fab part of olokizumab in a complex with IL-6 (PDB ID: 4CNI) to uncover starting points for small molecule IL-6 antagonist discovery. Firstly, a structure‑based pharmacophore model of the protein active site cavity was generated to identify possible candidates, followed by virtual screening with a significant database Drugbank. After the docking protocol validation, a virtual screening by molecular docking was carried out and a total of 11 top hits were reported. Detailed analysis of the best scoring molecules was performed with ADME/T analysis and molecular dynamics simulation. Furthermore, the Molecular Mechanics-Generalized Born Surface Area (MM/GBSA) technique has been utilized to evaluate the free binding energy. Based on the finding, one newly obtained compound in this study, namely DB15187, may serve as a lead compound for the discovery of IL-6 inhibitors.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Que-Huong Tran
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
- Department of Pharmaceutical Chemistry, Da Nang University of Medical Technology and Pharmacy, Da Nang, Vietnam
| | - Hoang-Nhi Cao
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Dac-Nhan Nguyen
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Thi-Thuy-Nga Tran
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
- Department of Pharmaceutical Chemistry, Da Nang University of Medical Technology and Pharmacy, Da Nang, Vietnam
| | - Minh-Tri Le
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
- School of Medicine, Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Quoc-Thai Nguyen
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Van-Thanh Tran
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Viet-Hung Tran
- Faculty of Traditional Medicine, University of Medicine and Pharmacy at Ho Chi Minh City, Vietnam
- Institute of Drug Quality Control Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Khac-Minh Thai
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
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Goel H, Yu W, MacKerell AD. hERG Blockade Prediction by Combining Site Identification by Ligand Competitive Saturation and Physicochemical Properties. CHEMISTRY (BASEL, SWITZERLAND) 2022; 4:630-646. [PMID: 36712295 PMCID: PMC9881610 DOI: 10.3390/chemistry4030045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Human ether-a-go-go-related gene (hERG) potassium channel is well-known contributor to drug-induced cardiotoxicity and therefore an extremely important target when performing safety assessments of drug candidates. Ligand-based approaches in connection with quantitative structure active relationships (QSAR) analyses have been developed to predict hERG toxicity. Availability of the recent published cryogenic electron microscopy (cryo-EM) structure for the hERG channel opened the prospect for using structure-based simulation and docking approaches for hERG drug liability predictions. In recent time, the idea of combining structure- and ligand-based approaches for modeling hERG drug liability has gained momentum offering improvements in predictability when compared to ligand-based QSAR practices alone. The present article demonstrates uniting the structure-based SILCS (site-identification by ligand competitive saturation) approach in conjunction with physicochemical properties to develop predictive models for hERG blockade. This combination leads to improved model predictability based on Pearson's R and percent correct (represents rank-ordering of ligands) metric for different validation sets of hERG blockers involving diverse chemical scaffold and wide range of pIC50 values. The inclusion of the SILCS structure-based approach allows determination of the hERG region to which compounds bind and the contribution of different chemical moieties in the compounds to blockade, thereby facilitating the rational ligand design to minimize hERG liability.
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Affiliation(s)
- Himanshu Goel
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn St. Baltimore, MD 21201, United States
| | - Wenbo Yu
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn St. Baltimore, MD 21201, United States
| | - Alexander D. MacKerell
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn St. Baltimore, MD 21201, United States
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