1
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York DM. Modern Alchemical Free Energy Methods for Drug Discovery Explained. ACS PHYSICAL CHEMISTRY AU 2023; 3:478-491. [PMID: 38034038 PMCID: PMC10683484 DOI: 10.1021/acsphyschemau.3c00033] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 09/12/2023] [Accepted: 09/13/2023] [Indexed: 12/02/2023]
Abstract
This Perspective provides a contextual explanation of the current state-of-the-art alchemical free energy methods and their role in drug discovery as well as highlights select emerging technologies. The narrative attempts to answer basic questions about what goes on "under the hood" in free energy simulations and provide general guidelines for how to run simulations and analyze the results. It is the hope that this work will provide a valuable introduction to students and scientists in the field.
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Affiliation(s)
- Darrin M. York
- Laboratory for Biomolecular
Simulation Research, Institute for Quantitative Biomedicine, and Department
of Chemistry and Chemical Biology, Rutgers
University, Piscataway, New Jersey 08854, United States
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2
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Papadourakis M, Sinenka H, Matricon P, Hénin J, Brannigan G, Pérez-Benito L, Pande V, van Vlijmen H, de Graaf C, Deflorian F, Tresadern G, Cecchini M, Cournia Z. Alchemical Free Energy Calculations on Membrane-Associated Proteins. J Chem Theory Comput 2023; 19:7437-7458. [PMID: 37902715 PMCID: PMC11017255 DOI: 10.1021/acs.jctc.3c00365] [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: 03/31/2023] [Indexed: 10/31/2023]
Abstract
Membrane proteins have diverse functions within cells and are well-established drug targets. The advances in membrane protein structural biology have revealed drug and lipid binding sites on membrane proteins, while computational methods such as molecular simulations can resolve the thermodynamic basis of these interactions. Particularly, alchemical free energy calculations have shown promise in the calculation of reliable and reproducible binding free energies of protein-ligand and protein-lipid complexes in membrane-associated systems. In this review, we present an overview of representative alchemical free energy studies on G-protein-coupled receptors, ion channels, transporters as well as protein-lipid interactions, with emphasis on best practices and critical aspects of running these simulations. Additionally, we analyze challenges and successes when running alchemical free energy calculations on membrane-associated proteins. Finally, we highlight the value of alchemical free energy calculations calculations in drug discovery and their applicability in the pharmaceutical industry.
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Affiliation(s)
- Michail Papadourakis
- Biomedical
Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece
| | - Hryhory Sinenka
- Institut
de Chimie de Strasbourg, UMR7177, CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France
| | - Pierre Matricon
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Jérôme Hénin
- Laboratoire
de Biochimie Théorique UPR 9080, CNRS and Université Paris Cité, 75005 Paris, France
| | - Grace Brannigan
- Center
for Computational and Integrative Biology, Rutgers University−Camden, Camden, New Jersey 08103, United States of America
- Department
of Physics, Rutgers University−Camden, Camden, New Jersey 08102, United States
of America
| | - Laura Pérez-Benito
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Vineet Pande
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Herman van Vlijmen
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Chris de Graaf
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Francesca Deflorian
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Gary Tresadern
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Marco Cecchini
- Institut
de Chimie de Strasbourg, UMR7177, CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France
| | - Zoe Cournia
- Biomedical
Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece
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3
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Emigh Cortez AM, DeMarco KR, Furutani K, Bekker S, Sack JT, Wulff H, Clancy CE, Vorobyov I, Yarov-Yarovoy V. Structural modeling of hERG channel-drug interactions using Rosetta. Front Pharmacol 2023; 14:1244166. [PMID: 38035013 PMCID: PMC10682396 DOI: 10.3389/fphar.2023.1244166] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 10/23/2023] [Indexed: 12/02/2023] Open
Abstract
The human ether-a-go-go-related gene (hERG) not only encodes a potassium-selective voltage-gated ion channel essential for normal electrical activity in the heart but is also a major drug anti-target. Genetic hERG mutations and blockage of the channel pore by drugs can cause long QT syndrome, which predisposes individuals to potentially deadly arrhythmias. However, not all hERG-blocking drugs are proarrhythmic, and their differential affinities to discrete channel conformational states have been suggested to contribute to arrhythmogenicity. We used Rosetta electron density refinement and homology modeling to build structural models of open-state hERG channel wild-type and mutant variants (Y652A, F656A, and Y652A/F656 A) and a closed-state wild-type channel based on cryo-electron microscopy structures of hERG and EAG1 channels. These models were used as protein targets for molecular docking of charged and neutral forms of amiodarone, nifekalant, dofetilide, d/l-sotalol, flecainide, and moxifloxacin. We selected these drugs based on their different arrhythmogenic potentials and abilities to facilitate hERG current. Our docking studies and clustering provided atomistic structural insights into state-dependent drug-channel interactions that play a key role in differentiating safe and harmful hERG blockers and can explain hERG channel facilitation through drug interactions with its open-state hydrophobic pockets.
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Affiliation(s)
- Aiyana M. Emigh Cortez
- Biophysics Graduate Group, University of California, Davis, Davis, CA, United States
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
| | - Kevin R. DeMarco
- Biophysics Graduate Group, University of California, Davis, Davis, CA, United States
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
| | - Kazuharu Furutani
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
- Department of Pharmacology, Tokushima Bunri University, Tokushima, Japan
| | - Slava Bekker
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
- American River College, Sacramento, CA, United States
| | - Jon T. Sack
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
- Department of Anesthesiology and Pain Medicine, University of California, Davis, Davis, CA, United States
| | - Heike Wulff
- Department of Pharmacology, University of California, Davis, Davis, CA, United States
| | - Colleen E. Clancy
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
- Department of Pharmacology, University of California, Davis, Davis, CA, United States
- Center for Precision Medicine and Data Sciences, University of California, Davis, Davis, CA, United States
| | - Igor Vorobyov
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
- Department of Pharmacology, University of California, Davis, Davis, CA, United States
| | - Vladimir Yarov-Yarovoy
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
- Department of Anesthesiology and Pain Medicine, University of California, Davis, Davis, CA, United States
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4
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Negami T, Terada T. Calculations of the binding free energies of the Comprehensive in vitro Proarrhythmia Assay (CiPA) reference drugs to cardiac ion channels. Biophys Physicobiol 2023; 20:e200016. [PMID: 38496247 PMCID: PMC10941965 DOI: 10.2142/biophysico.bppb-v20.0016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 03/24/2023] [Indexed: 03/19/2024] Open
Abstract
The evaluation of the inhibitory activities of drugs on multiple cardiac ion channels is required for the accurate assessment of proarrhythmic risks. Moreover, the in silico prediction of such inhibitory activities of drugs on cardiac channels can improve the efficiency of the drug-development process. Here, we performed molecular docking simulations to predict the complex structures of 25 reference drugs that were proposed by the Comprehensive in vitro Proarrhythmia Assay consortium using two cardiac ion channels, the human ether-a-go-go-related gene (hERG) potassium channel and human NaV1.5 (hNaV1.5) sodium channel, with experimentally available structures. The absolute binding free energy (ΔGbind) values of the predicted structures were calculated by a molecular dynamics-based method and compared with the experimental half-maximal inhibitory concentration (IC50) data. Furthermore, the regression analysis between the calculated values and negative of the common logarithm of the experimental IC50 values (pIC50) revealed that the calculated values of four and ten drugs deviated significantly from the regression lines of the hERG and hNaV1.5 channels, respectively. We reconsidered the docking poses and protonation states of the drugs based on the experimental data and recalculated their ΔGbind values. Finally, the calculated ΔGbind values of 24 and 19 drugs correlated with their experimental pIC50 values (coefficients of determination=0.791 and 0.613 for the hERG and hNaV1.5 channels, respectively). Thus, the regression analysis between the calculated ΔGbind and experimental IC50 data ensured the realization of an increased number of reliable complex structures.
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Affiliation(s)
- Tatsuki Negami
- Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo-ku, Tokyo 113-8657, Japan
| | - Tohru Terada
- Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo-ku, Tokyo 113-8657, Japan
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5
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Wang T, Sun J, Zhao Q. Investigating cardiotoxicity related with hERG channel blockers using molecular fingerprints and graph attention mechanism. Comput Biol Med 2023; 153:106464. [PMID: 36584603 DOI: 10.1016/j.compbiomed.2022.106464] [Citation(s) in RCA: 108] [Impact Index Per Article: 108.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 12/12/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022]
Abstract
Human ether-a-go-go-related gene (hERG) channel blockade by small molecules is a big concern during drug development in the pharmaceutical industry. Failure or inhibition of hERG channel activity caused by drug molecules can lead to prolonging QT interval, which will result in serious cardiotoxicity. Thus, evaluating the hERG blocking activity of all these small molecular compounds is technically challenging, and the relevant procedures are expensive and time-consuming. In this study, we develop a novel deep learning predictive model named DMFGAM for predicting hERG blockers. In order to characterize the molecule more comprehensively, we first consider the fusion of multiple molecular fingerprint features to characterize its final molecular fingerprint features. Then, we use the multi-head attention mechanism to extract the molecular graph features. Both molecular fingerprint features and molecular graph features are fused as the final features of the compounds to make the feature expression of compounds more comprehensive. Finally, the molecules are classified into hERG blockers or hERG non-blockers through the fully connected neural network. We conduct 5-fold cross-validation experiment to evaluate the performance of DMFGAM, and verify the robustness of DMFGAM on external validation datasets. We believe DMFGAM can serve as a powerful tool to predict hERG channel blockers in the early stages of drug discovery and development.
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Affiliation(s)
- Tianyi Wang
- School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, 114051, China
| | - Jianqiang Sun
- School of Automation and Electrical Engineering, Linyi University, Linyi, 276000, China
| | - Qi Zhao
- School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, 114051, China.
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6
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Fu H, Zhou Y, Jing X, Shao X, Cai W. Meta-Analysis Reveals That Absolute Binding Free-Energy Calculations Approach Chemical Accuracy. J Med Chem 2022; 65:12970-12978. [PMID: 36179112 DOI: 10.1021/acs.jmedchem.2c00796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Systematic and quantitative analysis of the reliability of formally exact methods that in silico calculate absolute protein-ligand binding free energies remains lacking. Here, we provide, for the first time, evidence-based information on the reliability of these methods by statistically studying 853 cases from 34 different research groups through meta-analysis. The results show that formally exact methods approach chemical accuracy (error = 1.58 kcal/mol), even if people are challenging difficult tasks such as blind drug screening in recent years. The geometrical-pathway-based methods prove to possess a better convergence ability than the alchemical ones, while the latter have a larger application range. We also reveal the importance of always using the latest force fields to guarantee reliability and discuss the pros and cons of turning to an implicit solvent model in absolute binding free-energy calculations. Moreover, based on the meta-analysis, an evidence-based guideline for in silico binding free-energy calculations is provided.
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Affiliation(s)
- Haohao Fu
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin300071, China.,Haihe Laboratory of Sustainable Chemical Transformations, Tianjin300192, China
| | - Yan Zhou
- School of Medicine, Nankai University, Tianjin300071, China.,Department of Ultrasound, Tianjin Third Central Hospital, Tianjin300170, China
| | - Xiang Jing
- Department of Ultrasound, Tianjin Third Central Hospital, Tianjin300170, China
| | - Xueguang Shao
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin300071, China.,Haihe Laboratory of Sustainable Chemical Transformations, Tianjin300192, China
| | - Wensheng Cai
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin300071, China.,Haihe Laboratory of Sustainable Chemical Transformations, Tianjin300192, China
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7
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Maly J, Emigh AM, DeMarco KR, Furutani K, Sack JT, Clancy CE, Vorobyov I, Yarov-Yarovoy V. Structural modeling of the hERG potassium channel and associated drug interactions. Front Pharmacol 2022; 13:966463. [PMID: 36188564 PMCID: PMC9523588 DOI: 10.3389/fphar.2022.966463] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 08/25/2022] [Indexed: 11/13/2022] Open
Abstract
The voltage-gated potassium channel, KV11.1, encoded by the human Ether-à-go-go-Related Gene (hERG), is expressed in cardiac myocytes, where it is crucial for the membrane repolarization of the action potential. Gating of the hERG channel is characterized by rapid, voltage-dependent, C-type inactivation, which blocks ion conduction and is suggested to involve constriction of the selectivity filter. Mutations S620T and S641A/T within the selectivity filter region of hERG have been shown to alter the voltage dependence of channel inactivation. Because hERG channel blockade is implicated in drug-induced arrhythmias associated with both the open and inactivated states, we used Rosetta to simulate the effects of hERG S620T and S641A/T mutations to elucidate conformational changes associated with hERG channel inactivation and differences in drug binding between the two states. Rosetta modeling of the S641A fast-inactivating mutation revealed a lateral shift of the F627 side chain in the selectivity filter into the central channel axis along the ion conduction pathway and the formation of four lateral fenestrations in the pore. Rosetta modeling of the non-inactivating mutations S620T and S641T suggested a potential molecular mechanism preventing F627 side chain from shifting into the ion conduction pathway during the proposed inactivation process. Furthermore, we used Rosetta docking to explore the binding mechanism of highly selective and potent hERG blockers - dofetilide, terfenadine, and E4031. Our structural modeling correlates well with much, but not all, existing experimental evidence involving interactions of hERG blockers with key residues in hERG pore and reveals potential molecular mechanisms of ligand interactions with hERG in an inactivated state.
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Affiliation(s)
- Jan Maly
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
- Biophysics Graduate Group, University of California, Davis, Davis, CA, United States
| | - Aiyana M. Emigh
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
- Biophysics Graduate Group, University of California, Davis, Davis, CA, United States
| | - Kevin R. DeMarco
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
- Biophysics Graduate Group, University of California, Davis, Davis, CA, United States
| | - Kazuharu Furutani
- Department of Pharmacology, Tokushima Bunri University, Tokushima, Japan
| | - Jon T. Sack
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
| | - Colleen E. Clancy
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
- Department of Pharmacology, University of California, Davis, Davis, CA, United States
| | - Igor Vorobyov
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
- Department of Pharmacology, University of California, Davis, Davis, CA, United States
| | - Vladimir Yarov-Yarovoy
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, United States
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8
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New Insights into Ion Channels: Predicting hERG-Drug Interactions. Int J Mol Sci 2022; 23:ijms231810732. [PMID: 36142644 PMCID: PMC9503154 DOI: 10.3390/ijms231810732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 08/31/2022] [Accepted: 09/06/2022] [Indexed: 11/16/2022] Open
Abstract
Drug-induced long QT syndrome can be a very dangerous side effect of existing and developmental drugs. In this work, a model proposed two decades ago addressing the ion specificity of potassium channels is extended to the human ether-à-gogo gene (hERG). hERG encodes the protein that assembles into the potassium channel responsible for the delayed rectifier current in ventricular cardiac myocytes that is often targeted by drugs associated with QT prolongation. The predictive value of this model can guide a rational drug design decision early in the drug development process and enhance NCE (New Chemical Entity) retention. Small molecule drugs containing a nitrogen that can be protonated to afford a formal +1 charge can interact with hERG to prevent the repolarization of outward rectifier currents. Low-level ab initio calculations are employed to generate electronic features of the drug molecules that are known to interact with hERG. These calculations were employed to generate structure–activity relationships (SAR) that predict whether a small molecule drug containing a protonated nitrogen has the potential to interact with and inhibit the activity of the hERG potassium channels of the heart. The model of the mechanism underlying the ion specificity of potassium channels offers predictive value toward optimizing drug design and, therefore, minimizes the effort and expense invested in compounds with the potential for life-threatening inhibitory activity of the hERG potassium channel.
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9
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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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10
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Shan M, Jiang C, Qin L, Cheng G. A Review of Computational Methods in Predicting hERG Channel Blockers. ChemistrySelect 2022. [DOI: 10.1002/slct.202201221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Mengyi Shan
- School of Pharmaceutical Sciences Zhejiang Chinese Medical University Hangzhou 310053 People's Republic of China
| | - Chen Jiang
- QuanMin RenZheng (HangZhou) Technology Co. Ltd. China
| | - Lu‐Ping Qin
- School of Pharmaceutical Sciences Zhejiang Chinese Medical University Hangzhou 310053 People's Republic of China
| | - Gang Cheng
- School of Pharmaceutical Sciences Zhejiang Chinese Medical University Hangzhou 310053 People's Republic of China
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11
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Ding W, Nan Y, Wu J, Han C, Xin X, Li S, Liu H, Zhang L. Combining multi-dimensional molecular fingerprints to predict the hERG cardiotoxicity of compounds. Comput Biol Med 2022; 144:105390. [DOI: 10.1016/j.compbiomed.2022.105390] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/06/2022] [Accepted: 03/07/2022] [Indexed: 01/28/2023]
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12
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Staszak M, Staszak K, Wieszczycka K, Bajek A, Roszkowski K, Tylkowski B. Machine learning in drug design: Use of artificial intelligence to explore the chemical structure–biological activity relationship. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2022. [DOI: 10.1002/wcms.1568] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Maciej Staszak
- Institute of Technology and Chemical Engineering Poznan University of Technology Poznan Poland
| | - Katarzyna Staszak
- Institute of Technology and Chemical Engineering Poznan University of Technology Poznan Poland
| | - Karolina Wieszczycka
- Institute of Technology and Chemical Engineering Poznan University of Technology Poznan Poland
| | - Anna Bajek
- Department of Tissue Engineering Collegium Medicum, Nicolaus Copernicus University Bydgoszcz Poland
| | - Krzysztof Roszkowski
- Department of Oncology Collegium Medicum Nicolaus Copernicus University Bydgoszcz Poland
| | - Bartosz Tylkowski
- Department of Chemical Engineering University Rovira i Virgili Tarragona Spain
- Eurecat, Centre Tecnològic de Catalunya Chemical Technologies Unit Tarragona Spain
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13
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Lagoutte-Renosi J, Allemand F, Ramseyer C, Yesylevskyy S, Davani S. Molecular modeling in cardiovascular pharmacology: Current state of the art and perspectives. Drug Discov Today 2021; 27:985-1007. [PMID: 34863931 DOI: 10.1016/j.drudis.2021.11.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 11/02/2021] [Accepted: 11/25/2021] [Indexed: 01/10/2023]
Abstract
Molecular modeling in pharmacology is a promising emerging tool for exploring drug interactions with cellular components. Recent advances in molecular simulations, big data analysis, and artificial intelligence (AI) have opened new opportunities for rationalizing drug interactions with their pharmacological targets. Despite the obvious utility and increasing impact of computational approaches, their development is not progressing at the same speed in different fields of pharmacology. Here, we review current in silico techniques used in cardiovascular diseases (CVDs), cardiological drug discovery, and assessment of cardiotoxicity. In silico techniques are paving the way to a new era in cardiovascular medicine, but their use somewhat lags behind that in other fields.
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Affiliation(s)
- Jennifer Lagoutte-Renosi
- EA 3920 Université Bourgogne Franche-Comté, 25000 Besançon, France; Laboratoire de Pharmacologie Clinique et Toxicologie-CHU de Besançon, 25000 Besançon, France
| | - Florentin Allemand
- EA 3920 Université Bourgogne Franche-Comté, 25000 Besançon, France; Laboratoire Chrono Environnement UMR CNRS 6249, Université de Bourgogne Franche-Comté, 16 route de Gray, 25000 Besançon, France
| | - Christophe Ramseyer
- Laboratoire Chrono Environnement UMR CNRS 6249, Université de Bourgogne Franche-Comté, 16 route de Gray, 25000 Besançon, France
| | - Semen Yesylevskyy
- Laboratoire Chrono Environnement UMR CNRS 6249, Université de Bourgogne Franche-Comté, 16 route de Gray, 25000 Besançon, France; Department of Physics of Biological Systems, Institute of Physics of The National Academy of Sciences of Ukraine, Nauky Sve. 46, Kyiv, Ukraine; Receptor.ai inc, 16192 Coastal Highway, Lewes, DE, USA
| | - Siamak Davani
- EA 3920 Université Bourgogne Franche-Comté, 25000 Besançon, France; Laboratoire de Pharmacologie Clinique et Toxicologie-CHU de Besançon, 25000 Besançon, France.
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14
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Meng J, Zhang L, Wang L, Li S, Xie D, Zhang Y, Liu H. TSSF-hERG: A machine-learning-based hERG potassium channel-specific scoring function for chemical cardiotoxicity prediction. Toxicology 2021; 464:153018. [PMID: 34757159 DOI: 10.1016/j.tox.2021.153018] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 10/15/2021] [Accepted: 10/26/2021] [Indexed: 11/27/2022]
Abstract
The human ether-à-go-go-related gene (hERG) encodes the Kv11.1 voltage-gated potassium ion (K+) channel that conducts the rapidly activating delayed rectifier current (IKr) in cardiomyocytes to regulate the repolarization process. Some drugs, as blockers of hERG potassium channels, cannot be marketed due to prolonged QT intervals, as well known as cardiotoxicity. Predetermining the binding affinity values between drugs and hERG through in silico methods can greatly reduce the time and cost required for experimental verification. In this study, we collected 9,215 compounds with AutoDock Vina's docking structures as training set, and collected compounds from four references as test sets. A series of models for predicting the binding affinities of hERG blockers were built based on five machine learning algorithms and combinations of interaction features and ligand features. The model built by support vector regression (SVR) using the combination of all features achieved the best performance on both tenfold cross-validation and external verification, which was selected and named as TSSF-hERG (target-specific scoring function for hERG). TSSF-hERG is more accurate than the classic scoring function of AutoDock Vina and the machine-learning-based generic scoring function RF-Score, with a Pearson's correlation coefficient (Rp) of 0.765, a Spearman's rank correlation coefficient (Rs) of 0.757, a root-mean-square error (RMSE) of 0.585 in a tenfold cross-validation study. All results demonstrated that TSSF-hERG would be useful for improving the power of binding affinity prediction between hERG and compounds, which can be further used for prediction or virtual screening of the hERG-related cardiotoxicity of drug candidates.
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Affiliation(s)
- Jinhui Meng
- School of Life Science, Liaoning University, Shenyang, 110036, China
| | - Li Zhang
- School of Life Science, Liaoning University, Shenyang, 110036, China; Technology Innovation Center for Computer Simulating and Information Processing of Bio-macromolecules of Liaoning Province, Shenyang, 110036, China; Engineering Laboratory for Molecular Simulation and Designing of Drug Molecules of Liaoning, Shenyang, 110036, China
| | - Lianxin Wang
- School of Life Science, Liaoning University, Shenyang, 110036, China
| | - Shimeng Li
- School of Life Science, Liaoning University, Shenyang, 110036, China
| | - Di Xie
- School of Life Science, Liaoning University, Shenyang, 110036, China
| | - Yuxi Zhang
- School of Life Science, Liaoning University, Shenyang, 110036, China
| | - Hongsheng Liu
- Technology Innovation Center for Computer Simulating and Information Processing of Bio-macromolecules of Liaoning Province, Shenyang, 110036, China; Engineering Laboratory for Molecular Simulation and Designing of Drug Molecules of Liaoning, Shenyang, 110036, China; School of Pharmacy, Liaoning University, Shenyang, 110036, China.
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15
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Toplak Ž, Merzel F, Pardo LA, Peterlin Mašič L, Tomašič T. Molecular Dynamics-Derived Pharmacophore Model Explaining the Nonselective Aspect of K V10.1 Pore Blockers. Int J Mol Sci 2021; 22:ijms22168999. [PMID: 34445705 PMCID: PMC8396485 DOI: 10.3390/ijms22168999] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 08/18/2021] [Accepted: 08/19/2021] [Indexed: 11/21/2022] Open
Abstract
The KV10.1 voltage-gated potassium channel is highly expressed in 70% of tumors, and thus represents a promising target for anticancer drug discovery. However, only a few ligands are known to inhibit KV10.1, and almost all also inhibit the very similar cardiac hERG channel, which can lead to undesirable side-effects. In the absence of the structure of the KV10.1–inhibitor complex, there remains the need for new strategies to identify selective KV10.1 inhibitors and to understand the binding modes of the known KV10.1 inhibitors. To investigate these binding modes in the central cavity of KV10.1, a unique approach was used that allows derivation and analysis of ligand–protein interactions from molecular dynamics trajectories through pharmacophore modeling. The final molecular dynamics-derived structure-based pharmacophore model for the simulated KV10.1–ligand complexes describes the necessary pharmacophore features for KV10.1 inhibition and is highly similar to the previously reported ligand-based hERG pharmacophore model used to explain the nonselectivity of KV10.1 pore blockers. Moreover, analysis of the molecular dynamics trajectories revealed disruption of the π–π network of aromatic residues F359, Y464, and F468 of KV10.1, which has been reported to be important for binding of various ligands for both KV10.1 and hERG channels. These data indicate that targeting the KV10.1 channel pore is also likely to result in undesired hERG inhibition, and other potential binding sites should be explored to develop true KV10.1-selective inhibitors as new anticancer agents.
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Affiliation(s)
- Žan Toplak
- Faculty of Pharmacy, University of Ljubljana, 1000 Ljubljana, Slovenia; (Ž.T.); (L.P.M.)
| | - Franci Merzel
- Theory Department, National Institute of Chemistry, 1000 Ljubljana, Slovenia;
| | - Luis A. Pardo
- AG Oncophysiology, Max-Planck Institute for Experimental Medicine, 37075 Göttingen, Germany;
| | - Lucija Peterlin Mašič
- Faculty of Pharmacy, University of Ljubljana, 1000 Ljubljana, Slovenia; (Ž.T.); (L.P.M.)
| | - Tihomir Tomašič
- Faculty of Pharmacy, University of Ljubljana, 1000 Ljubljana, Slovenia; (Ž.T.); (L.P.M.)
- Correspondence: ; Tel.: +386-14769-556
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16
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DeMarco KR, Yang PC, Singh V, Furutani K, Dawson JRD, Jeng MT, Fettinger JC, Bekker S, Ngo VA, Noskov SY, Yarov-Yarovoy V, Sack JT, Wulff H, Clancy CE, Vorobyov I. Molecular determinants of pro-arrhythmia proclivity of d- and l-sotalol via a multi-scale modeling pipeline. J Mol Cell Cardiol 2021; 158:163-177. [PMID: 34062207 PMCID: PMC8906354 DOI: 10.1016/j.yjmcc.2021.05.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 05/03/2021] [Accepted: 05/24/2021] [Indexed: 11/20/2022]
Abstract
Drug isomers may differ in their proarrhythmia risk. An interesting example is the drug sotalol, an antiarrhythmic drug comprising d- and l- enantiomers that both block the hERG cardiac potassium channel and confer differing degrees of proarrhythmic risk. We developed a multi-scale in silico pipeline focusing on hERG channel – drug interactions and used it to probe and predict the mechanisms of pro-arrhythmia risks of the two enantiomers of sotalol. Molecular dynamics (MD) simulations predicted comparable hERG channel binding affinities for d- and l-sotalol, which were validated with electrophysiology experiments. MD derived thermodynamic and kinetic parameters were used to build multi-scale functional computational models of cardiac electrophysiology at the cell and tissue scales. Functional models were used to predict inactivated state binding affinities to recapitulate electrocardiogram (ECG) QT interval prolongation observed in clinical data. Our study demonstrates how modeling and simulation can be applied to predict drug effects from the atom to the rhythm for dl-sotalol and also increased proarrhythmia proclivity of d- vs. l-sotalol when accounting for stereospecific beta-adrenergic receptor blocking.
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Affiliation(s)
- Kevin R DeMarco
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA
| | - Pei-Chi Yang
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA
| | - Vikrant Singh
- Department of Pharmacology, University of California Davis, Davis, CA 95616, USA
| | - Kazuharu Furutani
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Department of Pharmacology, Faculty of Pharmaceutical Sciences, Tokushima Bunri University, Tokushima, Tokushima 770-8514, Japan
| | - John R D Dawson
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Biophysics Graduate Group, University of California Davis, Davis, CA 95616, USA
| | - Mao-Tsuen Jeng
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA
| | - James C Fettinger
- Department of Chemistry, University of California Davis, Davis, CA 95616, USA
| | - Slava Bekker
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Department of Science and Engineering, American River College, Sacramento, CA 95841, USA
| | - Van A Ngo
- Centre for Molecular Simulation and Biochemistry Research Cluster, Department of Biological Sciences, University of Calgary, Calgary, AB T2N1N4, Canada
| | - Sergei Y Noskov
- Centre for Molecular Simulation and Biochemistry Research Cluster, Department of Biological Sciences, University of Calgary, Calgary, AB T2N1N4, Canada
| | - Vladimir Yarov-Yarovoy
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Department of Anesthesiology and Pain Medicine, University of California Davis, Davis, CA 95616, USA
| | - Jon T Sack
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Department of Anesthesiology and Pain Medicine, University of California Davis, Davis, CA 95616, USA
| | - Heike Wulff
- Department of Pharmacology, University of California Davis, Davis, CA 95616, USA
| | - Colleen E Clancy
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Department of Pharmacology, University of California Davis, Davis, CA 95616, USA
| | - Igor Vorobyov
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Department of Pharmacology, University of California Davis, Davis, CA 95616, USA.
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17
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Zhu S, Wu M, Huang Z, An J. Trends in application of advancing computational approaches in GPCR ligand discovery. Exp Biol Med (Maywood) 2021; 246:1011-1024. [PMID: 33641446 PMCID: PMC8113737 DOI: 10.1177/1535370221993422] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
G protein-coupled receptors (GPCRs) comprise the most important superfamily of protein targets in current ligand discovery and drug development. GPCRs are integral membrane proteins that play key roles in various cellular signaling processes. Therefore, GPCR signaling pathways are closely associated with numerous diseases, including cancer and several neurological, immunological, and hematological disorders. Computer-aided drug design (CADD) can expedite the process of GPCR drug discovery and potentially reduce the actual cost of research and development. Increasing knowledge of biological structures, as well as improvements on computer power and algorithms, have led to unprecedented use of CADD for the discovery of novel GPCR modulators. Similarly, machine learning approaches are now widely applied in various fields of drug target research. This review briefly summarizes the application of rising CADD methodologies, as well as novel machine learning techniques, in GPCR structural studies and bioligand discovery in the past few years. Recent novel computational strategies and feasible workflows are updated, and representative cases addressing challenging issues on olfactory receptors, biased agonism, and drug-induced cardiotoxic effects are highlighted to provide insights into future GPCR drug discovery.
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Affiliation(s)
- Siyu Zhu
- Division of Infectious Diseases and Global Public Health, Department of Medicine, School of Medicine, University of California at San Diego, La Jolla, CA 92093, USA
- Ciechanover Institute of Precision and Regenerative Medicine, School of Life and Health Sciences, Chinese University of Hong Kong, Shenzhen 518172, China
| | - Meixian Wu
- Division of Infectious Diseases and Global Public Health, Department of Medicine, School of Medicine, University of California at San Diego, La Jolla, CA 92093, USA
| | - Ziwei Huang
- Division of Infectious Diseases and Global Public Health, Department of Medicine, School of Medicine, University of California at San Diego, La Jolla, CA 92093, USA
- Ciechanover Institute of Precision and Regenerative Medicine, School of Life and Health Sciences, Chinese University of Hong Kong, Shenzhen 518172, China
- School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Jing An
- Division of Infectious Diseases and Global Public Health, Department of Medicine, School of Medicine, University of California at San Diego, La Jolla, CA 92093, USA
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18
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Koulgi S, Jani V, Nair V, Saini JS, Phukan S, Sonavane U, Joshi R, Kamboj R, Palle V. Molecular dynamics of hERG channel: insights into understanding the binding of small molecules for detuning cardiotoxicity. J Biomol Struct Dyn 2021; 40:5996-6012. [PMID: 33494645 DOI: 10.1080/07391102.2021.1875883] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Evaluation of cardiotoxicity potential of new chemical entities (NCEs) has lately become one of the stringent filters in the drug discovery and development process. Cardiotoxicity is caused mainly by the inhibition of human ether-a-go-go related gene (hERG) channel protein. Inhibition of the hERG channel leads to a life-threatening condition known as cardiac arrhythmia. Knowledge of the structural behaviour of the hERG would aid greatly in the design of new drug molecules that do not interact with the protein and add to the safety index. In this study, a computational model for the active-state of hERG was developed. This model was equilibrated by performing the molecular dynamics simulations for 100 ns followed by clustering and selection of a representative structure based on the largest populated cluster. To study the changes in the protein structure on inhibition, three inhibitory ligands, namely, dofetilide, cisapride and terfenadine were docked, followed by molecular dynamics simulations of 200 ns for the apo and each ligand-bound structure. It was observed that docking and simulation studies of the hERG model exhibited noticeable conformational changes in the protein upon ligand-binding. A significant change in the kink of the S6-transmembrane helix was observed. Inter-chain distances between the crucial residues Y652 and F656 (present below the ion-selectivity filter), their side-chain orientation and hydrogen bonding indicated a probable collapse of the pore. These changes may infer the initiation in transition of hERG from an open to an inactive state. Hence, these findings would help in designing compounds devoid of hERG inhibition with reduced cardiotoxicity.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Shruti Koulgi
- High Performance Computing - Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Panchawati, Pashan, Pune
| | - Vinod Jani
- High Performance Computing - Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Panchawati, Pashan, Pune
| | | | - Jagmohan S Saini
- Novel Drug Discovery and Development, Lupin Research Park, Pune, India
| | - Samiron Phukan
- Novel Drug Discovery and Development, Lupin Research Park, Pune, India
| | - Uddhavesh Sonavane
- High Performance Computing - Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Panchawati, Pashan, Pune
| | - Rajendra Joshi
- High Performance Computing - Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Panchawati, Pashan, Pune
| | - Raj Kamboj
- Novel Drug Discovery and Development, Lupin Research Park, Pune, India
| | - Venkata Palle
- Novel Drug Discovery and Development, Lupin Research Park, Pune, India
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19
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Asai T, Adachi N, Moriya T, Oki H, Maru T, Kawasaki M, Suzuki K, Chen S, Ishii R, Yonemori K, Igaki S, Yasuda S, Ogasawara S, Senda T, Murata T. Cryo-EM Structure of K +-Bound hERG Channel Complexed with the Blocker Astemizole. Structure 2021; 29:203-212.e4. [PMID: 33450182 DOI: 10.1016/j.str.2020.12.007] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 11/25/2020] [Accepted: 12/10/2020] [Indexed: 12/11/2022]
Abstract
The hERG channel is a voltage-gated potassium channel involved in cardiac repolarization. Off-target hERG inhibition by drugs has become a critical issue in the pharmaceutical industry. The three-dimensional structure of the hERG channel was recently reported at 3.8-Å resolution using cryogenic electron microscopy (cryo-EM). However, the drug inhibition mechanism remains unclear because of the scarce structural information regarding the drug- and potassium-bound hERG channels. In this study, we obtained the cryo-EM density map of potassium-bound hERG channel complexed with astemizole, a well-known hERG inhibitor that increases risk of potentially fatal arrhythmia, at 3.5-Å resolution. The structure suggested that astemizole inhibits potassium conduction by binding directly below the selectivity filter. Furthermore, we propose a possible binding model of astemizole to the hERG channel and provide insights into the unusual sensitivity of hERG to several drugs.
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Affiliation(s)
- Tatsuki Asai
- Department of Chemistry, Graduate School of Science, Chiba University, 1-33 Yayoi-cho, Inage, Chiba 263-8522, Japan
| | - Naruhiko Adachi
- Structural Biology Research Center, Institute of Materials Structure Science, High Energy Accelerator Research Organization (KEK), 1-1, Oho, Tsukuba 305-0801, Japan
| | - Toshio Moriya
- Structural Biology Research Center, Institute of Materials Structure Science, High Energy Accelerator Research Organization (KEK), 1-1, Oho, Tsukuba 305-0801, Japan
| | - Hideyuki Oki
- Axcelead Drug Discovery Partners, Inc., 26-1, Muraoka-Higashi 2-chome, Fujisawa, Kanagawa 251-0012, Japan
| | - Takamitsu Maru
- Axcelead Drug Discovery Partners, Inc., 26-1, Muraoka-Higashi 2-chome, Fujisawa, Kanagawa 251-0012, Japan
| | - Masato Kawasaki
- Structural Biology Research Center, Institute of Materials Structure Science, High Energy Accelerator Research Organization (KEK), 1-1, Oho, Tsukuba 305-0801, Japan
| | - Kano Suzuki
- Department of Chemistry, Graduate School of Science, Chiba University, 1-33 Yayoi-cho, Inage, Chiba 263-8522, Japan
| | - Sisi Chen
- Department of Chemistry, Graduate School of Science, Chiba University, 1-33 Yayoi-cho, Inage, Chiba 263-8522, Japan
| | - Ryohei Ishii
- Structure-Based Drug Design Group, Organic Synthesis Department, Daiichi Sankyo RD Novare Co., Ltd, 1-16-13 Kitakasai, Edogawa-ku, Tokyo 134-8630, Japan
| | - Kazuko Yonemori
- Drug Safety Research and Evaluation, Research, Takeda Pharmaceutical Company Limited, 26-1 Muraoka-Higashi 2-chome, Fujisawa, Kanagawa 251-8555, Japan
| | - Shigeru Igaki
- Drug Safety Research and Evaluation, Research, Takeda Pharmaceutical Company Limited, 26-1 Muraoka-Higashi 2-chome, Fujisawa, Kanagawa 251-8555, Japan
| | - Satoshi Yasuda
- Department of Chemistry, Graduate School of Science, Chiba University, 1-33 Yayoi-cho, Inage, Chiba 263-8522, Japan; Molecular Chirality Research Center, Chiba University, 1-33 Yayoi-cho, Inage, Chiba 263-8522, Japan
| | - Satoshi Ogasawara
- Department of Chemistry, Graduate School of Science, Chiba University, 1-33 Yayoi-cho, Inage, Chiba 263-8522, Japan; Molecular Chirality Research Center, Chiba University, 1-33 Yayoi-cho, Inage, Chiba 263-8522, Japan
| | - Toshiya Senda
- Structural Biology Research Center, Institute of Materials Structure Science, High Energy Accelerator Research Organization (KEK), 1-1, Oho, Tsukuba 305-0801, Japan
| | - Takeshi Murata
- Department of Chemistry, Graduate School of Science, Chiba University, 1-33 Yayoi-cho, Inage, Chiba 263-8522, Japan; Molecular Chirality Research Center, Chiba University, 1-33 Yayoi-cho, Inage, Chiba 263-8522, Japan.
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20
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Inhibition of the hERG potassium channel by phenanthrene: a polycyclic aromatic hydrocarbon pollutant. Cell Mol Life Sci 2021; 78:7899-7914. [PMID: 34727194 PMCID: PMC8629796 DOI: 10.1007/s00018-021-03967-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 09/25/2021] [Accepted: 10/01/2021] [Indexed: 11/07/2022]
Abstract
The lipophilic polycyclic aromatic hydrocarbon (PAH) phenanthrene is relatively abundant in polluted air and water and can access and accumulate in human tissue. Phenanthrene has been reported to interact with cardiac ion channels in several fish species. This study was undertaken to investigate the ability of phenanthrene to interact with hERG (human Ether-à-go-go-Related Gene) encoded Kv11.1 K+ channels, which play a central role in human ventricular repolarization. Pharmacological inhibition of hERG can be proarrhythmic. Whole-cell patch clamp recordings of hERG current (IhERG) were made from HEK293 cells expressing wild-type (WT) and mutant hERG channels. WT IhERG1a was inhibited by phenanthrene with an IC50 of 17.6 ± 1.7 µM, whilst IhERG1a/1b exhibited an IC50 of 1.8 ± 0.3 µM. WT IhERG block showed marked voltage and time dependence, indicative of dependence of inhibition on channel gating. The inhibitory effect of phenanthrene was markedly impaired by the attenuated inactivation N588K mutation. Remarkably, mutations of S6 domain aromatic amino acids (Y652, F656) in the canonical drug binding site did not impair the inhibitory action of phenanthrene; the Y652A mutation augmented IhERG block. In contrast, the F557L (S5) and M651A (S6) mutations impaired the ability of phenanthrene to inhibit IhERG, as did the S624A mutation below the selectivity filter region. Computational docking using a cryo-EM derived hERG structure supported the mutagenesis data. Thus, phenanthrene acts as an inhibitor of the hERG K+ channel by directly interacting with the channel, binding to a distinct site in the channel pore domain.
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21
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Mousaei M, Kudaibergenova M, MacKerell AD, Noskov S. Assessing hERG1 Blockade from Bayesian Machine-Learning-Optimized Site Identification by Ligand Competitive Saturation Simulations. J Chem Inf Model 2020; 60:6489-6501. [PMID: 33196188 PMCID: PMC7839320 DOI: 10.1021/acs.jcim.0c01065] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Drug-induced cardiotoxicity is a potentially lethal and yet one of the most common side effects with the drugs in clinical use. Most of the drug-induced cardiotoxicity is associated with an off-target pharmacological blockade of K+ currents carried out by the cardiac Human-Ether-a-go-go-Related (hERG1) potassium channel. There is a compulsory preclinical stage safety assessment for the hERG1 blockade for all classes of drugs, which adds substantially to the cost of drug development. The availability of a high-resolution cryogenic electron microscopy (cryo-EM) structure for the channel in its open/depolarized state solved in 2017 enabled the application of molecular modeling for rapid assessment of drug blockade by molecular docking and simulation techniques. More importantly, if successful, in silico methods may allow a path to lead-compound salvaging by mapping out key block determinants. Here, we report the blind application of the site identification by the ligand competitive saturation (SILCS) protocol to map out druggable/regulatory hotspots in the hERG1 channel available for blockers and activators. The SILCS simulations use small solutes representative of common functional groups to sample the chemical space for the entire protein and its environment using all-atom simulations. The resulting chemical maps, FragMaps, explicitly account for receptor flexibility, protein-fragment interactions, and fragment desolvation penalty allowing for rapid ranking of potential ligands as blockers or nonblockers of hERG1. To illustrate the power of the approach, SILCS was applied to a test set of 55 blockers with diverse chemical scaffolds and pIC50 values measured under uniform conditions. The original SILCS model was based on the all-atom modeling of the hERG1 channel in an explicit lipid bilayer and was further augmented with a Bayesian-optimization/machine-learning (BML) stage employing an independent literature-derived training set of 163 molecules. BML approach was used to determine weighting factors for the FragMaps contributions to the scoring function. pIC50 predictions from the combined SILCS/BML approach to the 55 blockers showed a Pearson correlation (PC) coefficient of >0.535 relative to the experimental data. SILCS/BML model was shown to yield substantially improved performance as compared to commonly used rigid and flexible molecular docking methods for a well-established cohort of hERG1 blockers, where no correlation with experimental data was recorded. SILCS/BML results also suggest that a proper weighting of protonation states of common blockers present at physiological pH is essential for accurate predictions of blocker potency. The precalculated and optimized SILCS FragMaps can now be used for the rapid screening of small molecules for their cardiotoxic potential as well as for exploring alternative binding pockets in the hERG1 channel with applications to the rational design of activators.
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Affiliation(s)
- Mahdi Mousaei
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Meruyert Kudaibergenova
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Alexander D. MacKerell
- Computer-Aided Drug Design Center, Department of Pharmaceutical Science, School of Pharmacy, University of Maryland, Baltimore, MD 21201, USA
| | - Sergei Noskov
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada
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22
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Zhang Y, Dempsey CE, Hancox JC. Electrophysiological characterization of the modified hERG T potassium channel used to obtain the first cryo-EM hERG structure. Physiol Rep 2020; 8:e14568. [PMID: 33091232 PMCID: PMC7580876 DOI: 10.14814/phy2.14568] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 08/13/2020] [Accepted: 08/14/2020] [Indexed: 01/02/2023] Open
Abstract
The voltage-gated hERG (human-Ether-à-go-go Related Gene) K+ channel plays a fundamental role in cardiac action potential repolarization. Loss-of-function mutations or pharmacological inhibition of hERG leads to long QT syndrome, whilst gain-of-function mutations lead to short QT syndrome. A recent open channel cryo-EM structure of hERG represents a significant advance in the ability to interrogate hERG channel structure-function. In order to suppress protein aggregation, a truncated channel construct of hERG (hERGT ) was used to obtain this structure. In hERGT cytoplasmic domain residues 141 to 350 and 871 to 1,005 were removed from the full-length channel protein. There are limited data on the electrophysiological properties of hERGT channels. Therefore, this study was undertaken to determine how hERGT influences channel function at physiological temperature. Whole-cell measurements of hERG current (IhERG ) were made at 37°C from HEK 293 cells expressing wild-type (WT) or hERGT channels. With a standard +20 mV activating command protocol, neither end-pulse nor tail IhERG density significantly differed between WT and hERGT . However, the IhERG deactivation rate was significantly slower for hERGT . Half-maximal activation voltage (V0.5 ) was positively shifted for hERGT by ~+8 mV (p < .05 versus WT), without significant change to the activation relation slope factor. Neither the voltage dependence of inactivation, nor time course of development of inactivation significantly differed between WT and hERGT , but recovery of IhERG from inactivation was accelerated for hERGT (p < .05 versus WT). Steady-state "window" current was positively shifted for hERGT with a modest increase in the window current peak. Under action potential (AP) voltage clamp, hERGT IhERG showed modestly increased current throughout the AP plateau phase with a significant increase in current integral during the AP. The observed consequences for hERGT IhERG of deletion of the two cytoplasmic regions may reflect changes to electrostatic interactions influencing the voltage sensor domain.
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Affiliation(s)
- Yihong Zhang
- School of Physiology and Pharmacology and NeuroscienceBiomedical Sciences BuildingThe University of BristolUniversity WalkBristolUK
| | - Christopher E. Dempsey
- School of BiochemistryBiomedical Sciences BuildingThe University of BristolUniversity WalkBristolUK
| | - Jules C. Hancox
- School of Physiology and Pharmacology and NeuroscienceBiomedical Sciences BuildingThe University of BristolUniversity WalkBristolUK
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Leão RP, Cruz JV, da Costa GV, Cruz JN, Ferreira EFB, Silva RC, de Lima LR, Borges RS, dos Santos GB, Santos CBR. Identification of New Rofecoxib-Based Cyclooxygenase-2 Inhibitors: A Bioinformatics Approach. Pharmaceuticals (Basel) 2020; 13:E209. [PMID: 32858871 PMCID: PMC7559105 DOI: 10.3390/ph13090209] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Revised: 08/17/2020] [Accepted: 08/17/2020] [Indexed: 02/07/2023] Open
Abstract
The cyclooxygenase-2 receptor is a therapeutic target for planning potential drugs with anti-inflammatory activity. The selective cyclooxygenase-2 (COX-2) inhibitor rofecoxib was selected as a pivot molecule to perform virtual ligand-based screening from six commercial databases. We performed the search for similarly shaped Rapid Overlay of Chemical Structures (ROCS) and electrostatic (EON) compounds. After, we used pharmacokinetic and toxicological parameters to determine the best potential compounds, obtained through the softwares QikProp and Derek, respectively. Then, the compounds proceeded to the molecular anchorage study, which showed promising results of binding affinity with the hCOX-2 receptor: LMQC72 (∆G = -11.0 kcal/mol), LMQC36 (∆G = -10.6 kcal/mol), and LMQC50 (∆G = -10.2 kcal/mol). LMQC72 and LMQC36 showed higher binding affinity compared to rofecoxib (∆G = -10.4 kcal/mol). Finally, molecular dynamics (MD) simulations were used to evaluate the interaction of the compounds with the target hCOX-2 during 150 ns. In all MD simulation trajectories, the ligands remained interacting with the protein until the end of the simulation. The compounds were also complexing with hCOX-2 favorably. The compounds obtained the following affinity energy values: rofecoxib: ΔGbind = -45.31 kcal/mol; LMQC72: ΔGbind = -38.58 kcal/mol; LMQC36: ΔGbind = -36.10 kcal/mol; and LMQC50: ΔGbind = -39.40 kcal/mol. The selected LMQC72, LMQC50, and LMQC36 structures showed satisfactory pharmacokinetic results related to absorption and distribution. The toxicological predictions of these compounds did not display alerts for possible toxic groups and lower risk of cardiotoxicity compared to rofecoxib. Therefore, future in vitro and in vivo studies are needed to confirm the anti-inflammatory potential of the compounds selected here with bioinformatics approaches based on rofecoxib ligand.
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Affiliation(s)
- Rozires P. Leão
- Graduate Program in Medicinal Chemistry and Molecular Modeling, Health Science Institute, Federal University of Pará, Belém 66075-110, PA, Brazil; (R.P.L.); (R.C.S.); (L.R.d.L.); (R.S.B.)
- Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, Brazil.; (J.V.C.); (G.V.d.C.); (J.N.C.); (E.F.B.F.)
| | - Josiane V. Cruz
- Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, Brazil.; (J.V.C.); (G.V.d.C.); (J.N.C.); (E.F.B.F.)
| | - Glauber V. da Costa
- Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, Brazil.; (J.V.C.); (G.V.d.C.); (J.N.C.); (E.F.B.F.)
| | - Jorddy N. Cruz
- Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, Brazil.; (J.V.C.); (G.V.d.C.); (J.N.C.); (E.F.B.F.)
| | - Elenilze F. B. Ferreira
- Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, Brazil.; (J.V.C.); (G.V.d.C.); (J.N.C.); (E.F.B.F.)
- Laboratory of Organic Chemistry and Biochemistry, University of State of Amapá, Macapá 68900-070, AP, Brazil
| | - Raí C. Silva
- Graduate Program in Medicinal Chemistry and Molecular Modeling, Health Science Institute, Federal University of Pará, Belém 66075-110, PA, Brazil; (R.P.L.); (R.C.S.); (L.R.d.L.); (R.S.B.)
- Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, Brazil.; (J.V.C.); (G.V.d.C.); (J.N.C.); (E.F.B.F.)
- Department of Chemistry, Faculty of Philosophy, Sciences and Letters of Ribeirão Preto, University of São Paulo, Ribeirão Preto 14090-901, SP, Brazil
| | - Lúcio R. de Lima
- Graduate Program in Medicinal Chemistry and Molecular Modeling, Health Science Institute, Federal University of Pará, Belém 66075-110, PA, Brazil; (R.P.L.); (R.C.S.); (L.R.d.L.); (R.S.B.)
- Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, Brazil.; (J.V.C.); (G.V.d.C.); (J.N.C.); (E.F.B.F.)
| | - Rosivaldo S. Borges
- Graduate Program in Medicinal Chemistry and Molecular Modeling, Health Science Institute, Federal University of Pará, Belém 66075-110, PA, Brazil; (R.P.L.); (R.C.S.); (L.R.d.L.); (R.S.B.)
| | - Gabriela B. dos Santos
- Institute of Collective Health, Federal University of Western Pará, Santarém 68040-255, PA, Brazil;
| | - Cleydson B. R. Santos
- Graduate Program in Medicinal Chemistry and Molecular Modeling, Health Science Institute, Federal University of Pará, Belém 66075-110, PA, Brazil; (R.P.L.); (R.C.S.); (L.R.d.L.); (R.S.B.)
- Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, AP, Brazil.; (J.V.C.); (G.V.d.C.); (J.N.C.); (E.F.B.F.)
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Kudaibergenova M, Guo J, Khan HM, Zahid F, Lees-Miller J, Noskov SY, Duff HJ. Allosteric Coupling Between Drug Binding and the Aromatic Cassette in the Pore Domain of the hERG1 Channel: Implications for a State-Dependent Blockade. Front Pharmacol 2020; 11:914. [PMID: 32694995 PMCID: PMC7338687 DOI: 10.3389/fphar.2020.00914] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 06/04/2020] [Indexed: 12/18/2022] Open
Abstract
Human-ether-a-go-go-related channel (hERG1) is the pore-forming domain of the delayed rectifier K+ channel in the heart which underlies the IKr current. The channel has been extensively studied due to its propensity to bind chemically diverse group of drugs. The subsequent hERG1 block can lead to a prolongation of the QT interval potentially leading to an abnormal cardiac electrical activity. The recently solved cryo-EM structure featured a striking non-swapped topology of the Voltage-Sensor Domain (VSD) which is packed against the pore-domain as well as a small and hydrophobic intra-cavity space. The small size and hydrophobicity of the cavity was unexpected and challenges the already-established hypothesis of drugs binding to the wide cavity. Recently, we showed that an amphipathic drug, ivabradine, may favorably bind the channel from the lipid-facing surface and we discovered a mutant (M651T) on the lipid facing domain between the VSD and the PD which inhibited the blocking capacity of the drug. Using multi-microseconds Molecular Dynamics (MD) simulations of wild-type and M651T mutant hERG1, we suggested the block of the channel through the lipid mediated pathway, the opening of which is facilitated by the flexible phenylalanine ring (F656). In this study, we characterize the dynamic interaction of the methionine-aromatic cassette in the S5-S6 helices by combining data from electrophysiological experiments with MD simulations and molecular docking to elucidate the complex allosteric coupling between drug binding to lipid-facing and intra-cavity sites and aromatic cassette dynamics. We investigated two well-established hERG1 blockers (ivabradine and dofetilide) for M651 sensitivity through electrophysiology and mutagenesis techniques. Our electrophysiology data reveal insensitivity of dofetilide to the mutations at site M651 on the lipid facing side of the channel, mirroring our results obtained from docking experiments. Moreover, we show that the dofetilide-induced block of hERG1 occurs through the intracellular space, whereas little to no block of ivabradine is observed during the intracellular application of the drug. The dynamic conformational rearrangement of the F656 appears to regulate the translocation of ivabradine into the central cavity. M651T mutation appears to disrupt this entry pathway by altering the molecular conformation of F656.
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Affiliation(s)
- Meruyert Kudaibergenova
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada.,Cumming School of Medicine, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
| | - Jiqing Guo
- Cumming School of Medicine, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
| | - Hanif M Khan
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - Farhan Zahid
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - James Lees-Miller
- Cumming School of Medicine, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
| | - Sergei Yu Noskov
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - Henry J Duff
- Cumming School of Medicine, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
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Brewer KR, Kuenze G, Vanoye CG, George AL, Meiler J, Sanders CR. Structures Illuminate Cardiac Ion Channel Functions in Health and in Long QT Syndrome. Front Pharmacol 2020; 11:550. [PMID: 32431610 PMCID: PMC7212895 DOI: 10.3389/fphar.2020.00550] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Accepted: 04/09/2020] [Indexed: 12/13/2022] Open
Abstract
The cardiac action potential is critical to the production of a synchronized heartbeat. This electrical impulse is governed by the intricate activity of cardiac ion channels, among them the cardiac voltage-gated potassium (Kv) channels KCNQ1 and hERG as well as the voltage-gated sodium (Nav) channel encoded by SCN5A. Each channel performs a highly distinct function, despite sharing a common topology and structural components. These three channels are also the primary proteins mutated in congenital long QT syndrome (LQTS), a genetic condition that predisposes to cardiac arrhythmia and sudden cardiac death due to impaired repolarization of the action potential and has a particular proclivity for reentrant ventricular arrhythmias. Recent cryo-electron microscopy structures of human KCNQ1 and hERG, along with the rat homolog of SCN5A and other mammalian sodium channels, provide atomic-level insight into the structure and function of these proteins that advance our understanding of their distinct functions in the cardiac action potential, as well as the molecular basis of LQTS. In this review, the gating, regulation, LQTS mechanisms, and pharmacological properties of KCNQ1, hERG, and SCN5A are discussed in light of these recent structural findings.
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Affiliation(s)
- Kathryn R. Brewer
- Center for Structural Biology, Vanderbilt University School of Medicine Basic Sciences, Nashville, TN, United States
- Department of Biochemistry, Vanderbilt University, Nashville, TN, United States
| | - Georg Kuenze
- Center for Structural Biology, Vanderbilt University School of Medicine Basic Sciences, Nashville, TN, United States
- Department of Chemistry, Vanderbilt University, Nashville, TN, United States
| | - Carlos G. Vanoye
- Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Alfred L. George
- Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Jens Meiler
- Center for Structural Biology, Vanderbilt University School of Medicine Basic Sciences, Nashville, TN, United States
- Department of Chemistry, Vanderbilt University, Nashville, TN, United States
- Department of Pharmacology, Vanderbilt University School of Medicine Basic Sciences, Nashville, TN, United States
- Institute for Drug Discovery, Leipzig University Medical School, Leipzig, Germany
| | - Charles R. Sanders
- Center for Structural Biology, Vanderbilt University School of Medicine Basic Sciences, Nashville, TN, United States
- Department of Biochemistry, Vanderbilt University, Nashville, TN, United States
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Hemmerich J, Ecker GF. In silico toxicology: From structure–activity relationships towards deep learning and adverse outcome pathways. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2020; 10:e1475. [PMID: 35866138 PMCID: PMC9286356 DOI: 10.1002/wcms.1475] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Revised: 03/09/2020] [Accepted: 03/10/2020] [Indexed: 12/18/2022]
Abstract
In silico toxicology is an emerging field. It gains increasing importance as research is aiming to decrease the use of animal experiments as suggested in the 3R principles by Russell and Burch. In silico toxicology is a means to identify hazards of compounds before synthesis, and thus in very early stages of drug development. For chemical industries, as well as regulatory agencies it can aid in gap‐filling and guide risk minimization strategies. Techniques such as structural alerts, read‐across, quantitative structure–activity relationship, machine learning, and deep learning allow to use in silico toxicology in many cases, some even when data is scarce. Especially the concept of adverse outcome pathways puts all techniques into a broader context and can elucidate predictions by mechanistic insights. This article is categorized under:Structure and Mechanism > Computational Biochemistry and Biophysics Data Science > Chemoinformatics
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Affiliation(s)
- Jennifer Hemmerich
- Department of Pharmaceutical Chemistry University of Vienna Vienna Austria
| | - Gerhard F. Ecker
- Department of Pharmaceutical Chemistry University of Vienna Vienna Austria
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27
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Butler A, Helliwell MV, Zhang Y, Hancox JC, Dempsey CE. An Update on the Structure of hERG. Front Pharmacol 2020; 10:1572. [PMID: 32038248 PMCID: PMC6992539 DOI: 10.3389/fphar.2019.01572] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 12/04/2019] [Indexed: 01/22/2023] Open
Abstract
The human voltage-sensitive K+ channel hERG plays a fundamental role in cardiac action potential repolarization, effectively controlling the QT interval of the electrocardiogram. Inherited loss- or gain-of-function mutations in hERG can result in dangerous “long” (LQTS) or “short” QT syndromes (SQTS), respectively, and the anomalous susceptibility of hERG to block by a diverse range of drugs underlies an acquired LQTS. A recent open channel cryo-EM structure of hERG should greatly advance understanding of the molecular basis of hERG channelopathies and drug-induced LQTS. Here we describe an update of recent research that addresses the nature of the particular gated state of hERG captured in the new structure, and the insight afforded by the structure into the molecular basis for high affinity drug block of hERG, the binding of hERG activators and the molecular basis of hERG's peculiar gating properties. Interpretation of the pharmacology of natural SQTS mutants in the context of the structure is a promising approach to understanding the molecular basis of hERG inactivation, and the structure suggests how voltage-dependent changes in the membrane domain may be transmitted to an extracellular “turret” to effect inactivation through aromatic side chain motifs that are conserved throughout the KCNH family of channels.
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Affiliation(s)
- Andrew Butler
- School of Physiology, Pharmacology and Neuroscience, Medical Sciences Building, Bristol, United Kingdom
| | - Matthew V Helliwell
- School of Physiology, Pharmacology and Neuroscience, Medical Sciences Building, Bristol, United Kingdom
| | - Yihong Zhang
- School of Physiology, Pharmacology and Neuroscience, Medical Sciences Building, Bristol, United Kingdom
| | - Jules C Hancox
- School of Physiology, Pharmacology and Neuroscience, Medical Sciences Building, Bristol, United Kingdom
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