1
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Thakur A, Gizzio J, Levy RM. Potts Hamiltonian Models and Molecular Dynamics Free Energy Simulations for Predicting the Impact of Mutations on Protein Kinase Stability. J Phys Chem B 2024; 128:1656-1667. [PMID: 38350894 PMCID: PMC10939730 DOI: 10.1021/acs.jpcb.3c08097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2024]
Abstract
Single-point mutations in kinase proteins can affect their stability and fitness, and computational analysis of these effects can provide insights into the relationships among protein sequence, structure, and function for this enzyme family. To assess the impact of mutations on protein stability, we used a sequence-based Potts Hamiltonian model trained on a kinase family multiple-sequence alignment (MSA) to calculate the statistical energy (fitness) effects of mutations and compared these against relative folding free energies (ΔΔGs) calculated from all-atom molecular dynamics free energy perturbation (FEP) simulations in explicit solvent. The fitness effects of mutations in the Potts model (ΔEs) showed good agreement with experimental thermostability data (Pearson r = 0.68), similar to the correlation we observed with ΔΔGs predicted from structure-based relative FEP simulations. Recognizing the possible advantages of using Potts models to rapidly estimate protein stability effects of kinase mutations seen in cancer genomics data, we used the Potts statistical energy model to estimate the stability effects of 65 conservative and nonconservative mutations across three distinct kinases (Wee1, Abl1, and Cdc7) with somatic mutations reported in the Genomic Data Commons (GDC) database. The ΔEs of these mutations calculated from the Potts model are consistent with the corresponding ΔΔGs from FEP simulations (Pearson ratio of 0.72). The agreement between these methods suggests that the Potts model may be used as a sequence-based tool for high-throughput screening of mutational effects as part of a computational pipeline for predicting the stability effects of mutations. We also demonstrate how the scalability of the fitness-based Potts model calculations permits analyses that are not easily accessed using FEP simulations. To this end, we employed site-saturation mutagenesis in the Potts model in order to investigate the relative stability effects of mutations seen in different cancer evolutionary scenarios. We used this approach to analyze the effects of drug pressure in Abl kinase by contrasting the relative fitness penalties of somatic mutations seen in miscellaneous cancer types with those calculated for mutations associated with cancer drug resistance. We observed that, in contrast to somatic mutations of Abl seen in various tumors that appear to have evolved neutrally, cancer mutations that evolved under drug pressure in Abl-targeted therapies tend to preserve enzyme stability.
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Affiliation(s)
- Abhishek Thakur
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - Joan Gizzio
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - Ronald M Levy
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, United States
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2
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Khuttan S, Azimi S, Wu JZ, Dick S, Wu C, Xu H, Gallicchio E. Taming multiple binding poses in alchemical binding free energy prediction: the β-cyclodextrin host-guest SAMPL9 blinded challenge. Phys Chem Chem Phys 2023; 25:24364-24376. [PMID: 37676233 DOI: 10.1039/d3cp02125d] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
We apply the Alchemical Transfer Method (ATM) and a bespoke fixed partial charge force field to the SAMPL9 bCD host-guest binding free energy prediction challenge that comprises a combination of complexes formed between five phenothiazine guests and two cyclodextrin hosts. Multiple chemical forms, competing binding poses, and computational modeling challenges pose significant obstacles to obtaining reliable computational predictions for these systems. The phenothiazine guests exist in solution as racemic mixtures of enantiomers related by nitrogen inversions that bind the hosts in various binding poses, each requiring an individual free energy analysis. Due to the large size of the guests and the conformational reorganization of the hosts, which prevent a direct absolute binding free energy route, binding free energies are obtained by a series of absolute and relative binding alchemical steps for each chemical species in each binding pose. Metadynamics-accelerated conformational sampling was found to be necessary to address the poor convergence of some numerical estimates affected by conformational trapping. Despite these challenges, our blinded predictions quantitatively reproduced the experimental affinities for the β-cyclodextrin host and, to a lesser extent, those with a methylated derivative. The work illustrates the challenges of obtaining reliable free energy data in in silico drug design for even seemingly simple systems and introduces some of the technologies available to tackle them.
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Affiliation(s)
- Sheenam Khuttan
- Department of Chemistry, Brooklyn College of the City University of New York, New York, USA.
- PhD Program in Biochemistry, Graduate Center of the City University of New York, USA
| | - Solmaz Azimi
- Department of Chemistry, Brooklyn College of the City University of New York, New York, USA.
- PhD Program in Biochemistry, Graduate Center of the City University of New York, USA
| | - Joe Z Wu
- Department of Chemistry, Brooklyn College of the City University of New York, New York, USA.
- PhD Program in Chemistry, Graduate Center of the City University of New York, USA
| | | | | | | | - Emilio Gallicchio
- Department of Chemistry, Brooklyn College of the City University of New York, New York, USA.
- PhD Program in Biochemistry, Graduate Center of the City University of New York, USA
- PhD Program in Chemistry, Graduate Center of the City University of New York, USA
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3
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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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4
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Feng M, Heinzelmann G, Gilson MK. Absolute binding free energy calculations improve enrichment of actives in virtual compound screening. Sci Rep 2022; 12:13640. [PMID: 35948614 PMCID: PMC9365818 DOI: 10.1038/s41598-022-17480-w] [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: 05/10/2022] [Accepted: 07/26/2022] [Indexed: 12/04/2022] Open
Abstract
We determined the effectiveness of absolute binding free energy (ABFE) calculations to refine the selection of active compounds in virtual compound screening, a setting where the more commonly used relative binding free energy approach is not readily applicable. To do this, we conducted baseline docking calculations of structurally diverse compounds in the DUD-E database for three targets, BACE1, CDK2 and thrombin, followed by ABFE calculations for compounds with high docking scores. The docking calculations alone achieved solid enrichment of active compounds over decoys. Encouragingly, the ABFE calculations then improved on this baseline. Analysis of the results emphasizes the importance of establishing high quality ligand poses as starting points for ABFE calculations, a nontrivial goal when processing a library of diverse compounds without informative co-crystal structures. Overall, our results suggest that ABFE calculations can play a valuable role in the drug discovery process.
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Affiliation(s)
- Mudong Feng
- Department of Chemistry and Biochemistry, and Skaggs School of Pharmacy and Pharmaceutical Sciences, UC San Diego, La Jolla, CA, 92093, USA
| | - Germano Heinzelmann
- Departamento de Física, Universidade Federal de Santa Catarina, Florianópolis, Santa Catarina, Brazil
| | - Michael K Gilson
- Department of Chemistry and Biochemistry, and Skaggs School of Pharmacy and Pharmaceutical Sciences, UC San Diego, La Jolla, CA, 92093, USA.
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5
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Fiedler W, Freisleben F, Wellbrock J, Kirschner KN. Mebendazole's Conformational Space and Its Predicted Binding to Human Heat-Shock Protein 90. J Chem Inf Model 2022; 62:3604-3617. [PMID: 35867562 DOI: 10.1021/acs.jcim.2c00290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Recent experimental evidence suggests that mebendazole, a popular antiparasitic drug, binds to heat shock protein 90 (Hsp90) and inhibits acute myeloid leukemia cell growth. In this study we use quantum mechanics (QM), molecular similarity, and molecular dynamics (MD) calculations to predict possible binding poses of mebendazole to the adenosine triphosphate (ATP) binding site of Hsp90. Extensive conformational searches and minimization of the five mebendazole tautomers using the MP2/aug-cc-pVTZ theory level resulted in 152 minima. Mebendazole-Hsp90 complex models were subsequently created using the QM optimized conformations and protein coordinates obtained from experimental crystal structures that were chosen through similarity calculations. Nine different poses were identified from a total of 600 ns of explicit solvent, all-atom MD simulations using two different force fields. All simulations support the hypothesis that mebendazole is able to bind to the ATP binding site of Hsp90.
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Affiliation(s)
- Walter Fiedler
- Department of Oncology, Hematology and Bone Marrow Transplantation with Section Pneumology, Hubertus Wald University Cancer Center, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Fabian Freisleben
- Department of Oncology, Hematology and Bone Marrow Transplantation with Section Pneumology, Hubertus Wald University Cancer Center, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Jasmin Wellbrock
- Department of Oncology, Hematology and Bone Marrow Transplantation with Section Pneumology, Hubertus Wald University Cancer Center, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Karl N Kirschner
- Department of Computer Science, University of Applied Sciences Bonn-Rhein-Sieg, 53757 Sankt Augustin, Germany
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6
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Sun Q, Biswas A, Vijayan RSK, Craveur P, Forli S, Olson AJ, Castaner AE, Kirby KA, Sarafianos SG, Deng N, Levy R. Structure-based virtual screening workflow to identify antivirals targeting HIV-1 capsid. J Comput Aided Mol Des 2022; 36:193-203. [PMID: 35262811 PMCID: PMC8904208 DOI: 10.1007/s10822-022-00446-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 02/24/2022] [Indexed: 02/07/2023]
Abstract
We have identified novel HIV-1 capsid inhibitors targeting the PF74 binding site. Acting as the building block of the HIV-1 capsid core, the HIV-1 capsid protein plays an important role in the viral life cycle and is an attractive target for antiviral development. A structure-based virtual screening workflow for hit identification was employed, which includes docking 1.6 million commercially-available drug-like compounds from the ZINC database to the capsid dimer, followed by applying two absolute binding free energy (ABFE) filters on the 500 top-ranked molecules from docking. The first employs the Binding Energy Distribution Analysis Method (BEDAM) in implicit solvent. The top-ranked compounds are then refined using the Double Decoupling method in explicit solvent. Both docking and BEDAM refinement were carried out on the IBM World Community Grid as part of the FightAIDS@Home project. Using this virtual screening workflow, we identified 24 molecules with calculated binding free energies between − 6 and − 12 kcal/mol. We performed thermal shift assays on these molecules to examine their potential effects on the stability of HIV-1 capsid hexamer and found that two compounds, ZINC520357473 and ZINC4119064 increased the melting point of the latter by 14.8 °C and 33 °C, respectively. These results support the conclusion that the two ZINC compounds are primary hits targeting the capsid dimer interface. Our simulations also suggest that the two hit molecules may bind at the capsid dimer interface by occupying a new sub-pocket that has not been exploited by existing CA inhibitors. The possible causes for why other top-scored compounds suggested by ABFE filters failed to show measurable activity are discussed.
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Affiliation(s)
- Qinfang Sun
- Center for Biophysics and Computational Biology and Department of Chemistry, Temple University, Philadelphia, PA, 19122, USA
| | - Avik Biswas
- Center for Biophysics and Computational Biology and Department of Chemistry, Temple University, Philadelphia, PA, 19122, USA
| | - R S K Vijayan
- Institute for Applied Cancer Science, MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Pierrick Craveur
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Stefano Forli
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Arthur J Olson
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Andres Emanuelli Castaner
- Laboratory of Biochemical Pharmacology, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, 30322, USA.,Children's Healthcare of Atlanta, Atlanta, GA, 30322, USA
| | - Karen A Kirby
- Laboratory of Biochemical Pharmacology, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, 30322, USA.,Children's Healthcare of Atlanta, Atlanta, GA, 30322, USA
| | - Stefan G Sarafianos
- Laboratory of Biochemical Pharmacology, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, 30322, USA.,Children's Healthcare of Atlanta, Atlanta, GA, 30322, USA
| | - Nanjie Deng
- Department of Chemistry and Physical Sciences, Pace University, New York, NY, 10038, USA.
| | - Ronald Levy
- Center for Biophysics and Computational Biology and Department of Chemistry, Temple University, Philadelphia, PA, 19122, USA
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7
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Azimi S, Wu JZ, Khuttan S, Kurtzman T, Deng N, Gallicchio E. Application of the alchemical transfer and potential of mean force methods to the SAMPL8 host-guest blinded challenge. J Comput Aided Mol Des 2022; 36:63-76. [PMID: 35059940 PMCID: PMC8982563 DOI: 10.1007/s10822-021-00437-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 12/01/2021] [Indexed: 01/23/2023]
Abstract
We report the results of our participation in the SAMPL8 GDCC Blind Challenge for host-guest binding affinity predictions. Absolute binding affinity prediction is of central importance to the biophysics of molecular association and pharmaceutical discovery. The blinded SAMPL series have provided an important forum for assessing the reliability of binding free energy methods in an objective way. In this challenge, we employed two binding free energy methods, the newly developed alchemical transfer method (ATM) and the well-established potential of mean force (PMF) physical pathway method, using the same setup and force field model. The calculated binding free energies from the two methods are in excellent quantitative agreement. Importantly, the results from the two methods were also found to agree well with the experimental binding affinities released subsequently, with R values of 0.89 (ATM) and 0.83 (PMF). These results were ranked among the best of the SAMPL8 GDCC challenge and second only to those obtained with the more accurate AMOEBA force field. Interestingly, the two host molecules included in the challenge (TEMOA and TEETOA) displayed distinct binding mechanisms, with TEMOA undergoing a dehydration transition whereas guest binding to TEETOA resulted in the opening of the binding cavity that remains essentially dry during the process. The coupled reorganization and hydration equilibria observed in these systems is a useful prototype for the study of these phenomena often observed in the formation of protein-ligand complexes. Given that the two free energy methods employed here are based on entirely different thermodynamic pathways, the close agreement between the two and their general agreement with the experimental binding free energies are a testament to the high quality and precision achieved by theory and methods. The study provides further validation of the novel ATM binding free energy estimation protocol and paves the way to further extensions of the method to more complex systems.
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Affiliation(s)
- Solmaz Azimi
- Department of Chemistry, Brooklyn College of the City University of New York,PhD Program in Biochemistry, Graduate Center of the City University of New York
| | - Joe Z. Wu
- Department of Chemistry, Brooklyn College of the City University of New York,PhD Program in Chemistry, Graduate Center of the City University of New York
| | - Sheenam Khuttan
- Department of Chemistry, Brooklyn College of the City University of New York,PhD Program in Biochemistry, Graduate Center of the City University of New York
| | - Tom Kurtzman
- Department of Chemistry, Lehman College of the City University of New York,PhD Program in Chemistry, Graduate Center of the City University of New York,PhD Program in Biochemistry, Graduate Center of the City University of New York
| | - Nanjie Deng
- Department of Chemistry and Physical Sciences, Pace University, New York, New York
| | - Emilio Gallicchio
- Department of Chemistry, Brooklyn College of the City University of New York,PhD Program in Chemistry, Graduate Center of the City University of New York,PhD Program in Biochemistry, Graduate Center of the City University of New York
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8
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Granadino-Roldán JM, Mey ASJS, Pérez González JJ, Bosisio S, Rubio-Martinez J, Michel J. Effect of set up protocols on the accuracy of alchemical free energy calculation over a set of ACK1 inhibitors. PLoS One 2019; 14:e0213217. [PMID: 30861030 PMCID: PMC6413950 DOI: 10.1371/journal.pone.0213217] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 02/15/2019] [Indexed: 11/19/2022] Open
Abstract
Hit-to-lead virtual screening frequently relies on a cascade of computational methods that starts with rapid calculations applied to a large number of compounds and ends with more expensive computations restricted to a subset of compounds that passed initial filters. This work focuses on set up protocols for alchemical free energy (AFE) scoring in the context of a Docking–MM/PBSA–AFE cascade. A dataset of 15 congeneric inhibitors of the ACK1 protein was used to evaluate the performance of AFE set up protocols that varied in the steps taken to prepare input files (using previously docked and best scored poses, manual selection of poses, manual placement of binding site water molecules). The main finding is that use of knowledge derived from X-ray structures to model binding modes, together with the manual placement of a bridging water molecule, improves the R2 from 0.45 ± 0.06 to 0.76 ± 0.02 and decreases the mean unsigned error from 2.11 ± 0.08 to 1.24 ± 0.04 kcal mol-1. By contrast a brute force automated protocol that increased the sampling time ten-fold lead to little improvements in accuracy. Besides, it is shown that for the present dataset hysteresis can be used to flag poses that need further attention even without prior knowledge of experimental binding affinities.
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Affiliation(s)
- José M. Granadino-Roldán
- Departamento de Química Física, Facultad de Ciencias Experimentales, Universidad de Jaén, Campus “Las Lagunillas” s/n, Jaén, Spain
- * E-mail: (JMG); (JM)
| | | | - Juan J. Pérez González
- Department of Chemical Engineering, Universitat Politecnica de Catalunya, Barcelona, Spain
| | - Stefano Bosisio
- EaStCHEM School of Chemistry, Joseph Black Building, Edinburgh, United Kingdom
| | - Jaime Rubio-Martinez
- Departament de Química Física, Universitat de Barcelona (UB) and the Institut de Recerca en Quimica Teorica i Computacional (IQTCUB), Martí i Franqués 1, Barcelona, Spain
| | - Julien Michel
- EaStCHEM School of Chemistry, Joseph Black Building, Edinburgh, United Kingdom
- * E-mail: (JMG); (JM)
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9
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Türková A, Zdrazil B. Current Advances in Studying Clinically Relevant Transporters of the Solute Carrier (SLC) Family by Connecting Computational Modeling and Data Science. Comput Struct Biotechnol J 2019; 17:390-405. [PMID: 30976382 PMCID: PMC6438991 DOI: 10.1016/j.csbj.2019.03.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 02/28/2019] [Accepted: 03/01/2019] [Indexed: 01/18/2023] Open
Abstract
Organic anion and cation transporting proteins (OATs, OATPs, and OCTs), as well as the Multidrug and Toxin Extrusion (MATE) transporters of the Solute Carrier (SLC) family are playing a pivotal role in the discovery and development of new drugs due to their involvement in drug disposition, drug-drug interactions, adverse drug effects and related toxicity. Computational methods to understand and predict clinically relevant transporter interactions can provide useful guidance at early stages in drug discovery and design, especially if they include contemporary data science approaches. In this review, we summarize the current state-of-the-art of computational approaches for exploring ligand interactions and selectivity for these drug (uptake) transporters. The computational methods discussed here by highlighting interesting examples from the current literature are ranging from semiautomatic data mining and integration, to ligand-based methods (such as quantitative structure-activity relationships, and combinatorial pharmacophore modeling), and finally structure-based methods (such as comparative modeling, molecular docking, and molecular dynamics simulations). We are focusing on promising computational techniques such as fold-recognition methods, proteochemometric modeling or techniques for enhanced sampling of protein conformations used in the context of these ADMET-relevant SLC transporters with a special focus on methods useful for studying ligand selectivity.
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Affiliation(s)
- Alžběta Türková
- Department of Pharmaceutical Chemistry, Divison of Drug Design and Medicinal Chemistry, University of Vienna, Althanstraße 14, A-1090 Vienna, Austria
| | - Barbara Zdrazil
- Department of Pharmaceutical Chemistry, Divison of Drug Design and Medicinal Chemistry, University of Vienna, Althanstraße 14, A-1090 Vienna, Austria
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10
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Lam PCH, Abagyan R, Totrov M. Hybrid receptor structure/ligand-based docking and activity prediction in ICM: development and evaluation in D3R Grand Challenge 3. J Comput Aided Mol Des 2018; 33:35-46. [PMID: 30094533 DOI: 10.1007/s10822-018-0139-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Accepted: 07/23/2018] [Indexed: 12/11/2022]
Abstract
In context of D3R Grand Challenge 3 we have investigated several ligand activity prediction protocols that combined elements of a physics-based energy function (ICM VLS score) and the knowledge-based Atomic Property Field 3D QSAR approach. Activity prediction models utilized poses produced by ICM-Dock with ligand bias and 4D receptor conformational ensembles (LigBEnD). Hybrid APF/P (APF/Physics) models were superior to pure physics- or knowledge-based models in our preliminary tests using rigorous three-fold clustered cross-validation and later proved successful in the blind prediction for D3R GC3 sets, consistently performing well across four different targets. The results demonstrate that knowledge-based and physics-based inputs into the machine-learning activity model can be non-redundant and synergistic.
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Affiliation(s)
- Polo C-H Lam
- Molsoft L.L.C., 11199 Sorrento Valley Road, S209, San Diego, CA, 92121, USA
| | - Ruben Abagyan
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
| | - Maxim Totrov
- Molsoft L.L.C., 11199 Sorrento Valley Road, S209, San Diego, CA, 92121, USA.
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11
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Wingert BM, Camacho CJ. Improving small molecule virtual screening strategies for the next generation of therapeutics. Curr Opin Chem Biol 2018; 44:87-92. [PMID: 29920436 DOI: 10.1016/j.cbpa.2018.06.006] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2018] [Revised: 04/27/2018] [Accepted: 06/04/2018] [Indexed: 01/05/2023]
Abstract
The new generation of post-genomic targets, such as protein-protein interactions (PPIs), often require new chemotypes not well represented in current compound libraries. This is one reason for why traditional high throughput screening (HTS) approaches are not more successful in delivering medicinal chemistry starting points for PPIs. In silico screening methods of an expanded chemical space are then potential alternatives for developing novel chemical probes to modulate PPIs. In this review, we report on the state-of-the-art pipelines for virtual screening, emphasizing prospectively validated methods capable of addressing the challenge of drugging difficult targets in the human interactome. Collectively, we show that optimal strategies for structure based virtual screening vary depending on receptor structure and degree of flexibility.
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Affiliation(s)
- Bentley M Wingert
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Carlos J Camacho
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA.
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12
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Deng N, Wickstrom L, Cieplak P, Lin C, Yang D. Resolving the Ligand-Binding Specificity in c-MYC G-Quadruplex DNA: Absolute Binding Free Energy Calculations and SPR Experiment. J Phys Chem B 2017; 121:10484-10497. [PMID: 29086571 DOI: 10.1021/acs.jpcb.7b09406] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
We report the absolute binding free energy calculation and surface plasmon resonance (SPR) experiment for ligand binding with the c-MYC G-quadruplex DNA. The unimolecular parallel DNA G-quadruplex formed in nuclease hypersensitivity element III1 of the c-MYC gene promoter regulates the c-MYC transcription and is recognized as an emerging drug target for cancer therapy. Quindoline derivatives have been shown to stabilize the G-quadruplex and inhibit the c-MYC expression in cancer cells. NMR revealed two binding sites located at the 5' and 3' termini of the G-quadruplex. Questions about which site is more favored and the basis for the ligand-induced binding site formation remain unresolved. Here, we employ two absolute binding free energy methods, the double decoupling and the potential of mean force methods, to dissect the ligand-binding specificity in the c-MYC G-quadruplex. The calculated absolute binding free energies are in general agreement with the SPR result and suggest that quindoline has a slight preference for the 5' site. The flanking residues around the two sites undergo significant reorganization as the ligand unbinds, which provides evidence for ligand-induced binding pocket formation. The results help interpret experimental data and inform rational design of small molecules targeting the c-MYC G-quadruplex.
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Affiliation(s)
- Nanjie Deng
- Department of Chemistry and Physical Sciences, Pace University , 1 Pace Plaza, New York, New York 10038, United States
| | - Lauren Wickstrom
- Department of Science, Borough of Manhattan Community College, the City University of New York , New York, New York 10007, United States
| | - Piotr Cieplak
- Sanford Burnham Prebys Medical Discovery Institute , La Jolla, San Diego, California 92037, United States
| | - Clement Lin
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University , West Lafayette, Indiana 47907, United States
| | - Danzhou Yang
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University , West Lafayette, Indiana 47907, United States
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Optimal affinity ranking for automated virtual screening validated in prospective D3R grand challenges. J Comput Aided Mol Des 2017; 32:287-297. [PMID: 28918599 DOI: 10.1007/s10822-017-0065-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Accepted: 09/08/2017] [Indexed: 10/18/2022]
Abstract
The goal of virtual screening is to generate a substantially reduced and enriched subset of compounds from a large virtual chemistry space. Critical in these efforts are methods to properly rank the binding affinity of compounds. Prospective evaluations of ranking strategies in the D3R grand challenges show that for targets with deep pockets the best correlations (Spearman ρ ~ 0.5) were obtained by our submissions that docked compounds to the holo-receptors with the most chemically similar ligand. On the other hand, for targets with open pockets using multiple receptor structures is not a good strategy. Instead, docking to a single optimal receptor led to the best correlations (Spearman ρ ~ 0.5), and overall performs better than any other method. Yet, choosing a suboptimal receptor for crossdocking can significantly undermine the affinity rankings. Our submissions that evaluated the free energy of congeneric compounds were also among the best in the community experiment. Error bars of around 1 kcal/mol are still too large to significantly improve the overall rankings. Collectively, our top of the line predictions show that automated virtual screening with rigid receptors perform better than flexible docking and other more complex methods.
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Kadukova M, Grudinin S. Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2. J Comput Aided Mol Des 2017; 32:151-162. [DOI: 10.1007/s10822-017-0062-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 09/08/2017] [Indexed: 10/18/2022]
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