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Botha MJ, Kirton SB. In Silico Investigations into the Selectivity of Psychoactive and New Psychoactive Substances in Monoamine Transporters. ACS OMEGA 2022; 7:38311-38321. [PMID: 36340072 PMCID: PMC9631908 DOI: 10.1021/acsomega.2c02714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 10/07/2022] [Indexed: 06/16/2023]
Abstract
New psychoactive substances (NPS) are a group of compounds that mimic the effects of illicit substances. A range of NPS have been shown to interact with the three main classes of monoamine transporters (DAT, NET, and SERT) to differing extents, but it is unclear why these differences arise. To aid in understanding the differences in affinity between the classes of monoamine transporters, several in silico experiments were conducted. Docking experiments showed there was no direct correlation between a range of scoring functions and experimental activity, but Spearman ranking analysis showed a significant correlation (α = 0.1) for DAT, with the affinity ΔG (0.42), αHB (0.40), GoldScore (0.40), and PLP (0.41) scoring functions, and for DAT (0.38) and SERT (0.40) using a consensus scoring approach. Qualitative structure-activity relationship (QSAR) experiments resulted in the generation of robust and predictive three-descriptor models for SERT (r 2 = 0.87, q 2 = 0.8, and test set r 2 = 0.74) and DAT (r 2 = 0.68, q 2 = 0.51, test set r 2 = 0.63). Both QSAR models described similar characteristics for binding, i.e., rigid hydrophobic molecules with a biogenic amine moiety, and were not sufficient to facilitate a deeper understanding of differences in affinity between the monoamine transporters. This contextualizes the observed promiscuity for NPS between the isoforms and highlights the difficulty in the design and development of compounds that are isoform-selective.
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Dos Santos Maia M, Soares Rodrigues GC, Silva Cavalcanti AB, Scotti L, Scotti MT. Consensus Analyses in Molecular Docking Studies Applied to Medicinal Chemistry. Mini Rev Med Chem 2020; 20:1322-1340. [PMID: 32013847 DOI: 10.2174/1389557520666200204121129] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 10/31/2019] [Accepted: 11/04/2019] [Indexed: 02/08/2023]
Abstract
The increasing number of computational studies in medicinal chemistry involving molecular docking has put the technique forward as promising in Computer-Aided Drug Design. Considering the main method in the virtual screening based on the structure, consensus analysis of docking has been applied in several studies to overcome limitations of algorithms of different programs and mainly to increase the reliability of the results and reduce the number of false positives. However, some consensus scoring strategies are difficult to apply and, in some cases, are not reliable due to the small number of datasets tested. Thus, for such a methodology to be successful, it is necessary to understand why, when and how to use consensus docking. Therefore, the present study aims to present different approaches to docking consensus, applications, and several scoring strategies that have been successful and can be applied in future studies.
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Affiliation(s)
- Mayara Dos Santos Maia
- Program of Natural and Synthetic Bioactive Products (PgPNSB), Health Sciences Center, Federal University of Paraiba, Joao Pessoa-PB, Brazil
| | - Gabriela Cristina Soares Rodrigues
- Program of Natural and Synthetic Bioactive Products (PgPNSB), Health Sciences Center, Federal University of Paraiba, Joao Pessoa-PB, Brazil
| | - Andreza Barbosa Silva Cavalcanti
- Program of Natural and Synthetic Bioactive Products (PgPNSB), Health Sciences Center, Federal University of Paraiba, Joao Pessoa-PB, Brazil
| | - Luciana Scotti
- Program of Natural and Synthetic Bioactive Products (PgPNSB), Health Sciences Center, Federal University of Paraiba, Joao Pessoa-PB, Brazil
| | - Marcus Tullius Scotti
- Program of Natural and Synthetic Bioactive Products (PgPNSB), Health Sciences Center, Federal University of Paraiba, Joao Pessoa-PB, Brazil
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Comparison of the umbrella sampling and the double decoupling method in binding free energy predictions for SAMPL6 octa-acid host-guest challenges. J Comput Aided Mol Des 2018; 32:1075-1086. [PMID: 30324304 DOI: 10.1007/s10822-018-0166-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 09/21/2018] [Indexed: 12/14/2022]
Abstract
We calculate the absolute binding free energies of tetra-methylated octa-acids host-guest systems as a part of the SAMPL6 blind challenge (receipt ID vq30p). We employed two different free energy simulation methods, i.e., the umbrella sampling (US) and double decoupling method (DDM). The US method was used with the weighted histogram analysis method (WHAM) (US-WHAM scheme). In the DDM scheme, Hamiltonian replica-exchange method (HREM) was combined with the Bennett acceptance ratio (BAR) (HREM-BAR scheme). We obtained initial binding poses via molecular docking using GalaxyDock-HG program, which is developed for the SAMPL challenge. The root mean square deviation (RMSD) and the mean absolute deviations (MAD) using US-WHAM scheme were 1.33 and 1.02 kcal/mol, respectively. The MAD was the top among all submissions, however the correlation with respect to experiment was unexceptional. While the RMSD and MAD via HREM-BAR scheme were greater than US-WHAM scheme, (i.e., 2.09 and 1.76 kcal/mol), their correlations were slightly better than US-WHAM. The correlation between the two methods was high. Further discussion on the DDM method can be found in a companion paper by Han et al. (receipt ID 3z83m) in the same issue.
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Ren X, Shi YS, Zhang Y, Liu B, Zhang LH, Peng YB, Zeng R. Novel Consensus Docking Strategy to Improve Ligand Pose Prediction. J Chem Inf Model 2018; 58:1662-1668. [PMID: 30044626 DOI: 10.1021/acs.jcim.8b00329] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Molecular docking, which mainly includes pose prediction and binding affinity calculation, has become an important tool for assisting structure-based drug design. Correctly predicting the ligand binding pose to a protein target enables the estimation of binding free energy using various tools. Previous studies have shown that the consensus method can be used to improve the docking performance with respect to compound scoring and pose prediction. In this report, a novel consensus docking strategy was proposed, which uses a dynamic benchmark data set selection to determine the best program combinations to improve the docking success rate. Using the complexes from PDBbind as a benchmark data set, a 4.9% enhancement in success rate was achieved compared with the best program.
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Affiliation(s)
- Xiaodong Ren
- Department of Pharmacy , Guizhou Provincial People's Hospital , Guiyang 550002 , P.R. China
| | - Yu-Sheng Shi
- Key Laboratory of Biotechnology and Bioresources Utilization, Educational of Minister, College of Life Science , Dalian Nationalities University , Dalian 116600 , P.R. China
| | - Yan Zhang
- Jiamusi College , Heilongjiang University of Chinese Medicine , Jiamusi 154007 , P.R. China
| | - Bin Liu
- Jiamusi College , Heilongjiang University of Chinese Medicine , Jiamusi 154007 , P.R. China
| | - Li-Hong Zhang
- Jiamusi College , Heilongjiang University of Chinese Medicine , Jiamusi 154007 , P.R. China
| | - Yu-Bo Peng
- Jiamusi College , Heilongjiang University of Chinese Medicine , Jiamusi 154007 , P.R. China
| | - Rui Zeng
- College of Pharmacy , Southwest University for Nationalities , Chengdu 610041 , P.R. China
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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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Tofoleanu F, Lee J, Pickard Iv FC, König G, Huang J, Baek M, Seok C, Brooks BR. Absolute binding free energies for octa-acids and guests in SAMPL5 : Evaluating binding free energies for octa-acid and guest complexes in the SAMPL5 blind challenge. J Comput Aided Mol Des 2017; 31:107-118. [PMID: 27696242 PMCID: PMC6472255 DOI: 10.1007/s10822-016-9965-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Accepted: 09/02/2016] [Indexed: 02/07/2023]
Abstract
As part of the SAMPL5 blind prediction challenge, we calculate the absolute binding free energies of six guest molecules to an octa-acid (OAH) and to a methylated octa-acid (OAMe). We use the double decoupling method via thermodynamic integration (TI) or Hamiltonian replica exchange in connection with the Bennett acceptance ratio (HREM-BAR). We produce the binding poses either through manual docking or by using GalaxyDock-HG, a docking software developed specifically for this study. The root mean square deviations for our most accurate predictions are 1.4 kcal mol-1 for OAH with TI and 1.9 kcal mol-1 for OAMe with HREM-BAR. Our best results for OAMe were obtained for systems with ionic concentrations corresponding to the ionic strength of the experimental solution. The most problematic system contains a halogenated guest. Our attempt to model the σ-hole of the bromine using a constrained off-site point charge, does not improve results. We use results from molecular dynamics simulations to argue that the distinct binding affinities of this guest to OAH and OAMe are due to a difference in the flexibility of the host. We believe that the results of this extensive analysis of host-guest complexes will help improve the protocol used in predicting binding affinities for larger systems, such as protein-substrate compounds.
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Affiliation(s)
- Florentina Tofoleanu
- Laboratory of Computational Biology, National Institutes of Health - National Heart, Lung, and Blood Institute, 5635 Fishers Lane, T-900 Suite, Rockville, MD, 20852, USA.
| | - Juyong Lee
- Laboratory of Computational Biology, National Institutes of Health - National Heart, Lung, and Blood Institute, 5635 Fishers Lane, T-900 Suite, Rockville, MD, 20852, USA
| | - Frank C Pickard Iv
- Laboratory of Computational Biology, National Institutes of Health - National Heart, Lung, and Blood Institute, 5635 Fishers Lane, T-900 Suite, Rockville, MD, 20852, USA
| | - Gerhard König
- Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr, Germany
| | - Jing Huang
- Laboratory of Computational Biology, National Institutes of Health - National Heart, Lung, and Blood Institute, 5635 Fishers Lane, T-900 Suite, Rockville, MD, 20852, USA
- Department of Pharmaceutical Science, School of Pharmacy, University of Maryland, 20 Penn Street, Baltimore, MD 21201, USA
| | - Minkyung Baek
- Department of Chemistry, Seoul National University, Seoul, 08826, Republic of Korea
| | - Chaok Seok
- Department of Chemistry, Seoul National University, Seoul, 08826, Republic of Korea
| | - Bernard R Brooks
- Laboratory of Computational Biology, National Institutes of Health - National Heart, Lung, and Blood Institute, 5635 Fishers Lane, T-900 Suite, Rockville, MD, 20852, USA
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Absolute binding free energy calculations of CBClip host-guest systems in the SAMPL5 blind challenge. J Comput Aided Mol Des 2016; 31:71-85. [PMID: 27677749 DOI: 10.1007/s10822-016-9968-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2016] [Accepted: 09/08/2016] [Indexed: 12/11/2022]
Abstract
Herein, we report the absolute binding free energy calculations of CBClip complexes in the SAMPL5 blind challenge. Initial conformations of CBClip complexes were obtained using docking and molecular dynamics simulations. Free energy calculations were performed using thermodynamic integration (TI) with soft-core potentials and Bennett's acceptance ratio (BAR) method based on a serial insertion scheme. We compared the results obtained with TI simulations with soft-core potentials and Hamiltonian replica exchange simulations with the serial insertion method combined with the BAR method. The results show that the difference between the two methods can be mainly attributed to the van der Waals free energies, suggesting that either the simulations used for TI or the simulations used for BAR, or both are not fully converged and the two sets of simulations may have sampled difference phase space regions. The penalty scores of force field parameters of the 10 guest molecules provided by CHARMM Generalized Force Field can be an indicator of the accuracy of binding free energy calculations. Among our submissions, the combination of docking and TI performed best, which yielded the root mean square deviation of 2.94 kcal/mol and an average unsigned error of 3.41 kcal/mol for the ten guest molecules. These values were best overall among all participants. However, our submissions had little correlation with experiments.
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Carlson HA, Smith RD, Damm-Ganamet KL, Stuckey JA, Ahmed A, Convery MA, Somers DO, Kranz M, Elkins PA, Cui G, Peishoff CE, Lambert MH, Dunbar JB. CSAR 2014: A Benchmark Exercise Using Unpublished Data from Pharma. J Chem Inf Model 2016; 56:1063-77. [PMID: 27149958 DOI: 10.1021/acs.jcim.5b00523] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The 2014 CSAR Benchmark Exercise was the last community-wide exercise that was conducted by the group at the University of Michigan, Ann Arbor. For this event, GlaxoSmithKline (GSK) donated unpublished crystal structures and affinity data from in-house projects. Three targets were used: tRNA (m1G37) methyltransferase (TrmD), Spleen Tyrosine Kinase (SYK), and Factor Xa (FXa). A particularly strong feature of the GSK data is its large size, which lends greater statistical significance to comparisons between different methods. In Phase 1 of the CSAR 2014 Exercise, participants were given several protein-ligand complexes and asked to identify the one near-native pose from among 200 decoys provided by CSAR. Though decoys were requested by the community, we found that they complicated our analysis. We could not discern whether poor predictions were failures of the chosen method or an incompatibility between the participant's method and the setup protocol we used. This problem is inherent to decoys, and we strongly advise against their use. In Phase 2, participants had to dock and rank/score a set of small molecules given only the SMILES strings of the ligands and a protein structure with a different ligand bound. Overall, docking was a success for most participants, much better in Phase 2 than in Phase 1. However, scoring was a greater challenge. No particular approach to docking and scoring had an edge, and successful methods included empirical, knowledge-based, machine-learning, shape-fitting, and even those with solvation and entropy terms. Several groups were successful in ranking TrmD and/or SYK, but ranking FXa ligands was intractable for all participants. Methods that were able to dock well across all submitted systems include MDock,1 Glide-XP,2 PLANTS,3 Wilma,4 Gold,5 SMINA,6 Glide-XP2/PELE,7 FlexX,8 and MedusaDock.9 In fact, the submission based on Glide-XP2/PELE7 cross-docked all ligands to many crystal structures, and it was particularly impressive to see success across an ensemble of protein structures for multiple targets. For scoring/ranking, submissions that showed statistically significant achievement include MDock1 using ITScore1,10 with a flexible-ligand term,11 SMINA6 using Autodock-Vina,12,13 FlexX8 using HYDE,14 and Glide-XP2 using XP DockScore2 with and without ROCS15 shape similarity.16 Of course, these results are for only three protein targets, and many more systems need to be investigated to truly identify which approaches are more successful than others. Furthermore, our exercise is not a competition.
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Affiliation(s)
- Heather A Carlson
- Department of Medicinal Chemistry, College of Pharmacy, University of Michigan , 428 Church St., Ann Arbor, Michigan 48109-1065, United States
| | - Richard D Smith
- Department of Medicinal Chemistry, College of Pharmacy, University of Michigan , 428 Church St., Ann Arbor, Michigan 48109-1065, United States
| | - Kelly L Damm-Ganamet
- Department of Medicinal Chemistry, College of Pharmacy, University of Michigan , 428 Church St., Ann Arbor, Michigan 48109-1065, United States
| | - Jeanne A Stuckey
- Center for Structural Biology, University of Michigan , 3358E Life Sciences Institute, 210 Washtenaw Ave., Ann Arbor, Michigan 48109-2216, United States
| | - Aqeel Ahmed
- Department of Medicinal Chemistry, College of Pharmacy, University of Michigan , 428 Church St., Ann Arbor, Michigan 48109-1065, United States
| | - Maire A Convery
- Computational and Structural Sciences, Medicines Research Centre, GlaxoSmithKline Research & Development , Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, United Kingdom
| | - Donald O Somers
- Computational and Structural Sciences, Medicines Research Centre, GlaxoSmithKline Research & Development , Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, United Kingdom
| | - Michael Kranz
- Computational and Structural Sciences, Medicines Research Centre, GlaxoSmithKline Research & Development , Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, United Kingdom
| | - Patricia A Elkins
- Computational and Structural Sciences, GlaxoSmithKline Research & Development , 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Guanglei Cui
- Computational and Structural Sciences, GlaxoSmithKline Research & Development , 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Catherine E Peishoff
- Computational and Structural Sciences, GlaxoSmithKline Research & Development , 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Millard H Lambert
- Computational and Structural Sciences, GlaxoSmithKline Research & Development , 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - James B Dunbar
- Department of Medicinal Chemistry, College of Pharmacy, University of Michigan , 428 Church St., Ann Arbor, Michigan 48109-1065, United States
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Lee GR, Seok C. Galaxy7TM: flexible GPCR-ligand docking by structure refinement. Nucleic Acids Res 2016; 44:W502-6. [PMID: 27131365 PMCID: PMC4987912 DOI: 10.1093/nar/gkw360] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2016] [Accepted: 04/21/2016] [Indexed: 01/21/2023] Open
Abstract
G-protein-coupled receptors (GPCRs) play important physiological roles related to signal transduction and form a major group of drug targets. Prediction of GPCR-ligand complex structures has therefore important implications to drug discovery. With previously available servers, it was only possible to first predict GPCR structures by homology modeling and then perform ligand docking on the model structures. However, model structures generated without explicit consideration of specific ligands of interest can be inaccurate because GPCR structures can be affected by ligand binding. The Galaxy7TM server, freely accessible at http://galaxy.seoklab.org/7TM, improves an input GPCR structure by simultaneous ligand docking and flexible structure refinement using GALAXY methods. The server shows better performance in both ligand docking and GPCR structure refinement than commonly used programs AutoDock Vina and Rosetta MPrelax, respectively.
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Affiliation(s)
- Gyu Rie Lee
- Department of Chemistry, Seoul National University, Seoul 151-747, Korea
| | - Chaok Seok
- Department of Chemistry, Seoul National University, Seoul 151-747, Korea
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