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Yuan Z, Chen X, Fan S, Chang L, Chu L, Zhang Y, Wang J, Li S, Xie J, Hu J, Miao R, Zhu L, Zhao Z, Li H, Li S. Binding Free Energy Calculation Based on the Fragment Molecular Orbital Method and Its Application in Designing Novel SHP-2 Allosteric Inhibitors. Int J Mol Sci 2024; 25:671. [PMID: 38203841 PMCID: PMC10779950 DOI: 10.3390/ijms25010671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 12/28/2023] [Accepted: 12/29/2023] [Indexed: 01/12/2024] Open
Abstract
The accurate prediction of binding free energy is a major challenge in structure-based drug design. Quantum mechanics (QM)-based approaches show promising potential in predicting ligand-protein binding affinity by accurately describing the behavior and structure of electrons. However, traditional QM calculations face computational limitations, hindering their practical application in drug design. Nevertheless, the fragment molecular orbital (FMO) method has gained widespread application in drug design due to its ability to reduce computational costs and achieve efficient ab initio QM calculations. Although the FMO method has demonstrated its reliability in calculating the gas phase potential energy, the binding of proteins and ligands also involves other contributing energy terms, such as solvent effects, the 'deformation energy' of a ligand's bioactive conformations, and entropy. Particularly in cases involving ionized fragments, the calculation of solvation free energy becomes particularly crucial. We conducted an evaluation of some previously reported implicit solvent methods on the same data set to assess their potential for improving the performance of the FMO method. Herein, we develop a new QM-based binding free energy calculation method called FMOScore, which enhances the performance of the FMO method. The FMOScore method incorporates linear fitting of various terms, including gas-phase potential energy, deformation energy, and solvation free energy. Compared to other widely used traditional prediction methods such as FEP+, MM/PBSA, MM/GBSA, and Autodock vina, FMOScore showed good performance in prediction accuracies. By constructing a retrospective case study, it was observed that incorporating calculations for solvation free energy and deformation energy can further enhance the precision of FMO predictions for binding affinity. Furthermore, using FMOScore-guided lead optimization against Src homology-2-containing protein tyrosine phosphatase 2 (SHP-2), we discovered a novel and potent allosteric SHP-2 inhibitor (compound 8).
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Affiliation(s)
- Zhen Yuan
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Xingyu Chen
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Sisi Fan
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Longfeng Chang
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Linna Chu
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Ying Zhang
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Jie Wang
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Shuang Li
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Jinxin Xie
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Jianguo Hu
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Runyu Miao
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Lili Zhu
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Zhenjiang Zhao
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
| | - Honglin Li
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
- Innovation Center for AI and Drug Discovery, East China Normal University, Shanghai 200062, China
- Lingang Laboratory, Shanghai 200031, China
| | - Shiliang Li
- Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai 200237, China; (Z.Y.); (X.C.); (S.F.); (Z.Z.)
- Innovation Center for AI and Drug Discovery, East China Normal University, Shanghai 200062, China
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2
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Bello M, Bandala C. Evaluating the ability of end-point methods to predict the binding affinity tendency of protein kinase inhibitors. RSC Adv 2023; 13:25118-25128. [PMID: 37614784 PMCID: PMC10443623 DOI: 10.1039/d3ra04916g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 08/14/2023] [Indexed: 08/25/2023] Open
Abstract
Because of the high economic cost of exploring the experimental impact of mutations occurring in kinase proteins, computational approaches have been employed as alternative methods for evaluating the structural and energetic aspects of kinase mutations. Among the main computational methods used to explore the affinity linked to kinase mutations are docking procedures and molecular dynamics (MD) simulations combined with end-point methods or alchemical methods. Although it is known that end-point methods are not able to reproduce experimental binding free energy (ΔG) values, it is also true that they are able to discriminate between a better or a worse ligand through the estimation of ΔG. In this contribution, we selected ten wild-type and mutant cocrystallized EGFR-inhibitor complexes containing experimental binding affinities to evaluate whether MMGBSA or MMPBSA approaches can predict the differences in affinity between the wild type and mutants forming a complex with a similar inhibitor. Our results show that a long MD simulation (the last 50 ns of a 100 ns-long MD simulation) using the MMGBSA method without considering the entropic components reproduced the experimental affinity tendency with a Pearson correlation coefficient of 0.779 and an R2 value of 0.606. On the other hand, the correlation between theoretical and experimental ΔΔG values indicates that the MMGBSA and MMPBSA methods are helpful for obtaining a good correlation using a short rather than a long simulation period.
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Affiliation(s)
- Martiniano Bello
- Laboratorio de Diseño y Desarrollo de Nuevos Fármacos e Innovación Biotecnológica, Escuela Superior de Medicina, Instituto Politécnico Nacional, Plan de San Luis y Diaz Mirón s/n, Col. Casco de Santo Tomas Ciudad de México 11340 Mexico
| | - Cindy Bandala
- Escuela Superior de Medicina, Instituto Politécnico Nacional México City 11340 Mexico
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3
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Akkus E, Tayfuroglu O, Yildiz M, Kocak A. Revisiting MMPBSA by Adoption of MC-Based Surface Area/Volume, ANI-ML Potentials, and Two-Valued Interior Dielectric Constant. J Phys Chem B 2023; 127:4415-4429. [PMID: 37171911 DOI: 10.1021/acs.jpcb.3c00834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Here, we report the accuracy improvements of molecular mechanics Poisson-Boltzmann surface area (MMPBSA) calculations by adoption of ANI-ML potentials in replacement of MM terms, the use of solvent-accessible surface area (SASA) and volume (SAV) values from the Monte Carlo sampling of the probe, and introducing two different interior dielectric constants for electrostatic interactions of protein-ligand (P-L) and polar solvation term in the MMPBSA calculations. Our results show that the Pearson correlation coefficients of MMPBSA-calculated values with respect to experimental binding free energies can be drastically improved from 0.48 to 0.90 by adoption of ANI-ML potentials in replacement of MM energy terms in the equation, referred to as ANI-PBSA. Moreover, we show that the SASA/SAV-combined equation in the scaled particle theory (SPT) can be a better choice to model nonpolar solvation term, reaching nearly the same accuracy by ANI-PBSA calculations. Finally, we introduce two different values of interior dielectric constants, which could be an alternative strategy between the single and variable constant definitions.
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Affiliation(s)
- Ebru Akkus
- Department of Chemistry, Gebze Technical University, 41400 Kocaeli, Turkey
| | - Omer Tayfuroglu
- Department of Chemistry, Gebze Technical University, 41400 Kocaeli, Turkey
| | - Muslum Yildiz
- Department of Molecular Biology and Genetics, Gebze Technical University, 41400 Kocaeli, Turkey
| | - Abdulkadir Kocak
- Department of Chemistry, Gebze Technical University, 41400 Kocaeli, Turkey
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4
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Dutkiewicz Z. Computational methods for calculation of protein-ligand binding affinities in structure-based drug design. PHYSICAL SCIENCES REVIEWS 2022. [DOI: 10.1515/psr-2020-0034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Abstract
Drug design is an expensive and time-consuming process. Any method that allows reducing the time the costs of the drug development project can have great practical value for the pharmaceutical industry. In structure-based drug design, affinity prediction methods are of great importance. The majority of methods used to predict binding free energy in protein-ligand complexes use molecular mechanics methods. However, many limitations of these methods in describing interactions exist. An attempt to go beyond these limits is the application of quantum-mechanical description for all or only part of the analyzed system. However, the extensive use of quantum mechanical (QM) approaches in drug discovery is still a demanding challenge. This chapter briefly reviews selected methods used to calculate protein-ligand binding affinity applied in virtual screening (VS), rescoring of docked poses, and lead optimization stage, including QM methods based on molecular simulations.
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Affiliation(s)
- Zbigniew Dutkiewicz
- Department of Chemical Technology of Drugs , Poznan University of Medical Sciences , ul. Grunwaldzka 6 , 60-780 Poznań , Poznan , 60-780, Poland
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5
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Yu Y, Wang Z, Wang L, Tian S, Hou T, Sun H. Predicting the mutation effects of protein–ligand interactions via end-point binding free energy calculations: strategies and analyses. J Cheminform 2022; 14:56. [PMID: 35987841 PMCID: PMC9392442 DOI: 10.1186/s13321-022-00639-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 08/08/2022] [Indexed: 12/04/2022] Open
Abstract
Protein mutations occur frequently in biological systems, which may impact, for example, the binding of drugs to their targets through impairing the critical H-bonds, changing the hydrophobic interactions, etc. Thus, accurately predicting the effects of mutations on biological systems is of great interests to various fields. Unfortunately, it is still unavailable to conduct large-scale wet-lab mutation experiments because of the unaffordable experimental time and financial costs. Alternatively, in silico computation can serve as a pioneer to guide the experiments. In fact, numerous pioneering works have been conducted from computationally cheaper machine-learning (ML) methods to the more expensive alchemical methods with the purpose to accurately predict the mutation effects. However, these methods usually either cannot result in a physically understandable model (ML-based methods) or work with huge computational resources (alchemical methods). Thus, compromised methods with good physical characteristics and high computational efficiency are expected. Therefore, here, we conducted a comprehensive investigation on the mutation issues of biological systems with the famous end-point binding free energy calculation methods represented by MM/GBSA and MM/PBSA. Different computational strategies considering different length of MD simulations, different value of dielectric constants and whether to incorporate entropy effects to the predicted total binding affinities were investigated to provide a more accurate way for predicting the energetic change upon protein mutations. Overall, our result shows that a relatively long MD simulation (e.g. 100 ns) benefits the prediction accuracy for both MM/GBSA and MM/PBSA (with the best Pearson correlation coefficient between the predicted ∆∆G and the experimental data of ~ 0.44 for a challenging dataset). Further analyses shows that systems involving large perturbations (e.g. multiple mutations and large number of atoms change in the mutation site) are much easier to be accurately predicted since the algorithm works more sensitively to the large change of the systems. Besides, system-specific investigation reveals that conformational adjustment is needed to refine the micro-environment of the manually mutated systems and thus lead one to understand why longer MD simulation is necessary to improve the predicting result. The proposed strategy is expected to be applied in large-scale mutation effects investigation with interpretation.
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6
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Akkus E, Tayfuroglu O, Yildiz M, Kocak A. Accurate Binding Free Energy Method from End-State MD Simulations. J Chem Inf Model 2022; 62:4095-4106. [PMID: 35972783 PMCID: PMC9472276 DOI: 10.1021/acs.jcim.2c00601] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
![]()
Herein, we introduce a new strategy to estimate binding
free energies
using end-state molecular dynamics simulation trajectories. The method
is adopted from linear interaction energy (LIE) and ANI-2x neural
network potentials (machine learning) for the atomic simulation environment
(ASE). It predicts the single-point interaction energies between ligand–protein
and ligand–solvent pairs at the accuracy of the wb97x/6-31G*
level for the conformational space that is sampled by molecular dynamics
(MD) simulations. Our results on 54 protein–ligand complexes
show that the method can be accurate and have a correlation of R = 0.87–0.88 to the experimental binding free energies,
outperforming current end-state methods with reduced computational
cost. The method also allows us to compare BFEs of ligands with different
scaffolds. The code is available free of charge (documentation and
test files) at https://github.com/otayfuroglu/deepQM.
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Affiliation(s)
- Ebru Akkus
- Department of Bioengineering, Gebze Technical University, 41400 Gebze, Kocaeli, Turkey
| | - Omer Tayfuroglu
- Department of Chemistry, Gebze Technical University, 41400 Gebze, Kocaeli, Turkey
| | - Muslum Yildiz
- Department of Molecular Biology and Genetics, Gebze Technical University, 41400 Gebze, Kocaeli, Turkey
| | - Abdulkadir Kocak
- Department of Chemistry, Gebze Technical University, 41400 Gebze, Kocaeli, Turkey
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7
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Gundelach L, Fox T, Tautermann CS, Skylaris CK. Protein–ligand free energies of binding from full-protein DFT calculations: convergence and choice of exchange–correlation functional. Phys Chem Chem Phys 2021; 23:9381-9393. [DOI: 10.1039/d1cp00206f] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Quantum mechanical binding free energies based on thousands of full-protein DFT calculations are tractable, reproducible and converge well.
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Affiliation(s)
- Lennart Gundelach
- University of Southampton Faculty of Engineering Science and Mathematics, Chemistry
- University Road
- Southampton
- UK
| | - Thomas Fox
- Boehringer Ingelheim Pharma GmbH & Co KG
- Medicinal Chemistry
- 88397 Biberach an der Riss
- Germany
| | | | - Chris-Kriton Skylaris
- University of Southampton Faculty of Engineering Science and Mathematics, Chemistry
- University Road
- Southampton
- UK
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8
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Pecina A, Eyrilmez SM, Köprülüoğlu C, Miriyala VM, Lepšík M, Fanfrlík J, Řezáč J, Hobza P. SQM/COSMO Scoring Function: Reliable Quantum-Mechanical Tool for Sampling and Ranking in Structure-Based Drug Design. Chempluschem 2020; 85:2362-2371. [PMID: 32609421 DOI: 10.1002/cplu.202000120] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 05/27/2020] [Indexed: 12/17/2022]
Abstract
Quantum mechanical (QM) methods have been gaining importance in structure-based drug design where a reliable description of protein-ligand interactions is of utmost significance. However, strategies i. e. QM/MM, fragmentation or semiempirical (SQM) methods had to be pursued to overcome the unfavorable scaling of QM methods. Various SQM-based approaches have significantly contributed to the accuracy of docking and improvement of lead compounds. Parametrizations of SQM and implicit solvent methods in our laboratory have been instrumental to obtain a reliable SQM-based scoring function. The experience gained in its application for activity ranking of ligands binding to tens of protein targets resulted in setting up a faster SQM/COSMO scoring approach, which outperforms standard scoring methods in native pose identification for two dozen protein targets with ten thousand poses. Recently, SQM/COSMO was effectively applied in a proof-of-concept study of enrichment in virtual screening. Due to its superior performance, feasibility and chemical generality, we propose the SQM/COSMO approach as an efficient tool in structure-based drug design.
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Affiliation(s)
- Adam Pecina
- Institute of Organic Chemistry, and Biochemistry of Czech Academy of Sciences, Flemingovo namesti 2, 166 10, Prague, Czech Republic
| | - Saltuk M Eyrilmez
- Institute of Organic Chemistry, and Biochemistry of Czech Academy of Sciences, Flemingovo namesti 2, 166 10, Prague, Czech Republic.,Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Palacky University, 771 46, Olomouc, Czech Republic
| | - Cemal Köprülüoğlu
- Institute of Organic Chemistry, and Biochemistry of Czech Academy of Sciences, Flemingovo namesti 2, 166 10, Prague, Czech Republic.,Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Palacky University, 771 46, Olomouc, Czech Republic
| | - Vijay Madhav Miriyala
- Institute of Organic Chemistry, and Biochemistry of Czech Academy of Sciences, Flemingovo namesti 2, 166 10, Prague, Czech Republic
| | - Martin Lepšík
- Institute of Organic Chemistry, and Biochemistry of Czech Academy of Sciences, Flemingovo namesti 2, 166 10, Prague, Czech Republic
| | - Jindřich Fanfrlík
- Institute of Organic Chemistry, and Biochemistry of Czech Academy of Sciences, Flemingovo namesti 2, 166 10, Prague, Czech Republic
| | - Jan Řezáč
- Institute of Organic Chemistry, and Biochemistry of Czech Academy of Sciences, Flemingovo namesti 2, 166 10, Prague, Czech Republic
| | - Pavel Hobza
- Institute of Organic Chemistry, and Biochemistry of Czech Academy of Sciences, Flemingovo namesti 2, 166 10, Prague, Czech Republic.,Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Palacky University, 771 46, Olomouc, Czech Republic
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9
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Huang K, Luo S, Cong Y, Zhong S, Zhang JZH, Duan L. An accurate free energy estimator: based on MM/PBSA combined with interaction entropy for protein-ligand binding affinity. NANOSCALE 2020; 12:10737-10750. [PMID: 32388542 DOI: 10.1039/c9nr10638c] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
The molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) method is constantly used to calculate the binding free energy of protein-ligand complexes, and has been shown to effectively balance computational cost against accuracy. The relative binding affinities obtained by the MM/PBSA approach are acceptable, while it usually overestimates the absolute binding free energy. This paper proposes four free energy estimators based on the MM/PBSA for enthalpy change combined with interaction entropy (IE) for entropy change using different weights for individual energy terms. The ΔGPBSA_IE method is determined to be an optimal estimator based on its performance in terms of the correlation between experimental and theoretical values and error estimations. This approach is optimized using high-quality experimental values from a training set containing 84 protein-ligand systems, and the coefficients for the sum of electrostatic energy and polar solvation free energy, van der Waals (vdW) energy, non-polar solvation energy and entropy change are obtained by multivariate linear fitting to the corresponding experimental values. A comparison between the traditional MM/PBSA method and this method shows that the correlation coefficient is improved from 0.46 to 0.72 and the slope of the regression line increases from 0.10 to 1.00. More importantly, the mean absolute error (MAE) is significantly reduced from 22.52 to 1.59 kcal mol-1. Furthermore, the numerical stability of this method is validated on a test set with a similar correlation coefficient, slope and MAE to those of the training set. Based on the above advantages, the ΔGPBSA_IE method can be a powerful tool for a reliable and accurate estimation of binding free energy and plays a significant role in a detailed energetic investigation of protein-ligand interaction.
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Affiliation(s)
- Kaifang Huang
- School of Physics and Electronics, Shandong Normal University, Jinan, 250014, China.
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10
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QM Implementation in Drug Design: Does It Really Help? Methods Mol Biol 2020. [PMID: 32016884 DOI: 10.1007/978-1-0716-0282-9_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/13/2023]
Abstract
Computational chemistry allows one to characterize the structure, dynamics, and energetics of protein-ligand interactions, which makes it a valuable tool in drug discovery in both academic research and pharmaceutical industry. Molecular mechanics (MM)-based approaches are widely utilized to assist the discovery of new drug candidates. However, the complexity of protein-ligand interactions challenges the accuracy and efficiency of the commonly used empirical methods. Aiming to provide better accuracy in the description of protein-ligand interactions, quantum mechanics (QM)-based approaches are becoming increasingly explored. In principle, QM calculation includes all contributions to the energy, accounting for terms usually missing in empirical force fields, and provides a greater degree of transferability. The usefulness of QM in drug design cannot be overemphasized. In this chapter, we present recent developments and applications of fragment-based QM method in studying the protein-ligand and protein-protein interactions. We critically discuss the performance of the fragment-based QM method at different ab initio levels while trying to answer a critical question: do QM-based methods really help in drug design?
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11
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Abstract
This chapter describes the current status of development of the fragment molecular orbital (FMO) method for analyzing the electronic state and intermolecular interactions of biomolecular systems in solvent. The orbital energies and the inter-fragment interaction energies (IFIEs) for a specific molecular structure can be obtained directly by performing FMO calculations by exposing water molecules and counterions around biomolecular systems. Then, it is necessary to pay attention to the thickness of the water shell surrounding the biomolecules. The single-point calculation for snapshots from MD trajectory does not incorporate the effects of temperature and configurational fluctuation, but the SCIFIE (statistically corrected IFIE) method is proposed as a many-body correlated method that partially compensates for this deficiency. Furthermore, implicit continuous dielectric models have been developed as effective approaches to incorporating the screening effect of the solvent in thermal equilibrium, and we illustrate their usefulness for theoretical evaluation of IFIEs and ligand-binding free energy on the basis of the FMO-PBSA (Poisson-Boltzmann surface area) method and other computational methods.
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12
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Fedorov DG. Solvent Screening in Zwitterions Analyzed with the Fragment Molecular Orbital Method. J Chem Theory Comput 2019; 15:5404-5416. [PMID: 31461277 DOI: 10.1021/acs.jctc.9b00715] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Based on induced solvent charges, a new model of solvent screening is developed in the framework of the fragment molecular orbital combined with the polarizable continuum model. The developed model is applied to analyze interactions in a prototypical zwitterionic system, sodium chloride in water, and it is shown that the large underestimation of the interaction in the original solvent screening based on local charges is successfully corrected. The model is also applied to a complex of the Trp-cage (PDB: 1L2Y ) miniprotein with an anionic ligand, and the physical factors determined protein-ligand binding in solution are unraveled.
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Affiliation(s)
- Dmitri G Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat) , National Institute of Advanced Industrial Science and Technology (AIST) , Central 2, Umezono 1-1-1 , Tsukuba 305-8568 , Japan
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13
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Fedorov DG, Brekhov A, Mironov V, Alexeev Y. Molecular Electrostatic Potential and Electron Density of Large Systems in Solution Computed with the Fragment Molecular Orbital Method. J Phys Chem A 2019; 123:6281-6290. [DOI: 10.1021/acs.jpca.9b04936] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Dmitri G. Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba, 305-8568, Japan
| | - Anton Brekhov
- Department of Chemistry, Lomonosov Moscow State University, Moscow, 119991, Russian Federation
| | - Vladimir Mironov
- Department of Chemistry, Lomonosov Moscow State University, Moscow, 119991, Russian Federation
| | - Yuri Alexeev
- Argonne Leadership Computing Facility and Computational Science Division, Argonne National Laboratory, Argonne, Illinois, 60439, United States
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14
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Wang E, Sun H, Wang J, Wang Z, Liu H, Zhang JZH, Hou T. End-Point Binding Free Energy Calculation with MM/PBSA and MM/GBSA: Strategies and Applications in Drug Design. Chem Rev 2019; 119:9478-9508. [DOI: 10.1021/acs.chemrev.9b00055] [Citation(s) in RCA: 578] [Impact Index Per Article: 115.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Ercheng Wang
- Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Huiyong Sun
- Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Junmei Wang
- Department of Pharmaceutical Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Zhe Wang
- Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Hui Liu
- Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - John Z. H. Zhang
- Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China
- NYU−ECNU Center for Computational Chemistry, NYU Shanghai, Shanghai 200122, China
- Department of Chemistry, New York University, New York, New York 10003, United States
- Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006, China
| | - Tingjun Hou
- Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
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15
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Shao D, Tapio K, Auer S, Toppari JJ, Hytönen VP, Ahlskog M. Surface Characteristics Control the Attachment and Functionality of (Chimeric) Avidin. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2018; 34:15335-15342. [PMID: 30398878 DOI: 10.1021/acs.langmuir.8b02855] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The physical adsorption (physisorption) of proteins to surfaces is an important but incompletely understood factor in many biological processes and is of increasing significance in bionanotechnology as well. Avidin is an important protein because of strong avidin-biotin binding, which has been exploited in numerous applications. We have undertaken thorough experimentation on the physisorption of avidin, to chemically different flat surfaces of Si and graphite and also to the curved version of the latter, on multiwalled carbon nanotubes (MWNTs) of different diameters. The difference in the behavior of avidin on Si versus graphite is drastic; on Si, avidin deposits as single globular tetrameric units and maintains functionality, whereas on graphite, it forms irregular networks of two-layer thick filaments, where the first layer has lost its biological activity. On MWNTs, avidin also deposits as one-dimensional formations, or stripes, but these appear to order in a perpendicular arrangement to the MWNT axis. A better understanding of protein-surface interactions is essential for the development of robust and reliable methods for biofunctionalization of materials. This work also provides insights into the importance of the nanoscale surface architecture.
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Affiliation(s)
- Dongkai Shao
- Nanoscience Center, Department of Physics , University of Jyväskylä , Jyväskylä FI-40014 , Finland
| | - Kosti Tapio
- Nanoscience Center, Department of Physics , University of Jyväskylä , Jyväskylä FI-40014 , Finland
| | - Sanna Auer
- Faculty of Medicine and Life Sciences and BioMediTech , University of Tampere , and Fimlab Laboratories, Tampere FI-33520 , Finland
| | - J Jussi Toppari
- Nanoscience Center, Department of Physics , University of Jyväskylä , Jyväskylä FI-40014 , Finland
| | - Vesa P Hytönen
- Faculty of Medicine and Life Sciences and BioMediTech , University of Tampere , and Fimlab Laboratories, Tampere FI-33520 , Finland
| | - Markus Ahlskog
- Nanoscience Center, Department of Physics , University of Jyväskylä , Jyväskylä FI-40014 , Finland
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16
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Thapa B, Beckett D, Erickson J, Raghavachari K. Theoretical Study of Protein–Ligand Interactions Using the Molecules-in-Molecules Fragmentation-Based Method. J Chem Theory Comput 2018; 14:5143-5155. [DOI: 10.1021/acs.jctc.8b00531] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Affiliation(s)
- Bishnu Thapa
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
| | - Daniel Beckett
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
| | - Jon Erickson
- Lilly Research Laboratories, Eli Lilly & Co., Indianapolis, Indiana 47285, United States
| | - Krishnan Raghavachari
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
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17
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Fedorov DG. Analysis of solute-solvent interactions using the solvation model density combined with the fragment molecular orbital method. Chem Phys Lett 2018. [DOI: 10.1016/j.cplett.2018.05.002] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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18
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Okimoto N, Otsuka T, Hirano Y, Taiji M. Use of the Multilayer Fragment Molecular Orbital Method to Predict the Rank Order of Protein-Ligand Binding Affinities: A Case Study Using Tankyrase 2 Inhibitors. ACS OMEGA 2018; 3:4475-4485. [PMID: 31458673 PMCID: PMC6641631 DOI: 10.1021/acsomega.8b00175] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2018] [Accepted: 03/23/2018] [Indexed: 06/10/2023]
Abstract
In computational drug discovery, ranking a series of compound analogues in the order that is consistent with the experimental binding affinities remains a challenge. Many of the computational methods available for evaluating binding affinities have adopted molecular mechanics (MM)-based force fields, although they cannot completely describe protein-ligand interactions. By contrast, quantum mechanics (QM) calculations play an important role in understanding the protein-ligand interactions; however, their huge computational costs hinder their application in drug discovery. In this study, we have evaluated the ability to rank the binding affinities of tankyrase 2 ligands by combining both MM and QM calculations. Our computational approach uses the protein-ligand binding energies obtained from a cost-effective multilayer fragment molecular orbital (MFMO) method combined with the solvation energy obtained from the MM-Poisson-Boltzmann/surface area (MM-PB/SA) method to predict the binding affinity. This approach enabled us to rank tankyrase 2 inhibitor analogues, outperforming several MM-based methods, including rescoring by molecular docking and the MM-PB/SA method alone. Our results show that this computational approach using the MFMO method is a promising tool for predicting the rank order of the binding affinities of inhibitor analogues.
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19
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Ajani H, Jansa J, Köprülüoğlu C, Hobza P, Kryštof V, Lyčka A, Lepsik M. Imidazo[1,2-c
]pyrimidin-5(6H
)-one as a novel core of cyclin-dependent kinase 2 inhibitors: Synthesis, activity measurement, docking, and quantum mechanical scoring. J Mol Recognit 2018; 31:e2720. [DOI: 10.1002/jmr.2720] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 02/26/2018] [Accepted: 03/21/2018] [Indexed: 12/17/2022]
Affiliation(s)
- Haresh Ajani
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences; Prague 6 Czech Republic
- Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry; Palacký University; Olomouc Czech Republic
| | - Josef Jansa
- Research Institute for Organic Syntheses (VUOS); Pardubice-Rybitví Czech Republic
- Department of Organic Chemistry, Faculty of Science; Palacký University; Olomouc Czech Republic
| | - Cemal Köprülüoğlu
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences; Prague 6 Czech Republic
- Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry; Palacký University; Olomouc Czech Republic
| | - Pavel Hobza
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences; Prague 6 Czech Republic
- Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry; Palacký University; Olomouc Czech Republic
| | - Vladimír Kryštof
- Laboratory of Growth Regulators, Centre of the Region Haná for Biotechnological and Agricultural Research, Faculty of Science; Palacký University and Institute of Experimental Botany; Olomouc Czech Republic
| | - Antonín Lyčka
- Research Institute for Organic Syntheses (VUOS); Pardubice-Rybitví Czech Republic
- Faculty of Science; University of Hradec Králové; Hradec Králové Czech Republic
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20
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Nishimoto Y, Fedorov DG. Adaptive frozen orbital treatment for the fragment molecular orbital method combined with density-functional tight-binding. J Chem Phys 2018; 148:064115. [DOI: 10.1063/1.5012935] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Affiliation(s)
- Yoshio Nishimoto
- Fukui Institute for Fundamental Chemistry, Kyoto University, 34-4 Takano Nishihiraki-cho, Sakyo-ku, Kyoto 606-8103, Japan
| | - Dmitri G. Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan
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21
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Lima Neto JX, Soares-Rachetti VP, Albuquerque EL, Manzoni V, Fulco UL. Outlining migrainous through dihydroergotamine–serotonin receptor interactions using quantum biochemistry. NEW J CHEM 2018. [DOI: 10.1039/c7nj03645k] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
We present the electronic structure of the complex dihydroergotamine–serotonin receptor to unveil new medications to treat migraine and related diseases.
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Affiliation(s)
- José X. Lima Neto
- Departamento de Biofísica e Farmacologia
- Universidade Federal do Rio Grande do Norte
- Natal-RN
- Brazil
| | | | | | - Vinicius Manzoni
- Instituto de Física
- Universidade Federal de Alagoas
- Maceio-AL
- Brazil
| | - Umberto L. Fulco
- Departamento de Biofísica e Farmacologia
- Universidade Federal do Rio Grande do Norte
- Natal-RN
- Brazil
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22
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Aldeghi M, Bodkin MJ, Knapp S, Biggin PC. Statistical Analysis on the Performance of Molecular Mechanics Poisson-Boltzmann Surface Area versus Absolute Binding Free Energy Calculations: Bromodomains as a Case Study. J Chem Inf Model 2017; 57:2203-2221. [PMID: 28786670 PMCID: PMC5615372 DOI: 10.1021/acs.jcim.7b00347] [Citation(s) in RCA: 90] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Binding free energy calculations that make use of alchemical pathways are becoming increasingly feasible thanks to advances in hardware and algorithms. Although relative binding free energy (RBFE) calculations are starting to find widespread use, absolute binding free energy (ABFE) calculations are still being explored mainly in academic settings due to the high computational requirements and still uncertain predictive value. However, in some drug design scenarios, RBFE calculations are not applicable and ABFE calculations could provide an alternative. Computationally cheaper end-point calculations in implicit solvent, such as molecular mechanics Poisson-Boltzmann surface area (MMPBSA) calculations, could too be used if one is primarily interested in a relative ranking of affinities. Here, we compare MMPBSA calculations to previously performed absolute alchemical free energy calculations in their ability to correlate with experimental binding free energies for three sets of bromodomain-inhibitor pairs. Different MMPBSA approaches have been considered, including a standard single-trajectory protocol, a protocol that includes a binding entropy estimate, and protocols that take into account the ligand hydration shell. Despite the improvements observed with the latter two MMPBSA approaches, ABFE calculations were found to be overall superior in obtaining correlation with experimental affinities for the test cases considered. A difference in weighted average Pearson ([Formula: see text]) and Spearman ([Formula: see text]) correlations of 0.25 and 0.31 was observed when using a standard single-trajectory MMPBSA setup ([Formula: see text] = 0.64 and [Formula: see text] = 0.66 for ABFE; [Formula: see text] = 0.39 and [Formula: see text] = 0.35 for MMPBSA). The best performing MMPBSA protocols returned weighted average Pearson and Spearman correlations that were about 0.1 inferior to ABFE calculations: [Formula: see text] = 0.55 and [Formula: see text] = 0.56 when including an entropy estimate, and [Formula: see text] = 0.53 and [Formula: see text] = 0.55 when including explicit water molecules. Overall, the study suggests that ABFE calculations are indeed the more accurate approach, yet there is also value in MMPBSA calculations considering the lower compute requirements, and if agreement to experimental affinities in absolute terms is not of interest. Moreover, for the specific protein-ligand systems considered in this study, we find that including an explicit ligand hydration shell or a binding entropy estimate in the MMPBSA calculations resulted in significant performance improvements at a negligible computational cost.
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Affiliation(s)
- Matteo Aldeghi
- Structural Bioinformatics and Computational Biochemistry, Department of Biochemistry, University of Oxford , South Parks Road, Oxford OX1 3QU, United Kingdom
| | - Michael J Bodkin
- Evotec (U.K.) Ltd. , 114 Innovation Drive, Milton Park, Abingdon OX14 4RZ, United Kingdom
| | - Stefan Knapp
- Structural Genomics Consortium, Nuffield Department of Clinical Medicine, University of Oxford , Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, United Kingdom.,Institute for Pharmaceutical Chemistry and Buchmann Institute for Life Sciences, Johann Wolfgang Goethe-University , D-60438 Frankfurt am Main, Germany
| | - Philip C Biggin
- Structural Bioinformatics and Computational Biochemistry, Department of Biochemistry, University of Oxford , South Parks Road, Oxford OX1 3QU, United Kingdom
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23
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Nishimoto Y, Fedorov DG. Three-body expansion of the fragment molecular orbital method combined with density-functional tight-binding. J Comput Chem 2017; 38:406-418. [DOI: 10.1002/jcc.24693] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Revised: 11/14/2016] [Accepted: 11/17/2016] [Indexed: 12/20/2022]
Affiliation(s)
- Yoshio Nishimoto
- Fukui Institute for Fundamental Chemistry, Kyoto University; 34-4 Takano Nishihiraki-cho Sakyo-ku Kyoto 606-8103 Japan
| | - Dmitri G. Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat); National Institute of Advanced Industrial Science and Technology (AIST); 1-1-1 Umezono Tsukuba Ibaraki 305-8568 Japan
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24
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Pecina A, Haldar S, Fanfrlík J, Meier R, Řezáč J, Lepšík M, Hobza P. SQM/COSMO Scoring Function at the DFTB3-D3H4 Level: Unique Identification of Native Protein–Ligand Poses. J Chem Inf Model 2017; 57:127-132. [DOI: 10.1021/acs.jcim.6b00513] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Adam Pecina
- Institute
of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nám. 2, 16610 Prague 6, Czech Republic
| | - Susanta Haldar
- Institute
of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nám. 2, 16610 Prague 6, Czech Republic
| | - Jindřich Fanfrlík
- Institute
of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nám. 2, 16610 Prague 6, Czech Republic
| | - René Meier
- Leibniz Institute of Plant Biochemistry, Weinberg 3, 06120 Halle, Germany
| | - Jan Řezáč
- Institute
of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nám. 2, 16610 Prague 6, Czech Republic
| | - Martin Lepšík
- Institute
of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nám. 2, 16610 Prague 6, Czech Republic
| | - Pavel Hobza
- Institute
of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nám. 2, 16610 Prague 6, Czech Republic
- Regional
Centre of Advanced Technologies and Materials, Palacký University, 77146 Olomouc, Czech Republic
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25
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Hylsová M, Carbain B, Fanfrlík J, Musilová L, Haldar S, Köprülüoğlu C, Ajani H, Brahmkshatriya PS, Jorda R, Kryštof V, Hobza P, Echalier A, Paruch K, Lepšík M. Explicit treatment of active-site waters enhances quantum mechanical/implicit solvent scoring: Inhibition of CDK2 by new pyrazolo[1,5-a]pyrimidines. Eur J Med Chem 2016; 126:1118-1128. [PMID: 28039837 DOI: 10.1016/j.ejmech.2016.12.023] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Revised: 12/07/2016] [Accepted: 12/09/2016] [Indexed: 12/17/2022]
Abstract
We present comprehensive testing of solvent representation in quantum mechanics (QM)-based scoring of protein-ligand affinities. To this aim, we prepared 21 new inhibitors of cyclin-dependent kinase 2 (CDK2) with the pyrazolo[1,5-a]pyrimidine core, whose activities spanned three orders of magnitude. The crystal structure of a potent inhibitor bound to the active CDK2/cyclin A complex revealed that the biphenyl substituent at position 5 of the pyrazolo[1,5-a]pyrimidine scaffold was located in a previously unexplored pocket and that six water molecules resided in the active site. Using molecular dynamics, protein-ligand interactions and active-site water H-bond networks as well as thermodynamics were probed. Thereafter, all the inhibitors were scored by the QM approach utilizing the COSMO implicit solvent model. Such a standard treatment failed to produce a correlation with the experiment (R2 = 0.49). However, the addition of the active-site waters resulted in significant improvement (R2 = 0.68). The activities of the compounds could thus be interpreted by taking into account their specific noncovalent interactions with CDK2 and the active-site waters. In summary, using a combination of several experimental and theoretical approaches we demonstrate that the inclusion of explicit solvent effects enhance QM/COSMO scoring to produce a reliable structure-activity relationship with physical insights. More generally, this approach is envisioned to contribute to increased accuracy of the computational design of novel inhibitors.
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Affiliation(s)
- Michaela Hylsová
- Department of Chemistry, CZ Openscreen, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Benoit Carbain
- Department of Chemistry, CZ Openscreen, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital Brno, Pekařská 53, 656 91 Brno, Czech Republic
| | - Jindřich Fanfrlík
- Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nam. 2, 166 10 Prague 6, Czech Republic
| | - Lenka Musilová
- Department of Chemistry, CZ Openscreen, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Susanta Haldar
- Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nam. 2, 166 10 Prague 6, Czech Republic; Regional Center of Advanced Technologies and Materials, Department of Physical Chemistry, Palacký University, 771 46 Olomouc, Czech Republic
| | - Cemal Köprülüoğlu
- Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nam. 2, 166 10 Prague 6, Czech Republic; Regional Center of Advanced Technologies and Materials, Department of Physical Chemistry, Palacký University, 771 46 Olomouc, Czech Republic
| | - Haresh Ajani
- Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nam. 2, 166 10 Prague 6, Czech Republic; Regional Center of Advanced Technologies and Materials, Department of Physical Chemistry, Palacký University, 771 46 Olomouc, Czech Republic
| | - Pathik S Brahmkshatriya
- Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nam. 2, 166 10 Prague 6, Czech Republic
| | - Radek Jorda
- Laboratory of Growth Regulators, Faculty of Science, Palacký University, Institute of Experimental Botany, Šlechtitelů 27, 783 71 Olomouc, Czech Republic
| | - Vladimír Kryštof
- Laboratory of Growth Regulators, Faculty of Science, Palacký University, Institute of Experimental Botany, Šlechtitelů 27, 783 71 Olomouc, Czech Republic
| | - Pavel Hobza
- Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nam. 2, 166 10 Prague 6, Czech Republic; Regional Center of Advanced Technologies and Materials, Department of Physical Chemistry, Palacký University, 771 46 Olomouc, Czech Republic
| | - Aude Echalier
- Centre de Biochimie Structurale, CNRS UMR 5048 - UM - INSERM U 1054, 29 rue de Navacelles, 34090 Montpellier, France
| | - Kamil Paruch
- Department of Chemistry, CZ Openscreen, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital Brno, Pekařská 53, 656 91 Brno, Czech Republic.
| | - Martin Lepšík
- Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nam. 2, 166 10 Prague 6, Czech Republic.
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26
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Nakata H, Fedorov DG. Efficient Geometry Optimization of Large Molecular Systems in Solution Using the Fragment Molecular Orbital Method. J Phys Chem A 2016; 120:9794-9804. [DOI: 10.1021/acs.jpca.6b09743] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Hiroya Nakata
- Department
of Fundamental Technology Research, R and D Center Kagoshima, Kyocera, 1-4 Kokubu Yamashita-cho, Kirishima-shi, Kagoshima 899-4312, Japan
| | - Dmitri G. Fedorov
- Research
Center for Computational Design of Advanced Functional Materials, National Institute of Advanced Industrial Science and Technology, 1-1-1
Umezono, Tsukuba, Ibaraki 305-8568, Japan
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27
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Nakata H, Nishimoto Y, Fedorov DG. Analytic second derivative of the energy for density-functional tight-binding combined with the fragment molecular orbital method. J Chem Phys 2016; 145:044113. [DOI: 10.1063/1.4959231] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Affiliation(s)
- Hiroya Nakata
- Department of Fundamental Technology Research, R and D Center Kagoshima, Kyocera, 1-4 Kokubu Yamashita-cho, Kirishima-shi, Kagoshima 899-4312, Japan
| | - Yoshio Nishimoto
- Fukui Institute for Fundamental Chemistry, Kyoto University, 34-4 Takano Nishihiraki-cho, Sakyo-ku, Kyoto 606-8103, Japan
| | - Dmitri G. Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan
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28
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Olsson MA, Söderhjelm P, Ryde U. Converging ligand-binding free energies obtained with free-energy perturbations at the quantum mechanical level. J Comput Chem 2016; 37:1589-600. [PMID: 27117350 PMCID: PMC5074236 DOI: 10.1002/jcc.24375] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Revised: 03/08/2016] [Accepted: 03/09/2016] [Indexed: 12/15/2022]
Abstract
In this article, the convergence of quantum mechanical (QM) free-energy simulations based on molecular dynamics simulations at the molecular mechanics (MM) level has been investigated. We have estimated relative free energies for the binding of nine cyclic carboxylate ligands to the octa-acid deep-cavity host, including the host, the ligand, and all water molecules within 4.5 Å of the ligand in the QM calculations (158-224 atoms). We use single-step exponential averaging (ssEA) and the non-Boltzmann Bennett acceptance ratio (NBB) methods to estimate QM/MM free energy with the semi-empirical PM6-DH2X method, both based on interaction energies. We show that ssEA with cumulant expansion gives a better convergence and uses half as many QM calculations as NBB, although the two methods give consistent results. With 720,000 QM calculations per transformation, QM/MM free-energy estimates with a precision of 1 kJ/mol can be obtained for all eight relative energies with ssEA, showing that this approach can be used to calculate converged QM/MM binding free energies for realistic systems and large QM partitions. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.
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Affiliation(s)
- Martin A Olsson
- Department of Theoretical Chemistry, Lund University, Chemical Centre, P. O. Box 124, Lund, SE-221 00, Sweden
| | - Pär Söderhjelm
- Department of Biophysical Chemistry, Lund University, Chemical Centre, P. O. Box 124, Lund, SE-221 00, Sweden
| | - Ulf Ryde
- Department of Theoretical Chemistry, Lund University, Chemical Centre, P. O. Box 124, Lund, SE-221 00, Sweden
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29
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Yilmazer ND, Korth M. Recent Progress in Treating Protein-Ligand Interactions with Quantum-Mechanical Methods. Int J Mol Sci 2016; 17:ijms17050742. [PMID: 27196893 PMCID: PMC4881564 DOI: 10.3390/ijms17050742] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Revised: 04/18/2016] [Accepted: 05/03/2016] [Indexed: 11/16/2022] Open
Abstract
We review the first successes and failures of a “new wave” of quantum chemistry-based approaches to the treatment of protein/ligand interactions. These approaches share the use of “enhanced”, dispersion (D), and/or hydrogen-bond (H) corrected density functional theory (DFT) or semi-empirical quantum mechanical (SQM) methods, in combination with ensemble weighting techniques of some form to capture entropic effects. Benchmark and model system calculations in comparison to high-level theoretical as well as experimental references have shown that both DFT-D (dispersion-corrected density functional theory) and SQM-DH (dispersion and hydrogen bond-corrected semi-empirical quantum mechanical) perform much more accurately than older DFT and SQM approaches and also standard docking methods. In addition, DFT-D might soon become and SQM-DH already is fast enough to compute a large number of binding modes of comparably large protein/ligand complexes, thus allowing for a more accurate assessment of entropic effects.
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Affiliation(s)
- Nusret Duygu Yilmazer
- Institute for Theoretical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89069 Ulm, Germany.
| | - Martin Korth
- Institute for Theoretical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89069 Ulm, Germany.
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30
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Ryde U, Söderhjelm P. Ligand-Binding Affinity Estimates Supported by Quantum-Mechanical Methods. Chem Rev 2016; 116:5520-66. [DOI: 10.1021/acs.chemrev.5b00630] [Citation(s) in RCA: 175] [Impact Index Per Article: 21.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Ulf Ryde
- Department of Theoretical
Chemistry and ‡Department of Biophysical Chemistry, Lund University, Chemical Centre, P.O. Box 124, SE-221 00 Lund, Sweden
| | - Pär Söderhjelm
- Department of Theoretical
Chemistry and ‡Department of Biophysical Chemistry, Lund University, Chemical Centre, P.O. Box 124, SE-221 00 Lund, Sweden
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31
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Pruitt SR, Nakata H, Nagata T, Mayes M, Alexeev Y, Fletcher G, Fedorov DG, Kitaura K, Gordon MS. Importance of Three-Body Interactions in Molecular Dynamics Simulations of Water Demonstrated with the Fragment Molecular Orbital Method. J Chem Theory Comput 2016; 12:1423-35. [DOI: 10.1021/acs.jctc.5b01208] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Spencer R. Pruitt
- Argonne
Leadership Computing Facility, Argonne National Laboratory, 9700 S. Cass
Avenue, Lemont, Illinois 60439, United States
| | - Hiroya Nakata
- Department of Fundamental Technology Research, R&D Center Kagoshima, Kyocera Corporation, 1-4 Kokubu Yamashita-cho, Kirishima-shi, Kagoshima 899-4312, Japan
| | - Takeshi Nagata
- Nanosystem Research
Institute, National Institute of Advanced Industrial Science and Technology, 1-1-1 Umenzono, Tsukuba, Ibaraki 305-8568, Japan
| | - Maricris Mayes
- Department
of Chemistry and Biochemistry, University of Massachusetts Dartmouth, 285 Old Westport Road, Dartmouth, Massachusetts 02747-2300, United States
| | - Yuri Alexeev
- Argonne
Leadership Computing Facility, Argonne National Laboratory, 9700 S. Cass
Avenue, Lemont, Illinois 60439, United States
| | - Graham Fletcher
- Argonne
Leadership Computing Facility, Argonne National Laboratory, 9700 S. Cass
Avenue, Lemont, Illinois 60439, United States
| | - Dmitri G. Fedorov
- Nanosystem Research
Institute, National Institute of Advanced Industrial Science and Technology, 1-1-1 Umenzono, Tsukuba, Ibaraki 305-8568, Japan
| | - Kazuo Kitaura
- Graduate
School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501, Japan
| | - Mark S. Gordon
- Department
of Chemistry and Ames Laboratory, Iowa State University, 201 Spedding
Hall, Ames, Iowa 50011, United States
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32
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Pecina A, Meier R, Fanfrlík J, Lepšík M, Řezáč J, Hobza P, Baldauf C. The SQM/COSMO filter: reliable native pose identification based on the quantum-mechanical description of protein–ligand interactions and implicit COSMO solvation. Chem Commun (Camb) 2016; 52:3312-5. [DOI: 10.1039/c5cc09499b] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Strictly uphill – in cognate docking experiments we show that a quantum mechanical description of interaction and solvation outperforms established scoring functions in sharply distinguishing the native state from decoy poses.
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Affiliation(s)
- Adam Pecina
- Institute of Organic Chemistry and Biochemistry (IOCB) and Gilead Sciences and IOCB Research Center
- 16610 Prague 6
- Czech Republic
| | - René Meier
- Institut für Biochemie
- Fakultät für Biowissenschaften
- Pharmazie und Psychologie
- Universität Leipzig
- D-04109 Leipzig
| | - Jindřich Fanfrlík
- Institute of Organic Chemistry and Biochemistry (IOCB) and Gilead Sciences and IOCB Research Center
- 16610 Prague 6
- Czech Republic
| | - Martin Lepšík
- Institute of Organic Chemistry and Biochemistry (IOCB) and Gilead Sciences and IOCB Research Center
- 16610 Prague 6
- Czech Republic
| | - Jan Řezáč
- Institute of Organic Chemistry and Biochemistry (IOCB) and Gilead Sciences and IOCB Research Center
- 16610 Prague 6
- Czech Republic
| | - Pavel Hobza
- Institute of Organic Chemistry and Biochemistry (IOCB) and Gilead Sciences and IOCB Research Center
- 16610 Prague 6
- Czech Republic
- Regional Centre of Advanced Technologies and Materials
- Department of Physical Chemistry
| | - Carsten Baldauf
- Fritz-Haber-Institut der Max-Planck-Gesellschaft
- D-14195 Berlin
- Germany
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33
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Nishimoto Y, Fedorov DG. The fragment molecular orbital method combined with density-functional tight-binding and the polarizable continuum model. Phys Chem Chem Phys 2016; 18:22047-61. [DOI: 10.1039/c6cp02186g] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The electronic gap in proteins is analyzed in detail, and it is shown that FMO-DFTB/PCM is efficient and accurate in describing the molecular structure of proteins in solution.
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Affiliation(s)
- Yoshio Nishimoto
- Fukui Institute for Fundamental Chemistry
- Kyoto University
- Sakyo-ku, Kyoto 606-8103
- Japan
| | - Dmitri G. Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat)
- National Institute of Advanced Industrial Science and Technology (AIST)
- Tsukuba
- Japan
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34
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Roos K, Hogner A, Ogg D, Packer MJ, Hansson E, Granberg KL, Evertsson E, Nordqvist A. Predicting the relative binding affinity of mineralocorticoid receptor antagonists by density functional methods. J Comput Aided Mol Des 2015; 29:1109-22. [PMID: 26572910 DOI: 10.1007/s10822-015-9880-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2015] [Accepted: 11/05/2015] [Indexed: 11/28/2022]
Abstract
In drug discovery, prediction of binding affinity ahead of synthesis to aid compound prioritization is still hampered by the low throughput of the more accurate methods and the lack of general pertinence of one method that fits all systems. Here we show the applicability of a method based on density functional theory using core fragments and a protein model with only the first shell residues surrounding the core, to predict relative binding affinity of a matched series of mineralocorticoid receptor (MR) antagonists. Antagonists of MR are used for treatment of chronic heart failure and hypertension. Marketed MR antagonists, spironolactone and eplerenone, are also believed to be highly efficacious in treatment of chronic kidney disease in diabetes patients, but is contra-indicated due to the increased risk for hyperkalemia. These findings and a significant unmet medical need among patients with chronic kidney disease continues to stimulate efforts in the discovery of new MR antagonist with maintained efficacy but low or no risk for hyperkalemia. Applied on a matched series of MR antagonists the quantum mechanical based method gave an R(2) = 0.76 for the experimental lipophilic ligand efficiency versus relative predicted binding affinity calculated with the M06-2X functional in gas phase and an R(2) = 0.64 for experimental binding affinity versus relative predicted binding affinity calculated with the M06-2X functional including an implicit solvation model. The quantum mechanical approach using core fragments was compared to free energy perturbation calculations using the full sized compound structures.
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Affiliation(s)
- Katarina Roos
- RIA Medicinal Chemistry, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden.
| | - Anders Hogner
- CVMD Medicinal Chemistry, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden
| | - Derek Ogg
- Discovery Sciences, AstraZeneca, Alderley Park, Macclesfield, Cheshire, SK10 4TF, UK
| | - Martin J Packer
- Oncology Medicinal Chemistry, AstraZeneca, Alderley Park, Macclesfield, Cheshire, SK10 4TF, UK
| | - Eva Hansson
- Discovery Sciences, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden
| | - Kenneth L Granberg
- CVMD Medicinal Chemistry, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden
| | - Emma Evertsson
- RIA Medicinal Chemistry, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden
| | - Anneli Nordqvist
- CVMD Medicinal Chemistry, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden.
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35
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Genheden S, Ryde U, Söderhjelm P. Binding affinities by alchemical perturbation using QM/MM with a large QM system and polarizable MM model. J Comput Chem 2015; 36:2114-24. [PMID: 26280564 DOI: 10.1002/jcc.24048] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Revised: 06/13/2015] [Accepted: 07/17/2015] [Indexed: 12/19/2022]
Abstract
The most general way to improve the accuracy of binding-affinity calculations for protein-ligand systems is to use quantum-mechanical (QM) methods together with rigorous alchemical-perturbation (AP) methods. We explore this approach by calculating the relative binding free energy of two synthetic disaccharides binding to galectin-3 at a reasonably high QM level (dispersion-corrected density functional theory with a triple-zeta basis set) and with a sufficiently large QM system to include all short-range interactions with the ligand (744-748 atoms). The rest of the protein is treated as a collection of atomic multipoles (up to quadrupoles) and polarizabilities. Several methods for evaluating the binding free energy from the 3600 QM calculations are investigated in terms of stability and accuracy. In particular, methods using QM calculations only at the endpoints of the transformation are compared with the recently proposed non-Boltzmann Bennett acceptance ratio (NBB) method that uses QM calculations at several stages of the transformation. Unfortunately, none of the rigorous approaches give sufficient statistical precision. However, a novel approximate method, involving the direct use of QM energies in the Bennett acceptance ratio method, gives similar results as NBB but with better precision, ∼3 kJ/mol. The statistical error can be further reduced by performing a greater number of QM calculations.
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Affiliation(s)
- Samuel Genheden
- School of Chemistry, University of Southampton, Highfield, Southampton, SO17 1BJ, United Kingdom
| | - Ulf Ryde
- Department of Theoretical Chemistry, Lund University, Chemical Centre, P. O. Box 124, Lund, SE-221 00, Sweden
| | - Pär Söderhjelm
- Department of Biophysical Chemistry, Lund University, Chemical Centre, P. O. Box 124, Lund, SE-221 00, Sweden
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36
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Nakata H, Fedorov DG, Nagata T, Kitaura K, Nakamura S. Simulations of Chemical Reactions with the Frozen Domain Formulation of the Fragment Molecular Orbital Method. J Chem Theory Comput 2015; 11:3053-64. [DOI: 10.1021/acs.jctc.5b00277] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Hiroya Nakata
- Department
of Biomolecular Engineering, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, Kanagawa 226-8501, Japan
- Research
Cluster for Innovation, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
- Japan Society for the Promotion of Science, Kojimachi Business Center Building, 5-3-1 Kojimachi, Chiyoda-ku, Tokyo 102-0083, Japan
| | - Dmitri G. Fedorov
- Nanosystem
Research Institute, National Institute of Advanced Industrial Science and Technology, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan
| | - Takeshi Nagata
- Nanosystem
Research Institute, National Institute of Advanced Industrial Science and Technology, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan
- Graduate
School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501, Japan
| | - Kazuo Kitaura
- Graduate
School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501, Japan
| | - Shinichiro Nakamura
- Research
Cluster for Innovation, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
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37
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Abstract
INTRODUCTION The molecular mechanics energies combined with the Poisson-Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to estimate the free energy of the binding of small ligands to biological macromolecules. They are typically based on molecular dynamics simulations of the receptor-ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchemical perturbation methods. They have been applied to a large number of systems with varying success. AREAS COVERED The authors review the use of MM/PBSA and MM/GBSA methods to calculate ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications. EXPERT OPINION MM/PBSA and MM/GBSA are attractive approaches owing to their modular nature and that they do not require calculations on a training set. They have been used successfully to reproduce and rationalize experimental findings and to improve the results of virtual screening and docking. However, they contain several crude and questionable approximations, for example, the lack of conformational entropy and information about the number and free energy of water molecules in the binding site. Moreover, there are many variants of the method and their performance varies strongly with the tested system. Likewise, most attempts to ameliorate the methods with more accurate approaches, for example, quantum-mechanical calculations, polarizable force fields or improved solvation have deteriorated the results.
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Affiliation(s)
- Samuel Genheden
- University of Southampton, School of Chemistry, Highfield, SO17 1BJ, Southampton, UK
| | - Ulf Ryde
- Lund University, Chemical Centre, Department of Theoretical Chemistry, P. O. Box 124, SE-221 00 Lund, Sweden+46 46 2224502; +46 46 2228648;
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38
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Analytic second derivative of the energy for density functional theory based on the three-body fragment molecular orbital method. J Chem Phys 2015; 142:124101. [DOI: 10.1063/1.4915068] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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39
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Yilmazer ND, Heitel P, Schwabe T, Korth M. Benchmark of electronic structure methods for protein–ligand interactions based on high-level reference data. JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY 2015. [DOI: 10.1142/s0219633615400015] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The accurate prediction of the strength of protein–ligand interactions is a very difficult problem despite impressive advances in the field of biomolecular modeling. There are good reasons to believe that quantum mechanical methods can help with this task, but the application of such methods in the context of scoring is still in its infancy. Here we benchmark several wave function theory (WFT), density functional theory (DFT) and semiempirical quantum mechanical (SQM) approaches against high-level theoretical references for realistic test cases. Based on our findings for systematically generated model systems of real protein/ligand complexes from the PDB-bind database, we can recommend SCS-MP2 and B2-PLYP-D3 as reference methods, TPSS-D3+Dabc/def-TZVPP as the best DFT approach and PM6-DH+ as a fast and accurate alternative to full ab initio treatments.
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Affiliation(s)
- Nusret Duygu Yilmazer
- Institute for Theoretical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89069 Ulm, Germany
| | - Pascal Heitel
- Institute for Theoretical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89069 Ulm, Germany
| | - Tobias Schwabe
- Center for Bioinformatics and Institute of Physical Chemistry, University of Hamburg, Bundesstraße 43, 20146 Hamburg, Germany
| | - Martin Korth
- Institute for Theoretical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89069 Ulm, Germany
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40
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Liu J, Wang X, Zhang JZH, He X. Calculation of protein–ligand binding affinities based on a fragment quantum mechanical method. RSC Adv 2015. [DOI: 10.1039/c5ra20185c] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
An efficient fragment-based quantum mechanical method has been successfully applied for reliable prediction of protein–ligand binding affinities.
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Affiliation(s)
- Jinfeng Liu
- State Key Laboratory of Precision Spectroscopy
- Institute of Theoretical and Computational Science
- College of Chemistry and Molecular Engineering
- East China Normal University
- Shanghai
| | - Xianwei Wang
- Center for Optics & Optoelectronics Research
- College of Science
- Zhejiang University of Technology
- Hangzhou
- China
| | - John Z. H. Zhang
- State Key Laboratory of Precision Spectroscopy
- Institute of Theoretical and Computational Science
- College of Chemistry and Molecular Engineering
- East China Normal University
- Shanghai
| | - Xiao He
- State Key Laboratory of Precision Spectroscopy
- Institute of Theoretical and Computational Science
- College of Chemistry and Molecular Engineering
- East China Normal University
- Shanghai
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41
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Chaskar P, Zoete V, Röhrig UF. Toward On-The-Fly Quantum Mechanical/Molecular Mechanical (QM/MM) Docking: Development and Benchmark of a Scoring Function. J Chem Inf Model 2014; 54:3137-52. [DOI: 10.1021/ci5004152] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Prasad Chaskar
- Swiss Institute of Bioinformatics, Molecular Modeling Group,
Quartier Sorge, Bâtiment
Génopode, CH-1015 Lausanne, Switzerland
| | - Vincent Zoete
- Swiss Institute of Bioinformatics, Molecular Modeling Group,
Quartier Sorge, Bâtiment
Génopode, CH-1015 Lausanne, Switzerland
| | - Ute F. Röhrig
- Swiss Institute of Bioinformatics, Molecular Modeling Group,
Quartier Sorge, Bâtiment
Génopode, CH-1015 Lausanne, Switzerland
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42
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Nishimoto Y, Fedorov DG, Irle S. Density-Functional Tight-Binding Combined with the Fragment Molecular Orbital Method. J Chem Theory Comput 2014; 10:4801-12. [DOI: 10.1021/ct500489d] [Citation(s) in RCA: 73] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Affiliation(s)
| | - Dmitri G. Fedorov
- Nanosystem
Research Institute (NRI), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba 305-8565, Japan
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43
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Andrejić M, Ryde U, Mata RA, Söderhjelm P. Coupled-Cluster Interaction Energies for 200-Atom Host-Guest Systems. Chemphyschem 2014; 15:3270-81. [DOI: 10.1002/cphc.201402379] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2014] [Indexed: 11/09/2022]
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44
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Nakata H, Fedorov DG, Yokojima S, Kitaura K, Nakamura S. Simulations of Raman Spectra Using the Fragment Molecular Orbital Method. J Chem Theory Comput 2014; 10:3689-98. [DOI: 10.1021/ct5003829] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Hiroya Nakata
- Department
of Biomolecular Engineering, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, Kanagawa 226-8501, Japan
- Nakamura
Lab, Research Cluster for Innovation, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
- Japan Society for the Promotion of Science, Kojimachi Business Center Building, 5-3-1 Kojimachi,
Chiyoda-ku, Tokyo 102-0083, Japan
| | - Dmitri G. Fedorov
- NRI, National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1
Umezono,Tsukuba, Ibaraki 305-8568, Japan
| | - Satoshi Yokojima
- Nakamura
Lab, Research Cluster for Innovation, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
- Tokyo University of Pharmacy and Life Sciences, 1432-1 Horinouchi, Hachiouji-shi, Tokyo 192-0392, Japan
| | - Kazuo Kitaura
- Graduate
School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501 Japan
| | - Shinichiro Nakamura
- Nakamura
Lab, Research Cluster for Innovation, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
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45
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Nakata H, Fedorov DG, Yokojima S, Kitaura K, Sakurai M, Nakamura S. Unrestricted density functional theory based on the fragment molecular orbital method for the ground and excited state calculations of large systems. J Chem Phys 2014; 140:144101. [DOI: 10.1063/1.4870261] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
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46
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Xu M, Lill MA. Induced fit docking, and the use of QM/MM methods in docking. DRUG DISCOVERY TODAY. TECHNOLOGIES 2014; 10:e411-8. [PMID: 24050138 DOI: 10.1016/j.ddtec.2013.02.003] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Docking methods are popular computational techniques in drug discovery to identify new active molecules that bind to a given biological target. Although widely used, the predictive reliability of docking methods is often limited by the inability to accurately and efficiently model protein flexibility and quantify binding strength. We highlight several emerging concepts that address those methodological issues including a discussion on the incorporation of QM/MM methodologies in the scoring process.
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47
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Nakata H, Fedorov DG, Yokojima S, Kitaura K, Nakamura S. Derivatives of the approximated electrostatic potentials in unrestricted Hartree–Fock based on the fragment molecular orbital method and an application to polymer radicals. Theor Chem Acc 2014. [DOI: 10.1007/s00214-014-1477-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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48
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Roos K, Viklund J, Meuller J, Kaspersson K, Svensson M. Potency prediction of β-secretase (BACE-1) inhibitors using density functional methods. J Chem Inf Model 2014; 54:818-25. [PMID: 24456077 DOI: 10.1021/ci400374z] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Scoring potency is a main challenge for structure based drug design. Inductive effects of subtle variations in the ligand are not possible to accurately predict by classical computational chemistry methods. In this study, the problem of predicting potency of ligands with electronic variations participating in key interactions with the protein was addressed. The potency was predicted for a large set of cyclic amidine and guanidine cores extracted from β-secretase (BACE-1) inhibitors. All cores were of similar size and had equal interaction motifs but were diverse with respect to electronic substitutions. A density functional theory approach, in combination with a representation of the active site of a protein using only key residues, was shown to be predictive. This computational approach was used to guide and support drug design, within the time frame of a normal drug discovery design cycle.
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Affiliation(s)
- Katarina Roos
- Department of Medicinal Chemistry and §Discovery Sciences, AstraZeneca R&D Mölndal , SE-431 83 Mölndal, Sweden
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49
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Christensen AS, Steinmann C, Fedorov DG, Jensen JH. Hybrid RHF/MP2 geometry optimizations with the effective fragment molecular orbital method. PLoS One 2014; 9:e88800. [PMID: 24558430 PMCID: PMC3928295 DOI: 10.1371/journal.pone.0088800] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2013] [Accepted: 01/15/2014] [Indexed: 11/18/2022] Open
Abstract
The frozen domain effective fragment molecular orbital method is extended to allow for the treatment of a single fragment at the MP2 level of theory. The approach is applied to the conversion of chorismate to prephenate by Chorismate Mutase, where the substrate is treated at the MP2 level of theory while the rest of the system is treated at the RHF level. MP2 geometry optimization is found to lower the barrier by up to 3.5 kcal/mol compared to RHF optimzations and ONIOM energy refinement and leads to a smoother convergence with respect to the basis set for the reaction profile. For double zeta basis sets the increase in CPU time relative to RHF is roughly a factor of two.
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Affiliation(s)
| | - Casper Steinmann
- Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Odense, Denmark
| | - Dmitri G. Fedorov
- Nanosystem Research Institute (NRI), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | - Jan H. Jensen
- Department of Chemistry, University of Copenhagen, Copenhagen, Denmark
- * E-mail:
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50
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Fanfrlík J, Brahmkshatriya PS, Řezáč J, Jílková A, Horn M, Mareš M, Hobza P, Lepšík M. Quantum mechanics-based scoring rationalizes the irreversible inactivation of parasitic Schistosoma mansoni cysteine peptidase by vinyl sulfone inhibitors. J Phys Chem B 2013; 117:14973-82. [PMID: 24195769 DOI: 10.1021/jp409604n] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The quantum mechanics (QM)-based scoring function that we previously developed for the description of noncovalent binding in protein-ligand complexes has been modified and extended to treat covalent binding of inhibitory ligands. The enhancements are (i) the description of the covalent bond breakage and formation using hybrid QM/semiempirical QM (QM/SQM) restrained optimizations and (ii) the addition of the new ΔG(cov)' term to the noncovalent score, describing the "free" energy difference between the covalent and noncovalent complexes. This enhanced QM-based scoring function is applied to a series of 20 vinyl sulfone-based inhibitory compounds inactivating the cysteine peptidase cathepsin B1 of the Schistosoma mansoni parasite (SmCB1). The available X-ray structure of the SmCB1 in complex with a potent vinyl sulfone inhibitor K11017 is used as a template to build the other covalently bound complexes and to model the derived noncovalent complexes. We present the correlation of the covalent score and its constituents with the experimental binding data. Four outliers are identified. They contain bulky R1' substituents structurally divergent from the template, which might induce larger protein rearrangements than could be accurately modeled. In summary, we propose a new computational approach and an optimal protocol for the rapid evaluation and prospective design of covalent inhibitors with a conserved binding mode.
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Affiliation(s)
- Jindřich Fanfrlík
- Institute of Organic Chemistry and Biochemistry, v.v.i., and Gilead Sciences and IOCB Research Center, Academy of Sciences of the Czech Republic , Flemingovo nám. 2, 166 10 Prague 6, Czech Republic
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