1
|
Jung J, Yagi K, Tan C, Oshima H, Mori T, Yu I, Matsunaga Y, Kobayashi C, Ito S, Ugarte La Torre D, Sugita Y. GENESIS 2.1: High-Performance Molecular Dynamics Software for Enhanced Sampling and Free-Energy Calculations for Atomistic, Coarse-Grained, and Quantum Mechanics/Molecular Mechanics Models. J Phys Chem B 2024; 128:6028-6048. [PMID: 38876465 DOI: 10.1021/acs.jpcb.4c02096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2024]
Abstract
GENeralized-Ensemble SImulation System (GENESIS) is a molecular dynamics (MD) software developed to simulate the conformational dynamics of a single biomolecule, as well as molecular interactions in large biomolecular assemblies and between multiple biomolecules in cellular environments. To achieve the latter purpose, the earlier versions of GENESIS emphasized high performance in atomistic MD simulations on massively parallel supercomputers, with or without graphics processing units (GPUs). Here, we implemented multiscale MD simulations that include atomistic, coarse-grained, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations. They demonstrate high performance and are integrated with enhanced conformational sampling algorithms and free-energy calculations without using external programs except for the QM programs. In this article, we review new functions, molecular models, and other essential features in GENESIS version 2.1 and discuss ongoing developments for future releases.
Collapse
Affiliation(s)
- Jaewoon Jung
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Kiyoshi Yagi
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Cheng Tan
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Hiraku Oshima
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
- Graduate School of Life Science, University of Hyogo, Harima Science Park City, Hyogo 678-1297, Japan
| | - Takaharu Mori
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Department of Chemistry, Tokyo University of Science, Shinjuku-ku, Tokyo 162-8601, Japan
| | - Isseki Yu
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Department of Bioinformatics, Maebashi Institute of Technology, Maebashi, Gunma 371-0816, Japan
| | - Yasuhiro Matsunaga
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
- Graduate School of Science and Engineering, Saitama University, Saitama 338-8570, Japan
| | - Chigusa Kobayashi
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Shingo Ito
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Diego Ugarte La Torre
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Yuji Sugita
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
| |
Collapse
|
2
|
Zhang S, Giese TJ, Lee TS, York DM. Alchemical Enhanced Sampling with Optimized Phase Space Overlap. J Chem Theory Comput 2024; 20:3935-3953. [PMID: 38666430 PMCID: PMC11157682 DOI: 10.1021/acs.jctc.4c00251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/15/2024]
Abstract
An alchemical enhanced sampling (ACES) method has recently been introduced to facilitate importance sampling in free energy simulations. The method achieves enhanced sampling from Hamiltonian replica exchange within a dual topology framework while utilizing new smoothstep softcore potentials. A common sampling problem encountered in lead optimization is the functionalization of aromatic rings that exhibit distinct conformational preferences when interacting with the protein. It is difficult to converge the distribution of ring conformations due to the long time scale of ring flipping events; however, the ACES method addresses this issue by modeling the syn and anti ring conformations within a dual topology. ACES thereby samples the conformer distributions by alchemically tunneling between states, as opposed to traversing a physical pathway with a high rotational barrier. We demonstrate the use of ACES to overcome conformational sampling issues involving ring flipping in ML300-derived noncovalent inhibitors of SARS-CoV-2 Main Protease (Mpro). The demonstrations explore how the use of replica exchange and the choice of softcore selection affects the convergence of the ring conformation distributions. Furthermore, we examine how the accuracy of the calculated free energies is affected by the degree of phase space overlap (PSO) between adjacent states (i.e., between neighboring λ-windows) and the Hamiltonian replica exchange acceptance ratios. Both of these factors are sensitive to the spacing between the intermediate states. We introduce a new method for choosing a schedule of λ values. The method analyzes short "burn-in" simulations to construct a 2D map of the nonlocal PSO. The schedule is obtained by optimizing an alchemical pathway on the 2D map that equalizes the PSO between the λ intervals. The optimized phase space overlap λ-spacing method (Opt-PSO) leads to more numerous end-to-end single passes and round trips due to the correlation between PSO and Hamiltonian replica exchange acceptance ratios. The improved exchange statistics enhance the efficiency of ACES method. The method has been implemented into the FE-ToolKit software package, which is freely available.
Collapse
Affiliation(s)
- Shi Zhang
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Timothy J. Giese
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Tai-Sung Lee
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Darrin M. York
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| |
Collapse
|
3
|
Binder J, Winkeljann J, Steinegger K, Trnovec L, Orekhova D, Zähringer J, Hörner A, Fell V, Tinnefeld P, Winkeljann B, Frieß W, Merkel OM. Closing the Gap between Experiment and Simulation─A Holistic Study on the Complexation of Small Interfering RNAs with Polyethylenimine. Mol Pharm 2024; 21:2163-2175. [PMID: 38373164 DOI: 10.1021/acs.molpharmaceut.3c00747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Rational design is pivotal in the modern development of nucleic acid nanocarrier systems. With the rising prominence of polymeric materials as alternatives to lipid-based carriers, understanding their structure-function relationships becomes paramount. Here, we introduce a newly developed coarse-grained model of polyethylenimine (PEI) based on the Martini 3 force field. This model facilitates molecular dynamics simulations of true-sized PEI molecules, exemplified by molecules with molecular weights of 1.3, 5, 10, and 25 kDa, with degrees of branching between 50.0 and 61.5%. We employed this model to investigate the thermodynamics of small interfering RNA (siRNA) complexation with PEI. Our simulations underscore the pivotal role of electrostatic interactions in the complexation process. Thermodynamic analyses revealed a stronger binding affinity with increased protonation, notably in acidic (endosomal) pH, compared to neutral conditions. Furthermore, the molecular weight of PEI was found to be a critical determinant of binding dynamics: smaller PEI molecules closely enveloped the siRNA, whereas larger ones extended outward, facilitating the formation of complexes with multiple RNA molecules. Experimental validations, encompassing isothermal titration calorimetry and single-molecule fluorescence spectroscopy, aligned well with our computational predictions. Our findings not only validate the fidelity of our PEI model but also accentuate the importance of in silico data in the rational design of polymeric drug carriers. The synergy between computational predictions and experimental validations, as showcased here, signals a refined and precise approach to drug carrier design.
Collapse
Affiliation(s)
- Jonas Binder
- Faculty for Chemistry and Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstraße 5-13, Haus B, 81377 München, Germany
| | - Joshua Winkeljann
- Center for NanoScience (CeNS), Ludwig-Maximilians-Universität München, 80799 München, Germany
- Chair of Experimental Physics I, University of Augsburg, Universitätsstraße 1, 86519 Augsburg, Germany
| | - Katharina Steinegger
- Faculty for Chemistry and Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstraße 5-13, Haus B, 81377 München, Germany
| | - Lara Trnovec
- Faculty for Chemistry and Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstraße 5-13, Haus B, 81377 München, Germany
| | - Daria Orekhova
- Faculty for Chemistry and Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstraße 5-13, Haus B, 81377 München, Germany
- Center for NanoScience (CeNS), Ludwig-Maximilians-Universität München, 80799 München, Germany
| | - Jonas Zähringer
- Faculty for Chemistry and Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstraße 5-13, Haus B, 81377 München, Germany
- Center for NanoScience (CeNS), Ludwig-Maximilians-Universität München, 80799 München, Germany
| | - Andreas Hörner
- Chair of Experimental Physics I, University of Augsburg, Universitätsstraße 1, 86519 Augsburg, Germany
| | - Valentin Fell
- Faculty for Chemistry and Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstraße 5-13, Haus B, 81377 München, Germany
| | - Philip Tinnefeld
- Faculty for Chemistry and Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstraße 5-13, Haus B, 81377 München, Germany
- Center for NanoScience (CeNS), Ludwig-Maximilians-Universität München, 80799 München, Germany
| | - Benjamin Winkeljann
- Faculty for Chemistry and Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstraße 5-13, Haus B, 81377 München, Germany
- Center for NanoScience (CeNS), Ludwig-Maximilians-Universität München, 80799 München, Germany
| | - Wolfgang Frieß
- Faculty for Chemistry and Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstraße 5-13, Haus B, 81377 München, Germany
| | - Olivia M Merkel
- Faculty for Chemistry and Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstraße 5-13, Haus B, 81377 München, Germany
- Center for NanoScience (CeNS), Ludwig-Maximilians-Universität München, 80799 München, Germany
| |
Collapse
|
4
|
Verteramo ML, Ignjatović MM, Kumar R, Wernersson S, Ekberg V, Wallerstein J, Carlström G, Chadimová V, Leffler H, Zetterberg F, Logan DT, Ryde U, Akke M, Nilsson UJ. Interplay of halogen bonding and solvation in protein-ligand binding. iScience 2024; 27:109636. [PMID: 38633000 PMCID: PMC11021960 DOI: 10.1016/j.isci.2024.109636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 02/13/2024] [Accepted: 03/26/2024] [Indexed: 04/19/2024] Open
Abstract
Halogen bonding is increasingly utilized in efforts to achieve high affinity and selectivity of molecules designed to bind proteins, making it paramount to understand the relationship between structure, dynamics, and thermodynamic driving forces. We present a detailed analysis addressing this problem using a series of protein-ligand complexes involving single halogen substitutions - F, Cl, Br, and I - and nearly identical structures. Isothermal titration calorimetry reveals an increasingly favorable binding enthalpy from F to I that correlates with the halogen size and σ-hole electropositive character, but is partially counteracted by unfavorable entropy, which is constant from F to Cl and Br, but worse for I. Consequently, the binding free energy is roughly equal for Cl, Br, and I. QM and solvation-free-energy calculations reflect an intricate balance between halogen bonding, hydrogen bonds, and solvation. These advances have the potential to aid future drug design initiatives involving halogenated compounds.
Collapse
Affiliation(s)
| | | | - Rohit Kumar
- Department of Chemistry, Lund University, Lund, Sweden
| | | | | | | | | | | | - Hakon Leffler
- Microbiology, Immunology, and Glycobiology, Department of Experimental Medicine, Lund University, Lund, Sweden
| | | | | | - Ulf Ryde
- Department of Chemistry, Lund University, Lund, Sweden
| | - Mikael Akke
- Department of Chemistry, Lund University, Lund, Sweden
| | | |
Collapse
|
5
|
Wang S, Liu F, Li P, Wang JN, Mo Y, Lin B, Mei Y. Potent inhibitors targeting cyclin-dependent kinase 9 discovered via virtual high-throughput screening and absolute binding free energy calculations. Phys Chem Chem Phys 2024; 26:5377-5386. [PMID: 38269624 DOI: 10.1039/d3cp05582e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2024]
Abstract
Due to the crucial regulatory mechanism of cyclin-dependent kinase 9 (CDK9) in mRNA transcription, the development of kinase inhibitors targeting CDK9 holds promise as a potential treatment strategy for cancer. A structure-based virtual screening approach has been employed for the discovery of potential novel CDK9 inhibitors. First, compounds with kinase inhibitor characteristics were identified from the ZINC15 database via virtual high-throughput screening. Next, the predicted binding modes were optimized by molecular dynamics simulations, followed by precise estimation of binding affinities using absolute binding free energy calculations based on the free energy perturbation scheme. The binding mode of molecule 006 underwent an inward-to-outward flipping, and the new binding mode exhibited binding affinity comparable to the small molecule T6Q in the crystal structure (PDB ID: 4BCF), highlighting the essential role of molecular dynamics simulation in capturing a plausible binding pose bridging docking and absolute binding free energy calculations. Finally, structural modifications based on these findings further enhanced the binding affinity with CDK9. The results revealed that enhancing the molecule's rigidity through ring formation, while maintaining the major interactions, reduced the entropy loss during the binding process and, thus, enhanced binding affinities.
Collapse
Affiliation(s)
- Shipeng Wang
- School of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China.
| | - Fengjiao Liu
- School of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China.
| | - Pengfei Li
- Single Particle, LLC, 10531 4S Commons Dr 166-629, San Diego, CA 92127, USA
| | - Jia-Ning Wang
- State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University, Shanghai 200241, China
| | - Yan Mo
- State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University, Shanghai 200241, China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
- Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006, China
| | - Bin Lin
- Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang 110016, China.
| | - Ye Mei
- State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University, Shanghai 200241, China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
- Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006, China
| |
Collapse
|
6
|
Georgiou K, Konstantinidi A, Hutterer J, Freudenberger K, Kolarov F, Lambrinidis G, Stylianakis I, Stampelou M, Gauglitz G, Kolocouris A. Accurate calculation of affinity changes to the close state of influenza A M2 transmembrane domain in response to subtle structural changes of adamantyl amines using free energy perturbation methods in different lipid bilayers. BIOCHIMICA ET BIOPHYSICA ACTA. BIOMEMBRANES 2024; 1866:184258. [PMID: 37995846 DOI: 10.1016/j.bbamem.2023.184258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 10/18/2023] [Accepted: 11/15/2023] [Indexed: 11/25/2023]
Abstract
Experimental binding free energies of 27 adamantyl amines against the influenza M2(22-46) WT tetramer, in its closed form at pH 8, were measured by ITC in DPC micelles. The measured Kd's range is ~44 while the antiviral potencies (IC50) range is ~750 with a good correlation between binding free energies computed with Kd and IC50 values (r = 0.76). We explored with MD simulations (ff19sb, CHARMM36m) the binding profile of complexes with strong, moderate and weak binders embedded in DMPC, DPPC, POPC or a viral mimetic membrane and using different experimental starting structures of M2. To predict accurately differences in binding free energy in response to subtle changes in the structure of the ligands, we performed 18 alchemical perturbative single topology FEP/MD NPT simulations (OPLS2005) using the BAR estimator (Desmond software) and 20 dual topology calculations TI/MD NVT simulations (ff19sb) using the MBAR estimator (Amber software) for adamantyl amines in complex with M2(22-46) WT in DMPC, DPPC, POPC. We observed that both methods with all lipids show a very good correlation between the experimental and calculated relative binding free energies (r = 0.77-0.87, mue = 0.36-0.92 kcal mol-1) with the highest performance achieved with TI/MBAR and lowest performance with FEP/BAR in DMPC bilayers. When antiviral potencies are used instead of the Kd values for computing the experimental binding free energies we obtained also good performance with both FEP/BAR (r = 0.83, mue = 0.75 kcal mol-1) and TI/MBAR (r = 0.69, mue = 0.77 kcal mol-1).
Collapse
Affiliation(s)
- Kyriakos Georgiou
- Laboratory of Medicinal Chemistry, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, National and Kapodistrian University of Athens (NKUA), Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Athina Konstantinidi
- Laboratory of Medicinal Chemistry, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, National and Kapodistrian University of Athens (NKUA), Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Johanna Hutterer
- Institut für Physikalische und Theoretische Chemie, Eberhard-Karls-Universität, D-72076 Tübingen, Germany
| | - Kathrin Freudenberger
- Institut für Physikalische und Theoretische Chemie, Eberhard-Karls-Universität, D-72076 Tübingen, Germany
| | - Felix Kolarov
- Institut für Physikalische und Theoretische Chemie, Eberhard-Karls-Universität, D-72076 Tübingen, Germany; Roche, Penzberg, Bavaria, Germany
| | - George Lambrinidis
- Laboratory of Medicinal Chemistry, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, National and Kapodistrian University of Athens (NKUA), Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Ioannis Stylianakis
- Laboratory of Medicinal Chemistry, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, National and Kapodistrian University of Athens (NKUA), Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Margarita Stampelou
- Laboratory of Medicinal Chemistry, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, National and Kapodistrian University of Athens (NKUA), Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Günter Gauglitz
- Institut für Physikalische und Theoretische Chemie, Eberhard-Karls-Universität, D-72076 Tübingen, Germany
| | - Antonios Kolocouris
- Laboratory of Medicinal Chemistry, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, National and Kapodistrian University of Athens (NKUA), Panepistimiopolis-Zografou, 15771 Athens, Greece.
| |
Collapse
|
7
|
Stampelou M, Ladds G, Kolocouris A. Computational Workflow for Refining AlphaFold Models in Drug Design Using Kinetic and Thermodynamic Binding Calculations: A Case Study for the Unresolved Inactive Human Adenosine A 3 Receptor. J Phys Chem B 2024; 128:914-936. [PMID: 38236582 DOI: 10.1021/acs.jpcb.3c05986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
A structure-based drug design pipeline that considers both thermodynamic and kinetic binding data of ligands against a receptor will enable the computational design of improved drug molecules. For unresolved GPCR-ligand complexes, a workflow that can apply both thermodynamic and kinetic binding data in combination with alpha-fold (AF)-derived or other homology models and experimentally resolved binding modes of relevant ligands in GPCR-homologs needs to be tested. Here, as test case, we studied a congeneric set of ligands that bind to a structurally unresolved G protein-coupled receptor (GPCR), the inactive human adenosine A3 receptor (hA3R). We tested three available homology models from which two have been generated from experimental structures of hA1R or hA2AR and one model was a multistate alphafold 2 (AF2)-derived model. We applied alchemical calculations with thermodynamic integration coupled with molecular dynamics (TI/MD) simulations to calculate the experimental relative binding free energies and residence time (τ)-random accelerated MD (τ-RAMD) simulations to calculate the relative residence times (RTs) for antagonists. While the TI/MD calculations produced, for the three homology models, good Pearson correlation coefficients, correspondingly, r = 0.74, 0.62, and 0.67 and mean unsigned error (mue) values of 0.94, 1.31, and 0.81 kcal mol-1, the τ-RAMD method showed r = 0.92 and 0.52 for the first two models but failed to produce accurate results for the multistate AF2-derived model. With subsequent optimization of the AF2-derived model by reorientation of the side chain of R1735.34 located in the extracellular loop 2 (EL2) that blocked ligand's unbinding, the computational model showed r = 0.84 for kinetic data and improved performance for thermodynamic data (r = 0.81, mue = 0.56 kcal mol-1). Overall, after refining the multistate AF2 model with physics-based tools, we were able to show a strong correlation between predicted and experimental ligand relative residence times and affinities, achieving a level of accuracy comparable to an experimental structure. The computational workflow used can be applied to other receptors, helping to rank candidate drugs in a congeneric series and enabling the prioritization of leads with stronger binding affinities and longer residence times.
Collapse
Affiliation(s)
- Margarita Stampelou
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Graham Ladds
- Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, U.K
| | - Antonios Kolocouris
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| |
Collapse
|
8
|
Duvail M, Moreno Martinez D, Žiberna L, Guillam E, Dufrêche JF, Guilbaud P. Modeling Lanthanide Ions in Solution: A Versatile Force Field in Aqueous and Organic Solvents. J Chem Theory Comput 2024. [PMID: 38221754 DOI: 10.1021/acs.jctc.3c01162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
In this paper, we propose a new nonpolarizable force field for describing the Ln3+ (Ln = lanthanide) series based on a 12-6-4 Lennard-Jones potential. The development of the force field was performed in pure water by adjusting both the ion-oxygen distance and the hydration free energy. This force field accurately reproduces the Ln3+ hydration properties through the series, especially the coordination number that is hardly accessible using a nonpolarizable force field. Then, the validity and the transferability of the current force field were evaluated for two different systems containing Ln3+ in various solvents, namely, 0.1 mol L-1 La(NO3)3 salts in methanol and Eu(NO3)3 salts in solvent organic phases composed of DMDOHEMA molecules in n-heptane. The good agreement between our simulations and the data available in the literature confirms the accuracy of the force field for describing the lanthanide cations in both aqueous and nonaqueous media.
Collapse
Affiliation(s)
- Magali Duvail
- ICSM, University of Montpellier, CEA, CNRS, ENSCM, 30207 Bagnols-sur-Cèze, France
| | - Diego Moreno Martinez
- CEA, DES, ISEC, DMRC, LILA, University of Montpellier, Marcoule, 30207 Bagnols-sur-Cèze, France
| | - Lara Žiberna
- ICSM, University of Montpellier, CEA, CNRS, ENSCM, 30207 Bagnols-sur-Cèze, France
| | - Erwann Guillam
- ICSM, University of Montpellier, CEA, CNRS, ENSCM, 30207 Bagnols-sur-Cèze, France
| | | | - Philippe Guilbaud
- CEA, DES, ISEC, DMRC, University of Montpellier, Marcoule, 30207 Bagnols-sur-Cèze, France
| |
Collapse
|
9
|
Chen L, Wu Y, Wu C, Silveira A, Sherman W, Xu H, Gallicchio E. Performance and Analysis of the Alchemical Transfer Method for Binding-Free-Energy Predictions of Diverse Ligands. J Chem Inf Model 2024; 64:250-264. [PMID: 38147877 DOI: 10.1021/acs.jcim.3c01705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2023]
Abstract
The Alchemical Transfer Method (ATM) is herein validated against the relative binding-free energies (RBFEs) of a diverse set of protein-ligand complexes. We employed a streamlined setup workflow, a bespoke force field, and AToM-OpenMM software to compute the RBFEs of the benchmark set prepared by Schindler and collaborators at Merck KGaA. This benchmark set includes examples of standard small R-group ligand modifications as well as more challenging scenarios, such as large R-group changes, scaffold hopping, formal charge changes, and charge-shifting transformations. The novel coordinate perturbation scheme and a dual-topology approach of ATM address some of the challenges of single-topology alchemical RBFE methods. Specifically, ATM eliminates the need for splitting electrostatic and Lennard-Jones interactions, atom mapping, defining ligand regions, and postcorrections for charge-changing perturbations. Thus, ATM is simpler and more broadly applicable than conventional alchemical methods, especially for scaffold-hopping and charge-changing transformations. Here, we performed well over 500 RBFE calculations for eight protein targets and found that ATM achieves accuracy comparable to that of existing state-of-the-art methods, albeit with larger statistical fluctuations. We discuss insights into the specific strengths and weaknesses of the ATM method that will inform future deployments. This study confirms that ATM can be applied as a production tool for RBFE predictions across a wide range of perturbation types within a unified, open-source framework.
Collapse
Affiliation(s)
- Lieyang Chen
- Roivant Sciences, 151 W 42nd Street, 15th Floor, New York, New York 10036, United States
| | - Yujie Wu
- Roivant Sciences, 151 W 42nd Street, 15th Floor, New York, New York 10036, United States
- Atommap Corporation, New York, New York 10017, United States
| | - Chuanjie Wu
- Roivant Sciences, 151 W 42nd Street, 15th Floor, New York, New York 10036, United States
| | - Ana Silveira
- Psivant Therapeutics, 451 D Street, Boston, Massachusetts 02210, United States
| | - Woody Sherman
- Psivant Therapeutics, 451 D Street, Boston, Massachusetts 02210, United States
| | - Huafeng Xu
- Roivant Sciences, 151 W 42nd Street, 15th Floor, New York, New York 10036, United States
- Atommap Corporation, New York, New York 10017, United States
| | - Emilio Gallicchio
- Department of Chemistry and Biochemistry, Brooklyn College of the City University of New York, New York, New York 11210, United States
- Ph.D. Program in Chemistry, The Graduate Center of the City University of New York, New York, New York 10016, United States
- Ph.D. Program in Biochemistry, The Graduate Center of the City University of New York, New York, New York 10016, United States
| |
Collapse
|
10
|
Niu T, He X, Han F, Wang L, Wang J. Development and test of highly accurate endpoint free energy methods. 3: partition coefficient prediction using a Poisson-Boltzmann method combined with a solvent accessible surface area model for SAMPL challenges. Phys Chem Chem Phys 2023; 26:85-94. [PMID: 38053433 PMCID: PMC10754273 DOI: 10.1039/d3cp04174c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
Accurately predicting solvation free energy is the key to predict protein-ligand binding free energy. In addition, the partition coefficient (log P), which is an important physicochemical property that determines the distribution of a drug in vivo, can be derived directly from transfer free energies, i.e., the difference between solvation free energies (SFEs) in different solvents. Within the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) 9 challenge, we applied the Poisson-Boltzmann (PB) surface area (SA) approach to predict the toluene/water transfer free energy and partition coefficient (log Ptoluene/water) from SFEs. For each solute, only a single conformation automatically generated by the free software Open Babel was used. The PB calculation directly adopts our previously optimized boundary definition - a set of general AMBER force field 2 (GAFF2) atom-type based sphere radii for solute atoms. For the non-polar SA model, we newly developed the solvent-related molecular surface tension parameters γ and offset b for toluene and cyclohexane targeting experimental SFEs. This approach yielded the highest predictive accuracy in terms of root mean square error (RMSE) of 1.52 kcal mol-1 in transfer free energy for 16 small drug molecules among all 18 submissions in the SAMPL9 blind prediction challenge. The re-evaluation of the challenge set using multi-conformation strategies based on molecular dynamics (MD) simulations further reduces the prediction RMSE to 1.33 kcal mol-1. At the same time, an additional evaluation of our PBSA method on the SAMPL5 cyclohexane/water distribution coefficient (log Dcyclohexane/water) prediction revealed that our model outperformed COSMO-RS, the best submission model with RMSEPBSA = 1.88 versus RMSECOSMO-RS = 2.11 log units. Two external log Ptoluene/water and log Pcyclohexane/water datasets that contain 110 and 87 data points, respectively, are collected for extra validation and provide an in-depth insight into the error source of the PBSA method.
Collapse
Affiliation(s)
- Taoyu Niu
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| | - Xibing He
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| | - Fengyang Han
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| | - Luxuan Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| | - Junmei Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| |
Collapse
|
11
|
York DM. Modern Alchemical Free Energy Methods for Drug Discovery Explained. ACS PHYSICAL CHEMISTRY AU 2023; 3:478-491. [PMID: 38034038 PMCID: PMC10683484 DOI: 10.1021/acsphyschemau.3c00033] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 09/12/2023] [Accepted: 09/13/2023] [Indexed: 12/02/2023]
Abstract
This Perspective provides a contextual explanation of the current state-of-the-art alchemical free energy methods and their role in drug discovery as well as highlights select emerging technologies. The narrative attempts to answer basic questions about what goes on "under the hood" in free energy simulations and provide general guidelines for how to run simulations and analyze the results. It is the hope that this work will provide a valuable introduction to students and scientists in the field.
Collapse
Affiliation(s)
- Darrin M. York
- Laboratory for Biomolecular
Simulation Research, Institute for Quantitative Biomedicine, and Department
of Chemistry and Chemical Biology, Rutgers
University, Piscataway, New Jersey 08854, United States
| |
Collapse
|
12
|
Stones AE, Aarts DGAL. Measuring many-body distribution functions in fluids using test-particle insertion. J Chem Phys 2023; 159:194502. [PMID: 37975484 DOI: 10.1063/5.0172664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 10/19/2023] [Indexed: 11/19/2023] Open
Abstract
We derive a hierarchy of equations, which allow a general n-body distribution function to be measured by test-particle insertion of between 1 and n particles. We apply it to measure the pair and three-body distribution functions in a simple fluid using snapshots from Monte Carlo simulations in the grand canonical ensemble. The resulting distribution functions obtained from insertion methods are compared with the conventional distance-histogram method: the insertion approach is shown to overcome the drawbacks of the histogram method, offering enhanced structural resolution and a more straightforward normalization. At high particle densities, the insertion method starts breaking down, which can be delayed by utilizing the underlying hierarchical structure of the insertion method. Our method will be especially useful in characterizing the structure of inhomogeneous fluids and investigating closure approximations in liquid state theory.
Collapse
Affiliation(s)
- Adam Edward Stones
- Department of Chemistry, Physical and Theoretical Chemistry Laboratory, University of Oxford, Oxford OX1 3QZ, United Kingdom
| | - Dirk G A L Aarts
- Department of Chemistry, Physical and Theoretical Chemistry Laboratory, University of Oxford, Oxford OX1 3QZ, United Kingdom
| |
Collapse
|
13
|
Bode J, Raabe G. Molecular dynamics studies of the solubility behavior of carbon dioxide (CO 2 ), difluoromethane (R-32), 1-chloro-3,3,3-trifluoropropene (R-1233zd(E)) and 2,3,3,3-tetrafluoro-1-propene (R-1234yf) in pentaerythritol tetra(2-ethylhexanoate) (PEB8), pentaerythritol tetrabutyrate (PEC4) and pentaerythritol tetraoctanoate (PEC8). J Comput Chem 2023; 44:2274-2283. [PMID: 37489606 DOI: 10.1002/jcc.27196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 07/05/2023] [Accepted: 07/07/2023] [Indexed: 07/26/2023]
Abstract
To reduce the climate impact of thermal engines such as heat pumps or refrigeration machines, refrigerants with a low global warming potential need to be paired with fitting lubricants. As the contamination of those liquid components influences the efficiency and lifetime of these machines, knowledge about their solubility behavior is of great interest. Molecular simulations offer mighty tools to investigate these solubilities while giving structural insight into the systems. Here the solubility behavior of CO2 , R-32, R-1233zd(E), and R-1234yf in PEB8, PEC4, and PEC8 is compared through the solvation free energy ∆GSolv obtained by molecular dynamics simulations. To derive ∆GSolv at low computational cost, an iterative method is used to find an optimal number and distribution of intermediate states. The resulting distributions are investigated with regard to different parameters of the employed softcore-potential. ∆GSolv values for the different refrigerant-lubricant pairings at different temperatures are provided, followed by a structural analysis.
Collapse
Affiliation(s)
- Jan Bode
- Institute of Thermodynamics, Technische Universität Braunschweig, Braunschweig, Germany
| | - Gabriele Raabe
- Institute of Thermodynamics, Technische Universität Braunschweig, Braunschweig, Germany
| |
Collapse
|
14
|
Horton JT, Boothroyd S, Behara PK, Mobley DL, Cole DJ. A transferable double exponential potential for condensed phase simulations of small molecules. DIGITAL DISCOVERY 2023; 2:1178-1187. [PMID: 38013814 PMCID: PMC10408570 DOI: 10.1039/d3dd00070b] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 07/07/2023] [Indexed: 11/29/2023]
Abstract
The Lennard-Jones potential is the most widely-used function for the description of non-bonded interactions in transferable force fields for the condensed phase. This is not because it has an optimal functional form, but rather it is a legacy resulting from when computational expense was a major consideration and this potential was particularly convenient numerically. At present, it persists because the effort that would be required to re-write molecular modelling software and train new force fields has, until now, been prohibitive. Here, we present Smirnoff-plugins as a flexible framework to extend the Open Force Field software stack to allow custom force field functional forms. We deploy Smirnoff-plugins with the automated Open Force Field infrastructure to train a transferable, small molecule force field based on the recently-proposed double exponential functional form, on over 1000 experimental condensed phase properties. Extensive testing of the resulting force field shows improvements in transfer free energies, with acceptable conformational energetics, run times and convergence properties compared to state-of-the-art Lennard-Jones based force fields.
Collapse
Affiliation(s)
- Joshua T Horton
- School of Natural and Environmental Sciences, Newcastle University Newcastle upon Tyne NE1 7RU UK
| | | | - Pavan Kumar Behara
- Department of Pharmaceutical Sciences, University of California Irvine California 92697 USA
| | - David L Mobley
- Department of Pharmaceutical Sciences, University of California Irvine California 92697 USA
- Department of Chemistry, University of California Irvine California 92697 USA
| | - Daniel J Cole
- School of Natural and Environmental Sciences, Newcastle University Newcastle upon Tyne NE1 7RU UK
| |
Collapse
|
15
|
Yu Y, Wang Z, Wang L, Wang Q, Tang R, Xiang S, Deng Q, Hou T, Sun H. Deciphering the Shared and Specific Drug Resistance Mechanisms of Anaplastic Lymphoma Kinase via Binding Free Energy Computation. RESEARCH (WASHINGTON, D.C.) 2023; 6:0170. [PMID: 37342628 PMCID: PMC10278961 DOI: 10.34133/research.0170] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 05/25/2023] [Indexed: 06/23/2023]
Abstract
Anaplastic lymphoma kinase (ALK), a tyrosine receptor kinase, has been proven to be associated with the occurrence of numerous malignancies. Although there have been already at least 3 generations of ALK inhibitors approved by FDA or in clinical trials, the occurrence of various mutations seriously attenuates the effectiveness of the drugs. Unfortunately, most of the drug resistance mechanisms still remain obscure. Therefore, it is necessary to reveal the bottom reasons of the drug resistance mechanisms caused by the mutations. In this work, on the basis of verifying the accuracy of 2 main kinds of binding free energy calculation methodologies [end-point method of Molecular Mechanics with Poisson-Boltzmann/Generalized Born and Surface Area (MM/PB(GB)SA) and alchemical method of Thermodynamic Integration (TI)], we performed a systematic analysis on the ALK systems to explore the underlying shared and specific drug resistance mechanisms, covering the one-drug-multiple-mutation and multiple-drug-one-mutation cases. Through conventional molecular dynamics (cMD) simulation in conjunction with MM/PB(GB)SA and umbrella sampling (US) in conjunction with contact network analysis (CNA), the resistance mechanisms of the in-pocket, out-pocket, and multiple-site mutations were revealed. Especially for the out-pocket mutation, a possible transfer chain of the mutation effect was revealed, and the reason why different drugs exhibited various sensitivities to the same mutation was also uncovered. The proposed mechanisms may be prevalent in various drug resistance cases.
Collapse
Affiliation(s)
- Yang Yu
- Department of Medicinal Chemistry,
China Pharmaceutical University, Nanjing 210009, Jiangsu, P. R. China
| | - Zhe Wang
- Innovation Institute for Artificial Intelligence in Medicine ofZhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, P. R. China
| | - Lingling Wang
- Department of Medicinal Chemistry,
China Pharmaceutical University, Nanjing 210009, Jiangsu, P. R. China
| | - Qinghua Wang
- Department of Medicinal Chemistry,
China Pharmaceutical University, Nanjing 210009, Jiangsu, P. R. China
| | - Rongfan Tang
- Department of Medicinal Chemistry,
China Pharmaceutical University, Nanjing 210009, Jiangsu, P. R. China
| | - Sutong Xiang
- Department of Medicinal Chemistry,
China Pharmaceutical University, Nanjing 210009, Jiangsu, P. R. China
| | - Qirui Deng
- Department of Medicinal Chemistry,
China Pharmaceutical University, Nanjing 210009, Jiangsu, P. R. China
| | - Tingjun Hou
- Innovation Institute for Artificial Intelligence in Medicine ofZhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, P. R. China
| | - Huiyong Sun
- Department of Medicinal Chemistry,
China Pharmaceutical University, Nanjing 210009, Jiangsu, P. R. China
| |
Collapse
|
16
|
Vögele J, Duchardt-Ferner E, Kruse H, Zhang Z, Sponer J, Krepl M, Wöhnert J. Structural and dynamic effects of pseudouridine modifications on noncanonical interactions in RNA. RNA (NEW YORK, N.Y.) 2023; 29:790-807. [PMID: 36868785 PMCID: PMC10187676 DOI: 10.1261/rna.079506.122] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 02/10/2023] [Indexed: 05/18/2023]
Abstract
Pseudouridine is the most frequently naturally occurring RNA modification, found in all classes of biologically functional RNAs. Compared to uridine, pseudouridine contains an additional hydrogen bond donor group and is therefore widely regarded as a structure stabilizing modification. However, the effects of pseudouridine modifications on the structure and dynamics of RNAs have so far only been investigated in a limited number of different structural contexts. Here, we introduced pseudouridine modifications into the U-turn motif and the adjacent U:U closing base pair of the neomycin-sensing riboswitch (NSR)-an extensively characterized model system for RNA structure, ligand binding, and dynamics. We show that the effects of replacing specific uridines with pseudouridines on RNA dynamics crucially depend on the exact location of the replacement site and can range from destabilizing to locally or even globally stabilizing. By using a combination of NMR spectroscopy, MD simulations and QM calculations, we rationalize the observed effects on a structural and dynamical level. Our results will help to better understand and predict the consequences of pseudouridine modifications on the structure and function of biologically important RNAs.
Collapse
Affiliation(s)
- Jennifer Vögele
- Institute of Molecular Biosciences and Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, 60438 Frankfurt, Germany
| | - Elke Duchardt-Ferner
- Institute of Molecular Biosciences and Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, 60438 Frankfurt, Germany
| | - Holger Kruse
- Institute of Biophysics of the Czech Academy of Sciences, 612 65 Brno, Czech Republic
| | - Zhengyue Zhang
- Institute of Biophysics of the Czech Academy of Sciences, 612 65 Brno, Czech Republic
- CEITEC-Central European Institute of Technology, Masaryk University, 625 00 Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic
| | - Jiri Sponer
- Institute of Biophysics of the Czech Academy of Sciences, 612 65 Brno, Czech Republic
| | - Miroslav Krepl
- Institute of Biophysics of the Czech Academy of Sciences, 612 65 Brno, Czech Republic
| | - Jens Wöhnert
- Institute of Molecular Biosciences and Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, 60438 Frankfurt, Germany
| |
Collapse
|
17
|
Stampolaki M, Stylianakis I, Zgurskaya HI, Kolocouris A. Study of SQ109 analogs binding to mycobacterium MmpL3 transporter using MD simulations and alchemical relative binding free energy calculations. J Comput Aided Mol Des 2023; 37:245-264. [PMID: 37129848 DOI: 10.1007/s10822-023-00504-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Accepted: 04/03/2023] [Indexed: 05/03/2023]
Abstract
N-geranyl-N΄-(2-adamantyl)ethane-1,2-diamine (SQ109) is a tuberculosis drug that has high potency against Mycobacterium tuberculosis (Mtb) and may function by blocking cell wall biosynthesis. After the crystal structure of MmpL3 from Mycobacterium smegmatis in complex with SQ109 became available, it was suggested that SQ109 inhibits Mmpl3 mycolic acid transporter. Here, we showed using molecular dynamics (MD) simulations that the binding profile of nine SQ109 analogs with inhibitory potency against Mtb and alkyl or aryl adducts at C-2 or C-1 adamantyl carbon to MmpL3 was consistent with the X-ray structure of MmpL3 - SQ109 complex. We showed that rotation of SQ109 around carbon-carbon bond in the monoprotonated ethylenediamine unit favors two gauche conformations as minima in water and lipophilic solvent using DFT calculations as well as inside the transporter's binding area using MD simulations. The binding assays in micelles suggested that the binding affinity of the SQ109 analogs was increased for the larger, more hydrophobic adducts, which was consistent with our results from MD simulations of the SQ109 analogues suggesting that sizeable C-2 adamantyl adducts of SQ109 can fill a lipophilic region between Y257, Y646, F260 and F649 in MmpL3. This was confirmed quantitatively by our calculations of the relative binding free energies using the thermodynamic integration coupled with MD simulations method with a mean assigned error of 0.74 kcal mol-1 compared to the experimental values.
Collapse
Affiliation(s)
- Marianna Stampolaki
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771, Athens, Greece
- Department of NMR-Based Structural Biology, Max Planck Institute for Multidisciplinary Sciences, Am Faßberg 11, 37077, Göttingen, Germany
| | - Ioannis Stylianakis
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771, Athens, Greece
| | - Helen I Zgurskaya
- Department of Chemistry and Biochemistry, University of Oklahoma, Stephenson Life Sciences Research Center, 101 Stephenson Parkway, Norman, OK, 73019-5251, USA
| | - Antonios Kolocouris
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771, Athens, Greece.
| |
Collapse
|
18
|
Plé T, Mauger N, Adjoua O, Inizan TJ, Lagardère L, Huppert S, Piquemal JP. Routine Molecular Dynamics Simulations Including Nuclear Quantum Effects: From Force Fields to Machine Learning Potentials. J Chem Theory Comput 2023; 19:1432-1445. [PMID: 36856658 DOI: 10.1021/acs.jctc.2c01233] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2023]
Abstract
We report the implementation of a multi-CPU and multi-GPU massively parallel platform dedicated to the explicit inclusion of nuclear quantum effects (NQEs) in the Tinker-HP molecular dynamics (MD) package. The platform, denoted Quantum-HP, exploits two simulation strategies: the Ring-Polymer Molecular Dynamics (RPMD) that provides exact structural properties at the cost of a MD simulation in an extended space of multiple replicas and the adaptive Quantum Thermal Bath (adQTB) that imposes the quantum distribution of energy on a classical system via a generalized Langevin thermostat and provides computationally affordable and accurate (though approximate) NQEs. We discuss some implementation details, efficient numerical schemes, and parallelization strategies and quickly review the GPU acceleration of our code. Our implementation allows an efficient inclusion of NQEs in MD simulations for very large systems, as demonstrated by scaling tests on water boxes with more than 200,000 atoms (simulated using the AMOEBA polarizable force field). We test the compatibility of the approach with Tinker-HP's recently introduced Deep-HP machine learning potentials module by computing water properties using the DeePMD potential with adQTB thermostatting. Finally, we show that the platform is also compatible with the alchemical free energy estimation capabilities of Tinker-HP and fast enough to perform simulations. Therefore, we study how NQEs affect the hydration free energy of small molecules solvated with the recently developed Q-AMOEBA water force field. Overall, the Quantum-HP platform allows users to perform routine quantum MD simulations of large condensed-phase systems and will help to shed new light on the quantum nature of important interactions in biological matter.
Collapse
Affiliation(s)
- Thomas Plé
- Sorbonne Université, LCT, UMR 7616 CNRS, F-75005 Paris, France
| | - Nastasia Mauger
- Sorbonne Université, LCT, UMR 7616 CNRS, F-75005 Paris, France
| | - Olivier Adjoua
- Sorbonne Université, LCT, UMR 7616 CNRS, F-75005 Paris, France
| | | | - Louis Lagardère
- Sorbonne Université, LCT, UMR 7616 CNRS, F-75005 Paris, France
| | - Simon Huppert
- Institut des Nanosciences de Paris (INSP), CNRS UMR 7588, and Sorbonne Université, F-75005 Paris, France
| | - Jean-Philip Piquemal
- Sorbonne Université, LCT, UMR 7616 CNRS, F-75005 Paris, France.,Institut Universitaire de France, 75005 Paris, France.,Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| |
Collapse
|
19
|
Solubility Determination and Comprehensive Analysis of the New Heat-Resistant Energetic Material TNBP. Molecules 2023; 28:molecules28062424. [PMID: 36985396 PMCID: PMC10054621 DOI: 10.3390/molecules28062424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 02/18/2023] [Accepted: 02/27/2023] [Indexed: 03/09/2023] Open
Abstract
To improve the crystal quality of 4,8-bis(2,4,6-trinitrophenyl)difurazolo [3,4-b:3′,4′-e] pyrazine (TNBP), the solubility of TNBP in organic solvents (six pure and four mixed solvents) was determined by the laser monitoring technique from 293.15 to 353.15 K. The results showed that the solubility was positively correlated with the increase in the experimental temperature and the main solvent content, except for the co-solvent phenomenon in the DMSO + ethyl acetate solvent mixture. To explain the dissolution behavior of TNBP, the KAT-SER model was analyzed for pure solvent systems, and it was found that hydrogen bonding alkalinity and self-cohesiveness were the main influencing factors. The free energy of solvation and radial distribution function of TNBP in mixed solvents were also obtained by molecular dynamics simulation, and the effect of solute–solvent and solvent–solvent interactions on the solubility trend was analyzed. The experimental data were correlated using three empirical equations (van’t Hoff equation, modified Apelblat equation, and λh equation), and the deviation analysis showed the good applicability of the modified Apelblat model. Furthermore, the dissolution of TNBP was heat-absorbing and not spontaneous, according to the thermodynamic characteristics estimated by the van’t Hoff equation.
Collapse
|
20
|
Sun Y, He X, Hou T, Cai L, Man VH, Wang J. Development and test of highly accurate endpoint free energy methods. 1: Evaluation of ABCG2 charge model on solvation free energy prediction and optimization of atom radii suitable for more accurate solvation free energy prediction by the PBSA method. J Comput Chem 2023; 44:1334-1346. [PMID: 36807356 DOI: 10.1002/jcc.27089] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 12/22/2022] [Accepted: 01/29/2023] [Indexed: 02/23/2023]
Abstract
Accurate estimation of solvation free energy (SFE) lays the foundation for accurate prediction of binding free energy. The Poisson-Boltzmann (PB) or generalized Born (GB) combined with surface area (SA) continuum solvation method (PBSA and GBSA) have been widely used in SFE calculations because they can achieve good balance between accuracy and efficiency. However, the accuracy of these methods can be affected by several factors such as the charge models, polar and nonpolar SFE calculation methods and the atom radii used in the calculation. In this work, the performance of the ABCG2 (AM1-BCC-GAFF2) charge model as well as other two charge models, that is, RESP (Restrained Electrostatic Potential) and AM1-BCC (Austin Model 1-bond charge corrections), on the SFE prediction of 544 small molecules in water by PBSA/GBSA was evaluated. In order to improve the performance of the PBSA prediction based on the ABCG2 charge, we further explored the influence of atom radii on the prediction accuracy and yielded a set of atom radius parameters for more accurate SFE prediction using PBSA based on the ABCG2/GAFF2 by reproducing the thermodynamic integration (TI) calculation results. The PB radius parameters of carbon, oxygen, sulfur, phosphorus, chloride, bromide and iodine, were adjusted. New atom types, on, oi, hn1, hn2, hn3, were introduced to further improve the fitting performance. Then, we tuned the parameters in the nonpolar SFE model using the experimental SFE data and the PB calculation results. By adopting the new radius parameters and new nonpolar SFE model, the root mean square error (RMSE) of the SFE calculation for the 544 molecules decreased from 2.38 to 1.05 kcal/mol. Finally, the new radius parameters were applied in the prediction of protein-ligand binding free energies using the MM-PBSA method. For the eight systems tested, we could observe higher correlation between the experiment data and calculation results and smaller prediction errors for the absolute binding free energies, demonstrating that our new radius parameters can improve the free energy calculation using the MM-PBSA method.
Collapse
Affiliation(s)
- Yuchen Sun
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Xibing He
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Tingjun Hou
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Lianjin Cai
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Viet Hoag Man
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Junmei Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| |
Collapse
|
21
|
Liu Q, Perez A. Assessing a computational pipeline to identify binding motifs to the α2 β1 integrin. Front Chem 2023; 11:1107400. [PMID: 36860646 PMCID: PMC9968975 DOI: 10.3389/fchem.2023.1107400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 01/27/2023] [Indexed: 02/16/2023] Open
Abstract
Integrins in the cell surface interact with functional motifs found in the extracellular matrix (ECM) that queue the cell for biological actions such as migration, adhesion, or growth. Multiple fibrous proteins such as collagen or fibronectin compose the ECM. The field of biomechanical engineering often deals with the design of biomaterials compatible with the ECM that will trigger cellular response (e.g., in tissue regeneration). However, there are a relative few number of known integrin binding motifs compared to all the possible peptide epitope sequences available. Computational tools could help identify novel motifs, but have been limited by the challenges in modeling the binding to integrin domains. We revisit a series of traditional and novel computational tools to assess their performance in identifying novel binding motifs for the I-domain of the α2β1 integrin.
Collapse
Affiliation(s)
- Qianchen Liu
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, United States
| | | |
Collapse
|
22
|
Bhatta T, Khanal P, Khanal SP, Adhikari NP. Thermodynamics and Transport Properties of Valine and Cysteine Peptides in Water. J Mol Liq 2023. [DOI: 10.1016/j.molliq.2023.121472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
|
23
|
Lee TS, Tsai HC, Ganguly A, York DM. ACES: Optimized Alchemically Enhanced Sampling. J Chem Theory Comput 2023; 19:10.1021/acs.jctc.2c00697. [PMID: 36630672 PMCID: PMC10333454 DOI: 10.1021/acs.jctc.2c00697] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
We present an alchemical enhanced sampling (ACES) method implemented in the GPU-accelerated AMBER free energy MD engine. The methods hinges on the creation of an "enhanced sampling state" by reducing or eliminating selected potential energy terms and interactions that lead to kinetic traps and conformational barriers while maintaining those terms that curtail the need to otherwise sample large volumes of phase space. For example, the enhanced sampling state might involve transforming regions of a ligand and/or protein side chain into a noninteracting "dummy state" with internal electrostatics and torsion angle terms turned off. The enhanced sampling state is connected to a real-state end point through a Hamiltonian replica exchange (HREMD) framework that is facilitated by newly developed alchemical transformation pathways and smoothstep softcore potentials. This creates a counterdiffusion of real and enhanced-sampling states along the HREMD network. The effect of a differential response of the environment to the real and enhanced-sampling states is minimized by leveraging the dual topology framework in AMBER to construct a counterbalancing HREMD network in the opposite alchemical direction with the same (or similar) real and enhanced sampling states at inverted end points. The method has been demonstrated in a series of test cases of increasing complexity where traditional MD, and in several cases alternative REST2-like enhanced sampling methods, are shown to fail. The hydration free energy for acetic acid was shown to be independent of the starting conformation, and the values for four additional edge case molecules from the FreeSolv database were shown to have a significantly closer agreement with experiment using ACES. The method was further able to handle different rotamer states in a Cdk2 ligand identified as fractionally occupied in crystal structures. Finally, ACES was applied to T4-lysozyme and demonstrated that the side chain distribution of V111χ1 could be reliably reproduced for the apo state, bound to p-xylene, and in p-xylene→ benzene transformations. In these cases, the ACES method is shown to be highly robust and superior to a REST2-like enhanced sampling implementation alone.
Collapse
Affiliation(s)
- Tai-Sung Lee
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Hsu-Chun Tsai
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Abir Ganguly
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Darrin M. York
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| |
Collapse
|
24
|
Tsai HC, Lee TS, Ganguly A, Giese TJ, Ebert MCCJC, Labute P, Merz KM, York DM. AMBER Free Energy Tools: A New Framework for the Design of Optimized Alchemical Transformation Pathways. J Chem Theory Comput 2023; 19:10.1021/acs.jctc.2c00725. [PMID: 36622640 PMCID: PMC10329732 DOI: 10.1021/acs.jctc.2c00725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
We develop a framework for the design of optimized alchemical transformation pathways in free energy simulations using nonlinear mixing and a new functional form for so-called "softcore" potentials. We describe the implementation and testing of this framework in the GPU-accelerated AMBER software suite. The new optimized alchemical transformation pathways integrate a number of important features, including (1) the use of smoothstep functions to stabilize behavior near the transformation end points, (2) consistent power scaling of Coulomb and Lennard-Jones (LJ) interactions with unitless control parameters to maintain balance of electrostatic attractions and exchange repulsions, (3) pairwise form based on the LJ contact radius for the effective interaction distance with separation-shifted scaling, and (4) rigorous smoothing of the potential at the nonbonded cutoff boundary. The new softcore potential form is combined with smoothly transforming nonlinear λ weights for mixing specific potential energy terms, along with flexible λ-scheduling features, to enable robust and stable alchemical transformation pathways. The resulting pathways are demonstrated and tested, and shown to be superior to the traditional methods in terms of numerical stability and minimal variance of the free energy estimates for all cases considered. The framework presented here can be used to design new alchemical enhanced sampling methods, and leveraged in robust free energy workflows for large ligand data sets.
Collapse
Affiliation(s)
- Hsu-Chun Tsai
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Tai-Sung Lee
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Abir Ganguly
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Timothy J. Giese
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Maximilian CCJC Ebert
- Congruence Therapeutics, 7171 Rue Frederick Banting #117, Saint-Laurent, Quebec, Canada H4S 1Z9
| | - Paul Labute
- Chemical Computing Group ULC, 910-1010 Sherbrooke West, Montreal, Quebec, Canada H3A 2R7
| | - Kenneth M. Merz
- Department of Chemistry and Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Darrin M. York
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| |
Collapse
|
25
|
Matsunaga Y, Kamiya M, Oshima H, Jung J, Ito S, Sugita Y. Use of multistate Bennett acceptance ratio method for free-energy calculations from enhanced sampling and free-energy perturbation. Biophys Rev 2022; 14:1503-1512. [PMID: 36659993 PMCID: PMC9842838 DOI: 10.1007/s12551-022-01030-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 12/01/2022] [Indexed: 12/15/2022] Open
Abstract
Multistate Bennett acceptance ratio (MBAR) works as a method to analyze molecular dynamics (MD) simulation data after the simulations have been finished. It is widely used to estimate free-energy changes between different states and averaged properties at the states of interest. MBAR allows us to treat a wide range of states from those at different temperature/pressure to those with different model parameters. Due to the broad applicability, the MBAR equations are rather difficult to apply for free-energy calculations using different types of MD simulations including enhanced conformational sampling methods and free-energy perturbation. In this review, we first summarize the basic theory of the MBAR equations and categorize the representative usages into the following four: (i) perturbation, (ii) scaling, (iii) accumulation, and (iv) full potential energy. For each, we explain how to prepare input data using MD simulation trajectories for solving the MBAR equations. MBAR is also useful to estimate reliable free-energy differences using MD trajectories based on a semi-empirical quantum mechanics/molecular mechanics (QM/MM) model and ab initio QM/MM energy calculations on the MD snapshots. We also explain how to use the MBAR software in the GENESIS package, which we call mbar_analysis, for the four representative cases. The proposed estimations of free-energy changes and thermodynamic averages are effective and useful for various biomolecular systems.
Collapse
Affiliation(s)
- Yasuhiro Matsunaga
- grid.263023.60000 0001 0703 3735Graduate School of Science and Engineering, Saitama University, Saitama, Saitama 338-8570 Japan
| | - Motoshi Kamiya
- grid.467196.b0000 0001 2285 6123Institute for Molecular Science, Myodaiji, Okazaki, Aichi 444-8585 Japan
| | - Hiraku Oshima
- grid.508743.dLaboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047 Japan
| | - Jaewoon Jung
- grid.474693.bComputational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047 Japan
| | - Shingo Ito
- grid.7597.c0000000094465255Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198 Japan
| | - Yuji Sugita
- grid.508743.dLaboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047 Japan ,grid.474693.bComputational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047 Japan ,grid.7597.c0000000094465255Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198 Japan
| |
Collapse
|
26
|
Zhou Y, Li J, Baryshnikov G, Tu Y. Unraveling the Abnormal Molecular Mechanism of Suicide Inhibition of Cytochrome P450 3A4. J Chem Inf Model 2022; 62:6172-6181. [PMID: 36457253 PMCID: PMC9749025 DOI: 10.1021/acs.jcim.2c01035] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
Suicide inhibition of the CYP3A4 enzyme by a drug inactivates the enzyme in the drug biotransformation process and often shows safety concerns about the drug. Despite extensive experimental studies, the abnormal molecular mechanism of a suicide inhibitor that forms a covalent bond with the residue far away from the catalytically active center of CYP3A4 inactivating the enzyme remains elusive. Here, the authors used molecular simulation approaches to study in detail how diquinone methide (DQR), the metabolite product of raloxifene, unbinds from CYP3A4 and inactivates the enzyme at the atomistic level. The results clearly indicate that in one of the intermediate states formed in its unbinding process, DQR covalently binds to Cys239, a residue far away from the catalytically active center of CYP3A4, and hinders the substrate from entering or leaving the enzyme. This work therefore provides an unprecedented way of clarifying the abnormal mechanism of suicide inhibition of the CYP3A4 enzyme.
Collapse
Affiliation(s)
- Yang Zhou
- School of Pharmacy, Jinan University, 601 Huangpu Avenue West, Guangzhou510632, China.,Department of Theoretical Chemistry and Biology, KTH Royal Institute of Technology, 114 28Stockholm, Sweden
| | - Junhao Li
- Department of Theoretical Chemistry and Biology, KTH Royal Institute of Technology, 114 28Stockholm, Sweden
| | - Glib Baryshnikov
- Laboratory of Organic Electronics, Department of Science and Technology, Linköping University, 60174Norrköping, Sweden
| | - Yaoquan Tu
- Department of Theoretical Chemistry and Biology, KTH Royal Institute of Technology, 114 28Stockholm, Sweden
| |
Collapse
|
27
|
Molecular Basis for Non-Covalent, Non-Competitive FAAH Inhibition. Int J Mol Sci 2022; 23:ijms232415502. [PMID: 36555144 PMCID: PMC9779292 DOI: 10.3390/ijms232415502] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/01/2022] [Accepted: 12/03/2022] [Indexed: 12/13/2022] Open
Abstract
Fatty acid amide hydrolase (FAAH) plays a key role in the control of cannabinoid signaling and it represents a promising therapeutic strategy for the treatment of a wide range of diseases, including neuropathic pain and chronic inflammation. Starting from kinetics experiments carried out in our previous work for the most potent inhibitor 2-amino-3-chloropyridine amide (TPA14), we have investigated its non-competitive mechanism of action using molecular dynamics, thermodynamic integration and QM-MM/GBSA calculations. The computational studies highlighted the impact of mutations on the receptor binding pockets and elucidated the molecular basis of the non-competitive inhibition mechanism of TPA14, which prevents the endocannabinoid anandamide (AEA) from reaching its pro-active conformation. Our study provides a rationale for the design of non-competitive potent FAAH inhibitors for the treatment of neuropathic pain and chronic inflammation.
Collapse
|
28
|
Erkoc C, Yildirim E, Yurtsever M, Okay O. Roadmap to Design Mechanically Robust Copolymer Hydrogels Naturally Cross-Linked by Hydrogen Bonds. Macromolecules 2022. [DOI: 10.1021/acs.macromol.2c01469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Cagla Erkoc
- Department of Chemistry, Istanbul Technical University, Maslak, 34469 Istanbul, Turkey
| | - Erol Yildirim
- Department of Chemistry, Middle East Technical University, 06800 Ankara, Turkey
| | - Mine Yurtsever
- Department of Chemistry, Istanbul Technical University, Maslak, 34469 Istanbul, Turkey
| | - Oguz Okay
- Department of Chemistry, Istanbul Technical University, Maslak, 34469 Istanbul, Turkey
| |
Collapse
|
29
|
Gohda K. Conformational Analysis of the Loop-to-Helix Transition of the α-Helix3 Plastic Region in the N-Terminal Domain of Human Hsp90α by a Computational Biochemistry Approach. J Chem Inf Model 2022; 62:5699-5714. [PMID: 36278922 DOI: 10.1021/acs.jcim.2c00984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Hsp90 is a chaperone protein aiding in correct protein folding and attractive for drug discovery. The structure of human Hsp90α N-terminal domain (NTD) is intriguing since the α-helix3 region of the ATP-binding site in the NTD plastically changes its conformation, i.e., loop-out, loop-in, and helical conformations, according to the bound inhibitor type. The plastic region structure is known to influence the mode of inhibition-inhibitors bound to a helix have a longer residence time in the complex, which is a factor of in vivo-active drugs, compared with loop binders. In this study, we analyzed the loop-to-helix transition of the plastic region through binding of a helix binder by a computational biochemistry approach. To generate the helical transition from the loop, the resorcinol inhibitor C1 complexed with a loop-in structure was alchemically transformed to the C10 inhibitor, which is known as a helix binder. The loop in the C1 complex possesses Leu107 tightly binding to the hydrophobic subpocket, considered as a key residue for the plasticity. From 10 × 1 μs simulations after the alchemical transformation, the helical transition was observed with a 29% success rate. Conformational analysis of the simulations identified residues possibly associated with the helical transition. The implementation of additional simulations (dihedral-constrained and in silico mutant simulations) led to a statistically significant increase in the transition success rate to 78%, as observed in Asn105 psi-constrained simulation. Therefore, we concluded that the Asn105 psi dihedral angle is most likely involved in the helical transition by a change of the dihedral angle to gauche-negative.
Collapse
Affiliation(s)
- Keigo Gohda
- Computer-aided Molecular Modeling Research Center, Kansai (CAMM-Kansai), 3-32-302, Tsuto-Otsuka, Nishinomiya 663-8241, Japan
| |
Collapse
|
30
|
Wu H, Zhang Y, Chang P, Hao H, Zhai L, Wang B. Solubility, dissolution properties and molecular dynamic simulation of 2,6-bis(picrylamino)-3,5-dinitropyridine in pure and binary solvents. J Mol Liq 2022. [DOI: 10.1016/j.molliq.2022.120567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
|
31
|
Stampelou M, Suchankova A, Tzortzini E, Dhingra L, Barkan K, Lougiakis N, Marakos P, Pouli N, Ladds G, Kolocouris A. Dual A1/A3 Adenosine Receptor Antagonists: Binding Kinetics and Structure-Activity Relationship Studies Using Mutagenesis and Alchemical Binding Free Energy Calculations. J Med Chem 2022; 65:13305-13327. [PMID: 36173355 DOI: 10.1021/acs.jmedchem.2c01123] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Drugs targeting adenosine receptors (AR) can provide treatment for diseases. We report the identification of 7-(phenylamino)-pyrazolo[3,4-c]pyridines L2-L10, A15, and A17 as low-micromolar to low-nanomolar A1R/A3R dual antagonists, with 3-phenyl-5-cyano-7-(trimethoxyphenylamino)-pyrazolo[3,4-c]pyridine (A17) displaying the highest affinity at both receptors with a long residence time of binding, as determined using a NanoBRET-based assay. Two binding orientations of A17 produce stable complexes inside the orthosteric binding area of A1R in molecular dynamics (MD) simulations, and we selected the most plausible orientation based on the agreement with alanine mutagenesis supported by affinity experiments. Interestingly, for drug design purposes, the mutation of L2506.51 to alanine increased the binding affinity of A17 at A1R. We explored the structure-activity relationships against A1R using alchemical binding free energy calculations with the thermodynamic integration coupled with the MD simulation (TI/MD) method, applied on the whole G-protein-coupled receptor-membrane system, which showed a good agreement (r = 0.73) between calculated and experimental relative binding free energies.
Collapse
Affiliation(s)
- Margarita Stampelou
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Anna Suchankova
- Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, U.K
| | - Efpraxia Tzortzini
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Lakshiv Dhingra
- Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, U.K
| | - Kerry Barkan
- Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, U.K
| | - Nikolaos Lougiakis
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Panagiotis Marakos
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Nicole Pouli
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Graham Ladds
- Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, U.K
| | - Antonios Kolocouris
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| |
Collapse
|
32
|
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.
Collapse
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
| |
Collapse
|
33
|
Kumar Verma A, Govind Rajan A. Surface Roughness Explains the Observed Water Contact Angle and Slip Length on 2D Hexagonal Boron Nitride. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2022; 38:9210-9220. [PMID: 35866875 DOI: 10.1021/acs.langmuir.2c00972] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Hexagonal boron nitride (hBN) is a two-dimensional (2D) material that is currently being explored in a number of applications, such as atomically thin coatings, water desalination, and biological sensors. In many of these applications, the hBN surface comes into intimate contact with water. In this work, we investigate the wetting and frictional behavior of realistic 2D hBN surfaces with atomic-scale defects and roughness. We combine density functional theory calculations of the charge distribution inside hBN with free energy calculations using molecular dynamics simulations of the hBN-water interface. We find that the presence of surface roughness, but not that of vacancy defects, leads to remarkable agreement with the experimentally observed water contact angle of 66° on freshly synthesized, uncontaminated hBN. Not only that, the inclusion of surface roughness predicts with exceptional accuracy the experimental water slip length of ∼1 nm on hBN. Our results underscore the importance of considering realistic models of 2D materials with surface roughness while modeling nanomaterial-water interfaces in molecular simulations.
Collapse
Affiliation(s)
- Ashutosh Kumar Verma
- Department of Chemical Engineering, Indian Institute of Science, Bengaluru, Karnataka 560012, India
| | - Ananth Govind Rajan
- Department of Chemical Engineering, Indian Institute of Science, Bengaluru, Karnataka 560012, India
| |
Collapse
|
34
|
Zhu F, Bourguet FA, Bennett WFD, Lau EY, Arrildt KT, Segelke BW, Zemla AT, Desautels TA, Faissol DM. Large-scale application of free energy perturbation calculations for antibody design. Sci Rep 2022; 12:12489. [PMID: 35864134 PMCID: PMC9302960 DOI: 10.1038/s41598-022-14443-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 06/07/2022] [Indexed: 01/02/2023] Open
Abstract
Alchemical free energy perturbation (FEP) is a rigorous and powerful technique to calculate the free energy difference between distinct chemical systems. Here we report our implementation of automated large-scale FEP calculations, using the Amber software package, to facilitate antibody design and evaluation. In combination with Hamiltonian replica exchange, our FEP simulations aim to predict the effect of mutations on both the binding affinity and the structural stability. Importantly, we incorporate multiple strategies to faithfully estimate the statistical uncertainties in the FEP results. As a case study, we apply our protocols to systematically evaluate variants of the m396 antibody for their conformational stability and their binding affinity to the spike proteins of SARS-CoV-1 and SARS-CoV-2. By properly adjusting relevant parameters, the particle collapse problems in the FEP simulations are avoided. Furthermore, large statistical errors in a small fraction of the FEP calculations are effectively reduced by extending the sampling, such that acceptable statistical uncertainties are achieved for the vast majority of the cases with a modest total computational cost. Finally, our predicted conformational stability for the m396 variants is qualitatively consistent with the experimentally measured melting temperatures. Our work thus demonstrates the applicability of FEP in computational antibody design.
Collapse
Affiliation(s)
- Fangqiang Zhu
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, USA.
| | - Feliza A Bourguet
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - William F D Bennett
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - Edmond Y Lau
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - Kathryn T Arrildt
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - Brent W Segelke
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - Adam T Zemla
- Global Security Computing Division, Computing Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - Thomas A Desautels
- Computational Engineering Division, Engineering Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - Daniel M Faissol
- Computational Engineering Division, Engineering Directorate, Lawrence Livermore National Laboratory, Livermore, USA.
| |
Collapse
|
35
|
Oshima H, Sugita Y. Modified Hamiltonian in FEP Calculations for Reducing the Computational Cost of Electrostatic Interactions. J Chem Inf Model 2022; 62:2846-2856. [PMID: 35639709 DOI: 10.1021/acs.jcim.1c01532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The free-energy perturbation (FEP) method predicts relative and absolute free-energy changes of biomolecules in solvation and binding with other molecules. FEP is, therefore, one of the most essential tools in in silico drug design. In conventional FEP, to smoothly connect two thermodynamic states, the potential energy is modified as a linear combination of the end-state potential energies by introducing scaling factors. When the particle mesh Ewald is used for electrostatic calculations, conventional FEP requires two reciprocal-space calculations per time step, which largely decreases the computational performance. To overcome this problem, we propose a new FEP scheme by introducing a modified Hamiltonian instead of interpolation of the end-state potential energies. The scheme introduces nonuniform scaling into the electrostatic potential as used in Replica Exchange with Solute Tempering 2 (REST2) and does not require additional reciprocal-space calculations. We tested this modified Hamiltonian in FEP calculations in several biomolecular systems. In all cases, the calculated free-energy changes with the current scheme are in good agreement with those from conventional FEP. The modified Hamiltonian in FEP greatly improves the computational performance, which is particularly marked for large biomolecular systems whose reciprocal-space calculations are the major bottleneck of total computational time.
Collapse
Affiliation(s)
- Hiraku Oshima
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Integrated Innovation Building 7F, 6-7-1 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Yuji Sugita
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Integrated Innovation Building 7F, 6-7-1 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan.,Computational Biophysics Research Team, RIKEN Center for Computational Science, Integrated Innovation Building 7F, 6-7-1 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| |
Collapse
|
36
|
Luo J, Zhou C, Li Q, Liu L. A unified approach for calculating free energies of liquid and defective crystals based on thermodynamic integration. J Chem Phys 2022; 156:214113. [DOI: 10.1063/5.0095638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
The free energy calculation is fundamentally important in the research of physics, chemistry and materials. Thermodynamic integration is the most common way to estimate free energies. In the research, we proposed a unified approach using atomic simulations to calculate the free energies of liquid and defective crystals. The new approach is based on thermodynamic integration (TI) using two alchemical pathways. Softcore potentials are developed for three-body interatomic potentials to realize the alchemical pathways. Employing the new approach, the free energy of the liquid can be calculated without requiring another reference system. The free energy of the defective crystal can be calculated directly at high temperature. It avoids the singularity at the integration endpoint caused by the defect diffusion which is a serious problem in the widely used Einstein crystal method. In addition, the new approach can capture the whole free energy of the defective crystal including the contribution of anharmonic and configurational entropy which are particularly important at high temperature. The new method is simple yet effective and can be extended to different materials and more complex liquid and defective crystal systems.
Collapse
Affiliation(s)
- Jinping Luo
- School of Energy and Power Engineering, Xi'an Jiaotong University, China
| | | | | | - Lijun Liu
- School of Energy and Power Engineering, Xi'an Jiaotong University, China
| |
Collapse
|
37
|
Zhang Q, Yang Y, Gong X, Zhao N, Zhang Y, Liu H. Thermodynamic integration combined with molecular dynamic simulations to explore the
cross‐resistance
mechanism of isoniazid and ethionamide. Proteins 2022; 90:1142-1151. [DOI: 10.1002/prot.26295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 12/25/2021] [Accepted: 12/30/2021] [Indexed: 11/10/2022]
Affiliation(s)
| | - Yuwei Yang
- School of Pharmacy Lanzhou University Lanzhou China
| | - Xiaoqing Gong
- State Key Laboratory of Applied Organic Chemistry and Department of Chemistry Lanzhou University Lanzhou China
| | - Nannan Zhao
- School of Pharmacy Lanzhou University Lanzhou China
| | - Yang Zhang
- Supercomputing Center of Lanzhou University Lanzhou China
| | | |
Collapse
|
38
|
Dai Z, Zhao L, Peng S, Yue Z, Zhan X, Wang J. Removal of oxytetracycline promoted by manganese-doped biochar based on density functional theory calculations: Comprehensive evaluation of the effect of transition metal doping. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 806:150268. [PMID: 34571226 DOI: 10.1016/j.scitotenv.2021.150268] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 09/07/2021] [Accepted: 09/07/2021] [Indexed: 06/13/2023]
Abstract
The regulation of surface electrons by non-metal doping of biochar (BC) is environmentally and ecologically significant. However, systematic studies on the regulation of surface electrons by transition metal doping are lacking. The present study is based on the observation that the removal efficiency of oxytetracycline (OTC) by Mn-doped BC is eight times higher than that of undoped BC in 20 min. The effects of Mn doping on the crystal phase formation, persistent free radicals (PFRs), electron density, molecular orbitals, and nucleophilic active sites of BC are investigated, and the intermediate products of OTC are evaluated. Mn doping enhances the signal for sp2-hybridised carbon-carbon double bond, forms more delocalised π-bonds, and promotes the formation of free radicals centred on the carbon atoms. The specific surface area of BC increases, and manganese oxide is formed on the its surface. Density functional theory calculations show that Mn doping accelerates the electron transfer of BC, provides additional electrons for the BC system, and makes this system more ionised. OTC molecules preferentially attack the nucleophilic reaction sites near Mn atoms based on molecular electrostatic potential measurements. Therefore, this study provides new insights into the surface electronic structures regulated by transition metal elements.
Collapse
Affiliation(s)
- Zhipeng Dai
- School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230000, China; Key Laboratory of Nanominerals and Pollution Control of Anhui Higher Education Institutes, Hefei University of Technology, Hefei, Anhui 230009, China
| | - Lu Zhao
- School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230000, China; Key Laboratory of Nanominerals and Pollution Control of Anhui Higher Education Institutes, Hefei University of Technology, Hefei, Anhui 230009, China
| | - Shuchuan Peng
- School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230000, China.
| | - Zhengbo Yue
- School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230000, China; Key Laboratory of Nanominerals and Pollution Control of Anhui Higher Education Institutes, Hefei University of Technology, Hefei, Anhui 230009, China
| | - Xinyuan Zhan
- School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230000, China
| | - Jin Wang
- School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230000, China; Key Laboratory of Nanominerals and Pollution Control of Anhui Higher Education Institutes, Hefei University of Technology, Hefei, Anhui 230009, China
| |
Collapse
|
39
|
Reif MM, Zacharias M. Computational Tools for Accurate Binding Free-Energy Prediction. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2022; 2385:255-292. [PMID: 34888724 DOI: 10.1007/978-1-0716-1767-0_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
A quantitative thermodynamic understanding of the noncovalent association of (bio)molecules is of central importance in molecular life sciences. An important quantity characterizing (bio)molecular association is the binding affinity or absolute binding free energy. In recent years, the computational prediction of absolute binding free energies has evolved considerably in terms of accuracy, computational speed, and user-friendliness. In this chapter, we first give an overview of how absolute free energies are defined and how they can be determined with computational means. We proceed with an outline of the theoretical basis of the two most reliable methods, potential of mean force, and double decoupling calculations. In particular, we describe how the sampling problem can be alleviated by application of restraints. Finally, we provide step-by-step instructions of how to set up corresponding molecular simulations with a commonly employed molecular dynamics simulation engine.
Collapse
Affiliation(s)
- Maria M Reif
- Physics Department (T38), Technische Universität München, Garching, Germany
| | - Martin Zacharias
- Physics Department (T38), Technische Universität München, Garching, Germany.
| |
Collapse
|
40
|
Azimi S, Khuttan S, Wu JZ, Pal RK, Gallicchio E. Relative Binding Free Energy Calculations for Ligands with Diverse Scaffolds with the Alchemical Transfer Method. J Chem Inf Model 2022; 62:309-323. [PMID: 34990555 DOI: 10.1021/acs.jcim.1c01129] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
We present an extension of the alchemical transfer method (ATM) for the estimation of relative binding free energies of molecular complexes applicable to conventional, as well as scaffold-hopping, alchemical transformations. Named ATM-RBFE, the method is implemented in the free and open-source OpenMM molecular simulation package and aims to provide a simpler and more generally applicable route to the calculation of relative binding free energies than what is currently available. ATM-RBFE is based on sound statistical mechanics theory and a novel coordinate perturbation scheme designed to swap the positions of a pair of ligands such that one is transferred from the bulk solvent to the receptor binding site while the other moves simultaneously in the opposite direction. The calculation is conducted directly in a single solvent box with a system prepared with conventional setup tools, without splitting of electrostatic and nonelectrostatic transformations, and without pairwise soft-core potentials. ATM-RBFE is validated here against the absolute binding free energies of the SAMPL8 GDCC host-guest benchmark set and against protein-ligand benchmark sets that include complexes of the estrogen receptor ERα and those of the methyltransferase EZH2. In each case the method yields self-consistent and converged relative binding free energy estimates in agreement with absolute binding free energies and reference literature values, as well as experimental measurements.
Collapse
Affiliation(s)
- Solmaz Azimi
- Department of Chemistry, Brooklyn College of the City University of New York, Brooklyn, New York 11210, United States.,Ph.D. Program in Biochemistry, The Graduate Center of the City University of New York, New York, New York 10016, United States
| | - Sheenam Khuttan
- Department of Chemistry, Brooklyn College of the City University of New York, Brooklyn, New York 11210, United States.,Ph.D. Program in Biochemistry, The Graduate Center of the City University of New York, New York, New York 10016, United States
| | - Joe Z Wu
- Department of Chemistry, Brooklyn College of the City University of New York, Brooklyn, New York 11210, United States.,Ph.D. Program in Chemistry, The Graduate Center of the City University of New York, New York, New York 10016, United States
| | - Rajat K Pal
- Roivant Sciences, Inc., Boston, Massachusetts 02210, United States
| | - Emilio Gallicchio
- Department of Chemistry, Brooklyn College of the City University of New York, Brooklyn, New York 11210, United States.,Ph.D. Program in Biochemistry, The Graduate Center of the City University of New York, New York, New York 10016, United States.,Ph.D. Program in Chemistry, The Graduate Center of the City University of New York, New York, New York 10016, United States
| |
Collapse
|
41
|
Waibl F, Kraml J, Fernández-Quintero ML, Loeffler JR, Liedl KR. Explicit solvation thermodynamics in ionic solution: extending grid inhomogeneous solvation theory to solvation free energy of salt-water mixtures. J Comput Aided Mol Des 2022; 36:101-116. [PMID: 35031880 PMCID: PMC8907097 DOI: 10.1007/s10822-021-00429-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 10/28/2021] [Indexed: 12/03/2022]
Abstract
Hydration thermodynamics play a fundamental role in fields ranging from the pharmaceutical industry to environmental research. Numerous methods exist to predict solvation thermodynamics of compounds ranging from small molecules to large biomolecules. Arguably the most precise methods are those based on molecular dynamics (MD) simulations in explicit solvent. One theory that has seen increased use is inhomogeneous solvation theory (IST). However, while many applications require accurate description of salt-water mixtures, no implementation of IST is currently able to estimate solvation properties involving more than one solvent species. Here, we present an extension to grid inhomogeneous solvation theory (GIST) that can take salt contributions into account. At the example of carbazole in 1 M NaCl solution, we compute the solvation energy as well as first and second order entropies. While the effect of the first order ion entropy is small, both the water-water and water-ion entropies contribute strongly. We show that the water-ion entropies are efficiently approximated using the Kirkwood superposition approximation. However, this approach cannot be applied to the water-water entropy. Furthermore, we test the quantitative validity of our method by computing salting-out coefficients and comparing them to experimental data. We find a good correlation to experimental salting-out constants, while the absolute values are overpredicted due to the approximate second order entropy. Since ions are frequently used in MD, either to neutralize the system or as a part of the investigated process, our method greatly extends the applicability of GIST. The use-cases range from biopharmaceuticals, where many assays require high salt concentrations, to environmental research, where solubility in sea water is important to model the fate of organic substances.
Collapse
Affiliation(s)
- Franz Waibl
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria
| | - Johannes Kraml
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria
| | - Monica L Fernández-Quintero
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria
| | - Johannes R Loeffler
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria
| | - Klaus R Liedl
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria.
| |
Collapse
|
42
|
Hu Q, Padron K, Hara D, Shi J, Pollack A, Prabhakar R, Tao W. Interactions of Urea-Based Inhibitors with Prostate-Specific Membrane Antigen for Boron Neutron Capture Therapy. ACS OMEGA 2021; 6:33354-33369. [PMID: 34926886 PMCID: PMC8674901 DOI: 10.1021/acsomega.1c03554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 10/04/2021] [Indexed: 06/14/2023]
Abstract
In this study, molecular interactions of prostate-specific membrane antigen (PSMA) with five chemically distinct urea-based boron-containing inhibitors have been investigated at the atomic level using molecular docking and molecular dynamics simulations. The PSMA-inhibitor complexations have been analyzed by comparing their binding modes, secondary structures, root-mean-square deviations, noncovalent interactions, principal components, and binding free energies. PSMA is a cell surface glycoprotein upregulated in cancerous cells and can be targeted by boron-labeled inhibitors for boron neutron capture therapy (BNCT). The effective BNCT requires the selective boron delivery to the tumor area and highly specific PSMA-mediated cellular uptake by tumor. Thus, a potent inhibitor must exhibit both high binding affinity and high boron density. The computational results suggest that the chemical nature of inhibitors affects the binding mode and their association with PSMA is primarily dominated by hydrogen bonding, salt bridge, electrostatic, and π-π interactions. The binding free energies (-28.0, -15.2, -43.9, -23.2, and -38.2 kcal/mol) calculated using λ-dynamics for all inhibitors (In1-5) predict preferential binding that is in accordance with experimental data. Among all inhibitors, In5 was found to be the best candidate for BNCT. The binding of this inhibitor to PSMA preserved its overall secondary structure. These results provide computational insights into the coordination flexibility of PSMA and its interaction with various inhibitors. They can be used for the design and synthesis of efficient BNCT agents with improved drug selectivity and high boron percentage.
Collapse
Affiliation(s)
- Qiaoyu Hu
- Department
of Chemistry, University of Miami, Coral Gables, Florida 33146, United States
| | - Kevin Padron
- Department
of Computer Science, University of Miami, Coral Gables, Florida 33146, United States
| | - Daiki Hara
- Department
of Radiation Oncology, University of Miami
Miller School of Medicine, Miami, Florida 33136, United States
| | - Junwei Shi
- Department
of Radiation Oncology, University of Miami
Miller School of Medicine, Miami, Florida 33136, United States
| | - Alan Pollack
- Department
of Radiation Oncology, University of Miami
Miller School of Medicine, Miami, Florida 33136, United States
| | - Rajeev Prabhakar
- Department
of Chemistry, University of Miami, Coral Gables, Florida 33146, United States
| | - Wensi Tao
- Department
of Radiation Oncology, University of Miami
Miller School of Medicine, Miami, Florida 33136, United States
| |
Collapse
|
43
|
Li P, Li Z, Wang Y, Dou H, Radak BK, Allen BK, Sherman W, Xu H. Precise Binding Free Energy Calculations for Multiple Molecules Using an Optimal Measurement Network of Pairwise Differences. J Chem Theory Comput 2021; 18:650-663. [PMID: 34871502 DOI: 10.1021/acs.jctc.1c00703] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Alchemical binding free energy (BFE) calculations offer an efficient and thermodynamically rigorous approach to in silico binding affinity predictions. As a result of decades of methodological improvements and recent advances in computer technology, alchemical BFE calculations are now widely used in drug discovery research. They help guide the prioritization of candidate drug molecules by predicting their binding affinities for a biomolecular target of interest (and potentially selectivity against undesirable antitargets). Statistical variance associated with such calculations, however, may undermine the reliability of their predictions, introducing uncertainty both in ranking candidate molecules and in benchmarking their predictive accuracy. Here, we present a computational method that substantially improves the statistical precision in BFE calculations for a set of ligands binding to a common receptor by dynamically allocating computational resources to different BFE calculations according to an optimality objective established in a previous work from our group and extended in this work. Our method, termed Network Binding Free Energy (NetBFE), performs adaptive BFE calculations in iterations, re-optimizing the allocations in each iteration based on the statistical variances estimated from previous iterations. Using examples of NetBFE calculations for protein binding of congeneric ligand series, we demonstrate that NetBFE approaches the optimal allocation in a small number (≤5) of iterations and that NetBFE reduces the statistical variance in the BFE estimates by approximately a factor of 2 when compared to a previously published and widely used allocation method at the same total computational cost.
Collapse
Affiliation(s)
- Pengfei Li
- Silicon Therapeutics, Suzhou, Jiangsu 215000, China
| | - Zhijie Li
- Silicon Therapeutics, Suzhou, Jiangsu 215000, China
| | - Yu Wang
- Silicon Therapeutics, Suzhou, Jiangsu 215000, China
| | - Huaixia Dou
- Silicon Therapeutics, Suzhou, Jiangsu 215000, China
| | - Brian K Radak
- Roivant Sciences, Boston, Massachusetts 02210, United States
| | - Bryce K Allen
- Silicon Therapeutics, Boston, Massachusetts 02210, United States
| | - Woody Sherman
- Roivant Sciences, Boston, Massachusetts 02210, United States
| | - Huafeng Xu
- Roivant Sciences, New York, New York 10036, United States
| |
Collapse
|
44
|
Zhang H, Kim S, Giese TJ, Lee TS, Lee J, York DM, Im W. CHARMM-GUI Free Energy Calculator for Practical Ligand Binding Free Energy Simulations with AMBER. J Chem Inf Model 2021; 61:4145-4151. [PMID: 34521199 DOI: 10.1021/acs.jcim.1c00747] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Alchemical free energy methods, such as free energy perturbation (FEP) and thermodynamic integration (TI), become increasingly popular and crucial for drug design and discovery. However, the system preparation of alchemical free energy simulation is an error-prone, time-consuming, and tedious process for a large number of ligands. To address this issue, we have recently presented CHARMM-GUI Free Energy Calculator that can provide input and postprocessing scripts for NAMD and GENESIS FEP molecular dynamics systems. In this work, we extended three submodules of Free Energy Calculator to work with the full suite of GPU-accelerated alchemical free energy methods and tools in AMBER, including input and postprocessing scripts. The BACE1 (β-secretase 1) benchmark set was used to validate the AMBER-TI simulation systems and scripts generated by Free Energy Calculator. The overall results of relatively large and diverse systems are almost equivalent with different protocols (unified and split) and with different timesteps (1, 2, and 4 fs), with R2 > 0.9. More importantly, the average free energy differences between two protocols are small and reliable with four independent runs, with a mean unsigned error (MUE) below 0.4 kcal/mol. Running at least four independent runs for each pair with AMBER20 (and FF19SB/GAFF2.1/OPC force fields), we obtained a MUE of 0.99 kcal/mol and root-mean-square error of 1.31 kcal/mol for 58 alchemical transformations in comparison with experimental data. In addition, a set of ligands for T4-lysozyme was used to further validate our free energy calculation protocol whose results are close to experimental data (within 1 kcal/mol). In summary, Free Energy Calculator provides a user-friendly web-based tool to generate the AMBER-TI system and input files for high-throughput binding free energy calculations with access to the full set of GPU-accelerated alchemical free energy, enhanced sampling, and analysis methods in AMBER.
Collapse
Affiliation(s)
- Han Zhang
- Department of Biological Sciences, Chemistry, Bioengineering, and Computer Science and Engineering, Lehigh University, Pennsylvania 18015, United States
| | - Seonghoon Kim
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul 02455, Republic of Korea
| | - Timothy J Giese
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine, and Department of Chemistry and Chemical Biology, Rutgers, the State University of New Jersey, New Jersey 08854, United States
| | - Tai-Sung Lee
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine, and Department of Chemistry and Chemical Biology, Rutgers, the State University of New Jersey, New Jersey 08854, United States
| | - Jumin Lee
- Department of Biological Sciences, Chemistry, Bioengineering, and Computer Science and Engineering, Lehigh University, Pennsylvania 18015, United States
| | - Darrin M York
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine, and Department of Chemistry and Chemical Biology, Rutgers, the State University of New Jersey, New Jersey 08854, United States
| | - Wonpil Im
- Department of Biological Sciences, Chemistry, Bioengineering, and Computer Science and Engineering, Lehigh University, Pennsylvania 18015, United States
| |
Collapse
|
45
|
King E, Aitchison E, Li H, Luo R. Recent Developments in Free Energy Calculations for Drug Discovery. Front Mol Biosci 2021; 8:712085. [PMID: 34458321 PMCID: PMC8387144 DOI: 10.3389/fmolb.2021.712085] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 07/27/2021] [Indexed: 01/11/2023] Open
Abstract
The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.
Collapse
Affiliation(s)
- Edward King
- Department of Molecular Biology and Biochemistry, University of California, Irvine, CA, United States
| | - Erick Aitchison
- Department of Molecular Biology and Biochemistry, University of California, Irvine, CA, United States
| | - Han Li
- Department of Chemical and Biomolecular Engineering, University of California, Irvine, CA, United States
| | - Ray Luo
- Department of Molecular Biology and Biochemistry, University of California, Irvine, CA, United States
- Department of Chemical and Biomolecular Engineering, University of California, Irvine, CA, United States
- Department of Materials Science and Engineering, University of California, Irvine, CA, United States
- Department of Biomedical Engineering, University of California, Irvine, CA, United States
| |
Collapse
|
46
|
Carvalho Martins L, Cino EA, Ferreira RS. PyAutoFEP: An Automated Free Energy Perturbation Workflow for GROMACS Integrating Enhanced Sampling Methods. J Chem Theory Comput 2021; 17:4262-4273. [PMID: 34142828 DOI: 10.1021/acs.jctc.1c00194] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Free energy perturbation (FEP) calculations are now routinely used in drug discovery to estimate the relative FEB (RFEB) of small molecules to a biomolecular target of interest. Using enhanced sampling can improve the correlation between predictions and experimental data, especially in systems with conformational changes. Due to the large number of perturbations required in drug discovery campaigns, the manual setup of FEP calculations is no longer viable. Here, we introduce PyAutoFEP, a flexible and open-source tool to aid the setup of RFEB FEP. PyAutoFEP is written in Python3, and automates the generation of perturbation maps, dual topologies, system building and molecular dynamics (MD), and analysis. PyAutoFEP supports multiple force fields, incorporates replica exchange with solute tempering (REST) and replica exchange with solute scaling (REST2) enhanced sampling methods, and allows flexible λ values along perturbation windows. To validate PyAutoFEP, it was applied to a set of 14 Farnesoid X receptor ligands, a system included in the drug design data resource grand challenge 2. An 88% mean correct sign prediction was achieved, and 75% of the predictions had an error below 1.5 kcal/mol. Results using Amber03/GAFF, CHARMM36m/CGenFF, and OPLS-AA/M/LigParGen had Pearson's r values of 0.71 ± 0.13, 0.30 ± 0.27, and 0.66 ± 0.20, respectively. The Amber03/GAFF and OPLS-AA/M/LigParGen results were on par with the top grand challenge 2 submissions. Applying REST2 improved the results using CHARMM36m/CGenFF (Pearson's r = 0.43 ± 0.21) but had little impact on the other force fields. CHARMM36-YF and CHARMM36-WYF modifications did not yield improved predictions compared to CHARMM36m. Finally, we estimated the probability of finding a molecule 1 pKi better than a lead when using PyAutoFEP to screen 10 or 100 analogues. The probabilities, when compared to random sampling, increased up to sevenfold when 100 molecules were to be screened, suggesting that PyAutoFEP would likely be useful for lead optimization. PyAutoFEP is available on GitHub at https://github.com/lmmpf/PyAutoFEP.
Collapse
Affiliation(s)
- Luan Carvalho Martins
- Graduate Program in Bioinformatics. Institute for Biological Sciences, Federal University of Minas Gerais, Belo Horizonte 31270-901, Brazil
| | - Elio A Cino
- Biochemistry and Immunology Department, Institute for Biological Sciences, Federal University of Minas Gerais, Belo Horizonte 31270-901, Brazil
| | - Rafaela Salgado Ferreira
- Biochemistry and Immunology Department, Institute for Biological Sciences, Federal University of Minas Gerais, Belo Horizonte 31270-901, Brazil
| |
Collapse
|
47
|
Emamian M, Azizpour H, Moradi H, Keynejad K, Bahmanyar H, Nasrollahi Z. Performance of molecular dynamics simulation for predicting of solvation free energy of neutral solutes in methanol. CHEMICAL PRODUCT AND PROCESS MODELING 2021. [DOI: 10.1515/cppm-2021-0014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
In this study, molecular dynamics simulation was applied for calculating solvation free energy of 16 solute molecules in methanol solvent. The thermodynamic integration method was used because it was possible to calculate the difference in free energy in any thermodynamic path. After comparing results for solvation free energy in different force fields, COMPASS force field was selected since it had the lowest error compared to experimental result. Group-based summation method was used to compute electrostatic and van der Waals forces at 298.15 K and 1 atm. The results of solvation free energy were obtained from molecular dynamics simulation and were compared to the results from Solvation Model Density (SMD) and Universal Continuum Solvation Model (denoted as SM8), which were obtained from other research works. Average square-root-error for molecular dynamics simulation, SMD and SM8 models were 0.096091, 0.595798, and 0.70649. Furthermore, the coefficient of determination (R
2) for molecular dynamics simulation was 0.9618, which shows higher accuracy of MD simulation for calculating solvation free energy comparing to two other models.
Collapse
Affiliation(s)
- Mohammad Emamian
- School of Chemical Engineering , College of Engineering, University of Tehran , Tehran , Iran
| | - Hedayat Azizpour
- School of Chemical Engineering , College of Engineering, University of Tehran , Tehran , Iran
- Fouman Faculty of Engineering, College of Engineering, University of Tehran , Fouman , Iran
| | - Hojatollah Moradi
- School of Chemical Engineering , College of Engineering, University of Tehran , Tehran , Iran
| | - Kamran Keynejad
- Fouman Faculty of Engineering, College of Engineering, University of Tehran , Fouman , Iran
| | - Hossein Bahmanyar
- School of Chemical Engineering , College of Engineering, University of Tehran , Tehran , Iran
| | - Zahra Nasrollahi
- Fouman Faculty of Engineering, College of Engineering, University of Tehran , Fouman , Iran
| |
Collapse
|
48
|
Zou J, Li Z, Liu S, Peng C, Fang D, Wan X, Lin Z, Lee TS, Raleigh DP, Yang M, Simmerling C. Scaffold Hopping Transformations Using Auxiliary Restraints for Calculating Accurate Relative Binding Free Energies. J Chem Theory Comput 2021; 17:3710-3726. [PMID: 34029468 PMCID: PMC8215533 DOI: 10.1021/acs.jctc.1c00214] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
In silico screening of drug-target interactions is a key part of the drug discovery process. Changes in the drug scaffold via contraction or expansion of rings, the breaking of rings, and the introduction of cyclic structures from acyclic structures are commonly applied by medicinal chemists to improve binding affinity and enhance favorable properties of candidate compounds. These processes, commonly referred to as scaffold hopping, are challenging to model computationally. Although relative binding free energy (RBFE) calculations have shown success in predicting binding affinity changes caused by perturbing R-groups attached to a common scaffold, applications of RBFE calculations to modeling scaffold hopping are relatively limited. Scaffold hopping inevitably involves breaking and forming bond interactions of quadratic functional forms, which is highly challenging. A novel method for handling ring opening/closure/contraction/expansion and linker contraction/expansion is presented here. To the best of our knowledge, RBFE calculations on linker contraction/expansion have not been previously reported. The method uses auxiliary restraints to hold the atoms at the ends of a bond in place during the breaking and forming of the bonds. The broad applicability of the method was demonstrated by examining perturbations involving small-molecule macrocycles and mutations of proline in proteins. High accuracy was obtained using the method for most of the perturbations studied. The rigor of the method was isolated from the force field by validating the method using relative and absolute hydration free energy calculations compared to standard simulation results. Unlike other methods that rely on λ-dependent functional forms for bond interactions, the method presented here can be employed using modern molecular dynamics software without modification of codes or force field functions.
Collapse
Affiliation(s)
- Junjie Zou
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
- Department of Chemistry, Stony Brook University, Stony Brook, New York 11794-3400, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794-3400, United States
| | - Zhipeng Li
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
| | - Shuai Liu
- XtalPi Inc., 245 Main St, 11th Floor, Cambridge, MA 02142, United States
| | - Chunwang Peng
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
| | - Dong Fang
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
| | - Xiao Wan
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
| | - Zhixiong Lin
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
| | - Tai-Sung Lee
- Laboratory for Biomolecular Simulation Research, Center for Integrative Proteomics Research, Rutgers University, Piscataway, New Jersey, 08854-8076, United States
| | - Daniel P. Raleigh
- Department of Chemistry, Stony Brook University, Stony Brook, New York 11794-3400, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794-3400, United States
| | - Mingjun Yang
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
| | - Carlos Simmerling
- Department of Chemistry, Stony Brook University, Stony Brook, New York 11794-3400, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794-3400, United States
| |
Collapse
|
49
|
King E, Qi R, Li H, Luo R, Aitchison E. Estimating the Roles of Protonation and Electronic Polarization in Absolute Binding Affinity Simulations. J Chem Theory Comput 2021; 17:2541-2555. [PMID: 33764050 DOI: 10.1021/acs.jctc.0c01305] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Accurate prediction of binding free energies is critical to streamlining the drug development and protein design process. With the advent of GPU acceleration, absolute alchemical methods, which simulate the removal of ligand electrostatics and van der Waals interactions with the protein, have become routinely accessible and provide a physically rigorous approach that enables full consideration of flexibility and solvent interaction. However, standard explicit solvent simulations are unable to model protonation or electronic polarization changes upon ligand transfer from water to the protein interior, leading to inaccurate prediction of binding affinities for charged molecules. Here, we perform extensive simulation totaling ∼540 μs to benchmark the impact of modeling conditions on predictive accuracy for absolute alchemical simulations. Binding to urokinase plasminogen activator (UPA), a protein frequently overexpressed in metastatic tumors, is evaluated for a set of 10 inhibitors with extended flexibility, highly charged character, and titratable properties. We demonstrate that the alchemical simulations can be adapted to utilize the MBAR/PBSA method to improve the accuracy upon incorporating electronic polarization, highlighting the importance of polarization in alchemical simulations of binding affinities. Comparison of binding energy prediction at various protonation states indicates that proper electrostatic setup is also crucial in binding affinity prediction of charged systems, prompting us to propose an alternative binding mode with protonated ligand phenol and Hid-46 at the binding site, a testable hypothesis for future experimental validation.
Collapse
Affiliation(s)
| | - Ruxi Qi
- Cryo-EM Center, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | | | | | | |
Collapse
|
50
|
Chen L, Cruz A, Roe DR, Simmonett AC, Wickstrom L, Deng N, Kurtzman T. Thermodynamic Decomposition of Solvation Free Energies with Particle Mesh Ewald and Long-Range Lennard-Jones Interactions in Grid Inhomogeneous Solvation Theory. J Chem Theory Comput 2021; 17:2714-2724. [PMID: 33830762 DOI: 10.1021/acs.jctc.0c01185] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Grid Inhomogeneous Solvation Theory (GIST) maps out solvation thermodynamic properties on a fine meshed grid and provides a statistical mechanical formalism for thermodynamic end-state calculations. However, differences in how long-range nonbonded interactions are calculated in molecular dynamics engines and in the current implementation of GIST have prevented precise comparisons between free energies estimated using GIST and those from other free energy methods such as thermodynamic integration (TI). Here, we address this by presenting PME-GIST, a formalism by which particle mesh Ewald (PME)-based electrostatic energies and long-range Lennard-Jones (LJ) energies are decomposed and assigned to individual atoms and the corresponding voxels they occupy in a manner consistent with the GIST approach. PME-GIST yields potential energy calculations that are precisely consistent with modern simulation engines and performs these calculations at a dramatically faster speed than prior implementations. Here, we apply PME-GIST end-state analyses to 32 small molecules whose solvation free energies are close to evenly distributed from 2 kcal/mol to -17 kcal/mol and obtain solvation energies consistent with TI calculations (R2 = 0.99, mean unsigned difference 0.8 kcal/mol). We also estimate the entropy contribution from the second and higher order entropy terms that are truncated in GIST by the differences between entropies calculated in TI and GIST. With a simple correction for the high order entropy terms, PME-GIST obtains solvation free energies that are highly consistent with TI calculations (R2 = 0.99, mean unsigned difference = 0.4 kcal/mol) and experimental results (R2 = 0.88, mean unsigned difference = 1.4 kcal/mol). The precision of PME-GIST also enables us to show that the solvation free energy of small hydrophobic and hydrophilic molecules can be largely understood based on perturbations of the solvent in a region extending a few solvation shells from the solute. We have integrated PME-GIST into the open-source molecular dynamics analysis software CPPTRAJ.
Collapse
Affiliation(s)
- Lieyang Chen
- Department of Chemistry, Lehman College, The City University of New York, 250 Bedford Park Boulevard West, Bronx, New York 10468, United States.,Ph.D. Program in Biochemistry, The Graduate Center of The City University of New York, New York, New York 10016, United States
| | - Anthony Cruz
- Department of Chemistry, Lehman College, The City University of New York, 250 Bedford Park Boulevard West, Bronx, New York 10468, United States.,Ph.D. Program in Chemistry, The Graduate Center of The City University of New York, New York, New York 10016, United States
| | - Daniel R Roe
- Laboratory of Computational Biology, National Institutes of Health - National Heart, Lung and Blood Institute, Bethesda, Maryland 20892, United States
| | - Andrew C Simmonett
- Laboratory of Computational Biology, National Institutes of Health - National Heart, Lung and Blood Institute, Bethesda, Maryland 20892, United States
| | - Lauren Wickstrom
- Department of Science, Borough of Manhattan Community College, The City University of New York, New York, New York 10007, United States
| | - Nanjie Deng
- Department of Chemistry and Physical Sciences, Pace University, New York, New York 10038, United States
| | - Tom Kurtzman
- Department of Chemistry, Lehman College, The City University of New York, 250 Bedford Park Boulevard West, Bronx, New York 10468, United States.,Ph.D. Program in Biochemistry, The Graduate Center of The City University of New York, New York, New York 10016, United States.,Ph.D. Program in Chemistry, The Graduate Center of The City University of New York, New York, New York 10016, United States
| |
Collapse
|