1
|
Heinzelmann G, Huggins DJ, Gilson MK. BAT2: an Open-Source Tool for Flexible, Automated, and Low Cost Absolute Binding Free Energy Calculations. J Chem Theory Comput 2024; 20:6518-6530. [PMID: 39088306 PMCID: PMC11325538 DOI: 10.1021/acs.jctc.4c00205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 07/19/2024] [Accepted: 07/23/2024] [Indexed: 08/03/2024]
Abstract
Absolute binding free energy (ABFE) calculations with all-atom molecular dynamics (MD) have the potential to greatly reduce costs in the first stages of drug discovery. Here, we introduce BAT2, the new version of the Binding Affinity Tool (BAT.py), designed to combine full automation of ABFE calculations with high-performance MD simulations, making it a potential tool for virtual screening. We describe and test several changes and new features that were incorporated into the code, such as relative restraints between the protein and the ligand instead of using fixed dummy atoms, support for the OpenMM simulation engine, a merged approach to the application/release of restraints, support for cobinders and proteins with multiple chains, and many others. We also reduced the simulation times for each ABFE calculation, assessing the effect on the expected robustness and accuracy of the calculations.
Collapse
Affiliation(s)
- Germano Heinzelmann
- Departamento
de Fisica, Universidade Federal de Santa
Catarina, Florianopolis 88040-970, Brasil
| | - David J. Huggins
- Department
of Physiology and Biophysics, Weill Cornell
Medical College of Cornell University, New York, New York 10065, United States
- Sanders
Tri-Institutional Therapeutics Discovery Institute, 1230 York Avenue, Box 122, New York, New York 10065, United States
| | - Michael K. Gilson
- Skaggs
School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego 92093, United States
| |
Collapse
|
2
|
Verma S, Nair NN. A Comprehensive Study of Factors Affecting the Prediction of the p Ka Shift of Asp 26 in Thioredoxin Protein. J Phys Chem B 2024; 128:7304-7312. [PMID: 39023356 DOI: 10.1021/acs.jpcb.4c01516] [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: 07/20/2024]
Abstract
The stable protonation state of ionizable amino acids in a protein can be predicted by computing the pKa shift of that residue within the protein environment. Thermodynamic Integration (TI) is an ideal molecular dynamics-based approach for predicting the pKa shift of ionizable protein residues. Here, we probe TI-based simulation protocols for their ability to accurately predict the pKa shift of Asp26 in thioredoxin. While implicit solvent models can predict the pKa shift accurately, explicit solvent models result in substantial errors. To understand the underlying reason for this surprising discrepancy, we investigate the role of various factors such as solvent models, conformational sampling, background charges, and polarization.
Collapse
Affiliation(s)
- Shivani Verma
- Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur - 208016, India
| | - Nisanth N Nair
- Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur - 208016, India
| |
Collapse
|
3
|
Sun Z, Procacci P. Methodological and force field effects in the molecular dynamics-based prediction of binding free energies of host-guest systems. Phys Chem Chem Phys 2024; 26:19887-19899. [PMID: 38990073 DOI: 10.1039/d4cp01804d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2024]
Abstract
As a contribution to the understanding and rationalization of methodological and modeling effects in recent host-guest SAMPL challenges, using an alchemical molecular dynamics technique we have examined the impact of force field parameterization and ionic strength in connection with guest charge neutralization on computed dissociation free energies in two typical SAMPL heavily charged macrocyclic hosts encapsulating small protonated amines with disparate binding affinities. We have shown that the methodological treatment for host neutralization, with explicit ions or with the background neutralizing plasma in the context of alchemical calculations under periodic boundary conditions, has a moderate effect on the calculated affinities. On the other hand, we have shown that seemingly small differences in the force field parameterization in highly symmetric hosts can produce systematic effects on the structural features that can have a significant impact on the predicted binding affinities.
Collapse
Affiliation(s)
- Zhaoxi Sun
- Changping Laboratory, Beijing 102206, China
| | - Piero Procacci
- Dipartimento di Chimica "Ugo Schiff", Università degli Studi di Firenze, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy.
| |
Collapse
|
4
|
Hayes RL, Cervantes LF, Abad Santos JC, Samadi A, Vilseck JZ, Brooks CL. How to Sample Dozens of Substitutions per Site with λ Dynamics. J Chem Theory Comput 2024; 20:6098-6110. [PMID: 38976796 PMCID: PMC11270746 DOI: 10.1021/acs.jctc.4c00514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 06/18/2024] [Accepted: 06/18/2024] [Indexed: 07/10/2024]
Abstract
Alchemical free energy methods are useful in computer-aided drug design and computational protein design because they provide rigorous statistical mechanics-based estimates of free energy differences from molecular dynamics simulations. λ dynamics is a free energy method with the ability to characterize combinatorial chemical spaces spanning thousands of related systems within a single simulation, which gives it a distinct advantage over other alchemical free energy methods that are mostly limited to pairwise comparisons. Recently developed methods have improved the scalability of λ dynamics to perturbations at many sites; however, the size of chemical space that can be explored at each individual site has previously been limited to fewer than ten substituents. As the number of substituents increases, the volume of alchemical space corresponding to nonphysical alchemical intermediates grows exponentially relative to the size corresponding to the physical states of interest. Beyond nine substituents, λ dynamics simulations become lost in an alchemical morass of intermediate states. In this work, we introduce new biasing potentials that circumvent excessive sampling of intermediate states by favoring sampling of physical end points relative to alchemical intermediates. Additionally, we present a more scalable adaptive landscape flattening algorithm for these larger alchemical spaces. Finally, we show that this potential enables more efficient sampling in both protein and drug design test systems with up to 24 substituents per site, enabling, for the first time, simultaneous simulation of all 20 amino acids.
Collapse
Affiliation(s)
- Ryan L. Hayes
- Department
of Chemical and Biomolecular Engineering, University of California Irvine, Irvine, California 92697, United States
- Department
of Pharmaceutical Sciences, University of
California Irvine, Irvine, California 92697, United States
| | - Luis F. Cervantes
- Department
of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Justin Cruz Abad Santos
- Department
of Chemical and Biomolecular Engineering, University of California Irvine, Irvine, California 92697, United States
| | - Amirmasoud Samadi
- Department
of Chemical and Biomolecular Engineering, University of California Irvine, Irvine, California 92697, United States
| | - Jonah Z. Vilseck
- Department
of Biochemistry and Molecular Biology, Indiana
University School of Medicine, Indianapolis, Indiana 46202, United States
- Center
for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
| | - Charles L. Brooks
- Department
of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
- Biophysics
Program, University of Michigan, Ann Arbor, Michigan 48109, United States
| |
Collapse
|
5
|
Mikaelian G, Megariotis G, Theodorou DN. Interactions of a Novel Anthracycline with Oligonucleotide DNA and Cyclodextrins in an Aqueous Environment. J Phys Chem B 2024; 128:6291-6307. [PMID: 38899795 PMCID: PMC11228990 DOI: 10.1021/acs.jpcb.4c02213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 06/07/2024] [Accepted: 06/11/2024] [Indexed: 06/21/2024]
Abstract
Berubicin, a chemotherapy medication belonging to the class of anthracyclines, is simulated in double-stranded DNA sequences and cyclodextrins in an aqueous environment via full-atom molecular dynamics simulations on the time scale of microseconds. The drug is studied in both the neutral and protonated states so as to better comprehend the role of its charge in the formed complexes. The noncovalent berubicin-DNA and berubicin-cyclodextrin complexes are investigated in detail, paying special attention to their thermodynamic description by employing the double decoupling method, the solvent balance method, the weighted solvent accessible surface model, and the linear interaction energy method. A novel approach for extracting the desolvation thermodynamics of the binding process is also presented. Both the binding and desolvation Gibbs energies are decomposed into entropic and enthalpic contributions so as to elucidate the nature of complexation and its driving forces. Selected structural and geometrical properties of all the complexes, which are all stable, are analyzed. Both cyclodextrins under consideration are widely utilized for drug delivery purposes, and a comparative investigation between their bound states with berubicin is carried out.
Collapse
Affiliation(s)
- Georgios Mikaelian
- School
of Chemical Engineering, National Technical
University of Athens (NTUA), 9 Heroon Polytechniou Street, Zografou Campus, 15780 Athens, GR ,Greece
| | - Grigorios Megariotis
- School
of Chemical Engineering, National Technical
University of Athens (NTUA), 9 Heroon Polytechniou Street, Zografou Campus, 15780 Athens, GR ,Greece
- School
of Engineering, Department of Mineral Resources Engineering, University of Western Macedonia, 50100 Kozani, Greece
| | - Doros N. Theodorou
- School
of Chemical Engineering, National Technical
University of Athens (NTUA), 9 Heroon Polytechniou Street, Zografou Campus, 15780 Athens, GR ,Greece
| |
Collapse
|
6
|
Champion C, Hünenberger PH, Riniker S. Multistate Method to Efficiently Account for Tautomerism and Protonation in Alchemical Free-Energy Calculations. J Chem Theory Comput 2024; 20:4350-4362. [PMID: 38742760 PMCID: PMC11137823 DOI: 10.1021/acs.jctc.4c00370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 04/25/2024] [Accepted: 04/29/2024] [Indexed: 05/16/2024]
Abstract
The majority of drug-like molecules contain at least one ionizable group, and many common drug scaffolds are subject to tautomeric equilibria. Thus, these compounds are found in a mixture of protonation and/or tautomeric states at physiological pH. Intrinsically, standard classical molecular dynamics (MD) simulations cannot describe such equilibria between states, which negatively impacts the prediction of key molecular properties in silico. Following the formalism described by de Oliveira and co-workers (J. Chem. Theory Comput. 2019, 15, 424-435) to consider the influence of all states on the binding process based on alchemical free-energy calculations, we demonstrate in this work that the multistate method replica-exchange enveloping distribution sampling (RE-EDS) is well suited to describe molecules with multiple protonation and/or tautomeric states in a single simulation. We apply our methodology to a series of eight inhibitors of factor Xa with two protonation states and a series of eight inhibitors of glycogen synthase kinase 3β (GSK3β) with two tautomeric states. In particular, we show that given a sufficient phase-space overlap between the states, RE-EDS is computationally more efficient than standard pairwise free-energy methods.
Collapse
Affiliation(s)
- Candide Champion
- Department of Chemistry and Applied
Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Philippe H. Hünenberger
- Department of Chemistry and Applied
Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Sereina Riniker
- Department of Chemistry and Applied
Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| |
Collapse
|
7
|
Chéron N. Binding Sites of Bicarbonate in Phosphoenolpyruvate Carboxylase. J Chem Inf Model 2024; 64:3375-3385. [PMID: 38533570 DOI: 10.1021/acs.jcim.3c01830] [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: 03/28/2024]
Abstract
Phosphoenolpyruvate carboxylase (PEPC) is used in plant metabolism for fruit maturation or seed development as well as in the C4 and crassulacean acid metabolism (CAM) mechanisms in photosynthesis, where it is used for the capture of hydrated CO2 (bicarbonate). To find the yet unknown binding site of bicarbonate in this enzyme, we have first identified putative binding sites with nonequilibrium molecular dynamics simulations and then ranked these sites with alchemical free energy calculations with corrections of computational artifacts. Fourteen pockets where bicarbonate could bind were identified, with three having realistic binding free energies with differences with the experimental value below 1 kcal/mol. One of these pockets is found far from the active site at 14 Å and predicted to be an allosteric binding site. In the two other binding sites, bicarbonate is in direct interaction with the magnesium ion; neither sequence alignment nor the study of mutant K606N allowed to discriminate between these two pockets, and both are good candidates as the binding site of bicarbonate in phosphoenolpyruvate carboxylase.
Collapse
Affiliation(s)
- Nicolas Chéron
- PASTEUR, Département de chimie, École normale supérieure, PSL University, Sorbonne Université, CNRS, 75005 Paris, France
| |
Collapse
|
8
|
Kumar A, Vashisth H. Quantitative Assessment of Energetic Contributions of Residues in a SARS-CoV-2 Viral Enzyme/Nanobody Interface. J Chem Inf Model 2024; 64:2068-2076. [PMID: 38460144 PMCID: PMC10966652 DOI: 10.1021/acs.jcim.3c01933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 02/23/2024] [Accepted: 02/26/2024] [Indexed: 03/11/2024]
Abstract
The highly conserved protease enzyme from SARS-CoV-2 (MPro) is crucial for viral replication and is an attractive target for the design of novel inhibitory compounds. MPro is known to be conformationally flexible and has been stabilized in an extended conformation in a complex with a novel nanobody (NB2B4), which inhibits the dimerization of the enzyme via binding to an allosteric site. However, the energetic contributions of the nanobody residues stabilizing the MPro/nanobody interface remain unresolved. We probed these residues using all-atom MD simulations in combination with alchemical free energy calculations by studying the physical residue-residue interactions and discovered the role of hydrophobic and electrostatic interactions in stabilizing the complex. Specifically, we found via mutational analysis that three interfacial nanobody residues (Y59, R106, and L109) contributed significantly, two residues (L107 and P110) contributed moderately, and two residues (H112 and T113) contributed minimally to the overall binding affinity of the nanobody. We also discovered that the nanobody affinity could be enhanced via a charge-reversal mutation (D62R) that alters the local interfacial electrostatic environment of this residue in the complex. These findings are potentially useful in designing novel synthetic nanobodies as allosteric inhibitors of MPro.
Collapse
Affiliation(s)
- Amit Kumar
- Department
of Physics and Astronomy, Wayne State University, Detroit, Michigan 48201, United States
| | - Harish Vashisth
- Department
of Chemical Engineering and Bioengineering, University of New Hampshire, Durham, New Hampshire 03824, United States
| |
Collapse
|
9
|
Lam CK, Fung LY, Wang Y. Orientation and Membrane Partition Free Energy of PeT-Based Voltage-Sensitive Dyes from Molecular Simulations. J Phys Chem B 2024; 128:2734-2744. [PMID: 38459942 PMCID: PMC10961725 DOI: 10.1021/acs.jpcb.3c08090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 02/19/2024] [Accepted: 02/20/2024] [Indexed: 03/11/2024]
Abstract
Voltage measurement via small-molecule fluorescent indicators is a valuable approach in deciphering complex dynamics in electrically excitable cells. However, our understanding of various physicochemical properties governing the performance of fluorescent voltage sensors based on the photoinduced electron transfer (PeT) mechanism remains incomplete. Here, through extensive molecular dynamics and free energy calculations, we systematically examine the orientation and membrane partition of three PeT-based voltage-sensing VoltageFluor (VF) dyes in different lipid environment. We show that the symmetry of the molecular scaffold and the net charge of the hydrophilic headgroup of a given VF dye dominate its orientation and membrane partition, respectively. Our work provides a mechanistic understanding of the physical properties contributing to the voltage sensitivity, signal-to-noise ratio, as well as membrane distribution of VF dyes and sheds light onto rational design principles of PeT-based fluorescent probes in general.
Collapse
Affiliation(s)
- Chun Kei Lam
- Department of Physics, The
Chinese University
of Hong Kong, Shatin, Hong Kong SAR, China
| | - Lap Yan Fung
- Department of Physics, The
Chinese University
of Hong Kong, Shatin, Hong Kong SAR, China
| | - Yi Wang
- Department of Physics, The
Chinese University
of Hong Kong, Shatin, Hong Kong SAR, China
| |
Collapse
|
10
|
Zhou M, Zhao F, Yu L, Liu J, Wang J, Zhang JZH. An Efficient Approach to the Accurate Prediction of Mutational Effects in Antigen Binding to the MHC1. Molecules 2024; 29:881. [PMID: 38398632 PMCID: PMC10892774 DOI: 10.3390/molecules29040881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 02/07/2024] [Accepted: 02/14/2024] [Indexed: 02/25/2024] Open
Abstract
The major histocompatibility complex (MHC) can recognize and bind to external peptides to generate effective immune responses by presenting the peptides to T cells. Therefore, understanding the binding modes of peptide-MHC complexes (pMHC) and predicting the binding affinity of pMHCs play a crucial role in the rational design of peptide vaccines. In this study, we employed molecular dynamics (MD) simulations and free energy calculations with an Alanine Scanning with Generalized Born and Interaction Entropy (ASGBIE) method to investigate the protein-peptide interaction between HLA-A*02:01 and the G9209 peptide derived from the melanoma antigen gp100. The energy contribution of individual residue was calculated using alanine scanning, and hotspots on both the MHC and the peptides were identified. Our study shows that the pMHC binding is dominated by the van der Waals interactions. Furthermore, we optimized the ASGBIE method, achieving a Pearson correlation coefficient of 0.91 between predicted and experimental binding affinity for mutated antigens. This represents a significant improvement over the conventional MM/GBSA method, which yields a Pearson correlation coefficient of 0.22. The computational protocol developed in this study can be applied to the computational screening of antigens for the MHC1 as well as other protein-peptide binding systems.
Collapse
Affiliation(s)
- Mengchen Zhou
- Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China;
| | - Fanyu Zhao
- NYU-ECNU Center for Computational Chemistry and Shanghai Frontiers Science Center of AI and DL, NYU Shanghai, 567 West Yangsi Road, Shanghai 200126, China;
| | - Lan Yu
- Department of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Jinfeng Liu
- Department of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Jian Wang
- Faculty of Synthetic Biology and Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China;
| | - John Z. H. Zhang
- Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China;
- NYU-ECNU Center for Computational Chemistry and Shanghai Frontiers Science Center of AI and DL, NYU Shanghai, 567 West Yangsi Road, Shanghai 200126, China;
- Faculty of Synthetic Biology and Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China;
- Department of Chemistry, New York University, New York, NY 10003, USA
- Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan 030006, China
| |
Collapse
|
11
|
Khuttan S, Gallicchio E. What to Make of Zero: Resolving the Statistical Noise from Conformational Reorganization in Alchemical Binding Free Energy Estimates with Metadynamics Sampling. J Chem Theory Comput 2024; 20:1489-1501. [PMID: 38252868 PMCID: PMC10867849 DOI: 10.1021/acs.jctc.3c01250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 01/03/2024] [Accepted: 01/03/2024] [Indexed: 01/24/2024]
Abstract
We introduce the self-relative binding free energy (self-RBFE) approach to evaluate the intrinsic statistical variance of dual-topology alchemical binding free energy estimators. The self-RBFE is the relative binding free energy between a ligand and a copy of the same ligand, and its true value is zero. Nevertheless, because the two copies of the ligand move independently, the self-RBFE value produced by a finite-length simulation fluctuates and can be used to measure the variance of the model. The results of this validation provide evidence that a significant fraction of the errors observed in benchmark studies reflect the statistical fluctuations of unconverged estimates rather than the models' accuracy. Furthermore, we find that ligand reorganization is a significant contributing factor to the statistical variance of binding free energy estimates and that metadynamics-accelerated conformational sampling of the torsional degrees of freedom of the ligand can drastically reduce the time to convergence.
Collapse
Affiliation(s)
- Sheenam Khuttan
- 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 Biochemistry, The Graduate Center
of the City University of New York, New York, New York 10016, 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 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
|
12
|
Wang X, Nayak S, Wilson RE, Soderholm L, Servis MJ. Solvent effects on extractant conformational energetics in liquid-liquid extraction: a simulation study of molecular solvents and ionic liquids. Phys Chem Chem Phys 2024; 26:2877-2886. [PMID: 38048065 DOI: 10.1039/d3cp04680j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Extractant design in liquid-liquid extraction (LLE) is a research frontier of metal ion separations that typically focuses on the direct extractant-metal interactions. However, a more detailed understanding of energetic drivers of separations beyond primary metal coordination is often lacking, including the role of solvent in the extractant phase. In this work, we propose a new mechanism for enhancing metal-complexant energetics with nanostructured solvents. Using molecular dynamics simulations with umbrella sampling, we find that the organic solvent can reshape the energetics of the extractant's intramolecular conformational landscape. We calculate free energy profiles of different conformations of a representative bidentate extractant, n-octyl(phenyl)-N,N-diisobutyl carbamoyl methyl phosphinoxide (CMPO), in four different solvents: dodecane, tributyl phosphate (TBP), and dry and wet ionic liquid (IL) 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][Tf2N]). By promoting reorganization of the extractant molecule into its binding conformation, our findings reveal how particular solvents can ameliorate this unfavorable step of the metal separation process. In particular, the charge alternating nanodomains formed in ILs substantially reduce the free energy penalty associated with extractant reorganization. Importantly, using alchemical free energy calculations, we find that this stabilization persists even when we explicitly include the extracted cation. These findings provide insight into the energetic drivers of metal ion separations and potentially suggest a new approach to designing effective separations using a molecular-level understanding of solvent effects.
Collapse
Affiliation(s)
- Xiaoyu Wang
- Chemical Sciences and Engineering Division, Argonne National Laboratory, 9700 S Cass Ave, Lemont, IL 60439, USA.
| | - Srikanth Nayak
- Chemical Sciences and Engineering Division, Argonne National Laboratory, 9700 S Cass Ave, Lemont, IL 60439, USA.
| | - Richard E Wilson
- Chemical Sciences and Engineering Division, Argonne National Laboratory, 9700 S Cass Ave, Lemont, IL 60439, USA.
| | - L Soderholm
- Chemical Sciences and Engineering Division, Argonne National Laboratory, 9700 S Cass Ave, Lemont, IL 60439, USA.
| | - Michael J Servis
- Chemical Sciences and Engineering Division, Argonne National Laboratory, 9700 S Cass Ave, Lemont, IL 60439, USA.
| |
Collapse
|
13
|
Hayes RL, Nixon CF, Marqusee S, Brooks CL. Selection pressures on evolution of ribonuclease H explored with rigorous free-energy-based design. Proc Natl Acad Sci U S A 2024; 121:e2312029121. [PMID: 38194446 PMCID: PMC10801872 DOI: 10.1073/pnas.2312029121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/22/2023] [Indexed: 01/11/2024] Open
Abstract
Understanding natural protein evolution and designing novel proteins are motivating interest in development of high-throughput methods to explore large sequence spaces. In this work, we demonstrate the application of multisite λ dynamics (MSλD), a rigorous free energy simulation method, and chemical denaturation experiments to quantify evolutionary selection pressure from sequence-stability relationships and to address questions of design. This study examines a mesophilic phylogenetic clade of ribonuclease H (RNase H), furthering its extensive characterization in earlier studies, focusing on E. coli RNase H (ecRNH) and a more stable consensus sequence (AncCcons) differing at 15 positions. The stabilities of 32,768 chimeras between these two sequences were computed using the MSλD framework. The most stable and least stable chimeras were predicted and tested along with several other sequences, revealing a designed chimera with approximately the same stability increase as AncCcons, but requiring only half the mutations. Comparing the computed stabilities with experiment for 12 sequences reveals a Pearson correlation of 0.86 and root mean squared error of 1.18 kcal/mol, an unprecedented level of accuracy well beyond less rigorous computational design methods. We then quantified selection pressure using a simple evolutionary model in which sequences are selected according to the Boltzmann factor of their stability. Selection temperatures from 110 to 168 K are estimated in three ways by comparing experimental and computational results to evolutionary models. These estimates indicate selection pressure is high, which has implications for evolutionary dynamics and for the accuracy required for design, and suggests accurate high-throughput computational methods like MSλD may enable more effective protein design.
Collapse
Affiliation(s)
- Ryan L. Hayes
- Department of Chemical and Biomolecular Engineering, University of California, Irvine, CA92697
- Department of Chemistry, University of Michigan, Ann Arbor, MI48109
| | - Charlotte F. Nixon
- Department of Molecular and Cell Biology, University of California, Berkeley, CA94720
| | - Susan Marqusee
- Department of Molecular and Cell Biology, University of California, Berkeley, CA94720
- California Institute for Quantitative Biosciences, University of California, Berkeley, CA94720
- Department of Chemistry, University of California, Berkeley, CA94720
| | - Charles L. Brooks
- Department of Chemistry, University of Michigan, Ann Arbor, MI48109
- Biophysics Program, University of Michigan, Ann Arbor, MI48109
| |
Collapse
|
14
|
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: 5] [Impact Index Per Article: 5.0] [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
|
15
|
Robo MT, Hayes RL, Ding X, Pulawski B, Vilseck JZ. Fast free energy estimates from λ-dynamics with bias-updated Gibbs sampling. Nat Commun 2023; 14:8515. [PMID: 38129400 PMCID: PMC10740020 DOI: 10.1038/s41467-023-44208-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 12/04/2023] [Indexed: 12/23/2023] Open
Abstract
Relative binding free energy calculations have become an integral computational tool for lead optimization in structure-based drug design. Classical alchemical methods, including free energy perturbation or thermodynamic integration, compute relative free energy differences by transforming one molecule into another. However, these methods have high operational costs due to the need to perform many pairwise perturbations independently. To reduce costs and accelerate molecular design workflows, we present a method called λ-dynamics with bias-updated Gibbs sampling. This method uses dynamic biases to continuously sample between multiple ligand analogues collectively within a single simulation. We show that many relative binding free energies can be determined quickly with this approach without compromising accuracy. For five benchmark systems, agreement to experiment is high, with root mean square errors near or below 1.0 kcal mol-1. Free energy results are consistent with other computational approaches and within statistical noise of both methods (0.4 kcal mol-1 or less). Notably, large efficiency gains over thermodynamic integration of 18-66-fold for small perturbations and 100-200-fold for whole aromatic ring substitutions are observed. The rapid determination of relative binding free energies will enable larger chemical spaces to be more readily explored and structure-based drug design to be accelerated.
Collapse
Affiliation(s)
- Michael T Robo
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Biosciences Research Institute, 1210 Waterway Blvd Ste. 2000, Indianapolis, IN, 46202, USA
| | - Ryan L Hayes
- Chemical and Biomolecular Engineering, University of California, Irvine, California, 92617, USA
- Pharmaceutical Sciences, University of California, Irvine, CA, 92617, USA
| | - Xinqiang Ding
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Chemistry, Tufts University, Medford, MA, 02144, USA
| | - Brian Pulawski
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Jonah Z Vilseck
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
| |
Collapse
|
16
|
Vögele M, Zhang BW, Kaindl J, Wang L. Is the Functional Response of a Receptor Determined by the Thermodynamics of Ligand Binding? J Chem Theory Comput 2023; 19:8414-8422. [PMID: 37943175 DOI: 10.1021/acs.jctc.3c00899] [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: 11/10/2023]
Abstract
For an effective drug, strong binding to the target protein is a prerequisite, but it is not enough. To produce a particular functional response, drugs need to either block the proteins' functions or modulate their activities by changing their conformational equilibrium. The binding free energy of a compound to its target is routinely calculated, but the timescales for the protein conformational changes are prohibitively long to be efficiently modeled via physics-based simulations. Thermodynamic principles suggest that the binding free energies of the ligands with different receptor conformations may infer their efficacy. However, this hypothesis has not been thoroughly validated. We present an actionable protocol and a comprehensive study to show that binding thermodynamics provides a strong predictor of the efficacy of a ligand. We apply the absolute binding free energy perturbation method to ligands bound to active and inactive states of eight G protein-coupled receptors and a nuclear receptor and then compare the resulting binding free energies. We find that carefully designed restraints are often necessary to efficiently model the corresponding conformational ensembles for each state. Our method achieves unprecedented performance in classifying ligands as agonists or antagonists across the various investigated receptors, all of which are important drug targets.
Collapse
Affiliation(s)
- Martin Vögele
- Schrödinger, Inc., 1540 Broadway 24th Floor, New York, New York 10036, United States
| | - Bin W Zhang
- Schrödinger, Inc., 1540 Broadway 24th Floor, New York, New York 10036, United States
| | - Jonas Kaindl
- Schrödinger GmbH, Glücksteinallee 25, Mannheim 68163, Germany
| | - Lingle Wang
- Schrödinger, Inc., 1540 Broadway 24th Floor, New York, New York 10036, United States
| |
Collapse
|
17
|
Papadourakis M, Sinenka H, Matricon P, Hénin J, Brannigan G, Pérez-Benito L, Pande V, van Vlijmen H, de Graaf C, Deflorian F, Tresadern G, Cecchini M, Cournia Z. Alchemical Free Energy Calculations on Membrane-Associated Proteins. J Chem Theory Comput 2023; 19:7437-7458. [PMID: 37902715 PMCID: PMC11017255 DOI: 10.1021/acs.jctc.3c00365] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Indexed: 10/31/2023]
Abstract
Membrane proteins have diverse functions within cells and are well-established drug targets. The advances in membrane protein structural biology have revealed drug and lipid binding sites on membrane proteins, while computational methods such as molecular simulations can resolve the thermodynamic basis of these interactions. Particularly, alchemical free energy calculations have shown promise in the calculation of reliable and reproducible binding free energies of protein-ligand and protein-lipid complexes in membrane-associated systems. In this review, we present an overview of representative alchemical free energy studies on G-protein-coupled receptors, ion channels, transporters as well as protein-lipid interactions, with emphasis on best practices and critical aspects of running these simulations. Additionally, we analyze challenges and successes when running alchemical free energy calculations on membrane-associated proteins. Finally, we highlight the value of alchemical free energy calculations calculations in drug discovery and their applicability in the pharmaceutical industry.
Collapse
Affiliation(s)
- Michail Papadourakis
- Biomedical
Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece
| | - Hryhory Sinenka
- Institut
de Chimie de Strasbourg, UMR7177, CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France
| | - Pierre Matricon
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Jérôme Hénin
- Laboratoire
de Biochimie Théorique UPR 9080, CNRS and Université Paris Cité, 75005 Paris, France
| | - Grace Brannigan
- Center
for Computational and Integrative Biology, Rutgers University−Camden, Camden, New Jersey 08103, United States of America
- Department
of Physics, Rutgers University−Camden, Camden, New Jersey 08102, United States
of America
| | - Laura Pérez-Benito
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Vineet Pande
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Herman van Vlijmen
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Chris de Graaf
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Francesca Deflorian
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Gary Tresadern
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Marco Cecchini
- Institut
de Chimie de Strasbourg, UMR7177, CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France
| | - Zoe Cournia
- Biomedical
Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece
| |
Collapse
|
18
|
Hernández González JE, de Araujo AS. Alchemical Calculation of Relative Free Energies for Charge-Changing Mutations at Protein-Protein Interfaces Considering Fixed and Variable Protonation States. J Chem Inf Model 2023; 63:6807-6822. [PMID: 37851531 DOI: 10.1021/acs.jcim.3c00972] [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: 10/20/2023]
Abstract
The calculation of relative free energies (ΔΔG) for charge-changing mutations at protein-protein interfaces through alchemical methods remains challenging due to variations in the system's net charge during charging steps, the possibility of mutated and contacting ionizable residues occurring in various protonation states, and undersampling issues. In this study, we present a set of strategies, collectively termed TIRST/TIRST-H+, to address some of these challenges. Our approaches combine thermodynamic integration (TI) with the prediction of pKa shifts to calculate ΔΔG values. Moreover, special sets of restraints are employed to keep the alchemically transformed molecules separated. The accuracy of the devised approaches was assessed on a large and diverse data set comprising 164 point mutations of charged residues (Asp, Glu, Lys, and Arg) to Ala at the protein-protein interfaces of complexes with known three-dimensional structures. Mean absolute and root-mean-square errors ranging from 1.38 to 1.66 and 1.89 to 2.44 kcal/mol, respectively, and Pearson correlation coefficients of ∼0.6 were obtained when testing the approaches on the selected data set using the GPU-TI module of Amber18 suite and the ff14SB force field. Furthermore, the inclusion of variable protonation states for the mutated acid residues improved the accuracy of the predicted ΔΔG values. Therefore, our results validate the use of TIRST/TIRST-H+ in prospective studies aimed at evaluating the impact of charge-changing mutations to Ala on the stability of protein-protein complexes.
Collapse
|
19
|
Baumann H, Dybeck E, McClendon CL, Pickard FC, Gapsys V, Pérez-Benito L, Hahn DF, Tresadern G, Mathiowetz AM, Mobley DL. Broadening the Scope of Binding Free Energy Calculations Using a Separated Topologies Approach. J Chem Theory Comput 2023; 19:5058-5076. [PMID: 37487138 PMCID: PMC10413862 DOI: 10.1021/acs.jctc.3c00282] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Indexed: 07/26/2023]
Abstract
Binding free energy calculations predict the potency of compounds to protein binding sites in a physically rigorous manner and see broad application in prioritizing the synthesis of novel drug candidates. Relative binding free energy (RBFE) calculations have emerged as an industry-standard approach to achieve highly accurate rank-order predictions of the potency of related compounds; however, this approach requires that the ligands share a common scaffold and a common binding mode, restricting the methods' domain of applicability. This is a critical limitation since complex modifications to the ligands, especially core hopping, are very common in drug design. Absolute binding free energy (ABFE) calculations are an alternate method that can be used for ligands that are not congeneric. However, ABFE suffers from a known problem of long convergence times due to the need to sample additional degrees of freedom within each system, such as sampling rearrangements necessary to open and close the binding site. Here, we report on an alternative method for RBFE, called Separated Topologies (SepTop), which overcomes the issues in both of the aforementioned methods by enabling large scaffold changes between ligands with a convergence time comparable to traditional RBFE. Instead of only mutating atoms that vary between two ligands, this approach performs two absolute free energy calculations at the same time in opposite directions, one for each ligand. Defining the two ligands independently allows the comparison of the binding of diverse ligands without the artificial constraints of identical poses or a suitable atom-atom mapping. This approach also avoids the need to sample the unbound state of the protein, making it more efficient than absolute binding free energy calculations. Here, we introduce an implementation of SepTop. We developed a general and efficient protocol for running SepTop, and we demonstrated the method on four diverse, pharmaceutically relevant systems. We report the performance of the method, as well as our practical insights into the strengths, weaknesses, and challenges of applying this method in an industrial drug design setting. We find that the accuracy of the approach is sufficiently high to rank order ligands with an accuracy comparable to traditional RBFE calculations while maintaining the additional flexibility of SepTop.
Collapse
Affiliation(s)
- Hannah
M. Baumann
- Department
of Pharmaceutical Sciences, University of
California, Irvine, Irvine, California 92697, United States
| | - Eric Dybeck
- Pfizer
Worldwide Research, Development, and Medical, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - Christopher L. McClendon
- Pfizer
Worldwide Research, Development, and Medical, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - Frank C. Pickard
- Pfizer
Worldwide Research, Development, and Medical, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - Vytautas Gapsys
- Computational
Chemistry, Janssen Research & Development, Janssen Pharmaceutica N. V., Turnhoutseweg 30, B-2340 Beerse, Belgium
| | - Laura Pérez-Benito
- Computational
Chemistry, Janssen Research & Development, Janssen Pharmaceutica N. V., Turnhoutseweg 30, B-2340 Beerse, Belgium
| | - David F. Hahn
- Computational
Chemistry, Janssen Research & Development, Janssen Pharmaceutica N. V., Turnhoutseweg 30, B-2340 Beerse, Belgium
| | - Gary Tresadern
- Computational
Chemistry, Janssen Research & Development, Janssen Pharmaceutica N. V., Turnhoutseweg 30, B-2340 Beerse, Belgium
| | - Alan M. Mathiowetz
- Pfizer
Worldwide Research, Development, and Medical, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - David L. Mobley
- Department
of Pharmaceutical Sciences, University of
California, Irvine, Irvine, California 92697, United States
- Department
of Chemistry, University of California,
Irvine, Irvine, California 92697, United States
| |
Collapse
|
20
|
Chen W, Cui D, Jerome SV, Michino M, Lenselink EB, Huggins DJ, Beautrait A, Vendome J, Abel R, Friesner RA, Wang L. Enhancing Hit Discovery in Virtual Screening through Absolute Protein-Ligand Binding Free-Energy Calculations. J Chem Inf Model 2023; 63:3171-3185. [PMID: 37167486 DOI: 10.1021/acs.jcim.3c00013] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
In the hit identification stage of drug discovery, a diverse chemical space needs to be explored to identify initial hits. Contrary to empirical scoring functions, absolute protein-ligand binding free-energy perturbation (ABFEP) provides a theoretically more rigorous and accurate description of protein-ligand binding thermodynamics and could, in principle, greatly improve the hit rates in virtual screening. In this work, we describe an implementation of an accurate and reliable ABFEP method in FEP+. We validated the ABFEP method on eight congeneric compound series binding to eight protein receptors including both neutral and charged ligands. For ligands with net charges, the alchemical ion approach is adopted to avoid artifacts in electrostatic potential energy calculations. The calculated binding free energies correlate with experimental results with a weighted average of R2 = 0.55 for the entire dataset. We also observe an overall root-mean-square error (RMSE) of 1.1 kcal/mol after shifting the zero-point of the simulation data to match the average experimental values. Through ABFEP calculations using apo versus holo protein structures, we demonstrated that the protein conformational and protonation state changes between the apo and holo proteins are the main physical factors contributing to the protein reorganization free energy manifested by the overestimation of raw ABFEP calculated binding free energies using the holo structures of the proteins. Furthermore, we performed ABFEP calculations in three virtual screening applications for hit enrichment. ABFEP greatly improves the hit rates as compared to docking scores or other methods like metadynamics. The good performance of ABFEP in rank ordering compounds demonstrated in this work confirms it as a useful tool to improve the hit rates in virtual screening, thus facilitating hit discovery.
Collapse
Affiliation(s)
- Wei Chen
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Di Cui
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Steven V Jerome
- Schrödinger, Inc., 10201 Wateridge Circle, Suite 220, San Diego, California 92121, United States
| | - Mayako Michino
- Tri-Institutional Therapeutics Discovery Institute, 413 E. 69th Street, New York, New York 10065, United States
| | | | - David J Huggins
- Tri-Institutional Therapeutics Discovery Institute, 413 E. 69th Street, New York, New York 10065, United States
- Department of Physiology and Biophysics, Weill Cornell Medical College of Cornell University, New York, New York 10065, United States
| | - Alexandre Beautrait
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Jeremie Vendome
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Robert Abel
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Richard A Friesner
- Department of Chemistry, Columbia University, New York, New York 10027, United States
| | - Lingle Wang
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| |
Collapse
|
21
|
Chung MKJ, Miller RJ, Novak B, Wang Z, Ponder JW. Accurate Host-Guest Binding Free Energies Using the AMOEBA Polarizable Force Field. J Chem Inf Model 2023; 63:2769-2782. [PMID: 37075788 PMCID: PMC10878370 DOI: 10.1021/acs.jcim.3c00155] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
Abstract
A grand challenge of computational biophysics is accurate prediction of interactions between molecules. Molecular dynamics (MD) simulations have recently gained much interest as a tool to directly compute rigorous intermolecular binding affinities. The choice of a fixed point-charge or polarizable multipole force field used in MD is a topic of ongoing discussion. To compare alternative methods, we participated in the SAMPL7 and SAMPL8 Gibb octaacid host-guest challenges to assess the Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) polarizable multipole force field. Advantages of AMOEBA over fixed charge models include improved representation of molecular electrostatic potentials and better description of water occupying the unligated host cavity. Prospective predictions for 26 host-guest systems exhibit a mean unsigned error vs experiment of 0.848 kcal/mol across all absolute binding free energies, demonstrating excellent agreement between computational and experimental results. In addition, we explore two topics related to the inclusion of ions in MD simulations: use of a neutral co-alchemical protocol and the effect of salt concentration on binding affinity. Use of the co-alchemical method minimally affects computed energies, but salt concentration significantly perturbs our binding results. Higher salt concentration strengthens binding through classical charge screening. In particular, added Na+ ions screen negatively charged carboxylate groups near the binding cavity, thereby diminishing repulsive coulomb interactions with negatively charged guests. Overall, the AMOEBA results demonstrate the accuracy available through a force field providing a detailed energetic description of the four octaacid hosts and 13 charged organic guests. Use of the AMOEBA polarizable atomic multipole force field in conjunction with an alchemical free energy protocol can achieve chemical accuracy in application to realistic molecular systems.
Collapse
Affiliation(s)
- Moses K. J. Chung
- Medical Scientist Training Program, Washington University School of Medicine, Saint Louis, MO 63110, USA
- Department of Physics, Washington University in St. Louis, Saint Louis, MO 63130, USA
| | - Ryan J. Miller
- Department of Chemistry, Washington University in St. Louis, Saint Louis, MO 63130, USA
| | - Borna Novak
- Medical Scientist Training Program, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Zhi Wang
- Department of Chemistry, Washington University in St. Louis, Saint Louis, MO 63130, USA
| | - Jay W. Ponder
- Department of Chemistry, Washington University in St. Louis, Saint Louis, MO 63130, USA
- Department of Biochemistry & Molecular Biophysics, Washington University School of Medicine, Saint Louis, MO 63110, USA
| |
Collapse
|
22
|
Sabanés Zariquiey F, Pérez A, Majewski M, Gallicchio E, De Fabritiis G. Validation of the Alchemical Transfer Method for the Estimation of Relative Binding Affinities of Molecular Series. J Chem Inf Model 2023; 63:2438-2444. [PMID: 37042797 PMCID: PMC10577236 DOI: 10.1021/acs.jcim.3c00178] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
The accurate prediction of protein-ligand binding affinities is crucial for drug discovery. Alchemical free energy calculations have become a popular tool for this purpose. However, the accuracy and reliability of these methods can vary depending on the methodology. In this study, we evaluate the performance of a relative binding free energy protocol based on the alchemical transfer method (ATM), a novel approach based on a coordinate transformation that swaps the positions of two ligands. The results show that ATM matches the performance of more complex free energy perturbation (FEP) methods in terms of Pearson correlation but with marginally higher mean absolute errors. This study shows that the ATM method is competitive compared to more traditional methods in speed and accuracy and offers the advantage of being applicable with any potential energy function.
Collapse
Affiliation(s)
- Francesc Sabanés Zariquiey
- Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), C Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Adrià Pérez
- Acellera Labs, C Dr Trueta 183, 08005 Barcelona, Spain
| | | | - Emilio Gallicchio
- Department of Chemistry, Brooklyn College of the City University of New York, New York, New York 11210, United States
- PhD Program in Chemistry Graduate Center of the City University of New York, New York, New York 10016, United States
- PhD Program in Biochemistry, Graduate Center of the City University of New York, New York, New York 10016, United States
| | - Gianni De Fabritiis
- Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), C Dr. Aiguader 88, 08003 Barcelona, Spain
- Acellera, Devonshire House 582 Honeypot Lane, Stanmore, Middlesex HA7 1JS, United Kingdom
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluis Companys 23, 08010 Barcelona, Spain
| |
Collapse
|
23
|
Farafonov VS, Lebed AV, Nerukh DA, Mchedlov-Petrossyan NO. Estimation of Nanoparticle's Surface Electrostatic Potential in Solution Using Acid-Base Molecular Probes I: In Silico Implementation for Surfactant Micelles. J Phys Chem B 2023; 127:1022-1030. [PMID: 36655872 DOI: 10.1021/acs.jpcb.2c07012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Surface electrostatic potential Ψ is a key characteristic of colloid particles. Since the surface of the particles adsorbs various compounds and facilitates chemical reactions between them, Ψ largely affects the properties of adsorbed reactants and governs the flow of chemical reactions occurring between them. One of the most popular methods for estimating Ψ in hydrophilic colloids, such as micellar surfactant solutions and related systems, is the application of molecular probes, predominantly acid-base indicator dyes. The Ψ value is calculated from the difference of the probe's indices of the apparent acidity constant between the examined colloid solution and, usually, some other colloid solution with noncharged particles. Here, we show how to implement this method in silico using alchemical free energy calculations within the framework of molecular dynamics simulations. The proposed implementation is tested on surfactant micelles and is shown to predict experimental Ψ values with quantitative accuracy depending on the kind of surfactant. The sources of errors in the method are discussed, and recommendations for its application are given.
Collapse
Affiliation(s)
- Vladimir S Farafonov
- Department of Physical Chemistry, V. N. Karazin National University, Kharkiv61022, Ukraine.,Department of Mathematics, Aston University, BirminghamB4 7ET, U.K
| | - Alexander V Lebed
- Department of Physical Chemistry, V. N. Karazin National University, Kharkiv61022, Ukraine
| | - Dmitry A Nerukh
- Department of Mathematics, Aston University, BirminghamB4 7ET, U.K
| | | |
Collapse
|
24
|
Xu H. The slow but steady rise of binding free energy calculations in drug discovery. J Comput Aided Mol Des 2023; 37:67-74. [PMID: 36469232 DOI: 10.1007/s10822-022-00494-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 11/28/2022] [Indexed: 12/12/2022]
Abstract
Binding free energy calculations are increasingly used in drug discovery research to predict protein-ligand binding affinities and to prioritize candidate drug molecules accordingly. It has taken decades of collective effort to transform this academic concept into a technology adopted by the pharmaceutical and biotech industry. Having personally witnessed and taken part in this transformation, here I recount the (incomplete) list of problems that had to be solved to make this computational tool practical and suggest areas of future development.
Collapse
Affiliation(s)
- Huafeng Xu
- Roivant Discovery, 151 West 42nd Street, New York, NY, 10036, USA.
| |
Collapse
|
25
|
Gizzio J, Thakur A, Haldane A, Levy RM. Evolutionary divergence in the conformational landscapes of tyrosine vs serine/threonine kinases. eLife 2022; 11:83368. [PMID: 36562610 PMCID: PMC9822262 DOI: 10.7554/elife.83368] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 12/22/2022] [Indexed: 12/24/2022] Open
Abstract
Inactive conformations of protein kinase catalytic domains where the DFG motif has a "DFG-out" orientation and the activation loop is folded present a druggable binding pocket that is targeted by FDA-approved 'type-II inhibitors' in the treatment of cancers. Tyrosine kinases (TKs) typically show strong binding affinity with a wide spectrum of type-II inhibitors while serine/threonine kinases (STKs) usually bind more weakly which we suggest here is due to differences in the folded to extended conformational equilibrium of the activation loop between TKs vs. STKs. To investigate this, we use sequence covariation analysis with a Potts Hamiltonian statistical energy model to guide absolute binding free-energy molecular dynamics simulations of 74 protein-ligand complexes. Using the calculated binding free energies together with experimental values, we estimated free-energy costs for the large-scale (~17-20 Å) conformational change of the activation loop by an indirect approach, circumventing the very challenging problem of simulating the conformational change directly. We also used the Potts statistical potential to thread large sequence ensembles over active and inactive kinase states. The structure-based and sequence-based analyses are consistent; together they suggest TKs evolved to have free-energy penalties for the classical 'folded activation loop' DFG-out conformation relative to the active conformation, that is, on average, 4-6 kcal/mol smaller than the corresponding values for STKs. Potts statistical energy analysis suggests a molecular basis for this observation, wherein the activation loops of TKs are more weakly 'anchored' against the catalytic loop motif in the active conformation and form more stable substrate-mimicking interactions in the inactive conformation. These results provide insights into the molecular basis for the divergent functional properties of TKs and STKs, and have pharmacological implications for the target selectivity of type-II inhibitors.
Collapse
Affiliation(s)
- Joan Gizzio
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, United States.,Department of Chemistry, Temple University, Philadelphia, United States
| | - Abhishek Thakur
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, United States.,Department of Chemistry, Temple University, Philadelphia, United States
| | - Allan Haldane
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, United States.,Department of Physics, Temple University, Philadelphia, United States
| | - Ronald M Levy
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, United States.,Department of Chemistry, Temple University, Philadelphia, United States
| |
Collapse
|
26
|
Gao Y, Wang B, Hu S, Zhu T, Zhang JZH. An efficient method to predict protein thermostability in alanine mutation. Phys Chem Chem Phys 2022; 24:29629-29639. [PMID: 36449314 DOI: 10.1039/d2cp04236c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The relationship between protein sequence and its thermodynamic stability is a critical aspect of computational protein design. In this work, we present a new theoretical method to calculate the free energy change (ΔΔG) resulting from a single-point amino acid mutation to alanine in a protein sequence. The method is derived based on physical interactions and is very efficient in estimating the free energy changes caused by a series of alanine mutations from just a single molecular dynamics (MD) trajectory. Numerical calculations are carried out on a total of 547 alanine mutations in 19 diverse proteins whose experimental results are available. The comparison between the experimental ΔΔGexp and the calculated values shows a generally good correlation with a correlation coefficient of 0.67. Both the advantages and limitations of this method are discussed. This method provides an efficient and valuable tool for protein design and engineering.
Collapse
Affiliation(s)
- Ya Gao
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai 201620, China
| | - Bo Wang
- Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.
| | - Shiyu Hu
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
| | - Tong Zhu
- Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China. .,NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
| | - John Z H Zhang
- Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China. .,NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China.,Shenzhen Institute of Synthetic Biology, Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| |
Collapse
|
27
|
Harris JA, Liu R, Martins de Oliveira V, Vázquez-Montelongo EA, Henderson JA, Shen J. GPU-Accelerated All-Atom Particle-Mesh Ewald Continuous Constant pH Molecular Dynamics in Amber. J Chem Theory Comput 2022; 18:7510-7527. [PMID: 36377980 PMCID: PMC10130738 DOI: 10.1021/acs.jctc.2c00586] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Constant pH molecular dynamics (MD) simulations sample protonation states on the fly according to the conformational environment and user specified pH conditions; however, the current accuracy is limited due to the use of implicit-solvent models or a hybrid solvent scheme. Here, we report the first GPU-accelerated implementation, parametrization, and validation of the all-atom continuous constant pH MD (CpHMD) method with particle-mesh Ewald (PME) electrostatics in the Amber22 pmemd.cuda engine. The titration parameters for Asp, Glu, His, Cys, and Lys were derived for the CHARMM c22 and Amber ff14sb and ff19sb force fields. We then evaluated the PME-CpHMD method using the asynchronous pH replica-exchange titration simulations with the c22 force field for six benchmark proteins, including BBL, hen egg white lysozyme (HEWL), staphylococcal nuclease (SNase), thioredoxin, ribonuclease A (RNaseA), and human muscle creatine kinase (HMCK). The root-mean-square deviation from the experimental pKa's of Asp, Glu, His, and Cys is 0.76 pH units, and the Pearson's correlation coefficient for the pKa shifts with respect to model values is 0.80. We demonstrated that a finite-size correction or much enlarged simulation box size can remove a systematic error of the calculated pKa's and improve agreement with experiment. Importantly, the simulations captured the relevant biology in several challenging cases, e.g., the titration order of the catalytic dyad Glu35/Asp52 in HEWL and the coupled residues Asp19/Asp21 in SNase, the large pKa upshift of the deeply buried catalytic Asp26 in thioredoxin, and the large pKa downshift of the deeply buried catalytic Cys283 in HMCK. We anticipate that PME-CpHMD will offer proper pH control to improve the accuracies of MD simulations and enable mechanistic studies of proton-coupled dynamical processes that are ubiquitous in biology but remain poorly understood due to the lack of experimental tools and limitation of current MD simulations.
Collapse
Affiliation(s)
- Julie A Harris
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, Baltimore, Maryland21201, United States
| | - Ruibin Liu
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, Baltimore, Maryland21201, United States
| | - Vinicius Martins de Oliveira
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, Baltimore, Maryland21201, United States.,Lilly Biotechnology Center, San Diego, California92121, United States
| | | | - Jack A Henderson
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, Baltimore, Maryland21201, United States
| | - Jana Shen
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, Baltimore, Maryland21201, United States
| |
Collapse
|
28
|
Ganguly A, Tsai HC, Fernández-Pendás M, Lee TS, Giese TJ, York DM. AMBER Drug Discovery Boost Tools: Automated Workflow for Production Free-Energy Simulation Setup and Analysis (ProFESSA). J Chem Inf Model 2022; 62:6069-6083. [PMID: 36450130 PMCID: PMC9881431 DOI: 10.1021/acs.jcim.2c00879] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
We report an automated workflow for production free-energy simulation setup and analysis (ProFESSA) using the GPU-accelerated AMBER free-energy engine with enhanced sampling features and analysis tools, part of the AMBER Drug Discovery Boost package that has been integrated into the AMBER22 release. The workflow establishes a flexible, end-to-end pipeline for performing alchemical free-energy simulations that brings to bear technologies, including new enhanced sampling features and analysis tools, to practical drug discovery problems. ProFESSA provides the user with top-level control of large sets of free-energy calculations and offers access to the following key functionalities: (1) automated setup of file infrastructure; (2) enhanced conformational and alchemical sampling with the ACES method; and (3) network-wide free-energy analysis with the optional imposition of cycle closure and experimental constraints. The workflow is applied to perform absolute and relative solvation free-energy and relative ligand-protein binding free-energy calculations using different atom-mapping procedures. Results demonstrate that the workflow is internally consistent and highly robust. Further, the application of a new network-wide Lagrange multiplier constraint analysis that imposes key experimental constraints substantially improves binding free-energy predictions.
Collapse
Affiliation(s)
- Abir Ganguly
- 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
| | - Mario Fernández-Pendás
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
- Donostia International Physics Center (DIPC), PK 1072, 20080 Donostia-San Sebastian, Spain
| | - 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
| | - 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
| | - 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
|
29
|
Eistrikh-Heller PA, Rubinsky SV, Samygina VR, Lashkov AA. Calculation of Free Energy of Binding for Widely Specific Pyrimidine-Nucleoside Phosphorylase and Suspected Inhibitors. RUSSIAN JOURNAL OF BIOORGANIC CHEMISTRY 2022. [DOI: 10.1134/s1068162022060103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
|
30
|
Li Z, Chan KC, Nickels JD, Cheng X. Electrostatic Contributions to the Binding Free Energy of Nicotine to the Acetylcholine Binding Protein. J Phys Chem B 2022; 126:8669-8679. [PMID: 36260486 PMCID: PMC10056799 DOI: 10.1021/acs.jpcb.2c04641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Biomolecular binding relies on specific attractive interactions between two partner molecules, including electrostatics, dispersion, hydrophobicity, and solvation. Assessing the contributions of electrostatic interactions to binding is key to the understanding of ligand binding mechanisms and the design of improved biomolecular binders. For example, nicotine is a well-known agonist of nicotinic acetylcholine receptors (nAChRs), but the molecular mechanisms for the differential action of nicotine on brain and muscle nAChRs remain elusive. In this work, we have chosen the acetylcholine binding protein (AChBP) in complex with nicotine as a model system to interrogate the electrostatic contributions to nicotine binding. Our absolute binding free energy simulations confirm that nicotine binds AChBP predominantly in its protonated (charged) form. By comparing energetic contributions from decomposed interactions for either neutral or charged nicotine, our calculations shed light on the nature of the binding of nicotine to the AChBP. The preferred binding of charged nicotine over neutral nicotine originates from its stronger electrostatic interactions with AChBP, a cation-π interaction to a tryptophan residue and a hydrogen bond between nicotine and the backbone carbonyl of the tryptophan, whereas the major force driving the binding process appears to be van der Waals interactions. The various nonelectrostatic terms can also indirectly modulate the electrostatic interactions through fine-tuning the binding pose of the ligand in the binding site, providing an explanation of why the binding specificity of nicotine to the brain versus muscle nAChRs is driven by electrostatic interaction, given that the immediate binding site residues, including the key tryptophan residue, are identical in the two receptors.
Collapse
Affiliation(s)
- Zoe Li
- Division of Medicinal Chemistry and Pharmacognosy, College of Pharmacy at The Ohio State University, Columbus, Ohio43210, United States
| | - Kevin C Chan
- Division of Medicinal Chemistry and Pharmacognosy, College of Pharmacy at The Ohio State University, Columbus, Ohio43210, United States
| | - Jonathan D Nickels
- Department of Chemical and Environmental Engineering, University of Cincinnati, Cincinnati, Ohio45221, United States
| | - Xiaolin Cheng
- Division of Medicinal Chemistry and Pharmacognosy, College of Pharmacy at The Ohio State University, Columbus, Ohio43210, United States
- Translational Data Analytics Institute (TDAI) at The Ohio State University, Columbus, Ohio43210, United States
| |
Collapse
|
31
|
Fu H, Zhou Y, Jing X, Shao X, Cai W. Meta-Analysis Reveals That Absolute Binding Free-Energy Calculations Approach Chemical Accuracy. J Med Chem 2022; 65:12970-12978. [PMID: 36179112 DOI: 10.1021/acs.jmedchem.2c00796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Systematic and quantitative analysis of the reliability of formally exact methods that in silico calculate absolute protein-ligand binding free energies remains lacking. Here, we provide, for the first time, evidence-based information on the reliability of these methods by statistically studying 853 cases from 34 different research groups through meta-analysis. The results show that formally exact methods approach chemical accuracy (error = 1.58 kcal/mol), even if people are challenging difficult tasks such as blind drug screening in recent years. The geometrical-pathway-based methods prove to possess a better convergence ability than the alchemical ones, while the latter have a larger application range. We also reveal the importance of always using the latest force fields to guarantee reliability and discuss the pros and cons of turning to an implicit solvent model in absolute binding free-energy calculations. Moreover, based on the meta-analysis, an evidence-based guideline for in silico binding free-energy calculations is provided.
Collapse
Affiliation(s)
- Haohao Fu
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin300071, China.,Haihe Laboratory of Sustainable Chemical Transformations, Tianjin300192, China
| | - Yan Zhou
- School of Medicine, Nankai University, Tianjin300071, China.,Department of Ultrasound, Tianjin Third Central Hospital, Tianjin300170, China
| | - Xiang Jing
- Department of Ultrasound, Tianjin Third Central Hospital, Tianjin300170, China
| | - Xueguang Shao
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin300071, China.,Haihe Laboratory of Sustainable Chemical Transformations, Tianjin300192, China
| | - Wensheng Cai
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin300071, China.,Haihe Laboratory of Sustainable Chemical Transformations, Tianjin300192, China
| |
Collapse
|
32
|
Buslaev P, Aho N, Jansen A, Bauer P, Hess B, Groenhof G. Best Practices in Constant pH MD Simulations: Accuracy and Sampling. J Chem Theory Comput 2022; 18:6134-6147. [PMID: 36107791 PMCID: PMC9558372 DOI: 10.1021/acs.jctc.2c00517] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
![]()
Various approaches
have been proposed to include the
effect of
pH in molecular dynamics (MD) simulations. Among these, the λ-dynamics approach proposed
by Brooks and
co-workers [Kong, X.; Brooks III, C. L. J. Chem. Phys.1996, 105, 2414−2423] can be performed
with little computational overhead and hfor each typeence be used
to routinely perform MD simulations at microsecond time scales, as
shown in the accompanying paper [Aho, N. et al. J. Chem. Theory
Comput.2022, DOI: 10.1021/acs.jctc.2c00516]. At
such time scales, however, the accuracy of the molecular mechanics
force field and the parametrization becomes critical. Here, we address
these issues and provide the community with guidelines on how to set
up and perform long time scale constant pH MD simulations. We found
that barriers associated with the torsions of side chains in the CHARMM36m
force field are too high for reaching convergence in constant pH MD
simulations on microsecond time scales. To avoid the high computational
cost of extending the sampling, we propose small modifications to
the force field to selectively reduce the torsional barriers. We demonstrate
that with such modifications we obtain converged distributions of
both protonation and torsional degrees of freedom and hence consistent
pKa estimates, while the sampling of the
overall configurational space accessible to proteins is unaffected
as compared to normal MD simulations. We also show that the results
of constant pH MD depend on the accuracy of the correction potentials.
While these potentials are typically obtained by fitting a low-order
polynomial to calculated free energy profiles, we find that higher
order fits are essential to provide accurate and consistent results.
By resolving problems in accuracy and sampling, the work described
in this and the accompanying paper paves the way to the widespread
application of constant pH MD beyond pKa prediction.
Collapse
Affiliation(s)
- Pavel Buslaev
- Nanoscience Center and Department of Chemistry, University of Jyväskylä, 40014 Jyväskylä, Finland
| | - Noora Aho
- Nanoscience Center and Department of Chemistry, University of Jyväskylä, 40014 Jyväskylä, Finland
| | - Anton Jansen
- Department of Applied Physics, Science for Life Laboratory, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden
| | - Paul Bauer
- Department of Applied Physics, Science for Life Laboratory, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden
| | - Berk Hess
- Department of Applied Physics and Swedish e-Science Research Center, Science for Life Laboratory, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden
| | - Gerrit Groenhof
- Nanoscience Center and Department of Chemistry, University of Jyväskylä, 40014 Jyväskylä, Finland
| |
Collapse
|
33
|
Silvestri A, Raiteri P, Gale JD. Obtaining Consistent Free Energies for Ion Binding at Surfaces from Solution: Pathways versus Alchemy for Determining Kink Site Stability. J Chem Theory Comput 2022; 18:5901-5919. [PMID: 36073829 DOI: 10.1021/acs.jctc.2c00787] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Ion incorporation or removal from a solid at the interface with solution is a fundamental part of crystal growth. Despite this, there have been few quantitative determinations of the thermodynamics for such processes from atomistic molecular dynamics due to the associated technical challenges. In this study, we compute the free energies for ion removal from kink sites at the interface between NaCl and water as an illustrative example. To examine the influence of the free energy technique used, we compare methods that follow an explicit pathway for dissolution with those that focus on the thermodynamics of the initial and final states using metadynamics and free energy perturbation, respectively. While the initial results of the two approaches are found to be completely different, it is demonstrated that the thermodynamics can be reconciled with appropriate corrections for the standard states, thus illustrating the need for caution in interpreting raw free energy curves for ion binding as widely found in the literature. In addition, a new efficient approach is introduced to correct for the system size dependence of kink site energies both due to the periodic interaction of charges in an inhomogeneous dielectric system and due to the dipolar interactions between pairs of kinks along a row. Ultimately, it is shown that with suitable care, both classes of free energy techniques are capable of producing kink site stabilities that are consistent with the solubility of the underlying bulk solid. However, the precise values for individual kink sites exhibit a small systematic offset, which can be ascribed to the contribution of the interfacial potential to the pathway-based results. For the case of NaCl, the free energies of the kink sites relative to a 1 M aqueous solution for Na+ and Cl- are found to be surprisingly different and of opposite sign, despite the ions having very similar hydration free energies.
Collapse
Affiliation(s)
- Alessandro Silvestri
- Curtin Institute for Computation, School of Molecular and Life Sciences, Curtin University, P.O. Box U1987, Perth, Western Australia 6845, Australia
| | - Paolo Raiteri
- Curtin Institute for Computation, School of Molecular and Life Sciences, Curtin University, P.O. Box U1987, Perth, Western Australia 6845, Australia
| | - Julian D Gale
- Curtin Institute for Computation, School of Molecular and Life Sciences, Curtin University, P.O. Box U1987, Perth, Western Australia 6845, Australia
| |
Collapse
|
34
|
Alibay I, Magarkar A, Seeliger D, Biggin PC. Evaluating the use of absolute binding free energy in the fragment optimisation process. Commun Chem 2022; 5:105. [PMID: 36697714 PMCID: PMC9814858 DOI: 10.1038/s42004-022-00721-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 08/10/2022] [Indexed: 02/01/2023] Open
Abstract
Key to the fragment optimisation process within drug design is the need to accurately capture the changes in affinity that are associated with a given set of chemical modifications. Due to the weakly binding nature of fragments, this has proven to be a challenging task, despite recent advancements in leveraging experimental and computational methods. In this work, we evaluate the use of Absolute Binding Free Energy (ABFE) calculations in guiding fragment optimisation decisions, retrospectively calculating binding free energies for 59 ligands across 4 fragment elaboration campaigns. We first demonstrate that ABFEs can be used to accurately rank fragment-sized binders with an overall Spearman's r of 0.89 and a Kendall τ of 0.67, although often deviating from experiment in absolute free energy values with an RMSE of 2.75 kcal/mol. We then also show that in several cases, retrospective fragment optimisation decisions can be supported by the ABFE calculations. Comparing against cheaper endpoint methods, namely Nwat-MM/GBSA, we find that ABFEs offer better ranking power and correlation metrics. Our results indicate that ABFE calculations can usefully guide fragment elaborations to maximise affinity.
Collapse
Affiliation(s)
- Irfan Alibay
- Department of Biochemistry, The University of Oxford, South Parks Road, OX1 3QU, Oxford, UK
| | - Aniket Magarkar
- Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Str. 65, 88397, Biberach an de Riß, Germany
| | - Daniel Seeliger
- Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Str. 65, 88397, Biberach an de Riß, Germany
- Exscientia Inc, Office 400E, 2125 Biscayne Blvd, Miami, FL, 33137, USA
| | - Philip Charles Biggin
- Department of Biochemistry, The University of Oxford, South Parks Road, OX1 3QU, Oxford, UK.
| |
Collapse
|
35
|
Souza FR, Moura PG, Costa RKM, Silva RS, Pimentel AS. Absolute binding free energies of mucroporin and its analog mucroporin-M1 with the heptad repeat 1 domain and RNA-dependent RNA polymerase of SARS-CoV-2. J Biomol Struct Dyn 2022:1-12. [PMID: 35993479 DOI: 10.1080/07391102.2022.2114014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The peptide Mucroporin and its analog Mucroporin-M1 were studied using the molecular docking and molecular dynamics simulation of their complexation with two protein targets, the Heptad Repeat 1 (HR1) domain and RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. The molecular docking of the peptide-protein complexes was performed using the glowworm swarm optimization algorithm. The lowest energy poses were submitted to molecular dynamics simulation. Then, the binding free energies of Mucroporin and its analog Mucroporin-M1 with these two protein targets were calculated using the Multistate Bennett Acceptance Ratio (MBAR) method. It was verified that the peptides/HR1 domain complex showed stability in the interaction site determined by molecular docking. It was also found that Mucroporin-M1 has a much higher affinity than Mucroporin to the HR1 protein target. The peptides showed similar stability and affinity at the NTP binding site in the RdRp protein. Additional experimental studies are needed to confirm the antiviral activity of Mucroporin-M1 and a possible mechanism of action against SARS-CoV-2. However, here we indicate that Mucroporin-M1 may have potential antiviral activity against the HR1 domain with the possibility for further peptide optimization.Communicated by Ramaswamy H. Sarma.
Collapse
Affiliation(s)
- Felipe Rodrigues Souza
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Paloma Guimarães Moura
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | | | - Rudielson Santos Silva
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - André Silva Pimentel
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| |
Collapse
|
36
|
Rieder SR, Ries BJ, Kubincová A, Champion C, Barros EP, Hünenberger PH, Riniker S. Leveraging the Sampling Efficiency of RE-EDS in OpenMM Using a Shifted Reaction-Field With an Atom-Based Cutoff. J Chem Phys 2022; 157:104117. [DOI: 10.1063/5.0107935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Replica-exchange enveloping distribution sampling (RE-EDS) is a pathway-independent multistate free-energy method, currently implemented in the GROMOS software package for molecular dynamics (MD) simulations. It has a high intrinsic sampling efficiency as the interactions between the unperturbed particles have to be calculated only once for multiple end-states. As a result, RE-EDS is an attractive method for the calculation of relative solvation and binding free energies. An essential requirement for reaching this high efficiency is the separability of the nonbonded interactions into solute-solute, solute-environment, and environment-environment contributions. Such a partitioning is trivial when using a Coulomb term with a reaction-field (RF) correction to model the electrostatic interactions, but not when using lattice- sum schemes. To avoid cutoff artifacts, the RF correction is typically used in combination with a charge-group based cutoff, which is not supported by most small-molecule force fields and other MD engines. To address this issue, we investigate the combination of RE-EDS simulations with a recently introduced RF scheme including a shifting function that enables the rigorous calculation of RF electrostatics with atom-based cutoffs. The resulting approach is validated by calculating solvation free energies with the generalized AMBER force field (GAFF) in water and chloroform using both the GROMOS software package and a proof-of-concept implementation in OpenMM.
Collapse
Affiliation(s)
| | | | | | | | | | | | - Sereina Riniker
- Laboratory of Physical Chemistry, ETH Zurich D-CHAB, Switzerland
| |
Collapse
|
37
|
Sun Z, Wang M, He Q, Liu Z. Molecular Modeling of Ionic Liquids: Force‐Field Validation and Thermodynamic Perspective from Large‐Scale Fast‐Growth Solvation Free Energy Calculations. ADVANCED THEORY AND SIMULATIONS 2022. [DOI: 10.1002/adts.202200274] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Zhaoxi Sun
- Beijing National Laboratory for Molecular Sciences College of Chemistry and Molecular Engineering Peking University Beijing 100871 China
| | - Mao Wang
- NCS Testing Technology Co., Ltd. No. 13, Gaoliangqiao Xiejie Beijing 100081 China
| | - Qiaole He
- AI Department of Enzymaster (Ningbo) Bio‐Engineering Co., Ltd. North Century Avenue 333 Ningbo 315100 China
| | - Zhirong Liu
- Beijing National Laboratory for Molecular Sciences College of Chemistry and Molecular Engineering Peking University Beijing 100871 China
| |
Collapse
|
38
|
Fan K, Zhang Y, Qiu Y, Zhang H. Impacts of targeting different hydration free energy references on the development of ion potentials. Phys Chem Chem Phys 2022; 24:16244-16262. [PMID: 35758314 DOI: 10.1039/d2cp01237e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Hydration free energy (HFE) as the most important solvation parameter is often targeted in ion model development, even though the reported values differ by dozens of kcal mol-1 mainly due to the experimentally undetermined HFE of the proton ΔG°(H+). The choice of ΔG°(H+) obviously affects the hydration of single ions and the relative HFE between the ions with different (magnitude or sign) charges, and the impacts of targeted HFEs on the ion solvation and ion-ion interactions are largely unrevealed. Here we designed point charge models of K+, Mg2+, Al3+, and Cl- ions targeting a variety of HFE references and then investigated the HFE influences on the simulations of dilute and concentrated ion solutions and of the salt ion pairs in gas, liquid, and solid phases. Targeting one more property of ion-water oxygen distances (IOD) leaves the ion-water binding distance invariant, while the binding strength increases with the decreasing (more negative) HFE of ions as a result of a decrease in ΔG°(H+) for the cation and an increase in ΔG°(H+) for the anion. The increase in ΔG°(H+) leads to strengthened cation-anion interactions and thus to close ion-ion contacts, low osmotic pressures, and small activity derivatives in concentrated ion solutions as well as too stable ion pairs of the salts in different phases. The ion diffusivity and water exchange rates around the ions are simply not HFE dependent but rather more complex. Targeting both the aqueous IOD and salt crystal properties of KCl was also attempted and the comparison between different models indicates the complexity and challenge in obtaining a balanced performance between different phases using classical force fields. Our results also support that a real ΔG°(H+) value of -259.8 kcal mol-1 recommended by Hünenberger and Reif guides ion models to reproduce ion-water and ion-ion interactions reasonably at relatively low salt concentrations. Simulations of a metalloprotein show that a relatively more positive ΔG°(H+) for Mg2+ model is better for a reasonable description of the metal binding network.
Collapse
Affiliation(s)
- Kun Fan
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, 100083 Beijing, China.
| | - Yongguang Zhang
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, 100083 Beijing, China.
| | - Yejie Qiu
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, 100083 Beijing, China.
| | - Haiyang Zhang
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, 100083 Beijing, China.
| |
Collapse
|
39
|
Reif MM, Zacharias M. Improving the Potential of Mean Force and Nonequilibrium Pulling Simulations by Simultaneous Alchemical Modifications. J Chem Theory Comput 2022; 18:3873-3893. [PMID: 35653503 DOI: 10.1021/acs.jctc.1c01194] [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
We present an approach combining alchemical modifications and physical-pathway methods to calculate absolute binding free energies. The employed physical-pathway method is either a stratified umbrella sampling to calculate a potential of mean force or nonequilibrium pulling. We devised two basic approaches: the simultaneous approach (S-approach), where, along the physical unbinding pathway, an alchemical transformation of ligand-protein interactions is installed and deinstalled, and the prior-plus-simultaneous approach (PPS-approach), where, prior to the physical-pathway simulation, an alchemical transformation of ligand-protein interactions is installed in the binding site and deinstalled during the physical-pathway simulation. Using a mutant of T4 lysozyme with a benzene ligand as an example, we show that installation and deinstallation of soft-core interactions concurrent with physical ligand unbinding (S-approach) allow successful potential of mean force calculations and nonequilibrium pulling simulations despite the problems posed by the occluded nature of the lysozyme binding pocket. Good agreement between the potential of the mean-force-based S-approach and double decoupling simulations as well as a remarkable efficiency and accuracy of the nonequilibrium-pulling-based S-approach is found. The latter turned out to be more compute-efficient than the potential of mean force calculation by approximately 70%. Furthermore, we illustrate the merits of reducing ligand-protein interactions prior to potential of mean force calculations using the murine double minute homologue protein MDM2 with a p53-derived peptide ligand (PPS-approach). Here, the problem of breaking strong interactions in the binding pocket is transferred to a prior alchemical transformation that reduces the free-energy barrier between the bound and unbound state in the potential of mean force. Besides, disentangling physical ligand displacement from the deinstallation of ligand-protein interactions was seen to allow a more uniform sampling of distance histograms in the umbrella sampling. In the future, physical ligand unbinding combined with simultaneous alchemical modifications may prove useful in the calculation of protein-protein binding free energies, where sampling problems posed by multiple, possibly sticky interactions and potential steric clashes can thus be reduced.
Collapse
Affiliation(s)
- Maria M Reif
- Center for Protein Assemblies (CPA), Physics Department, Chair of Theoretical Biophysics (T38), Technical University of Munich, Ernst-Otto-Fischer-Str. 8, Garching 85748, Germany
| | - Martin Zacharias
- Center for Protein Assemblies (CPA), Physics Department, Chair of Theoretical Biophysics (T38), Technical University of Munich, Ernst-Otto-Fischer-Str. 8, Garching 85748, Germany
| |
Collapse
|
40
|
Künzel N, Helms V. How Peptides Bind to PSD-95/Discs-Large/ZO-1 Domains. J Chem Theory Comput 2022; 18:3845-3859. [PMID: 35608157 DOI: 10.1021/acs.jctc.1c01140] [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
PSD-95/discs-large/ZO-1 (PDZ) domains form a large family of adaptor proteins that bind to the C-terminal tails of their binding partner proteins. Via extensive molecular dynamics simulations and alchemical free energy calculations, we characterized the binding modi of phosphorylated and unphosphorylated EQVSAV peptides and of a EQVEAV phosphate mimic to the hPTP1E PDZ2 and MAGI1 PDZ1 domains. The simulations reproduced the well-known binding characteristics such as tight coordination of the peptidic carboxyl tail and pronounced hydrogen bonding between the peptide backbone and the backbone atoms of a β-sheet in PDZ. Overall, coordination by hPTP1E PDZ2 appeared tighter than by MAGI1 PDZ1. Simulations of wild-type PDZ and arginine mutants suggest that contacts with Arg79/85 in hPTP1E/MAGI1 are more important for the EQVEAV peptide than for EQVSAV. Alchemical free energy calculations and PaCS-MD simulations could well reproduce the difference in binding free energy between unphosphorylated EQVSAV and EQVEAV peptides and the absolute binding free energy of EQVSAV. However, likely due to small force field inaccuracies, the simulations erroneously favored binding of the phosphorylated peptide instead of its unphosphorylated counterpart, which is in contrast to the experiment.
Collapse
Affiliation(s)
- Nicolas Künzel
- Center for Bioinformatics, Saarland University, P.O. Box 15 11 50, D-66041 Saarbrücken, Germany
| | - Volkhard Helms
- Center for Bioinformatics, Saarland University, P.O. Box 15 11 50, D-66041 Saarbrücken, Germany
| |
Collapse
|
41
|
Chen X, Briozzo P, Machover D, Simonson T. A Computational Model for the PLP-Dependent Enzyme Methionine γ-Lyase. Front Mol Biosci 2022; 9:886358. [PMID: 35558556 PMCID: PMC9087591 DOI: 10.3389/fmolb.2022.886358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 04/01/2022] [Indexed: 11/13/2022] Open
Abstract
Pyridoxal-5′-phosphate (PLP) is a cofactor in the reactions of over 160 enzymes, several of which are implicated in diseases. Methionine γ-lyase (MGL) is of interest as a therapeutic protein for cancer treatment. It binds PLP covalently through a Schiff base linkage and digests methionine, whose depletion is damaging for cancer cells but not normal cells. To improve MGL activity, it is important to understand and engineer its PLP binding. We develop a simulation model for MGL, starting with force field parameters for PLP in four main states: two phosphate protonation states and two tautomeric states, keto or enol for the Schiff base moiety. We used the force field to simulate MGL complexes with each form, and showed that those with a fully-deprotonated PLP phosphate, especially keto, led to the best agreement with MGL structures in the PDB. We then confirmed this result through alchemical free energy simulations that compared the keto and enol forms, confirming a moderate keto preference, and the fully-deprotonated and singly-protonated phosphate forms. Extensive simulations were needed to adequately sample conformational space, and care was needed to extrapolate the protonation free energy to the thermodynamic limit of a macroscopic, dilute protein solution. The computed phosphate pKa was 5.7, confirming that the deprotonated, −2 form is predominant. The PLP force field and the simulation methods can be applied to all PLP enzymes and used, as here, to reveal fine details of structure and dynamics in the active site.
Collapse
Affiliation(s)
- Xingyu Chen
- Laboratoire de Biologie Structurale de la Cellule (CNRS UMR7654), Ecole Polytechnique, Palaiseau, France
| | - Pierre Briozzo
- Institut Jean-Pierre Bourgin, INRAE-AgroParisTech, University Paris-Saclay, Paris, France
| | - David Machover
- INSERM U935-UA09, University Paris-Saclay, Hôpital Paul-Brousse, Paris, France
| | - Thomas Simonson
- Laboratoire de Biologie Structurale de la Cellule (CNRS UMR7654), Ecole Polytechnique, Palaiseau, France
- *Correspondence: Thomas Simonson,
| |
Collapse
|
42
|
Zhang L, Wang H, Muniz MC, Panagiotopoulos AZ, Car R, E W. A deep potential model with long-range electrostatic interactions. J Chem Phys 2022; 156:124107. [DOI: 10.1063/5.0083669] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Machine learning models for the potential energy of multi-atomic systems, such as the deep potential (DP) model, make molecular simulations with the accuracy of quantum mechanical density functional theory possible at a cost only moderately higher than that of empirical force fields. However, the majority of these models lack explicit long-range interactions and fail to describe properties that derive from the Coulombic tail of the forces. To overcome this limitation, we extend the DP model by approximating the long-range electrostatic interaction between ions (nuclei + core electrons) and valence electrons with that of distributions of spherical Gaussian charges located at ionic and electronic sites. The latter are rigorously defined in terms of the centers of the maximally localized Wannier distributions, whose dependence on the local atomic environment is modeled accurately by a deep neural network. In the DP long-range (DPLR) model, the electrostatic energy of the Gaussian charge system is added to short-range interactions that are represented as in the standard DP model. The resulting potential energy surface is smooth and possesses analytical forces and virial. Missing effects in the standard DP scheme are recovered, improving on accuracy and predictive power. By including long-range electrostatics, DPLR correctly extrapolates to large systems the potential energy surface learned from quantum mechanical calculations on smaller systems. We illustrate the approach with three examples: the potential energy profile of the water dimer, the free energy of interaction of a water molecule with a liquid water slab, and the phonon dispersion curves of the NaCl crystal.
Collapse
Affiliation(s)
| | - Han Wang
- Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Fenghao East Road 2, Beijing 100094, People’s Republic of China
- HEDPS, CAPT, College of Engineering, Peking University, Beijing 100871, People’s Republic of China
| | - Maria Carolina Muniz
- Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, USA
| | | | - Roberto Car
- Department of Chemistry, Department of Physics, Program in Applied and Computational Mathematics, Princeton Institute for the Science and Technology of Materials, Princeton University, Princeton, New Jersey 08544, USA
| | - Weinan E
- School of Mathematical Sciences, Peking University, Beijing 100871, People’s Republic of China
- AI for Science Institute, Beijing, People’s Republic of China
- Department of Mathematics and Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey 08544, USA
| |
Collapse
|
43
|
Wu Z, Biggin PC. Correction Schemes for Absolute Binding Free Energies Involving Lipid Bilayers. J Chem Theory Comput 2022; 18:2657-2672. [PMID: 35315270 PMCID: PMC9082507 DOI: 10.1021/acs.jctc.1c01251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
![]()
Absolute
binding free-energy (ABFE) calculations are playing an
increasing role in drug design, especially as they can be performed
on a range of disparate compounds and direct comparisons between them
can be made. It is, however, especially important to ensure that they
are as accurate as possible, as unlike relative binding free-energy
(RBFE) calculations, one does not benefit as much from a cancellation
of errors during the calculations. In most modern implementations
of ABFE calculations, a particle mesh Ewald scheme is typically used
to treat the electrostatic contribution to the free energy. A central
requirement of such schemes is that the box preserves neutrality throughout
the calculation. There are many ways to deal with this problem that
have been discussed over the years ranging from a neutralizing plasma
with a post hoc correction term through to a simple co-alchemical
ion within the same box. The post hoc correction approach is the most
widespread. However, the vast majority of these studies have been
applied to a soluble protein in a homogeneous solvent (water or salt
solution). In this work, we explore which of the more common approaches
would be the most suitable for a simulation box with a lipid bilayer
within it. We further develop the idea of the so-called Rocklin correction
for lipid-bilayer systems and show how such a correction could work.
However, we also show that it will be difficult to make this generalizable
in a practical way and thus we conclude that the use of a “co-alchemical
ion” is the most useful approach for simulations involving
lipid membrane systems.
Collapse
Affiliation(s)
- Zhiyi Wu
- Department of Biochemistry, South Parks Road, Oxford OX1 3QU, U.K
| | - Philip C Biggin
- Department of Biochemistry, South Parks Road, Oxford OX1 3QU, U.K
| |
Collapse
|
44
|
Markthaler D, Fleck M, Stankiewicz B, Hansen N. Exploring the Effect of Enhanced Sampling on Protein Stability Prediction. J Chem Theory Comput 2022; 18:2569-2583. [PMID: 35298174 DOI: 10.1021/acs.jctc.1c01012] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Changes in protein stability due to side-chain mutations are evaluated by alchemical free-energy calculations based on classical molecular dynamics (MD) simulations in explicit solvent using the GROMOS force field. Three proteins of different complexity with a total number of 93 single-point mutations are analyzed, and the relative free-energy differences are discussed with respect to configurational sampling and (dis)agreement with experimental data. For the smallest protein studied, a 34-residue WW domain, the starting structure dependence of the alchemical free-energy changes, is discussed in detail. Deviations from previous simulations for the two other proteins are shown to result from insufficient sampling in the earlier studies. Hamiltonian replica exchange in combination with multiple starting structures and sufficient sampling time of more than 100 ns per intermediate alchemical state is required in some cases to reach convergence.
Collapse
Affiliation(s)
- Daniel Markthaler
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
| | - Maximilian Fleck
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
| | - Bartosz Stankiewicz
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
| | - Niels Hansen
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
| |
Collapse
|
45
|
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
|
46
|
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: 23] [Impact Index Per Article: 11.5] [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
|
47
|
Qiu Y, Jiang Y, Zhang Y, Zhang H. Rational Design of Nonbonded Point Charge Models for Monovalent Ions with Lennard-Jones 12-6 Potential. J Phys Chem B 2021; 125:13502-13518. [PMID: 34860517 DOI: 10.1021/acs.jpcb.1c09103] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Ions are of central importance in nature, and a variety of potential models was proposed to model ions in different phases for an in-depth exploration of ion-related systems. Here, we developed point charge models of 14 monovalent ions with the traditional 12-6 Lennard-Jones (LJ) potential for use in conjunction with 11 water models of TIP3P, OPC3, SPC/E, SPC/Eb, TIP3P-FB, a99SB-disp, TIP4P-Ew, OPC, TIP4P/2005, TIP4P-D, and TIP4P-FB. The designed models reproduced the real hydration free energy (HFE) of ions and the ion-oxygen distance (IOD) in the first hydration shell accurately and simultaneously, a performance similar to the previously reported 12-6-4 LJ-type ion models (12-6 LJ plus an attractive C4 term for cations or a repulsive one for anions). This work, along with our previous work on di-, tri-, and tetravalent metal cations (J. Chem. Inf. Model. 2021, 61, 4031-4044; J. Chem. Inf. Model. 2021, 61, 4613-4629), demonstrates the feasibility of the simple 12-6 LJ potential in ion modeling. In order for the 12-6 LJ potential to reproduce both the HFE and IOD, the LJ R parameters need to be close to Shannon's ionic radii for the highly charged cations and to the Stokes's van der Waals (vdW) radii for the monovalent ions. With an additional C4 term, the R parameters of 12-6-4 LJ ion models agree well with the Stokes's vdW radii and have a more physical meaning. It appears that the C4 term can be merged into the 12-6 LJ potential by a rational tuning of R and the LJ well depth. Simulations of the osmotic coefficients of alkali chloride solutions and the properties of gaseous and solid alkali halides indicate the necessity of further optimizing ion-ion interactions via, for instance, targeting more properties or using a more physical (polarizable) model.
Collapse
Affiliation(s)
- Yejie Qiu
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, 100083 Beijing, China
| | - Yang Jiang
- Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Yongguang Zhang
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, 100083 Beijing, China
| | - Haiyang Zhang
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, 100083 Beijing, China
| |
Collapse
|
48
|
Garaev TM, Odnovorov AI, Lashkov AA, Grebennikova TV, Finogenova MP, Sadykova GK, Prilipov AG, Timofeeva TA, Rubinsky SV, Norkina SN, Zhuravleva MM. Studying the Effect of Amino Acid Substitutions in the M2 Ion Channel of the Influenza Virus on the Antiviral Activity of the Aminoadamantane Derivative In Vitro and In Silico. Adv Pharm Bull 2021; 11:700-711. [PMID: 34888217 PMCID: PMC8642805 DOI: 10.34172/apb.2021.079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 07/03/2020] [Accepted: 07/15/2020] [Indexed: 12/29/2022] Open
Abstract
Purpose: The aminoadamantane derivative of L-histidyl-1-adamantayl ethylamine hydrochloride (HCl*H-His-Rim) has showed a high inhibition level against influenza A virus strains in vitro. The aim of this work is to search and establish evidence of the direct effect of the drug on influenza A virus proton channel M2.
Methods: The compound HCl*H-His-Rim was obtained by classical peptide synthesis methods. Influenza A virus mutants of A/PuertoRico/8/34(H1N1) strain were obtained by reverse genetics methods. The mutant samples of the virus were cultured on chicken embryos with a virus titer in the hemagglutination test. ELISA was carried out on Madin-Darby canine kidney (MDCK) monolayer cells when multiplying the virus 10-4-10-6. The binding stability of HCl*H-His-Rim was compared to those of M2 (S31N) and M2 (S31N_A30T) channels by molecular dynamic (MD) modeling. The calculation was performed taking into account the interaction with the model lipid bilayer (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) in the presence of water molecules in accordance with the three-center model.
Results: It was found that HCl*H-His-Rim is a direct action drug against influenza A. The most likely conformation of drug binding to target protein has been shown. It has been found that the A30T mutation reduces the binding energy of the drug, and the results obtained in vitro have confirmed the data calculated in silico.
Conclusion: The mechanism of action of HCl*H-His-Rim is directly related to the suppression of the function of the proton channel M2 of influenza A virus.
Collapse
Affiliation(s)
- Timur Mansurovich Garaev
- Federal State Budgetary Institution «National Research Centre for Epidemiology and Microbiology named after the honorary academician N.F.Gamaleya» of the Ministry of Health of the Russian Federation (N.F.Gamaleya NRCEM), 123098, Moscow, Russian Federation
| | - Artyom Irorevich Odnovorov
- Peoples Friendship University of Russia (RUDN University), Ministry of Education of the Russian Federation, 117198, Moscow, Russian Federation
| | | | - Tatiana Vladimirovna Grebennikova
- Federal State Budgetary Institution «National Research Centre for Epidemiology and Microbiology named after the honorary academician N.F.Gamaleya» of the Ministry of Health of the Russian Federation (N.F.Gamaleya NRCEM), 123098, Moscow, Russian Federation
| | - Marina Pavlovna Finogenova
- Federal State Budgetary Institution «National Research Centre for Epidemiology and Microbiology named after the honorary academician N.F.Gamaleya» of the Ministry of Health of the Russian Federation (N.F.Gamaleya NRCEM), 123098, Moscow, Russian Federation
| | - Galina Kadymovna Sadykova
- Federal State Budgetary Institution «National Research Centre for Epidemiology and Microbiology named after the honorary academician N.F.Gamaleya» of the Ministry of Health of the Russian Federation (N.F.Gamaleya NRCEM), 123098, Moscow, Russian Federation
| | - Alexei Gennadievich Prilipov
- Federal State Budgetary Institution «National Research Centre for Epidemiology and Microbiology named after the honorary academician N.F.Gamaleya» of the Ministry of Health of the Russian Federation (N.F.Gamaleya NRCEM), 123098, Moscow, Russian Federation
| | - Tatiana Anatol'evna Timofeeva
- Federal State Budgetary Institution «National Research Centre for Epidemiology and Microbiology named after the honorary academician N.F.Gamaleya» of the Ministry of Health of the Russian Federation (N.F.Gamaleya NRCEM), 123098, Moscow, Russian Federation
| | | | - Svetlana Nikolaevna Norkina
- Federal State Budgetary Institution «National Research Centre for Epidemiology and Microbiology named after the honorary academician N.F.Gamaleya» of the Ministry of Health of the Russian Federation (N.F.Gamaleya NRCEM), 123098, Moscow, Russian Federation
| | - Marina Mikhailovna Zhuravleva
- Federal State Budgetary Institution «National Research Centre for Epidemiology and Microbiology named after the honorary academician N.F.Gamaleya» of the Ministry of Health of the Russian Federation (N.F.Gamaleya NRCEM), 123098, Moscow, Russian Federation
| |
Collapse
|
49
|
Lashkov AA, Tolmachev IV, Eistrikh-Heller PA, Rubinsky SV. PyFepRestr: Plugin to PyMOL Molecular Graphics System for Calculating the Free Energy of Ligand‒Receptor Binding. CRYSTALLOGR REP+ 2021. [DOI: 10.1134/s1063774521050126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
|
50
|
Wang Y, Murlidaran S, Pearlman DA. Quantum simulations of SARS-CoV-2 main protease M pro enable high-quality scoring of diverse ligands. J Comput Aided Mol Des 2021; 35:963-971. [PMID: 34328586 PMCID: PMC8321885 DOI: 10.1007/s10822-021-00412-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 07/12/2021] [Indexed: 11/05/2022]
Abstract
The COVID-19 pandemic has led to unprecedented efforts to identify drugs that can reduce its associated morbidity/mortality rate. Computational chemistry approaches hold the potential for triaging potential candidates far more quickly than their experimental counterparts. These methods have been widely used to search for small molecules that can inhibit critical proteins involved in the SARS-CoV-2 replication cycle. An important target is the SARS-CoV-2 main protease Mpro, an enzyme that cleaves the viral polyproteins into individual proteins required for viral replication and transcription. Unfortunately, standard computational screening methods face difficulties in ranking diverse ligands to a receptor due to disparate ligand scaffolds and varying charge states. Here, we describe full density functional quantum mechanical (DFT) simulations of Mpro in complex with various ligands to obtain absolute ligand binding energies. Our calculations are enabled by a new cloud-native parallel DFT implementation running on computational resources from Amazon Web Services (AWS). The results we obtain are promising: the approach is quite capable of scoring a very diverse set of existing drug compounds for their affinities to M pro and suggest the DFT approach is potentially more broadly applicable to repurpose screening against this target. In addition, each DFT simulation required only ~ 1 h (wall clock time) per ligand. The fast turnaround time raises the practical possibility of a broad application of large-scale quantum mechanics in the drug discovery pipeline at stages where ligand diversity is essential.
Collapse
Affiliation(s)
- Yuhang Wang
- Quantum Simulation Technologies, Inc, 625 Massachusetts Ave, Floor 2, Cambridge, MA, 02139, USA
| | - Sruthi Murlidaran
- Quantum Simulation Technologies, Inc, 625 Massachusetts Ave, Floor 2, Cambridge, MA, 02139, USA
| | - David A Pearlman
- Quantum Simulation Technologies, Inc, 625 Massachusetts Ave, Floor 2, Cambridge, MA, 02139, USA.
| |
Collapse
|