1
|
Summa CM, Langford DP, Dinshaw SH, Webb J, Rick SW. Calculations of Absolute Free Energies, Enthalpies, and Entropies for Drug Binding. J Chem Theory Comput 2024; 20:2812-2819. [PMID: 38538531 DOI: 10.1021/acs.jctc.4c00057] [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: 04/10/2024]
Abstract
Computer simulation methods can aid in the rational design of drugs aimed at a specific target, typically a protein. The affinity of a drug for its target is given by the free energy of binding. Binding can be further characterized by the enthalpy and entropy changes in the process. Methods exist to determine exact free energies, enthalpies, and entropies that are dependent only on the quality of the potential model and adequate sampling of conformational degrees of freedom. Entropy and enthalpy are roughly an order of magnitude more difficult to calculate than the free energy. This project combines a replica exchange method for enhanced sampling, designed to be efficient for protein-sized systems, with free energy calculations. This approach, replica exchange with dynamical scaling (REDS), uses two conventional simulations at different temperatures so that the entropy can be found from the temperature dependence of the free energy. A third replica is placed between them, with a modified Hamiltonian that allows it to span the temperature range of the conventional replicas. REDS provides temperature-dependent data and aids in sampling. It is applied to the bromodomain-containing protein 4 (BRD4) system. We find that for the force fields used, the free energies are accurate but the entropies and enthalpies are not, with the entropic contribution being too positive. Reproducing the entropy and enthalpy of binding appears to be a more stringent test of the force fields than reproducing the free energy.
Collapse
Affiliation(s)
- Christopher M Summa
- Department of Computer Science, University of New Orleans, New Orleans, Louisiana 70148, United States
| | - Dillon P Langford
- Department of Chemistry, University of New Orleans, New Orleans, Louisiana 70148, United States
| | - Sam H Dinshaw
- Department of Chemistry, University of New Orleans, New Orleans, Louisiana 70148, United States
| | - Jennifer Webb
- Department of Chemistry, University of New Orleans, New Orleans, Louisiana 70148, United States
| | - Steven W Rick
- Department of Chemistry, University of New Orleans, New Orleans, Louisiana 70148, United States
| |
Collapse
|
2
|
Awoonor-Williams E, Abu-Saleh AAAA. Molecular Insights into the Impact of Mutations on the Binding Affinity of Targeted Covalent Inhibitors of BTK. J Phys Chem B 2024; 128:2874-2884. [PMID: 38502552 DOI: 10.1021/acs.jpcb.4c00310] [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: 03/21/2024]
Abstract
Targeted covalent inhibitors (TCIs) have witnessed a significant resurgence in recent years, particularly in the kinase drug discovery field for treating diverse clinical indications. The inhibition of Bruton's tyrosine kinase (BTK) for treating B-cell cancers is a classic example where TCIs such as ibrutinib have had breakthroughs in targeted therapy. However, selectivity remains challenging, and the emergence of resistance mutations is a critical concern for clinical efficacy. Computational methods that can accurately predict the impact of mutations on inhibitor binding affinity could prove helpful in informing targeted approaches─providing insights into drug resistance mechanisms. In addition, such systems could help guide the systematic evaluation and impact of mutations in disease models for optimal experimental design. Here, we have employed in silico physics-based methods to understand the effects of mutations on the binding affinity and conformational dynamics of select TCIs of BTK. The TCIs studied include ibrutinib, acalabrutinib, and zanubrutinib─all of which are FDA-approved drugs for treating multiple forms of leukemia and lymphoma. Our results offer useful molecular insights into the structural determinants, thermodynamics, and conformational energies that impact ligand binding for this biological target of clinical relevance.
Collapse
Affiliation(s)
- Ernest Awoonor-Williams
- Department of Chemistry, Memorial University of Newfoundland, St. John's, NL A1B 3X7, Canada
| | - Abd Al-Aziz A Abu-Saleh
- Department of Chemistry and Biochemistry, University of Windsor, Windsor, ON N9B 3P4, Canada
| |
Collapse
|
3
|
Karrenbrock M, Rizzi V, Procacci P, Gervasio FL. Addressing Suboptimal Poses in Nonequilibrium Alchemical Calculations. J Phys Chem B 2024; 128:1595-1605. [PMID: 38323915 DOI: 10.1021/acs.jpcb.3c06516] [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: 02/08/2024]
Abstract
Alchemical transformations can be used to quantitatively estimate absolute binding free energies at a reasonable computational cost. However, most of the approaches currently in use require knowledge of the correct (crystallographic) pose. In this paper, we present a combined Hamiltonian replica exchange nonequilibrium alchemical method that allows us to reliably calculate absolute binding free energies, even when starting from suboptimal initial binding poses. Performing a preliminary Hamiltonian replica exchange enhances the sampling of slow degrees of freedom of the ligand and the target, allowing the system to populate the correct binding pose when starting from an approximate docking pose. We apply the method on 6 ligands of the first bromodomain of the BRD4 bromodomain-containing protein. For each ligand, we start nonequilibrium alchemical transformations from both the crystallographic pose and the top-scoring docked pose that are often significantly different. We show that the method produces statistically equivalent binding free energies, making it a useful tool for computational drug discovery pipelines.
Collapse
Affiliation(s)
- Maurice Karrenbrock
- School of Pharmaceutical Sciences, University of Geneva, Rue Michel-Servet 1, CH-1206 Geneva, Switzerland
| | - Valerio Rizzi
- School of Pharmaceutical Sciences, University of Geneva, Rue Michel-Servet 1, CH-1206 Geneva, Switzerland
| | - Piero Procacci
- Chemistry Department, University of Florence, Via della Lastruccia 3-13, 50019 Sesto Fiorentino, Italy
| | - Francesco Luigi Gervasio
- School of Pharmaceutical Sciences, University of Geneva, Rue Michel-Servet 1, CH-1206 Geneva, Switzerland
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, CH-1206 Geneva, Switzerland
- Chemistry Department, University College London (UCL), WC1E 6BT London, U.K
- Swiss Bioinformatics Institute, University of Geneva, CH-1206 Geneva, Switzerland
| |
Collapse
|
4
|
Bansal N, Wang Y, Sciabola S. Machine Learning Methods as a Cost-Effective Alternative to Physics-Based Binding Free Energy Calculations. Molecules 2024; 29:830. [PMID: 38398581 PMCID: PMC10893267 DOI: 10.3390/molecules29040830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 01/24/2024] [Accepted: 02/09/2024] [Indexed: 02/25/2024] Open
Abstract
The rank ordering of ligands remains one of the most attractive challenges in drug discovery. While physics-based in silico binding affinity methods dominate the field, they still have problems, which largely revolve around forcefield accuracy and sampling. Recent advances in machine learning have gained traction for protein-ligand binding affinity predictions in early drug discovery programs. In this article, we perform retrospective binding free energy evaluations for 172 compounds from our internal collection spread over four different protein targets and five congeneric ligand series. We compared multiple state-of-the-art free energy methods ranging from physics-based methods with different levels of complexity and conformational sampling to state-of-the-art machine-learning-based methods that were available to us. Overall, we found that physics-based methods behaved particularly well when the ligand perturbations were made in the solvation region, and they did not perform as well when accounting for large conformational changes in protein active sites. On the other end, machine-learning-based methods offer a good cost-effective alternative for binding free energy calculations, but the accuracy of their predictions is highly dependent on the experimental data available for training the model.
Collapse
Affiliation(s)
- Nupur Bansal
- Biotherapeutic and Medicinal Sciences, Biogen, 225 Binney Street, Cambridge, MA 02142, USA; (Y.W.); (S.S.)
| | | | | |
Collapse
|
5
|
Fu H, Chipot C, Shao X, Cai W. Standard Binding Free-Energy Calculations: How Far Are We from Automation? J Phys Chem B 2023; 127:10459-10468. [PMID: 37824848 DOI: 10.1021/acs.jpcb.3c04370] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2023]
Abstract
Recent success stories suggest that in silico protein-ligand binding free-energy calculations are approaching chemical accuracy. However, their widespread application remains limited by the extensive human intervention required, posing challenges for the neophyte. As such, it is critical to develop automated workflows for estimating protein-ligand binding affinities with minimum personal involvement. Key human efforts include setting up and tuning enhanced-sampling or alchemical-transformation algorithms as a preamble to computational binding free-energy estimations. Additionally, preparing input files, bookkeeping, and postprocessing represent nontrivial tasks. In this Perspective, we discuss recent progress in automating standard binding free-energy calculations, featuring the development of adaptive or parameter-free algorithms, standardization of binding free-energy calculation workflows, and the implementation of user-friendly software. We also assess the current state of automated standard binding free-energy calculations and evaluate the limitations of existing methods. Last, we outline the requirements for future algorithms and workflows to facilitate automated free-energy calculations for diverse protein-ligand complexes.
Collapse
Affiliation(s)
- Haohao Fu
- State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Biosensing and Molecular Recognition, Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Christophe Chipot
- Laboratoire International Associé CNRS and University of Illinois at Urbana-Champaign, UMR no. 7019, Université de Lorraine, BP 70239, F-54506 Vandoeuvre-lès-Nancy, France
- Department of Physics, University of Illinois at Urbana-Champaign, 1110 West Green Street, Urbana, Illinois 61801, United States
- Department of Chemistry, The University of Chicago, 5735 South Ellis Avenue, Chicago, Illinois 60637, United States
- Department of Chemistry, The University of Hawai'i at Ma̅noa, 2545 McCarthy Mall, Honolulu, Hawaii 96822, United States
| | - Xueguang Shao
- State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Biosensing and Molecular Recognition, Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Wensheng Cai
- State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Biosensing and Molecular Recognition, Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| |
Collapse
|
6
|
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
|
7
|
Çınaroğlu SS, Biggin PC. The role of loop dynamics in the prediction of ligand-protein binding enthalpy. Chem Sci 2023; 14:6792-6805. [PMID: 37350814 PMCID: PMC10284145 DOI: 10.1039/d2sc06471e] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 05/31/2023] [Indexed: 06/24/2023] Open
Abstract
The enthalpic and entropic components of ligand-protein binding free energy reflect the interactions and dynamics between ligand and protein. Despite decades of study, our understanding and hence our ability to predict these individual components remains poor. In recent years, there has been substantial effort and success in the prediction of relative and absolute binding free energies, but the prediction of the enthalpic (and entropic) contributions in biomolecular systems remains challenging. Indeed, it is not even clear what kind of performance in terms of accuracy could currently be obtained for such systems. It is, however, relatively straight-forward to compute the enthalpy of binding. We thus evaluated the performance of absolute enthalpy of binding calculations using molecular dynamics simulation for ten inhibitors against a member of the bromodomain family, BRD4-1, against isothermal titration calorimetry data. Initial calculations, with the AMBER force-field showed good agreement with experiment (R2 = 0.60) and surprisingly good accuracy with an average of root-mean-square error (RMSE) = 2.49 kcal mol-1. Of the ten predictions, three were obvious outliers that were all over-predicted compared to experiment. Analysis of various simulation factors, including parameterization, buffer concentration and conformational dynamics, revealed that the behaviour of a loop (the ZA loop on the periphery of the binding site) strongly dictates the enthalpic prediction. Consistent with previous observations, the loop exists in two distinct conformational states and by considering one or the other or both states, the prediction for the three outliers can be improved dramatically to the point where the R2 = 0.95 and the accuracy in terms of RMSE improves to 0.90 kcal mol-1. However, performance across force-fields is not consistent: if OPLS and CHARMM are used, different outliers are observed and the correlation with the ZA loop behaviour is not recapitulated, likely reflecting parameterization as a confounding problem. The results provide a benchmark standard for future study and comparison.
Collapse
Affiliation(s)
- Süleyman Selim Çınaroğlu
- Structural Bioinformatics and Computational Biochemistry, Department of Biochemistry, University of Oxford South Parks Road Oxford OX1 3QU UK +44 (0)1865 613238 +44 (0)1865 613305
| | - Philip C Biggin
- Structural Bioinformatics and Computational Biochemistry, Department of Biochemistry, University of Oxford South Parks Road Oxford OX1 3QU UK +44 (0)1865 613238 +44 (0)1865 613305
| |
Collapse
|
8
|
Blazhynska M, Goulard Coderc de Lacam E, Chen H, Chipot C. Improving Speed and Affordability without Compromising Accuracy: Standard Binding Free-Energy Calculations Using an Enhanced Sampling Algorithm, Multiple-Time Stepping, and Hydrogen Mass Repartitioning. J Chem Theory Comput 2023. [PMID: 37196198 DOI: 10.1021/acs.jctc.3c00141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Accurate evaluation of protein-ligand binding free energies in silico is of paramount importance for understanding the mechanisms of biological regulation and providing a theoretical basis for drug design and discovery. Based on a series of atomistic molecular dynamics simulations in an explicit solvent, using well-tempered metadynamics extended adaptive biasing force (WTM-eABF) as an enhanced sampling algorithm, the so-called "geometrical route" offers a rigorous theoretical framework for binding affinity calculations that match experimental values. However, although robust, this strategy remains expensive, requiring substantial computational time to achieve convergence of the simulations. Improving the efficiency of the geometrical route, while preserving its reliability through improved ergodic sampling, is, therefore, highly desirable. In this contribution, having identified the computational bottleneck of the geometrical route, to accelerate the calculations we combine (i) a longer time step for the integration of the equations of motion with hydrogen-mass repartitioning (HMR), and (ii) multiple time-stepping (MTS) for collective-variable and biasing-force evaluation. Altogether, we performed 50 independent WTM-eABF simulations in triplicate for the "physical" separation of the Abl kinase-SH3 domain:p41 complex, following different HMR and MTS schemes, while tuning, in distinct protocols, the parameters of the enhanced-sampling algorithm. To demonstrate the consistency and reliability of the results obtained with the best-performing setups, we carried out quintuple simulations. Furthermore, we demonstrated the transferability of our method to other complexes by triplicating a 200 ns separation simulation of nine chosen protocols for the MDM2-p53:NVP-CGM097 complex. [Holzer et al. J. Med. Chem. 2015, 58, 6348-6358.] Our results, based on an aggregate simulation time of 14.4 μs, allowed an optimal set of parameters to be identified, able to accelerate convergence by a factor of three without any noticeable loss of accuracy.
Collapse
Affiliation(s)
- Marharyta Blazhynska
- Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche n°7019, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy cedex, France
| | - Emma Goulard Coderc de Lacam
- Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche n°7019, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy cedex, France
| | - Haochuan Chen
- Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche n°7019, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy cedex, France
| | - Christophe Chipot
- Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche n°7019, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy cedex, France
- Theoretical and Computational Biophysics Group, Beckman Institute, and Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
- Department of Biochemistry and Molecular Biology, The University of Chicago, 929 E. 57th Street W225, Chicago, Illinois 60637, United States
| |
Collapse
|
9
|
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: 27] [Impact Index Per Article: 27.0] [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
|
10
|
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: 2] [Impact Index Per Article: 2.0] [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
|
11
|
Tsai HC, Lee TS, Ganguly A, Giese TJ, Ebert MCCJC, Labute P, Merz KM, York DM. AMBER Free Energy Tools: A New Framework for the Design of Optimized Alchemical Transformation Pathways. J Chem Theory Comput 2023; 19:10.1021/acs.jctc.2c00725. [PMID: 36622640 PMCID: PMC10329732 DOI: 10.1021/acs.jctc.2c00725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
We develop a framework for the design of optimized alchemical transformation pathways in free energy simulations using nonlinear mixing and a new functional form for so-called "softcore" potentials. We describe the implementation and testing of this framework in the GPU-accelerated AMBER software suite. The new optimized alchemical transformation pathways integrate a number of important features, including (1) the use of smoothstep functions to stabilize behavior near the transformation end points, (2) consistent power scaling of Coulomb and Lennard-Jones (LJ) interactions with unitless control parameters to maintain balance of electrostatic attractions and exchange repulsions, (3) pairwise form based on the LJ contact radius for the effective interaction distance with separation-shifted scaling, and (4) rigorous smoothing of the potential at the nonbonded cutoff boundary. The new softcore potential form is combined with smoothly transforming nonlinear λ weights for mixing specific potential energy terms, along with flexible λ-scheduling features, to enable robust and stable alchemical transformation pathways. The resulting pathways are demonstrated and tested, and shown to be superior to the traditional methods in terms of numerical stability and minimal variance of the free energy estimates for all cases considered. The framework presented here can be used to design new alchemical enhanced sampling methods, and leveraged in robust free energy workflows for large ligand data sets.
Collapse
Affiliation(s)
- Hsu-Chun Tsai
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Tai-Sung Lee
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Abir Ganguly
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Timothy J. Giese
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Maximilian CCJC Ebert
- Congruence Therapeutics, 7171 Rue Frederick Banting #117, Saint-Laurent, Quebec, Canada H4S 1Z9
| | - Paul Labute
- Chemical Computing Group ULC, 910-1010 Sherbrooke West, Montreal, Quebec, Canada H3A 2R7
| | - Kenneth M. Merz
- Department of Chemistry and Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Darrin M. York
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| |
Collapse
|
12
|
Bartocci A, Pereira G, Cecchini M, Dumont E. Capturing the Recognition Dynamics of para-Sulfonato-calix[4]arenes by Cytochrome c: Toward a Quantitative Free Energy Assessment. J Chem Inf Model 2022; 62:6739-6748. [PMID: 36054284 DOI: 10.1021/acs.jcim.2c00483] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Calix[n]arenes' selective recognition of protein surfaces covers a broad range of timely applications, from controlling protein assembly and crystallization to trapping partially disordered proteins. Here, the interaction of para-sulfonated calix-[4]-arenes with cytochrome c is investigated through all-atom, explicit water molecular dynamics simulations which allow characterization of two binding sites in quantitative agreement with experimental evidence. Free energy calculations based on the MM-PBSA and the attach-pull-release (APR) methods highlight key residues implicated in the recognition process and provide binding free energy results in quantitative agreement with isothermal titration calorimetry. Our study emphasizes the role of MD simulations to capture and describe the "walk" of sulfonated calix-[4]-arenes on the cytochrome c surface, with the arginine R13 as a pivotal interacting residue. Our MD investigation allows, through the quasi-harmonic multibasin (QHMB) method, probing an allosteric reinforcement of several per-residue interactions upon calixarene binding, which suggests a more complex mode of action of these supramolecular auxiliaries.
Collapse
Affiliation(s)
- Alessio Bartocci
- Laboratoire de Chimie, Ecole Normale Superieure de Lyon, F-69342 Lyon, France.,Institut de Chimie de Strasbourg, UMR 7177, CNRS, Université de Strasbourg, Strasbourg 67083, France
| | - Gilberto Pereira
- Institut de Chimie de Strasbourg, UMR 7177, CNRS, Université de Strasbourg, Strasbourg 67083, France.,Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS & University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
| | - Marco Cecchini
- Institut de Chimie de Strasbourg, UMR 7177, CNRS, Université de Strasbourg, Strasbourg 67083, France
| | - Elise Dumont
- Laboratoire de Chimie, Ecole Normale Superieure de Lyon, F-69342 Lyon, France.,Institut Universitaire de France, 5 rue Descartes, 75005 Paris, France
| |
Collapse
|
13
|
Norjmaa G, Himo F, Maréchal J, Ujaque G. Catalysis by [Ga 4 L 6 ] 12- Metallocage on the Nazarov Cyclization: The Basicity of Complexed Alcohol is Key. Chemistry 2022; 28:e202201792. [PMID: 35859038 PMCID: PMC9804567 DOI: 10.1002/chem.202201792] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Indexed: 01/05/2023]
Abstract
The Nazarov cyclization is investigated in solution and within K12 [Ga4 L6 ] supramolecular organometallic cage by means of computational methods. The reaction needs acidic condition in solution but works at neutral pH in the presence of the metallocage. The reaction steps for the process are analogous in both media: (a) protonation of the alcohol group, (b) water loss and (c) cyclization. The relative Gibbs energies of all the steps are affected by changing the environment from solvent to the metallocage. The first step in the mechanism, the alcohol protonation, turns out to be the most critical one for the acceleration of the reaction inside the metallocage. In order to calculate the relative stability of protonated alcohol inside the cavity, we propose a computational scheme for the calculation of basicity for species inside cavities and can be of general use. These results are in excellent agreement with the experiments, identifying key steps of catalysis and providing an in-depth understanding of the impact of the metallocage on all the reaction steps.
Collapse
Affiliation(s)
- Gantulga Norjmaa
- Departament de Química and Centro de Innovación en Química Avanzada (ORFEO-CINQA)Universitat Autònoma de Barcelona08193Cerdanyola del VallesBarcelona, CataloniaSpain
| | - Fahmi Himo
- Department of Organic ChemistryArrhenius LaboratoryStockholm University10691StockholmSweden
| | - Jean‐Didier Maréchal
- Departament de Química and Centro de Innovación en Química Avanzada (ORFEO-CINQA)Universitat Autònoma de Barcelona08193Cerdanyola del VallesBarcelona, CataloniaSpain
| | - Gregori Ujaque
- Departament de Química and Centro de Innovación en Química Avanzada (ORFEO-CINQA)Universitat Autònoma de Barcelona08193Cerdanyola del VallesBarcelona, CataloniaSpain
| |
Collapse
|
14
|
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
|
15
|
Staphylococcus aureus Exfoliative Toxin E, Oligomeric State and Flip of P186: Implications for Its Action Mechanism. Int J Mol Sci 2022; 23:ijms23179857. [PMID: 36077258 PMCID: PMC9456352 DOI: 10.3390/ijms23179857] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 08/23/2022] [Accepted: 08/26/2022] [Indexed: 11/17/2022] Open
Abstract
Staphylococcal exfoliative toxins (ETs) are glutamyl endopeptidases that specifically cleave the Glu381-Gly382 bond in the ectodomains of desmoglein 1 (Dsg1) via complex action mechanisms. To date, four ETs have been identified in different Staphylococcus aureus strains and ETE is the most recently characterized. The unusual properties of ETs have been attributed to a unique structural feature, i.e., the 180° flip of the carbonyl oxygen (O) of the nonconserved residue 192/186 (ETA/ETE numbering), not conducive to the oxyanion hole formation. We report the crystal structure of ETE determined at 1.61 Å resolution, in which P186(O) adopts two conformations displaying a 180° rotation. This finding, together with free energy calculations, supports the existence of a dynamic transition between the conformations under the tested conditions. Moreover, enzymatic assays showed no significant differences in the esterolytic efficiency of ETE and ETE/P186G, a mutant predicted to possess a functional oxyanion hole, thus downplaying the influence of the flip on the activity. Finally, we observed the formation of ETE homodimers in solution and the predicted homodimeric structure revealed the participation of a characteristic nonconserved loop in the interface and the partial occlusion of the protein active site, suggesting that monomerization is required for enzymatic activity.
Collapse
|
16
|
Zhu S. Computational characterization of homologous ligands binding to a deep hydrophobic pocket in
Shigella flexneri
pilot protein MxiM. Proteins 2022; 90:2116-2123. [DOI: 10.1002/prot.26402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 07/10/2022] [Accepted: 07/19/2022] [Indexed: 11/07/2022]
Affiliation(s)
- Shun Zhu
- Department of Cellular and Genetic Medicine, School of Basic Medical Sciences Fudan University Shanghai People's Republic of China
| |
Collapse
|
17
|
Blazhynska M, Goulard Coderc de Lacam E, Chen H, Roux B, Chipot C. Hazardous Shortcuts in Standard Binding Free Energy Calculations. J Phys Chem Lett 2022; 13:6250-6258. [PMID: 35771686 DOI: 10.1021/acs.jpclett.2c01490] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Calculating the standard binding free energies of protein-protein and protein-ligand complexes from atomistic molecular dynamics simulations in explicit solvent is a problem of central importance in computational biophysics. A rigorous strategy for carrying out such calculations is the so-called "geometrical route". In this method, two molecular objects are progressively separated from one another in the presence of orientational and conformational restraints serving to control the change in configurational entropy that accompanies the dissociation process, thereby allowing the computations to converge within simulations of affordable length. Although the geometrical route provides a rigorous theoretical framework, a tantalizing computational shortcut consists of simply leaving out such orientational and conformational degrees of freedom during the separation process. Here the accuracy and convergence of the two approaches are critically compared in the case of two protein-ligand complexes (Abl kinase-SH3:p41 and MDM2-p53:NVP-CGM097) and three protein-protein complexes (pig insulin dimer, SARS-CoV-2 spike RBD:ACE2, and CheA kinase-P2:CheY). The results of the simulations that strictly follow the geometrical route match the experimental standard binding free energies within chemical accuracy. In contrast, simulations bereft of geometrical restraints converge more poorly, yielding inconsistent results that are at variance with the experimental measurements. Furthermore, the orientational and positional time correlation functions of the protein in the unrestrained simulations decay over several microseconds, a time scale that is far longer than the typical simulation times of the geometrical route, which explains why those simulations fail to sample the relevant degrees of freedom during the separation process of the complexes.
Collapse
Affiliation(s)
- Marharyta Blazhynska
- Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche 7019, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy Cedex, France
| | - Emma Goulard Coderc de Lacam
- Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche 7019, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy Cedex, France
| | - Haochuan Chen
- Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche 7019, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy Cedex, France
| | - Benoît Roux
- Department of Biochemistry and Molecular Biology, The University of Chicago, 929 East 57th Street, W225, Chicago, Illinois 60637, United States
- Department of Chemistry, The University of Chicago, 5735 South Ellis Avenue, Chicago, Illinois 60637, United States
| | - Christophe Chipot
- Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche 7019, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy Cedex, France
- Department of Biochemistry and Molecular Biology, The University of Chicago, 929 East 57th Street, W225, Chicago, Illinois 60637, United States
- Theoretical and Computational Biophysics Group, Beckman Institute, and Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| |
Collapse
|
18
|
Singh H, Sharma S. Hydration of Linear Alkanes is Governed by the Small Length-Scale Hydrophobic Effect. J Chem Theory Comput 2022; 18:3805-3813. [PMID: 35648114 DOI: 10.1021/acs.jctc.2c00219] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Length-scale dependence of the hydrophobic effect is well understood for apolar spherical solutes: for small solutes (diameter, d ≲ 0.8 nm), the hydration free energy is entropically driven, while for larger solutes (d ≳ 2 nm), it is enthalpically driven. The nature of the hydrophobic effect in the case of anisotropic molecules such as linear alkanes is not understood yet. In this work, we have calculated the hydration free energy of linear alkanes going from methane to octadecane and of a spherical decane droplet of d ≈ 3 nm using molecular simulations. We show that the hydration free energies of alkanes, irrespective of their size, are governed by the small length-scale hydrophobic effect. That is, unlike the case of large spherical solutes, the hydration free energies of linear alkanes are entropically driven.
Collapse
Affiliation(s)
- Himanshu Singh
- Department of Chemical and Biomolecular Engineering, Ohio University, Athens, Ohio 45701, United States
| | - Sumit Sharma
- Department of Chemical and Biomolecular Engineering, Ohio University, Athens, Ohio 45701, United States
| |
Collapse
|
19
|
Hsueh SCC, Nijland M, Peng X, Hilton B, Plotkin SS. First Principles Calculation of Protein-Protein Dimer Affinities of ALS-Associated SOD1 Mutants. Front Mol Biosci 2022; 9:845013. [PMID: 35402516 PMCID: PMC8988244 DOI: 10.3389/fmolb.2022.845013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 02/08/2022] [Indexed: 01/03/2023] Open
Abstract
Cu,Zn superoxide dismutase (SOD1) is a 32 kDa homodimer that converts toxic oxygen radicals in neurons to less harmful species. The dimerization of SOD1 is essential to the stability of the protein. Monomerization increases the likelihood of SOD1 misfolding into conformations associated with aggregation, cellular toxicity, and neuronal death in familial amyotrophic lateral sclerosis (fALS). The ubiquity of disease-associated mutations throughout the primary sequence of SOD1 suggests an important role of physicochemical processes, including monomerization of SOD1, in the pathology of the disease. Herein, we use a first-principles statistical mechanics method to systematically calculate the free energy of dimer binding for SOD1 using molecular dynamics, which involves sequentially computing conformational, orientational, and separation distance contributions to the binding free energy. We consider the effects of two ALS-associated mutations in SOD1 protein on dimer stability, A4V and D101N, as well as the role of metal binding and disulfide bond formation. We find that the penalty for dimer formation arising from the conformational entropy of disordered loops in SOD1 is significantly larger than that for other protein–protein interactions previously considered. In the case of the disulfide-reduced protein, this leads to a bound complex whose formation is energetically disfavored. Somewhat surprisingly, the loop free energy penalty upon dimerization is still significant for the holoprotein, despite the increased structural order induced by the bound metal cations. This resulted in a surprisingly modest increase in dimer binding free energy of only about 1.5 kcal/mol upon metalation of the protein, suggesting that the most significant stabilizing effects of metalation are on folding stability rather than dimer binding stability. The mutant A4V has an unstable dimer due to weakened monomer-monomer interactions, which are manifested in the calculation by a separation free energy surface with a lower barrier. The mutant D101N has a stable dimer partially due to an unusually rigid β-barrel in the free monomer. D101N also exhibits anticooperativity in loop folding upon dimerization. These computational calculations are, to our knowledge, the most quantitatively accurate calculations of dimer binding stability in SOD1 to date.
Collapse
Affiliation(s)
- Shawn C C Hsueh
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Mark Nijland
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,Laboratory of Organic Chemistry, Wageningen University and Research, Wageningen, Netherlands.,Laboratory of Physical Chemistry and Soft Matter, Wageningen University and Research, Wageningen, Netherlands
| | - Xubiao Peng
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,Center for Quantum Technology Research, School of Physics, Beijing Institute of Technology, Beijing, China
| | - Benjamin Hilton
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,Imperial College London, London, United Kingdom
| | - Steven S Plotkin
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,Genome Science and Technology Program, University of British Columbia, Vancouver, BC, Canada
| |
Collapse
|
20
|
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
|
21
|
Huggins DJ. Comparing the Performance of Different AMBER Protein Forcefields, Partial Charge Assignments, and Water Models for Absolute Binding Free Energy Calculations. J Chem Theory Comput 2022; 18:2616-2630. [PMID: 35266690 DOI: 10.1021/acs.jctc.1c01208] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Identifying chemical starting points is a vital first step in small molecule drug discovery and can take significant time and money. For this reason, computational approaches to virtual screening are of great interest as they can lower the cost and shorten timeframes. However, simple approaches such as molecular docking and pharmacophore screening are of limited accuracy and provide a low probability of success. Alchemical binding free energies represent a promising approach for virtual screening as they naturally incorporate the key effects of water molecules, protein flexibility, and binding entropy. However, the calculations are technically very challenging, with performance depending on the specific forcefield used. For this reason, it is important that the community has access to benchmark test sets to assess prediction accuracy. In this paper, we present an approach to alchemical binding free energies using OpenMM. We identify effective simulation parameters using an existing BRD4(1) test set and present two new benchmark sets (cMET and PDE2A) that can be used in the community for validation purposes. Our findings also highlight the effectiveness of some AMBER forcefields, in particular, AMBER ff15ipq.
Collapse
Affiliation(s)
- David J Huggins
- Tri-Institutional Therapeutics Discovery Institute, New York, New York 10021, United States.,Department of Physiology and Biophysics, Weill Cornell Medical College of Cornell University, New York, New York 10065, United States
| |
Collapse
|
22
|
Gundelach L, Fox T, Tautermann CS, Skylaris CK. BRD4: quantum mechanical protein–ligand binding free energies using the full-protein DFT-based QM-PBSA method. Phys Chem Chem Phys 2022; 24:25240-25249. [PMID: 36222107 DOI: 10.1039/d2cp03705j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Fully quantum mechanical approaches to calculating protein–ligand free energies of binding have the potential to reduce empiricism and explicitly account for all physical interactions responsible for protein–ligand binding.
Collapse
Affiliation(s)
- Lennart Gundelach
- University of Southampton, Faculty of Engineering Science and Mathematics, Chemistry, University Road, Southampton, SO17 1BJ, UK
| | - Thomas Fox
- Boehringer Ingelheim Pharma GmbH & Co KG, Medicinal Chemistry, Birkendorfer Str 65, 88397, Biberach, Germany
| | - Christofer S. Tautermann
- Boehringer Ingelheim Pharma GmbH & Co KG, Medicinal Chemistry, Birkendorfer Str 65, 88397, Biberach, Germany
| | - Chris-Kriton Skylaris
- University of Southampton, Faculty of Engineering Science and Mathematics, Chemistry, University Road, Southampton, SO17 1BJ, UK
| |
Collapse
|
23
|
Hernández González JE, Alberca LN, Masforrol González Y, Reyes Acosta O, Talevi A, Salas-Sarduy E. Tetracycline Derivatives Inhibit Plasmodial Cysteine Protease Falcipain-2 through Binding to a Distal Allosteric Site. J Chem Inf Model 2021; 62:159-175. [PMID: 34962803 DOI: 10.1021/acs.jcim.1c01189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Allosteric inhibitors regulate enzyme activity from remote and usually specific pockets. As they promise an avenue for less toxic and safer drugs, the identification and characterization of allosteric inhibitors has gained great academic and biomedical interest in recent years. Research on falcipain-2 (FP-2), the major papain-like cysteine hemoglobinase of Plasmodium falciparum, might benefit from this strategy to overcome the low selectivity against human cathepsins shown by active site-directed inhibitors. Encouraged by our previous finding that methacycline inhibits FP-2 noncompetitively, here we assessed other five tetracycline derivatives against this target and characterized their inhibition mechanism. As previously shown for methacycline, tetracycline derivatives inhibited FP-2 in a noncompetitive fashion, with Ki values ranging from 121 to 190 μM. A possible binding to the S' side of the FP-2 active site, similar to that described by X-ray crystallography (PDB: 6SSZ) for the noncompetitive inhibitor E-chalcone 48 (EC48), was experimentally discarded by kinetic analysis using a large peptidyl substrate spanning the whole active site. By combining lengthy molecular dynamics (MD) simulations that allowed methacycline to diffuse from solution to different FP-2 surface regions and free energy calculations, we predicted the most likely binding mode of the ligand. Of note, the proposed binding pose explains the low differences in Ki values observed for the tested tetracycline derivatives and the calculated binding free energies match the experimental values. Overall, this study has implications for the design of novel allosteric inhibitors against FP-2 and sets the basis for further optimization of the tetracycline scaffold to produce more potent and selective inhibitors.
Collapse
Affiliation(s)
- Jorge Enrique Hernández González
- Departamento de Física, Instituto de Biociências, Letras e Ciências Exatas, Universidade Estadual Paulista Júlio de Mesquita Filho, Rua Cristóvão Colombo, 2265, Jardim Nazareth, São José do Rio Preto, São Paulo CEP 15054-000, Brazil
| | - Lucas N Alberca
- Laboratory of Bioactive Compounds Research and Development (LIDeB), Department of Biological Sciences, Exact Sciences College, Universidad Nacional de La Plata, La Plata B1900ADU, Argentina
| | | | - Osvaldo Reyes Acosta
- Chemistry and Physics Department, Center for Genetic Engineering and Biotechnology, Havana 10600, Cuba
| | - Alan Talevi
- Laboratory of Bioactive Compounds Research and Development (LIDeB), Department of Biological Sciences, Exact Sciences College, Universidad Nacional de La Plata, La Plata B1900ADU, Argentina
| | - Emir Salas-Sarduy
- Instituto de Investigaciones Biotecnológicas "Dr. Rodolfo Ugalde"─Universidad Nacional de San Martín─CONICET, San Martín B1650HMP, Buenos Aires, Argentina
| |
Collapse
|
24
|
Procacci P, Macchiagodena M. On the NS-DSSB unidirectional estimates in the SAMPL6 SAMPLing challenge. J Comput Aided Mol Des 2021; 35:1055-1065. [PMID: 34625885 PMCID: PMC8523005 DOI: 10.1007/s10822-021-00419-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 09/27/2021] [Indexed: 12/03/2022]
Abstract
In the context of the recent SAMPL6 SAMPLing challenge (Rizzi et al. 2020 in J Comput Aided Mol Des 34:601–633) aimed at assessing convergence properties and reproducibility of molecular dynamics binding free energy methodologies, we propose a simple explanation of the severe errors observed in the nonequilibrium switch double-system-single-box (NS-DSSB) approach when using unidirectional estimates. At the same time, we suggest a straightforward and minimal modification of the NS-DSSB protocol for obtaining reliable unidirectional estimates for the process where the ligand is decoupled in the bound state and recoupled in the bulk.
Collapse
Affiliation(s)
- Piero Procacci
- Department of Chemistry, University of Florence, Via Lastruccia n. 3, 50019, Sesto Fiorentino, FI, Italy.
| | - Marina Macchiagodena
- Department of Chemistry, University of Florence, Via Lastruccia n. 3, 50019, Sesto Fiorentino, FI, Italy
| |
Collapse
|
25
|
Valadares VS, Martins LC, Roman EA, Valente AP, Cino EA, Moraes AH. Conformational dynamics of Tetracenomycin aromatase/cyclase regulate polyketide binding and enzyme aggregation propensity. Biochim Biophys Acta Gen Subj 2021; 1865:129949. [PMID: 34139289 DOI: 10.1016/j.bbagen.2021.129949] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 06/01/2021] [Accepted: 06/10/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND The N-terminal domain of Tetracenomycin aromatase/cyclase (TcmN), an enzyme derived from Streptomyces glaucescens, is involved in polyketide cyclization, aromatization, and folding. Polyketides are a diverse class of secondary metabolites produced by certain groups of bacteria, fungi, and plants with various pharmaceutical applications. Examples include antibiotics, such as tetracycline, and anticancer drugs, such as doxorubicin. Because TcmN is a promising enzyme for in vitro production of polyketides, it is important to identify conditions that enhance its thermal resistance and optimize its function. METHODS TcmN unfolding, stability, and dynamics were evaluated by fluorescence spectroscopy, circular dichroism, nuclear magnetic resonance 15N relaxation experiments, and microsecond molecular dynamics (MD) simulations. RESULTS TcmN thermal resistance was enhanced at low protein and high salt concentrations, was pH-dependent, and denaturation was irreversible. Conformational dynamics on the μs-ms timescale were detected for residues in the substrate-binding cavity, and two predominant conformers representing opened and closed cavity states were observed in the MD simulations. CONCLUSION Based on the results, a mechanism was proposed in which the thermodynamics and kinetics of the TcmN conformational equilibrium modulate enzyme function by favoring ligand binding and avoiding aggregation. GENERAL SIGNIFICANCE Understanding the principles underlying TcmN stability and dynamics may help in designing mutants with optimal properties for biotechnological applications.
Collapse
Affiliation(s)
- Veronica S Valadares
- Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Luan C Martins
- Graduate Program in Bioinformatics, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Ernesto A Roman
- Facultad de Farmacia y Bioquimica, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Ana Paula Valente
- National Center of Nuclear Magnetic Resonance, Leopoldo de Meis Institute of Medical Biochemistry, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Elio A Cino
- Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
| | - Adolfo H Moraes
- Departamento de Química, Instituto de Ciências Exatas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil; Department of NMR-based Structural Biology, Max-Planck Institute for Biophysical Chemistry, Göttingen, Germany.
| |
Collapse
|
26
|
Zou J, Li Z, Liu S, Peng C, Fang D, Wan X, Lin Z, Lee TS, Raleigh DP, Yang M, Simmerling C. Scaffold Hopping Transformations Using Auxiliary Restraints for Calculating Accurate Relative Binding Free Energies. J Chem Theory Comput 2021; 17:3710-3726. [PMID: 34029468 PMCID: PMC8215533 DOI: 10.1021/acs.jctc.1c00214] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
In silico screening of drug-target interactions is a key part of the drug discovery process. Changes in the drug scaffold via contraction or expansion of rings, the breaking of rings, and the introduction of cyclic structures from acyclic structures are commonly applied by medicinal chemists to improve binding affinity and enhance favorable properties of candidate compounds. These processes, commonly referred to as scaffold hopping, are challenging to model computationally. Although relative binding free energy (RBFE) calculations have shown success in predicting binding affinity changes caused by perturbing R-groups attached to a common scaffold, applications of RBFE calculations to modeling scaffold hopping are relatively limited. Scaffold hopping inevitably involves breaking and forming bond interactions of quadratic functional forms, which is highly challenging. A novel method for handling ring opening/closure/contraction/expansion and linker contraction/expansion is presented here. To the best of our knowledge, RBFE calculations on linker contraction/expansion have not been previously reported. The method uses auxiliary restraints to hold the atoms at the ends of a bond in place during the breaking and forming of the bonds. The broad applicability of the method was demonstrated by examining perturbations involving small-molecule macrocycles and mutations of proline in proteins. High accuracy was obtained using the method for most of the perturbations studied. The rigor of the method was isolated from the force field by validating the method using relative and absolute hydration free energy calculations compared to standard simulation results. Unlike other methods that rely on λ-dependent functional forms for bond interactions, the method presented here can be employed using modern molecular dynamics software without modification of codes or force field functions.
Collapse
Affiliation(s)
- Junjie Zou
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
- Department of Chemistry, Stony Brook University, Stony Brook, New York 11794-3400, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794-3400, United States
| | - Zhipeng Li
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
| | - Shuai Liu
- XtalPi Inc., 245 Main St, 11th Floor, Cambridge, MA 02142, United States
| | - Chunwang Peng
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
| | - Dong Fang
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
| | - Xiao Wan
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
| | - Zhixiong Lin
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
| | - Tai-Sung Lee
- Laboratory for Biomolecular Simulation Research, Center for Integrative Proteomics Research, Rutgers University, Piscataway, New Jersey, 08854-8076, United States
| | - Daniel P. Raleigh
- Department of Chemistry, Stony Brook University, Stony Brook, New York 11794-3400, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794-3400, United States
| | - Mingjun Yang
- Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China
| | - Carlos Simmerling
- Department of Chemistry, Stony Brook University, Stony Brook, New York 11794-3400, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794-3400, United States
| |
Collapse
|
27
|
Heinzelmann G, Gilson MK. Automation of absolute protein-ligand binding free energy calculations for docking refinement and compound evaluation. Sci Rep 2021; 11:1116. [PMID: 33441879 PMCID: PMC7806944 DOI: 10.1038/s41598-020-80769-1] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 12/24/2020] [Indexed: 02/06/2023] Open
Abstract
Absolute binding free energy calculations with explicit solvent molecular simulations can provide estimates of protein-ligand affinities, and thus reduce the time and costs needed to find new drug candidates. However, these calculations can be complex to implement and perform. Here, we introduce the software BAT.py, a Python tool that invokes the AMBER simulation package to automate the calculation of binding free energies for a protein with a series of ligands. The software supports the attach-pull-release (APR) and double decoupling (DD) binding free energy methods, as well as the simultaneous decoupling-recoupling (SDR) method, a variant of double decoupling that avoids numerical artifacts associated with charged ligands. We report encouraging initial test applications of this software both to re-rank docked poses and to estimate overall binding free energies. We also show that it is practical to carry out these calculations cheaply by using graphical processing units in common machines that can be built for this purpose. The combination of automation and low cost positions this procedure to be applied in a relatively high-throughput mode and thus stands to enable new applications in early-stage drug discovery.
Collapse
Affiliation(s)
- Germano Heinzelmann
- Departamento de Física, Universidade Federal de Santa Catarina, Florianópolis, Santa Catarina, Brazil.
| | - Michael K Gilson
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, USA
| |
Collapse
|
28
|
Fu H, Chen H, Zhang H, Shao X, Cai W. Accurate Estimation of Protein-ligand Binding Free Energies Based on Geometric Restraints. ACTA CHIMICA SINICA 2021. [DOI: 10.6023/a20100489] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
|
29
|
Nguyen TH, Minh DDL. Implicit ligand theory for relative binding free energies: II. An estimator based on control variates. JOURNAL OF PHYSICS COMMUNICATIONS 2020; 4:115010. [PMID: 33817346 PMCID: PMC8018686 DOI: 10.1088/2399-6528/abcbac] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Implicit ligand theory describes the relationship between the noncovalent binding free energy and the binding free energy between a ligand and multiple rigid receptor conformations. We have previously shown that if the receptor conformations are sampled from or reweighed to a holo ensemble, the binding free energy relative to the ligand that defines the ensemble can be calculated. Here, we apply a variance reduction technique known as control variates to derive a new statistical estimator for the relative binding free energy. In applications to a data set of 6 reference ligands and 18 test ligands, statistically significant differences between the estimators are not observed for most systems. However, in cases where such differences are observed, the new estimator is more accurate, precise, and converges more quickly. Performance improvements are most consistent where there is a clear correlation, with a correlation coefficient greater than 0.3, between the control variate and the statistic being averaged.
Collapse
Affiliation(s)
- Trung Hai Nguyen
- Laboratory of Theoretical and Computational Biophysics, Ton Duc Thang University, Ho Chi Minh City, Vietnam, Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - David D L Minh
- Department of Chemistry, Illinois Institute of Technology, Chicago, IL 60616, USA
| |
Collapse
|
30
|
Zsidó BZ, Hetényi C. Molecular Structure, Binding Affinity, and Biological Activity in the Epigenome. Int J Mol Sci 2020; 21:ijms21114134. [PMID: 32531926 PMCID: PMC7311975 DOI: 10.3390/ijms21114134] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 06/07/2020] [Accepted: 06/08/2020] [Indexed: 02/07/2023] Open
Abstract
Development of valid structure–activity relationships (SARs) is a key to the elucidation of pathomechanisms of epigenetic diseases and the development of efficient, new drugs. The present review is based on selected methodologies and applications supplying molecular structure, binding affinity and biological activity data for the development of new SARs. An emphasis is placed on emerging trends and permanent challenges of new discoveries of SARs in the context of proteins as epigenetic drug targets. The review gives a brief overview and classification of the molecular background of epigenetic changes, and surveys both experimental and theoretical approaches in the field. Besides the results of sophisticated, cutting edge techniques such as cryo-electron microscopy, protein crystallography, and isothermal titration calorimetry, examples of frequently used assays and fast screening techniques are also selected. The review features how different experimental methods and theoretical approaches complement each other and result in valid SARs of the epigenome.
Collapse
|
31
|
Mey ASJS, Allen BK, Macdonald HEB, Chodera JD, Hahn DF, Kuhn M, Michel J, Mobley DL, Naden LN, Prasad S, Rizzi A, Scheen J, Shirts MR, Tresadern G, Xu H. Best Practices for Alchemical Free Energy Calculations [Article v1.0]. LIVING JOURNAL OF COMPUTATIONAL MOLECULAR SCIENCE 2020; 2:18378. [PMID: 34458687 PMCID: PMC8388617 DOI: 10.33011/livecoms.2.1.18378] [Citation(s) in RCA: 114] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Alchemical free energy calculations are a useful tool for predicting free energy differences associated with the transfer of molecules from one environment to another. The hallmark of these methods is the use of "bridging" potential energy functions representing alchemical intermediate states that cannot exist as real chemical species. The data collected from these bridging alchemical thermodynamic states allows the efficient computation of transfer free energies (or differences in transfer free energies) with orders of magnitude less simulation time than simulating the transfer process directly. While these methods are highly flexible, care must be taken in avoiding common pitfalls to ensure that computed free energy differences can be robust and reproducible for the chosen force field, and that appropriate corrections are included to permit direct comparison with experimental data. In this paper, we review current best practices for several popular application domains of alchemical free energy calculations performed with equilibrium simulations, in particular relative and absolute small molecule binding free energy calculations to biomolecular targets.
Collapse
Affiliation(s)
- Antonia S. J. S. Mey
- EaStCHEM School of Chemistry, David Brewster Road, Joseph Black Building, The King’s Buildings, Edinburgh, EH9 3FJ, UK
| | | | - Hannah E. Bruce Macdonald
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York NY, USA
| | - John D. Chodera
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York NY, USA
| | - David F. Hahn
- Computational Chemistry, Janssen Research & Development, Turnhoutseweg 30, Beerse B-2340, Belgium
| | - Maximilian Kuhn
- EaStCHEM School of Chemistry, David Brewster Road, Joseph Black Building, The King’s Buildings, Edinburgh, EH9 3FJ, UK
- Cresset, Cambridgeshire, UK
| | - Julien Michel
- EaStCHEM School of Chemistry, David Brewster Road, Joseph Black Building, The King’s Buildings, Edinburgh, EH9 3FJ, UK
| | - David L. Mobley
- Departments of Pharmaceutical Sciences and Chemistry, University of California, Irvine, Irvine, USA
| | - Levi N. Naden
- Molecular Sciences Software Institute, Blacksburg VA, USA
| | | | - Andrea Rizzi
- Silicon Therapeutics, Boston, MA, USA
- Tri-Institutional Training Program in Computational Biology and Medicine, New York, NY, USA
| | - Jenke Scheen
- EaStCHEM School of Chemistry, David Brewster Road, Joseph Black Building, The King’s Buildings, Edinburgh, EH9 3FJ, UK
| | | | - Gary Tresadern
- Computational Chemistry, Janssen Research & Development, Turnhoutseweg 30, Beerse B-2340, Belgium
| | | |
Collapse
|
32
|
Jiménez-Luna J, Pérez-Benito L, Martínez-Rosell G, Sciabola S, Torella R, Tresadern G, De Fabritiis G. DeltaDelta neural networks for lead optimization of small molecule potency. Chem Sci 2019; 10:10911-10918. [PMID: 32190246 PMCID: PMC7066671 DOI: 10.1039/c9sc04606b] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Accepted: 10/15/2019] [Indexed: 12/29/2022] Open
Abstract
The capability to rank different potential drug molecules against a protein target for potency has always been a fundamental challenge in computational chemistry due to its importance in drug design. While several simulation-based methodologies exist, they are hard to use prospectively and thus predicting potency in lead optimization campaigns remains an open challenge. Here we present the first machine learning approach specifically tailored for ranking congeneric series based on deep 3D-convolutional neural networks. Furthermore we prove its effectiveness by blindly testing it on datasets provided by Janssen, Pfizer and Biogen totalling over 3246 ligands and 13 targets as well as several well-known openly available sets, representing one the largest evaluations ever performed. We also performed online learning simulations of lead optimization using the approach in a predictive manner obtaining significant advantage over experimental choice. We believe that the evaluation performed in this study is strong evidence of the usefulness of a modern deep learning model in lead optimization pipelines against more expensive simulation-based alternatives.
Collapse
Affiliation(s)
- José Jiménez-Luna
- Computational Science Laboratory , Parc de Recerca Biomèdica de Barcelona , Universitat Pompeu Fabra , C Dr Aiguader 88 , Barcelona , 08003 , Spain .
| | - Laura Pérez-Benito
- Laboratori de Medicina Computacional , Unitat de Bioestadística , Facultat de Medicina , Universitat Autònoma de Barcelona , Spain
- Janssen Research and Development , Turnhoutseweg 30 , 2340 Beerse , Belgium
| | | | - Simone Sciabola
- Biogen Chemistry and Molecular Therapeutics , 115 Broadway Street , Cambridge , MA 02142 , USA
| | - Rubben Torella
- Pfizer I&I , 610 Main Street , Cambridge , MA 02139 , USA
| | - Gary Tresadern
- Janssen Research and Development , Turnhoutseweg 30 , 2340 Beerse , Belgium
| | - Gianni De Fabritiis
- Computational Science Laboratory , Parc de Recerca Biomèdica de Barcelona , Universitat Pompeu Fabra , C Dr Aiguader 88 , Barcelona , 08003 , Spain .
- Acellera , Carrer del Dr Trueta, 183 , 08005 Barcelona , Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA) , Passeig Lluis Companys 23 , 08010 Barcelona , Spain
| |
Collapse
|
33
|
Slochower DR, Henriksen NM, Wang LP, Chodera JD, Mobley DL, Gilson MK. Binding Thermodynamics of Host-Guest Systems with SMIRNOFF99Frosst 1.0.5 from the Open Force Field Initiative. J Chem Theory Comput 2019; 15:6225-6242. [PMID: 31603667 PMCID: PMC7328435 DOI: 10.1021/acs.jctc.9b00748] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Designing ligands that bind their target biomolecules with high affinity and specificity is a key step in small-molecule drug discovery, but accurately predicting protein-ligand binding free energies remains challenging. Key sources of errors in the calculations include inadequate sampling of conformational space, ambiguous protonation states, and errors in force fields. Noncovalent complexes between a host molecule with a binding cavity and a druglike guest molecule have emerged as powerful model systems. As model systems, host-guest complexes reduce many of the errors in more complex protein-ligand binding systems, as their small size greatly facilitates conformational sampling, and one can choose systems that avoid ambiguities in protonation states. These features, combined with their ease of experimental characterization, make host-guest systems ideal model systems to test and ultimately optimize force fields in the context of binding thermodynamics calculations. The Open Force Field Initiative aims to create a modern, open software infrastructure for automatically generating and assessing force fields using data sets. The first force field to arise out of this effort, named SMIRNOFF99Frosst, has approximately one tenth the number of parameters, in version 1.0.5, compared to typical general small molecule force fields, such as GAFF. Here, we evaluate the accuracy of this initial force field, using free energy calculations of 43 α and β-cyclodextrin host-guest pairs for which experimental thermodynamic data are available, and compare with matched calculations using two versions of GAFF. For all three force fields, we used TIP3P water and AM1-BCC charges. The calculations are performed using the attach-pull-release (APR) method as implemented in the open source package, pAPRika. For binding free energies, the root-mean-square error of the SMIRNOFF99Frosst calculations relative to experiment is 0.9 [0.7, 1.1] kcal/mol, while the corresponding results for GAFF 1.7 and GAFF 2.1 are 0.9 [0.7, 1.1] kcal/mol and 1.7 [1.5, 1.9] kcal/mol, respectively, with 95% confidence ranges in brackets. These results suggest that SMIRNOFF99Frosst performs competitively with existing small molecule force fields and is a parsimonious starting point for optimization.
Collapse
Affiliation(s)
- David R Slochower
- Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California, San Diego , La Jolla , California 92093 , United States
| | - Niel M Henriksen
- Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California, San Diego , La Jolla , California 92093 , United States
| | - Lee-Ping Wang
- Department of Chemistry , University of California , Davis , California 95616 , United States
| | - John D Chodera
- Computational and Systems Biology Program, Sloan Kettering Institute , Memorial Sloan Kettering Cancer Center , New York , New York 10065 , United States
| | - David L Mobley
- Department of Pharmaceutical Sciences and Department of Chemistry , University of California , Irvine , California 92697 , United States
| | - Michael K Gilson
- Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California, San Diego , La Jolla , California 92093 , United States
| |
Collapse
|
34
|
Leonhard AC, Whitmer JK. Accurate Determination of Cavitand Binding Free Energies via Unrestrained Advanced Sampling. J Chem Theory Comput 2019; 15:5761-5768. [DOI: 10.1021/acs.jctc.9b00348] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Anne C. Leonhard
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Jonathan K. Whitmer
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| |
Collapse
|
35
|
Darby JF, Hopkins AP, Shimizu S, Roberts SM, Brannigan JA, Turkenburg JP, Thomas GH, Hubbard RE, Fischer M. Water Networks Can Determine the Affinity of Ligand Binding to Proteins. J Am Chem Soc 2019; 141:15818-15826. [DOI: 10.1021/jacs.9b06275] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
| | - Adam P. Hopkins
- Demuris Ltd., The Biosphere, Draymans Way, Newcastle Helix, Newcastle upon Tyne NE4 5BX, United Kingdom
| | | | | | | | | | | | - Roderick E. Hubbard
- Vernalis (R&D) Ltd., Granta Park, Abington, Cambridge CB21 6GB, United Kingdom
| | - Marcus Fischer
- Department of Chemical Biology & Therapeutics, and Department of Structural Biology, St. Jude Children’s Research Hospital, Memphis, Tennessee 38105, United States
| |
Collapse
|
36
|
Hernández González JE, Hernández Alvarez L, Pascutti PG, Leite VBP. Prediction of Noncompetitive Inhibitor Binding Mode Reveals Promising Site for Allosteric Modulation of Falcipain-2. J Phys Chem B 2019; 123:7327-7342. [DOI: 10.1021/acs.jpcb.9b05021] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Jorge Enrique Hernández González
- Departamento de Física, Instituto de Biociências, Letras e Ciências Exatas, Universidade Estadual Paulista Júlio de Mesquita Filho, Rua Cristóvão Colombo,
2265, Jardim Nazareth, São José do Rio Preto, São Paulo, CEP 15054-000, Brazil
| | - Lilian Hernández Alvarez
- Departamento de Física, Instituto de Biociências, Letras e Ciências Exatas, Universidade Estadual Paulista Júlio de Mesquita Filho, Rua Cristóvão Colombo,
2265, Jardim Nazareth, São José do Rio Preto, São Paulo, CEP 15054-000, Brazil
| | - Pedro Geraldo Pascutti
- Laboratório de Dinâmica e Modelagem Molecular, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Ave. Carlos
Chagas Filho, 373, CCS-Bloco D sala 30, Cidade Universitária
Ilha de Fundão, Rio de Janeiro, CEP 21941-902, Brazil
| | - Vitor B. P. Leite
- Departamento de Física, Instituto de Biociências, Letras e Ciências Exatas, Universidade Estadual Paulista Júlio de Mesquita Filho, Rua Cristóvão Colombo,
2265, Jardim Nazareth, São José do Rio Preto, São Paulo, CEP 15054-000, Brazil
- Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005, United States
| |
Collapse
|
37
|
Feng M, Gilson MK. A Thermodynamic Limit on the Role of Self-Propulsion in Enhanced Enzyme Diffusion. Biophys J 2019; 116:1898-1906. [PMID: 31053258 PMCID: PMC6531786 DOI: 10.1016/j.bpj.2019.04.005] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Revised: 03/06/2019] [Accepted: 04/02/2019] [Indexed: 01/01/2023] Open
Abstract
A number of enzymes reportedly exhibit enhanced diffusion in the presence of their substrates, with a Michaelis-Menten-like concentration dependence. Although no definite explanation of this phenomenon has emerged, a physical picture of enzyme self-propulsion using energy from the catalyzed reaction has been widely considered. Here, we present a kinematic and thermodynamic analysis of enzyme self-propulsion that is independent of any specific propulsion mechanism. Using this theory, along with biophysical data compiled for all enzymes so far shown to undergo enhanced diffusion, we show that the propulsion speed required to generate experimental levels of enhanced diffusion exceeds the speeds of well-known active biomolecules, such as myosin, by several orders of magnitude. Furthermore, the minimal power dissipation required to account for enzyme enhanced diffusion by self-propulsion markedly exceeds the chemical power available from enzyme-catalyzed reactions. Alternative explanations for the observation of enhanced enzyme diffusion therefore merit stronger consideration.
Collapse
Affiliation(s)
- Mudong Feng
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California
| | - Michael K Gilson
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California.
| |
Collapse
|
38
|
From bench to bedside, via desktop. Recent advances in the application of cutting-edge in silico tools in the research of drugs targeting bromodomain modules. Biochem Pharmacol 2018; 159:40-51. [PMID: 30414936 DOI: 10.1016/j.bcp.2018.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2018] [Accepted: 11/07/2018] [Indexed: 11/22/2022]
Abstract
The discipline of drug discovery has greatly benefited by computational tools and in silico algorithms aiming at rationalization of many related processes, from the stage of early hit identification to the preclinical phases of drug candidate validation. The various methodologies referred to as molecular modeling tools span a broad spectrum of applications, from straightforward approaches such as virtual screening of compound libraries to more advanced techniques involving the precise estimation of free energy upon binding of the candidate drug to its macromolecular target. To this end, we report an overview of specific studies where implementation of such sophisticated modeling algorithms has shown to be indispensable for addressing challenging systems and biological questions otherwise difficult to answer. We focus our attention on the emerging field of bromodomain inhibitors. Bromodomains are small modules involved in epigenetic signaling and currently comprise high-priority targets for developing both drug candidates and chemical probes for basic biomedical research. We attempt a critical presentation of selected cases utilizing cutting-edge in silico methodologies, with our main emphasis being on absolute or relative free energy simulations, on implementation of quantum-mechanics level calculations and on characterization of solvent thermodynamics. We discuss the advantages and strengths as well as the drawbacks and weaknesses of computational tools utilized in those works and we attempt to comment on specific issues related to their integration into the regular medicinal chemistry practice. Our conclusion is that while such methods indeed represent highly promising resources for further advancing the discipline, their application is not always trivial.
Collapse
|
39
|
Han K, Hudson PS, Jones MR, Nishikawa N, Tofoleanu F, Brooks BR. Prediction of CB[8] host-guest binding free energies in SAMPL6 using the double-decoupling method. J Comput Aided Mol Des 2018; 32:1059-1073. [PMID: 30084077 DOI: 10.1007/s10822-018-0144-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 08/01/2018] [Indexed: 10/28/2022]
Abstract
This study reports the results of binding free energy calculations for CB[8] host-guest systems in the SAMPL6 blind challenge (receipt ID 3z83m). Force-field parameters were developed specific for each of host and guest molecules to improve configurational sampling. We used quantum mechanical (QM) implicit solvent calculations and QM force matching to determine non-bonded (partial atomic charges) and bonded terms, respectively. Free energy calculations were carried out using the double-decoupling method (DDM) combined with Hamiltonian replica exchange method (HREM) and Bennett acceptance ratio (BAR) method. The root mean square error (RMSE) of the predicted values using DDM with respect to the experimental results was 4.32 kcal/mol. The coefficient of determination (R2) and Kendall rank coefficient (τ) were 0.49 and 0.52, respectively, highest of all submissions. In addition, these were compared to the results obtained by umbrella sampling (US) and weighted histogram analysis method (WHAM). Overall, DDM achieved a higher prediction accuracy than the US method. Results are discussed in terms of parameterization and free energy simulations.
Collapse
Affiliation(s)
- Kyungreem Han
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Phillip S Hudson
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Michael R Jones
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Naohiro Nishikawa
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Florentina Tofoleanu
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Bernard R Brooks
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| |
Collapse
|
40
|
Deng N, Cui D, Zhang BW, Xia J, Cruz J, Levy R. Comparing alchemical and physical pathway methods for computing the absolute binding free energy of charged ligands. Phys Chem Chem Phys 2018; 20:17081-17092. [PMID: 29896599 DOI: 10.1039/c8cp01524d] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Accurately predicting absolute binding free energies of protein-ligand complexes is important as a fundamental problem in both computational biophysics and pharmaceutical discovery. Calculating binding free energies for charged ligands is generally considered to be challenging because of the strong electrostatic interactions between the ligand and its environment in aqueous solution. In this work, we compare the performance of the potential of mean force (PMF) method and the double decoupling method (DDM) for computing absolute binding free energies for charged ligands. We first clarify an unresolved issue concerning the explicit use of the binding site volume to define the complexed state in DDM together with the use of harmonic restraints. We also provide an alternative derivation for the formula for absolute binding free energy using the PMF approach. We use these formulas to compute the binding free energy of charged ligands at an allosteric site of HIV-1 integrase, which has emerged in recent years as a promising target for developing antiviral therapy. As compared with the experimental results, the absolute binding free energies obtained by using the PMF approach show unsigned errors of 1.5-3.4 kcal mol-1, which are somewhat better than the results from DDM (unsigned errors of 1.6-4.3 kcal mol-1) using the same amount of CPU time. According to the DDM decomposition of the binding free energy, the ligand binding appears to be dominated by nonpolar interactions despite the presence of very large and favorable intermolecular ligand-receptor electrostatic interactions, which are almost completely cancelled out by the equally large free energy cost of desolvation of the charged moiety of the ligands in solution. We discuss the relative strengths of computing absolute binding free energies using the alchemical and physical pathway methods.
Collapse
Affiliation(s)
- Nanjie Deng
- Department of Chemistry and Physical Sciences, Pace University, New York, NY 10038, USA.
| | | | | | | | | | | |
Collapse
|
41
|
Yin J, Henriksen NM, Muddana HS, Gilson MK. Bind3P: Optimization of a Water Model Based on Host-Guest Binding Data. J Chem Theory Comput 2018; 14:3621-3632. [PMID: 29874074 DOI: 10.1021/acs.jctc.8b00318] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We report a water model, Bind3P (Version 0.1), which was obtained by using sensitivity analysis to readjust the Lennard-Jones parameters of the TIP3P model against experimental binding free energies for six host-guest systems, along with pure liquid properties. Tests of Bind3P against >100 experimental binding free energies and enthalpies for host-guest systems distinct from the training set show a consistent drop in the mean signed error, relative to matched calculations with TIP3P. Importantly, Bind3P also yields some improvement in the hydration free energies of small organic molecules and preserves the accuracy of bulk water properties, such as density and the heat of vaporization. The same approach can be applied to more sophisticated water models that can better represent pure water properties. These results lend further support to the concept of integrating host-guest binding data into force field parametrization.
Collapse
Affiliation(s)
- Jian Yin
- Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California San Diego , La Jolla , California 92093 , United States
| | - Niel M Henriksen
- Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California San Diego , La Jolla , California 92093 , United States
| | - Hari S Muddana
- OpenEye Scientific Software , 9 Bisbee Court , Santa Fe , New Mexico 87508 , United States
| | - Michael K Gilson
- Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California San Diego , La Jolla , California 92093 , United States
| |
Collapse
|
42
|
Gill SC, Lim NM, Grinaway PB, Rustenburg AS, Fass J, Ross GA, Chodera JD, Mobley DL. Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes via Nonequilibrium Candidate Monte Carlo. J Phys Chem B 2018; 122:5579-5598. [PMID: 29486559 PMCID: PMC5980761 DOI: 10.1021/acs.jpcb.7b11820] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Accurately predicting protein-ligand binding affinities and binding modes is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation time scales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes. In this technique, the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over 2 orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step toward applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding modes of ligands using enhanced sampling (BLUES) package which is freely available on GitHub.
Collapse
Affiliation(s)
- Samuel C. Gill
- Department of Chemistry, University of California, Irvine
| | - Nathan M. Lim
- Department of Pharmaceutical Sciences, University of California, Irvine
| | - Patrick B. Grinaway
- Graduate Program in Physiology, Biophysics, and Systems Biology, Weill Cornell Medical College, New York, NY 10065
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065
| | - Ariën S. Rustenburg
- Graduate Program in Physiology, Biophysics, and Systems Biology, Weill Cornell Medical College, New York, NY 10065
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065
| | - Josh Fass
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065
- Tri-Institutional PhD Program in Computational Biology and Medicine, New York, NY 10065
| | - Gregory A. Ross
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065
| | | | - David L. Mobley
- Department of Chemistry, University of California, Irvine
- Department of Pharmaceutical Sciences, University of California, Irvine
| |
Collapse
|
43
|
Nguyen TH, Minh DDL. Implicit ligand theory for relative binding free energies. J Chem Phys 2018; 148:104114. [PMID: 29544299 DOI: 10.1063/1.5017136] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Implicit ligand theory enables noncovalent binding free energies to be calculated based on an exponential average of the binding potential of mean force (BPMF)-the binding free energy between a flexible ligand and rigid receptor-over a precomputed ensemble of receptor configurations. In the original formalism, receptor configurations were drawn from or reweighted to the apo ensemble. Here we show that BPMFs averaged over a holo ensemble yield binding free energies relative to the reference ligand that specifies the ensemble. When using receptor snapshots from an alchemical simulation with a single ligand, the new statistical estimator outperforms the original.
Collapse
Affiliation(s)
- Trung Hai Nguyen
- Department of Chemistry, Illinois Institute of Technology, Chicago, Illinois 60616, USA
| | - David D L Minh
- Department of Chemistry, Illinois Institute of Technology, Chicago, Illinois 60616, USA
| |
Collapse
|
44
|
Nguyen TH, Zhou HX, Minh DDL. Using the fast fourier transform in binding free energy calculations. J Comput Chem 2017; 39:621-636. [PMID: 29270990 DOI: 10.1002/jcc.25139] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Revised: 09/23/2017] [Accepted: 11/27/2017] [Indexed: 12/21/2022]
Abstract
According to implicit ligand theory, the standard binding free energy is an exponential average of the binding potential of mean force (BPMF), an exponential average of the interaction energy between the unbound ligand ensemble and a rigid receptor. Here, we use the fast Fourier transform (FFT) to efficiently evaluate BPMFs by calculating interaction energies when rigid ligand configurations from the unbound ensemble are discretely translated across rigid receptor conformations. Results for standard binding free energies between T4 lysozyme and 141 small organic molecules are in good agreement with previous alchemical calculations based on (1) a flexible complex ( R≈0.9 for 24 systems) and (2) flexible ligand with multiple rigid receptor configurations ( R≈0.8 for 141 systems). While the FFT is routinely used for molecular docking, to our knowledge this is the first time that the algorithm has been used for rigorous binding free energy calculations. © 2017 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Trung Hai Nguyen
- Department of Chemistry, Illinois Institute of Technology, Chicago, Illinois, 60616
| | - Huan-Xiang Zhou
- Departments of Chemistry and Physics, University of Illinois at Chicago, Chicago, Illinois, 60607
| | - David D L Minh
- Department of Chemistry, Illinois Institute of Technology, Chicago, Illinois, 60616
| |
Collapse
|
45
|
Modern drug design: the implication of using artificial neuronal networks and multiple molecular dynamic simulations. J Comput Aided Mol Des 2017; 32:299-311. [PMID: 29134430 PMCID: PMC5767208 DOI: 10.1007/s10822-017-0085-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Accepted: 11/08/2017] [Indexed: 01/31/2023]
Abstract
We report the implementation of molecular modeling approaches developed as a part of the 2016 Grand Challenge 2, the blinded competition of computer aided drug design technologies held by the D3R Drug Design Data Resource ( https://drugdesigndata.org/ ). The challenge was focused on the ligands of the farnesoid X receptor (FXR), a highly flexible nuclear receptor of the cholesterol derivative chenodeoxycholic acid. FXR is considered an important therapeutic target for metabolic, inflammatory, bowel and obesity related diseases (Expert Opin Drug Metab Toxicol 4:523-532, 2015), but in the context of this competition it is also interesting due to the significant ligand-induced conformational changes displayed by the protein. To deal with these conformational changes we employed multiple simulations of molecular dynamics (MD). Our MD-based protocols were top-ranked in estimating the free energy of binding of the ligands and FXR protein. Our approach was ranked second in the prediction of the binding poses where we also combined MD with molecular docking and artificial neural networks. Our approach showed mediocre results for high-throughput scoring of interactions.
Collapse
|
46
|
Aldeghi M, Bodkin MJ, Knapp S, Biggin PC. Statistical Analysis on the Performance of Molecular Mechanics Poisson-Boltzmann Surface Area versus Absolute Binding Free Energy Calculations: Bromodomains as a Case Study. J Chem Inf Model 2017; 57:2203-2221. [PMID: 28786670 PMCID: PMC5615372 DOI: 10.1021/acs.jcim.7b00347] [Citation(s) in RCA: 90] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Binding free energy calculations that make use of alchemical pathways are becoming increasingly feasible thanks to advances in hardware and algorithms. Although relative binding free energy (RBFE) calculations are starting to find widespread use, absolute binding free energy (ABFE) calculations are still being explored mainly in academic settings due to the high computational requirements and still uncertain predictive value. However, in some drug design scenarios, RBFE calculations are not applicable and ABFE calculations could provide an alternative. Computationally cheaper end-point calculations in implicit solvent, such as molecular mechanics Poisson-Boltzmann surface area (MMPBSA) calculations, could too be used if one is primarily interested in a relative ranking of affinities. Here, we compare MMPBSA calculations to previously performed absolute alchemical free energy calculations in their ability to correlate with experimental binding free energies for three sets of bromodomain-inhibitor pairs. Different MMPBSA approaches have been considered, including a standard single-trajectory protocol, a protocol that includes a binding entropy estimate, and protocols that take into account the ligand hydration shell. Despite the improvements observed with the latter two MMPBSA approaches, ABFE calculations were found to be overall superior in obtaining correlation with experimental affinities for the test cases considered. A difference in weighted average Pearson ([Formula: see text]) and Spearman ([Formula: see text]) correlations of 0.25 and 0.31 was observed when using a standard single-trajectory MMPBSA setup ([Formula: see text] = 0.64 and [Formula: see text] = 0.66 for ABFE; [Formula: see text] = 0.39 and [Formula: see text] = 0.35 for MMPBSA). The best performing MMPBSA protocols returned weighted average Pearson and Spearman correlations that were about 0.1 inferior to ABFE calculations: [Formula: see text] = 0.55 and [Formula: see text] = 0.56 when including an entropy estimate, and [Formula: see text] = 0.53 and [Formula: see text] = 0.55 when including explicit water molecules. Overall, the study suggests that ABFE calculations are indeed the more accurate approach, yet there is also value in MMPBSA calculations considering the lower compute requirements, and if agreement to experimental affinities in absolute terms is not of interest. Moreover, for the specific protein-ligand systems considered in this study, we find that including an explicit ligand hydration shell or a binding entropy estimate in the MMPBSA calculations resulted in significant performance improvements at a negligible computational cost.
Collapse
Affiliation(s)
- Matteo Aldeghi
- Structural Bioinformatics and Computational Biochemistry, Department of Biochemistry, University of Oxford , South Parks Road, Oxford OX1 3QU, United Kingdom
| | - Michael J Bodkin
- Evotec (U.K.) Ltd. , 114 Innovation Drive, Milton Park, Abingdon OX14 4RZ, United Kingdom
| | - Stefan Knapp
- Structural Genomics Consortium, Nuffield Department of Clinical Medicine, University of Oxford , Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, United Kingdom.,Institute for Pharmaceutical Chemistry and Buchmann Institute for Life Sciences, Johann Wolfgang Goethe-University , D-60438 Frankfurt am Main, Germany
| | - Philip C Biggin
- Structural Bioinformatics and Computational Biochemistry, Department of Biochemistry, University of Oxford , South Parks Road, Oxford OX1 3QU, United Kingdom
| |
Collapse
|