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Çınaroğlu S, Biggin PC. Computed Protein-Protein Enthalpy Signatures as a Tool for Identifying Conformation Sampling Problems. J Chem Inf Model 2023; 63:6095-6108. [PMID: 37759363 PMCID: PMC10565830 DOI: 10.1021/acs.jcim.3c01041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Indexed: 09/29/2023]
Abstract
Understanding the thermodynamic signature of protein-peptide binding events is a major challenge in computational chemistry. The complexity generated by both components possessing many degrees of freedom poses a significant issue for methods that attempt to directly compute the enthalpic contribution to binding. Indeed, the prevailing assumption has been that the errors associated with such approaches would be too large for them to be meaningful. Nevertheless, we currently have no indication of how well the present methods would perform in terms of predicting the enthalpy of binding for protein-peptide complexes. To that end, we carefully assembled and curated a set of 11 protein-peptide complexes where there is structural and isothermal titration calorimetry data available and then computed the absolute enthalpy of binding. The initial "out of the box" calculations were, as expected, very modest in terms of agreement with the experiment. However, careful inspection of the outliers allows for the identification of key sampling problems such as distinct conformations of peptide termini not being sampled or suboptimal cofactor parameters. Additional simulations guided by these aspects can lead to a respectable correlation with isothermal titration calorimetry (ITC) experiments (R2 of 0.88 and an RMSE of 1.48 kcal/mol overall). Although one cannot know prospectively whether computed ITC values will be correct or not, this work shows that if experimental ITC data are available, then this in conjunction with computed ITC, can be used as a tool to know if the ensemble being simulated is representative of the true ensemble or not. That is important for allowing the correct interpretation of the detailed dynamics of the system with respect to the measured enthalpy. The results also suggest that computational calorimetry is becoming increasingly feasible. We provide the data set as a resource for the community, which could be used as a benchmark to help further progress in this area.
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Affiliation(s)
| | - Philip C. Biggin
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, U.K.
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2
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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.
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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
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Minetti CA, Remeta DP. Forces Driving a Magic Bullet to Its Target: Revisiting the Role of Thermodynamics in Drug Design, Development, and Optimization. Life (Basel) 2022; 12:1438. [PMID: 36143474 PMCID: PMC9504344 DOI: 10.3390/life12091438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 09/02/2022] [Accepted: 09/03/2022] [Indexed: 11/27/2022] Open
Abstract
Drug discovery strategies have advanced significantly towards prioritizing target selectivity to achieve the longstanding goal of identifying "magic bullets" amongst thousands of chemical molecules screened for therapeutic efficacy. A myriad of emerging and existing health threats, including the SARS-CoV-2 pandemic, alarming increase in bacterial resistance, and potentially fatal chronic ailments, such as cancer, cardiovascular disease, and neurodegeneration, have incentivized the discovery of novel therapeutics in treatment regimens. The design, development, and optimization of lead compounds represent an arduous and time-consuming process that necessitates the assessment of specific criteria and metrics derived via multidisciplinary approaches incorporating functional, structural, and energetic properties. The present review focuses on specific methodologies and technologies aimed at advancing drug development with particular emphasis on the role of thermodynamics in elucidating the underlying forces governing ligand-target interaction selectivity and specificity. In the pursuit of novel therapeutics, isothermal titration calorimetry (ITC) has been utilized extensively over the past two decades to bolster drug discovery efforts, yielding information-rich thermodynamic binding signatures. A wealth of studies recognizes the need for mining thermodynamic databases to critically examine and evaluate prospective drug candidates on the basis of available metrics. The ultimate power and utility of thermodynamics within drug discovery strategies reside in the characterization and comparison of intrinsic binding signatures that facilitate the elucidation of structural-energetic correlations which assist in lead compound identification and optimization to improve overall therapeutic efficacy.
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Affiliation(s)
- Conceição A. Minetti
- Department of Chemistry and Chemical Biology, Rutgers—The State University of New Jersey, Piscataway, NJ 08854, USA
| | - David P. Remeta
- Department of Chemistry and Chemical Biology, Rutgers—The State University of New Jersey, Piscataway, NJ 08854, USA
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Fu H, Chen H, Blazhynska M, Goulard Coderc de Lacam E, Szczepaniak F, Pavlova A, Shao X, Gumbart JC, Dehez F, Roux B, Cai W, Chipot C. Accurate determination of protein:ligand standard binding free energies from molecular dynamics simulations. Nat Protoc 2022; 17:1114-1141. [PMID: 35277695 PMCID: PMC10082674 DOI: 10.1038/s41596-021-00676-1] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 12/07/2021] [Indexed: 11/09/2022]
Abstract
Designing a reliable computational methodology to calculate protein:ligand standard binding free energies is extremely challenging. The large change in configurational enthalpy and entropy that accompanies the association of ligand and protein is notoriously difficult to capture in naive brute-force simulations. Addressing this issue, the present protocol rests upon a rigorous statistical mechanical framework for the determination of protein:ligand binding affinities together with the comprehensive Binding Free-Energy Estimator 2 (BFEE2) application software. With the knowledge of the bound state, available from experiments or docking, application of the BFEE2 protocol with a reliable force field supplies in a matter of days standard binding free energies within chemical accuracy, for a broad range of protein:ligand complexes. Limiting undesirable human intervention, BFEE2 assists the end user in preparing all the necessary input files and performing the post-treatment of the simulations towards the final estimate of the binding affinity.
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Affiliation(s)
- Haohao Fu
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Tianjin, China
| | - Haochuan Chen
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Tianjin, China
| | - Marharyta Blazhynska
- Laboratoire International Associé CNRS and University of Illinois at Urbana-Champaign, UMR 7019, Université de Lorraine, Vandœuvre-lès-Nancy, France
| | - Emma Goulard Coderc de Lacam
- Laboratoire International Associé CNRS and University of Illinois at Urbana-Champaign, UMR 7019, Université de Lorraine, Vandœuvre-lès-Nancy, France
| | - Florence Szczepaniak
- Laboratoire International Associé CNRS and University of Illinois at Urbana-Champaign, UMR 7019, Université de Lorraine, Vandœuvre-lès-Nancy, France.,Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL, USA
| | - Anna Pavlova
- School of Physics, Georgia Institute of Technology, Atlanta, GA, USA
| | - Xueguang Shao
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Tianjin, China
| | - James C Gumbart
- School of Physics, Georgia Institute of Technology, Atlanta, GA, USA
| | - François Dehez
- Laboratoire International Associé CNRS and University of Illinois at Urbana-Champaign, UMR 7019, Université de Lorraine, Vandœuvre-lès-Nancy, France
| | - Benoît Roux
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL, USA.,Department of Chemistry, University of Chicago, Chicago, IL, USA.,Center for Nanoscale Materials, Argonne National Laboratory, Argonne, IL, USA
| | - Wensheng Cai
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Tianjin, China.
| | - Christophe Chipot
- Laboratoire International Associé CNRS and University of Illinois at Urbana-Champaign, UMR 7019, Université de Lorraine, Vandœuvre-lès-Nancy, France. .,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA. .,Theoretical and Computational Biophysics Group, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
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Çınaroğlu SS, Biggin PC. Evaluating the Performance of Water Models with Host-Guest Force Fields in Binding Enthalpy Calculations for Cucurbit[7]uril-Guest Systems. J Phys Chem B 2021; 125:1558-1567. [PMID: 33538161 DOI: 10.1021/acs.jpcb.0c11383] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Computational prediction of thermodynamic components with computational methods has become increasingly routine in computer-aided drug design. Although there has been significant recent effort and improvements in the calculation of free energy, the prediction of enthalpy (and entropy) remains underexplored. Furthermore, there has been relatively little work reported so far that attempts to comparatively assess how well different force fields and water models perform in conjunction with each other. Here, we report a comprehensive assessment of force fields and water models using host-guest systems that mimic many features of protein-ligand systems. These systems are computationally inexpensive, possibly because of their small size compared to protein-ligand systems. We present absolute enthalpy calculations using the multibox approach on a set of 25 cucurbit[7]uril-guest pairs. Eight water models were considered (TIP3P, TIP4P, TIP4P-Ew, SPC, SPC/E, OPC, TIP5P, Bind3P), along with five force fields commonly used in the literature (GAFFv1, GAFFv2, CGenFF, Parsley, and SwissParam). We observe that host-guest binding enthalpies are strongly sensitive to the selection of force field and water model. In terms of water models, we find that TIP3P and its derivative Bind3P are the best performing models for this particular host-guest system. The performance is generally better for aliphatic compounds than for aromatic ones, suggesting that aromaticity remains a difficult property to include accurately in these simple force fields.
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Affiliation(s)
| | - Philip C Biggin
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, U.K
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Abstract
Every protein has a story-how it folds, what it binds, its biological actions, and how it misbehaves in aging or disease. Stories are often inferred from a protein's shape (i.e., its structure). But increasingly, stories are told using computational molecular physics (CMP). CMP is rooted in the principled physics of driving forces and reveals granular detail of conformational populations in space and time. Recent advances are accessing longer time scales, larger actions, and blind testing, enabling more of biology's stories to be told in the language of atomistic physics.
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Affiliation(s)
- Emiliano Brini
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Carlos Simmerling
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA.,Department of Chemistry, Stony Brook University, Stony Brook, NY 11794, USA
| | - Ken Dill
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA. .,Department of Chemistry, Stony Brook University, Stony Brook, NY 11794, USA.,Department of Physics and Astronomy, Stony Brook University, Stony Brook, New NY 11794, USA
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Cramer DL, Cheng B, Tian J, Clements JH, Wypych RM, Martin SF. Some thermodynamic effects of varying nonpolar surfaces in protein-ligand interactions. Eur J Med Chem 2020; 208:112771. [PMID: 32916312 PMCID: PMC7680455 DOI: 10.1016/j.ejmech.2020.112771] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 08/11/2020] [Accepted: 08/15/2020] [Indexed: 12/18/2022]
Abstract
Understanding how making structural changes in small molecules affects their binding affinities for targeted proteins is central to improving strategies for rational drug design. To assess the effects of varying the nature of nonpolar groups upon binding entropies and enthalpies, we designed and prepared a set of Grb2-SH2 domain ligands, Ac-pTyr-Ac6c-Asn-(CH2)n-R, in which the size and electrostatic nature of R groups at the pTyr+3 site were varied. The complexes of these ligands with the Grb2-SH2 domain were evaluated in a series of studies in which the binding thermodynamics were determined using isothermal titration calorimetry, and binding interactions were examined in crystallographic studies of two different complexes. Notably, adding nonpolar groups to the pTyr+3 site leads to higher binding affinities, but the magnitude and energetic origins of these effects vary with the nature of the R substituent. For example, enhancements to binding affinities using aliphatic R groups are driven by more favorable changes in binding entropies, whereas aryl R groups improve binding free energies through a combination of more favorable changes in binding enthalpies and entropies. However, enthalpy/entropy compensation plays a significant role in these associations and mitigates against any significant variation in binding free energies, which vary by only 0.8 kcal•mol-1, with changes in the electrostatic nature and size of the R group. Crystallographic studies show that differences in ΔG° or ΔH° correlate with buried nonpolar surface area, but they do not correlate with the total number of polar or van der Waals contacts. The relative number of ordered water molecules and relative order in the side chains at pTyr+3 correlate with differences in -TΔS°. Overall, these studies show that burial of nonpolar surface can lead to enhanced binding affinities arising from dominating entropy- or enthalpy-driven hydrophobic effects, depending upon the electrostatic nature of the apolar R group.
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Affiliation(s)
- David L Cramer
- Department of Chemistry and the Institute of Cellular and Molecular Biology, The University of Texas, Austin, TX 78712, USA
| | - Bo Cheng
- Department of Chemistry and the Institute of Cellular and Molecular Biology, The University of Texas, Austin, TX 78712, USA
| | - Jianhua Tian
- Department of Chemistry and the Institute of Cellular and Molecular Biology, The University of Texas, Austin, TX 78712, USA
| | - John H Clements
- Department of Chemistry and the Institute of Cellular and Molecular Biology, The University of Texas, Austin, TX 78712, USA
| | - Rachel M Wypych
- Department of Chemistry and the Institute of Cellular and Molecular Biology, The University of Texas, Austin, TX 78712, USA
| | - Stephen F Martin
- Department of Chemistry and the Institute of Cellular and Molecular Biology, The University of Texas, Austin, TX 78712, USA.
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The role of water in ligand binding. Curr Opin Struct Biol 2020; 67:1-8. [PMID: 32942197 DOI: 10.1016/j.sbi.2020.08.002] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 08/11/2020] [Accepted: 08/13/2020] [Indexed: 02/06/2023]
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Geschwindner S, Ulander J. The current impact of water thermodynamics for small-molecule drug discovery. Expert Opin Drug Discov 2019; 14:1221-1225. [DOI: 10.1080/17460441.2019.1664468] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
- Stefan Geschwindner
- Structure, Biophysics and Fragment-based Lead Generation, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden
| | - Johan Ulander
- Data Science and Modelling, Pharmaceutical Sciences, R&D, AstraZeneca, Gothenburg, Sweden
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Bitencourt-Ferreira G, Veit-Acosta M, de Azevedo WF. Van der Waals Potential in Protein Complexes. Methods Mol Biol 2019; 2053:79-91. [PMID: 31452100 DOI: 10.1007/978-1-4939-9752-7_6] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Van der Waals forces are determinants of the formation of protein-ligand complexes. Physical models based on the Lennard-Jones potential can estimate van der Waals interactions with considerable accuracy and with a computational complexity that allows its application to molecular docking simulations and virtual screening of large databases of small organic molecules. Several empirical scoring functions used to evaluate protein-ligand interactions approximate van der Waals interactions with the Lennard-Jones potential. In this chapter, we present the main concepts necessary to understand van der Waals interactions relevant to molecular recognition of a ligand by the binding pocket of a protein target. We describe the Lennard-Jones potential and its application to calculate potential energy for an ensemble of structures to highlight the main features related to the importance of this interaction for binding affinity.
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Affiliation(s)
- Gabriela Bitencourt-Ferreira
- Escola de Ciências da Saúde, Pontifícia Universidade Católica do Rio Grande do Sul-PUCRS, Porto Alegre, RS, Brazil
| | - Martina Veit-Acosta
- Escola de Ciências da Saúde, Pontifícia Universidade Católica do Rio Grande do Sul-PUCRS, Porto Alegre, RS, Brazil
| | - Walter Filgueira de Azevedo
- Escola de Ciências da Saúde, Pontifícia Universidade Católica do Rio Grande do Sul-PUCRS, Porto Alegre, RS, Brazil.
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