Virtual Double-System Single-Box: A Nonequilibrium Alchemical Technique for Absolute Binding Free Energy Calculations: Application to Ligands of the SARS-CoV-2 Main Protease

Macchiagodena, Marina; Pagliai, Marco; Karrenbrock, Maurice; Guarnieri, Guido; Iannone, F.; Procacci, Piero

doi:10.1021/acs.jctc.0c00634

Cited by 45 publications

(79 citation statements)

References 79 publications

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“…In the present work we have performed a combined simulation based on classical MD and ab initio FMO methods for the analysis of ligand binding in the SARS-CoV-2 M pro -N3 complex system, thus finding the importance of statistical evaluation of interactions by employing a thousand of dynamically fluctuating structures. Recent studies 17,[20][21][22][23]53,[55][56] concerning SARS-CoV-2 proteins have shed light on the importance of "dynamic" aspects, and our quantum-chemical work accords with this direction.…”

Section: Resultsmentioning

confidence: 99%

Dynamical Cooperativity of Ligand-Residue Interactions Evaluated with the Fragment Molecular Orbital Method

Tanaka

Tokutomi²,

Hatada³

et al. 2021

Preprint

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By the splendid advance in computation power realized with Fugaku supercomputer, it has become possible to perform ab initio fragment molecular orbital (FMO) calculations for thousands of dynamical structures of a protein-ligand complex in a parallelized way. We have thus carried out the electron-correlated FMO calculations for a complex of the 3C-like (3CL) main protease (Mpro) of the new coronavirus (SARS-CoV-2) and its inhibitor N3 incorporating the structural fluctuations sampled by classical molecular dynamics (MD) simulation in hydrated condition. Along with a statistical evaluation of inter-fragment interaction energies (IFIEs) between the N3 ligand and surrounding amino-acid residues for a thousand of dynamical structure samples, we have applied in this study a novel approach based on the principal component analysis (PCA) and the singular value decomposition (SVD) to the analysis of IFIE data in order to extract the dynamically cooperative interactions between the ligand and residues. We have found that the relative importance of each residue is modified via the structural fluctuations and that the ligand is bound in the pharmacophore in a dynamical manner through collective interactions formed by multiple residues, thus providing a new insight into structure-based drug discovery

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Section: Resultsmentioning

confidence: 99%

Dynamical Cooperativity of Ligand-Residue Interactions Evaluated with the Fragment Molecular Orbital Method

Tanaka

Tokutomi²,

Hatada³

et al. 2021

Preprint

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“…It should be noted that the poor accuracy of AD4 was also revealed when the docking results were compared with NEMD simulations, = 0.36. 64 The MD simulations would be then accomplished. FEP approach was indicated that it provided the most accurate results, FEP = 0.80 ± 0.06, compared with the respective experiments.…”

Section: Resultsmentioning

confidence: 99%

“…It is probably caused by the difference in scoring functions as indicated by prior observations. 36 Furthermore, in the prior work, 64 AD4 gave poor correlation, = 0.36, with the ∆ Jarzynski , which obtained via NEMD simulations, 33 one of the most accurate free energy approaches until then. Therefore, it may argue that Vina is the appropriate protocol for preliminary assessment of the ligand-binding affinity to the SARS-CoV-2 Mpro.…”

Section: Molecular Docking Calculationsmentioning

confidence: 96%

A Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV2 Mpro

Tung

Ngo²,

Minh³

et al. 2020

Preprint

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COVID-19 pandemic has killed millions of people worldwide since its outbreak in Dec 2019. The pandemic is caused by the SARS-CoV-2 virus whose main protease (Mpro) is a promising drug target since it plays a key role in viral proliferation and replication. Currently, designing an effective therapy is an urgent task, which requires accurately estimating ligand-binding free energy to the SARS-CoV-2 Mpro. However, it should be noted that the accuracy of a free energy method probably depends on the protein target. A highly accurate approach for some targets may fail to produce a reasonable correlation with experiment when a novel enzyme is considered as a drug target. Therefore, in this context, the ligand-binding affinity to SARS-CoV-2 Mpro was calculated via various approaches. The Autodock Vina (Vina) and Autodock4 (AD4) packages were manipulated to preliminary investigate the ligand-binding affinity and pose to the SARS-CoV-2 Mpro. The binding free energy was then refined using the fast pulling of ligand (FPL), linear interaction energy (LIE), molecular mechanics-Poission Boltzmann surface area (MM-PBSA), and free energy perturbation (FEP) methods. The benchmark results indicated that for docking calculations, Vina is more accurate than AD4 and for free energy methods, FEP is the most accurate followed by LIE, FPL and MM-PBSA (FEP > LIE > FPL > MM-PBSA). Moreover, the binding mechanism was also revealed by atomistic simulations. The vdW interaction is the dominant factor. The residues Thr25, Thr26, His41, Ser46, Asn142, Gly143, Cys145, Glu166, and Gln189 are essential elements affecting on the binding process. Furthermore, the Ser46 and related residues probably are important elements affecting the enlarge/dwindle of the SARS-CoV-2 Mpro binding cleft. The benchmark probably guide for further investigations using computational approaches.

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“…It should be noted that the poor accuracy of AD4 was also revealed when the docking results were compared with the NEMD simulations, R = 0.36. 74 …”

Section: Discussionmentioning

confidence: 99%

Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV-2 Mpro

Ngo

Tam

Quan

et al. 2021

J. Chem. Inf. Model.

118

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The COVID-19 pandemic has killed millions of people worldwide since its outbreak in December 2019. The pandemic is caused by the SARS-CoV-2 virus whose main protease (Mpro) is a promising drug target since it plays a key role in viral proliferation and replication. Currently, developing an effective therapy is an urgent task, which requires accurately estimating the ligand-binding free energy to SARS-CoV-2 Mpro. However, it should be noted that the accuracy of a free energy method probably depends on the protein target. A highly accurate approach for some targets may fail to produce a reasonable correlation with the experiment when a novel enzyme is considered as a drug target. Therefore, in this context, the ligand-binding affinity to SARS-CoV-2 Mpro was calculated via various approaches. The molecular docking approach was manipulated using Autodock Vina (Vina) and Autodock4 (AD4) protocols to preliminarily investigate the ligand-binding affinity and pose to SARS-CoV-2 Mpro. The binding free energy was then refined using the fast pulling of ligand (FPL), linear interaction energy (LIE), molecular mechanics-Poisson–Boltzmann surface area (MM-PBSA), and free energy perturbation (FEP) methods. The benchmark results indicated that for docking calculations, Vina is more accurate than AD4, and for free energy methods, FEP is the most accurate method, followed by LIE, FPL, and MM-PBSA (FEP > LIE ≈ FPL > MM-PBSA). Moreover, atomistic simulations revealed that the van der Waals interaction is the dominant factor. The residues Thr26 , His41 , Ser46 , Asn142 , Gly143 , Cys145 , His164 , Glu166 , and Gln189 are essential elements affecting the binding process. Our benchmark provides guidelines for further investigations using computational approaches.

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Virtual Double-System Single-Box: A Nonequilibrium Alchemical Technique for Absolute Binding Free Energy Calculations: Application to Ligands of the SARS-CoV-2 Main Protease

Cited by 45 publications

References 79 publications

Dynamical Cooperativity of Ligand-Residue Interactions Evaluated with the Fragment Molecular Orbital Method

Dynamical Cooperativity of Ligand-Residue Interactions Evaluated with the Fragment Molecular Orbital Method

A Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV2 Mpro

Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV-2 Mpro

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