New approaches for computing ligand–receptor binding kinetics

Bruce, Neil J.; Ganotra, Gaurav K.; Kokh, Daria B.; Sadiq, S. Kashif; Wade, Rebecca C.

doi:10.1016/j.sbi.2017.10.001

Cited by 136 publications

(162 citation statements)

References 60 publications

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“…Moreover, when VAC-MetaD optimized CVs are used with the Infrequent Metadynamics scheme, it predicts the unbinding rate in good agreement with the experiment, thus providing a relatively cheap, rigorous and accurate calculation with respect to already existing methods. 56…”

Section: Discussionmentioning

confidence: 99%

Accelerating the Calculation of Protein-Ligand Binding Free Energy and Residence Times using Dynamically Optimized Collective Variables

Brotzakis

Limongelli

Parrinello

2018

Preprint

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Elucidation of the ligand/protein binding interaction is of paramount relevance in pharmacology to increase the success rate of drug design. To this end a number of computational methods have been proposed, however all of them suffer from limitations since the ligand binding/unbinding transitions to the molecular target involve many slow degrees of freedom that hamper a full characterization of the binding process.Being able to express this transition in simple and general slow degrees of freedom, would give a distinctive advantage, since it would require minimal knowledge of the system under study, while in turn it would elucidate its physics and accelerate the convergence speed of enhanced sampling methods relying on collective variables. In this study we pursuit this goal by combining for the first time Variation Approach to Conformational dynamics with Funnel-Metadynamics. In so doing, we predict for the benzamidine/trypsin system the ligand binding mode, and we accurately compute the absolute protein-ligand binding free energy and unbinding rate at unprecedented low computational cost. Finally, our simulation protocol reveals the energetics and structural details of the ligand binding mechanism and shows that water and binding pocket solvation/desolvation are the dominant slow degrees of freedom.

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Section: Discussionmentioning

confidence: 99%

Accelerating the Calculation of Protein-Ligand Binding Free Energy and Residence Times using Dynamically Optimized Collective Variables

Brotzakis

Limongelli

Parrinello

2018

Preprint

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“…Without explicit descriptions of individual water molecule, our theory predicts the key thermodynamic and kinetic properties of unbinding and binding, the latter in quantitative agreement with explicit-water molecular dynamics simulations. 33). While explicitly tracking water molecules, MD simulations are still limited to systems of relatively small sizes and events of relatively short time scales.…”

Section: Significance Statementmentioning

confidence: 99%

Variational implicit-solvent predictions of the dry–wet transition pathways for ligand–receptor binding and unbinding kinetics

Zhou

Weiß

Cheng

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

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Ligand-receptor binding and unbinding are fundamental biomolecular processes and particularly essential to drug efficacy. Environmental water fluctuations, however, impact the corresponding thermodynamics and kinetics and thereby challenge theoretical descriptions. Here, we devise a holistic, implicit-solvent, multi-method approach to predict the (un)binding kinetics for a generic ligand-pocket model. We use the variational implicit-solvent model (VISM) to calculate the solute-solvent interfacial structures and the corresponding free energies, and combine the VISM with the string method to obtain the minimum energy paths and transition states between the various metastable ("dry" and "wet") hydration states. The resulting dry-wet transition rates are then used in a spatially-dependent multi-state continuous-time Markov chain Brownian dynamics simulations, and the related Fokker-Planck equation calculations, of the ligand stochastic motion, providing the mean first-passage times for binding and unbinding. We find the hydration transitions to significantly slow down the binding process, in semi-quantitative agreement with existing explicit-water simulations, but significantly accelerate the unbinding process. Moreover, our methods allow the characterization of non-equilibrium hydration states of pocket and ligand during the ligand movement, for which we find substantial memory and hysteresis effects for binding versus unbinding. Our study thus provides a significant step forward towards efficient, physics-based interpretation and predictions of the complex kinetics in realistic ligand-receptor systems.Ligand-receptor binding/unbinding kinetics | dry-wet transitions | variational implicit-solvent model | level-set method | string method JD, JAM, and BL designed research. SZ, RGW, and LTC performed research. SZ, LTC, and BL developed numerical methods and LTC wrote the initial level-set code. SZ, RGW, and JD analyzed computational results. SZ, RGW, JD, JAM, and BL wrote the paper.The authors declare no conflict of interest.

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“…Therefore, strong AChE inhibitors are needed to treat AD without any side effects. Computational methods are very useful techniques to elucidate receptor-ligand interactions at the atomic level that are difficult to solve using experimental techniques [24][25][26]. Thus, aim of the study is to find novel hit compounds against AChE using rigorous virtual screening approaches.…”

Section: Introductionmentioning

confidence: 99%

Combined ligand and structure-based virtual screening approaches for identification of novel AChE inhibitors

Şahin

Durdağı

2020

Turk J Chem

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The excessive activity of acetylcholinesterase enzyme (AChE) causes different neuronal problems, especially dementia and neuronal cell deaths. Food and Drug Administration (FDA) approved drugs donepezil, rivastigmine, tacrine and galantamine are AChE inhibitors and in the treatment of Alzheimer’s disease (AD) these drugs are currently prescribed. However, these inhibitors have various adverse side effects. Therefore, there is a great need for the novel selective AChE inhibitors with fewer adverse side effects for the effective treatment. In this study, combined ligand-based and structure-based virtual screening approaches were used to identify new hit compounds from small molecules library of National Cancer Institute (NCI) containing approximately 265,000 small molecules. In the present study, we developed a computational pipeline method to predict the binding affinities of the studied compounds at the specific target sites. For this purpose, a text mining study was carried out initially and compounds containing the keyword “indol” were considered. The therapeutic activity values against AD were screened using the binary quantitative structure activity relationship (QSAR) models. We then performed docking, molecular dynamics (MD) simulations and free energy analysis to clarify the interactions between selected ligands and enzyme. Thus, in this study we identified new promising hit compounds from a large database that may be used to inhibit the enzyme activity of AChE.

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New approaches for computing ligand–receptor binding kinetics

Cited by 136 publications

References 60 publications

Accelerating the Calculation of Protein-Ligand Binding Free Energy and Residence Times using Dynamically Optimized Collective Variables

Accelerating the Calculation of Protein-Ligand Binding Free Energy and Residence Times using Dynamically Optimized Collective Variables

Variational implicit-solvent predictions of the dry–wet transition pathways for ligand–receptor binding and unbinding kinetics

Combined ligand and structure-based virtual screening approaches for identification of novel AChE inhibitors

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