Gapsys, Vytautas

[["dc.bibliographiccitation.artnumber","61"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Communications Chemistry"],["dc.bibliographiccitation.volume","4"],["dc.contributor.author","Gapsys, Vytautas"],["dc.contributor.author","Yildirim, Ahmet"],["dc.contributor.author","Aldeghi, Matteo"],["dc.contributor.author","Khalak, Yuriy"],["dc.contributor.author","van der Spoel, David"],["dc.contributor.author","de Groot, Bert L."],["dc.date.accessioned","2022-03-01T11:46:05Z"],["dc.date.available","2022-03-01T11:46:05Z"],["dc.date.issued","2021"],["dc.description.abstract","Abstract The accurate calculation of the binding free energy for arbitrary ligand–protein pairs is a considerable challenge in computer-aided drug discovery. Recently, it has been demonstrated that current state-of-the-art molecular dynamics (MD) based methods are capable of making highly accurate predictions. Conventional MD-based approaches rely on the first principles of statistical mechanics and assume equilibrium sampling of the phase space. In the current work we demonstrate that accurate absolute binding free energies (ABFE) can also be obtained via theoretically rigorous non-equilibrium approaches. Our investigation of ligands binding to bromodomains and T4 lysozyme reveals that both equilibrium and non-equilibrium approaches converge to the same results. The non-equilibrium approach achieves the same level of accuracy and convergence as an equilibrium free energy perturbation (FEP) method enhanced by Hamiltonian replica exchange. We also compare uni- and bi-directional non-equilibrium approaches and demonstrate that considering the work distributions from both forward and reverse directions provides substantial accuracy gains. In summary, non-equilibrium ABFE calculations are shown to yield reliable and well-converged estimates of protein–ligand binding affinity."],["dc.description.abstract","Abstract The accurate calculation of the binding free energy for arbitrary ligand–protein pairs is a considerable challenge in computer-aided drug discovery. Recently, it has been demonstrated that current state-of-the-art molecular dynamics (MD) based methods are capable of making highly accurate predictions. Conventional MD-based approaches rely on the first principles of statistical mechanics and assume equilibrium sampling of the phase space. In the current work we demonstrate that accurate absolute binding free energies (ABFE) can also be obtained via theoretically rigorous non-equilibrium approaches. Our investigation of ligands binding to bromodomains and T4 lysozyme reveals that both equilibrium and non-equilibrium approaches converge to the same results. The non-equilibrium approach achieves the same level of accuracy and convergence as an equilibrium free energy perturbation (FEP) method enhanced by Hamiltonian replica exchange. We also compare uni- and bi-directional non-equilibrium approaches and demonstrate that considering the work distributions from both forward and reverse directions provides substantial accuracy gains. In summary, non-equilibrium ABFE calculations are shown to yield reliable and well-converged estimates of protein–ligand binding affinity."],["dc.identifier.doi","10.1038/s42004-021-00498-y"],["dc.identifier.pii","498"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/103552"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-531"],["dc.relation.eissn","2399-3669"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Accurate absolute free energies for ligand–protein binding based on non-equilibrium approaches"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1468"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","ACS Central Science"],["dc.bibliographiccitation.lastpage","1474"],["dc.bibliographiccitation.volume","5"],["dc.contributor.author","Aldeghi, Matteo"],["dc.contributor.author","Gapsys, Vytautas"],["dc.contributor.author","de Groot, Bert L."],["dc.date.accessioned","2021-03-05T08:58:21Z"],["dc.date.available","2021-03-05T08:58:21Z"],["dc.date.issued","2019"],["dc.identifier.doi","10.1021/acscentsci.9b00590"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/80099"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-393"],["dc.relation.eissn","2374-7951"],["dc.relation.issn","2374-7943"],["dc.title","Predicting Kinase Inhibitor Resistance: Physics-Based and Data-Driven Approaches"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1708"],["dc.bibliographiccitation.issue","12"],["dc.bibliographiccitation.journal","ACS Central Science"],["dc.bibliographiccitation.lastpage","1718"],["dc.bibliographiccitation.volume","4"],["dc.contributor.author","Aldeghi, Matteo"],["dc.contributor.author","Gapsys, Vytautas"],["dc.contributor.author","de Groot, Bert L."],["dc.date.accessioned","2021-03-05T08:58:21Z"],["dc.date.available","2021-03-05T08:58:21Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.1021/acscentsci.8b00717"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/80098"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-393"],["dc.relation.eissn","2374-7951"],["dc.relation.issn","2374-7943"],["dc.title","Accurate Estimation of Ligand Binding Affinity Changes upon Protein Mutation"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","601"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Journal of Computer-Aided Molecular Design"],["dc.bibliographiccitation.lastpage","633"],["dc.bibliographiccitation.volume","34"],["dc.contributor.author","Rizzi, Andrea"],["dc.contributor.author","Jensen, Travis"],["dc.contributor.author","Slochower, David R."],["dc.contributor.author","Aldeghi, Matteo"],["dc.contributor.author","Gapsys, Vytautas"],["dc.contributor.author","Ntekoumes, Dimitris"],["dc.contributor.author","Bosisio, Stefano"],["dc.contributor.author","Papadourakis, Michail"],["dc.contributor.author","Henriksen, Niel M."],["dc.contributor.author","de Groot, Bert L."],["dc.contributor.author","Cournia, Zoe"],["dc.contributor.author","Dickson, Alex"],["dc.contributor.author","Michel, Julien"],["dc.contributor.author","Gilson, Michael K."],["dc.contributor.author","Shirts, Michael R."],["dc.contributor.author","Mobley, David L."],["dc.contributor.author","Chodera, John D."],["dc.date.accessioned","2021-03-05T09:05:21Z"],["dc.date.available","2021-03-05T09:05:21Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1007/s10822-020-00290-5"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/80448"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-393"],["dc.relation.eissn","1573-4951"],["dc.relation.issn","0920-654X"],["dc.title","The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1140"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Chemical Science"],["dc.bibliographiccitation.lastpage","1152"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Gapsys, Vytautas"],["dc.contributor.author","Pérez-Benito, Laura"],["dc.contributor.author","Aldeghi, Matteo"],["dc.contributor.author","Seeliger, Daniel"],["dc.contributor.author","van Vlijmen, Herman"],["dc.contributor.author","Tresadern, Gary"],["dc.contributor.author","de Groot, Bert L."],["dc.date.accessioned","2021-03-05T08:58:35Z"],["dc.date.available","2021-03-05T08:58:35Z"],["dc.date.issued","2020"],["dc.description.abstract","Relative ligand binding affinity calculations based on molecular dynamics (MD) simulations and non-physical (alchemical) thermodynamic cycles have shown great promise for structure-based drug design."],["dc.description.abstract","Ligand binding affinity calculations based on molecular dynamics (MD) simulations and non-physical (alchemical) thermodynamic cycles have shown great promise for structure-based drug design. However, their broad uptake and impact is held back by the notoriously complex setup of the calculations. Only a few tools other than the free energy perturbation approach by Schrödinger Inc. (referred to as FEP+) currently enable end-to-end application. Here, we present for the first time an approach based on the open-source software pmx that allows to easily set up and run alchemical calculations for diverse sets of small molecules using the GROMACS MD engine. The method relies on theoretically rigorous non-equilibrium thermodynamic integration (TI) foundations, and its flexibility allows calculations with multiple force fields. In this study, results from the Amber and Charmm force fields were combined to yield a consensus outcome performing on par with the commercial FEP+ approach. A large dataset of 482 perturbations from 13 different protein–ligand datasets led to an average unsigned error (AUE) of 3.64 ± 0.14 kJ mol −1 , equivalent to Schrödinger's FEP+ AUE of 3.66 ± 0.14 kJ mol −1 . For the first time, a setup is presented for overall high precision and high accuracy relative protein–ligand alchemical free energy calculations based on open-source software."],["dc.description.abstract","Relative ligand binding affinity calculations based on molecular dynamics (MD) simulations and non-physical (alchemical) thermodynamic cycles have shown great promise for structure-based drug design."],["dc.description.abstract","Ligand binding affinity calculations based on molecular dynamics (MD) simulations and non-physical (alchemical) thermodynamic cycles have shown great promise for structure-based drug design. However, their broad uptake and impact is held back by the notoriously complex setup of the calculations. Only a few tools other than the free energy perturbation approach by Schrödinger Inc. (referred to as FEP+) currently enable end-to-end application. Here, we present for the first time an approach based on the open-source software pmx that allows to easily set up and run alchemical calculations for diverse sets of small molecules using the GROMACS MD engine. The method relies on theoretically rigorous non-equilibrium thermodynamic integration (TI) foundations, and its flexibility allows calculations with multiple force fields. In this study, results from the Amber and Charmm force fields were combined to yield a consensus outcome performing on par with the commercial FEP+ approach. A large dataset of 482 perturbations from 13 different protein–ligand datasets led to an average unsigned error (AUE) of 3.64 ± 0.14 kJ mol −1 , equivalent to Schrödinger's FEP+ AUE of 3.66 ± 0.14 kJ mol −1 . For the first time, a setup is presented for overall high precision and high accuracy relative protein–ligand alchemical free energy calculations based on open-source software."],["dc.identifier.doi","10.1039/C9SC03754C"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/80191"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-393"],["dc.relation.eissn","2041-6539"],["dc.relation.issn","2041-6520"],["dc.rights.uri","http://creativecommons.org/licenses/by-nc/3.0/"],["dc.title","Large scale relative protein ligand binding affinities using non-equilibrium alchemy"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]