Relative free-energy calculations for scaffold hopping-type transformations with an automated RE-EDS sampling procedure.

Enveloping distribution sampling Free energy calculation Molecular dynamics Protein-ligand binding Replica exchange

Journal

Journal of computer-aided molecular design
ISSN: 1573-4951
Titre abrégé: J Comput Aided Mol Des
Pays: Netherlands
ID NLM: 8710425

Informations de publication

Date de publication:
02 2022
Historique:
received: 03 06 2021
accepted: 23 11 2021
pubmed: 4 1 2022
medline: 3 5 2022
entrez: 3 1 2022
Statut: ppublish

Résumé

The calculation of relative free-energy differences between different compounds plays an important role in drug design to identify potent binders for a given protein target. Most rigorous methods based on molecular dynamics simulations estimate the free-energy difference between pairs of ligands. Thus, the comparison of multiple ligands requires the construction of a "state graph", in which the compounds are connected by alchemical transformations. The computational cost can be optimized by reducing the state graph to a minimal set of transformations. However, this may require individual adaptation of the sampling strategy if a transformation process does not converge in a given simulation time. In contrast, path-free methods like replica-exchange enveloping distribution sampling (RE-EDS) allow the sampling of multiple states within a single simulation without the pre-definition of alchemical transition paths. To optimize sampling and convergence, a set of RE-EDS parameters needs to be estimated in a pre-processing step. Here, we present an automated procedure for this step that determines all required parameters, improving the robustness and ease of use of the methodology. To illustrate the performance, the relative binding free energies are calculated for a series of checkpoint kinase 1 inhibitors containing challenging transformations in ring size, opening/closing, and extension, which reflect changes observed in scaffold hopping. The simulation of such transformations with RE-EDS can be conducted with conventional force fields and, in particular, without soft bond-stretching terms.

Identifiants

pubmed: 34978000
doi: 10.1007/s10822-021-00436-z
pii: 10.1007/s10822-021-00436-z
pmc: PMC8907147
doi:

Substances chimiques

Ligands 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

117-130

Subventions

Organisme : Swiss National Science Foundation
ID : 200021-178762
Pays : Switzerland

Informations de copyright

© 2021. The Author(s).

Références

J Chem Theory Comput. 2017 Jun 13;13(6):3020-3030
pubmed: 28510459
Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Dec;78(6 Pt 1):061905
pubmed: 19256866
ACS Med Chem Lett. 2012 Jan 20;3(2):123-8
pubmed: 24900442
Nat Methods. 2020 Mar;17(3):261-272
pubmed: 32015543
J Chem Inf Model. 2020 Nov 23;60(11):5407-5423
pubmed: 32794763
J Chem Phys. 2007 May 14;126(18):184110
pubmed: 17508795
Chem Sci. 2016 Jan 14;7(1):207-218
pubmed: 26798447
J Chem Inf Model. 2017 Dec 26;57(12):2911-2937
pubmed: 29243483
J Chem Phys. 2011 Jul 14;135(2):024105
pubmed: 21766923
J Chem Theory Comput. 2017 Jan 10;13(1):42-54
pubmed: 27933808
J Chem Inf Model. 2018 Mar 26;58(3):579-590
pubmed: 29461814
J Chem Theory Comput. 2014 Jul 8;10(7):2738-2750
pubmed: 25061443
Eur Biophys J. 2011 Jul;40(7):843-56
pubmed: 21533652
J Chem Theory Comput. 2020 Mar 10;16(3):1630-1645
pubmed: 31995374
J Chem Theory Comput. 2011 Dec 13;7(12):4026-37
pubmed: 26598349
J Chem Theory Comput. 2015 Jun 9;11(6):2560-74
pubmed: 26575555
J Phys Chem B. 2018 May 17;122(19):5030-5037
pubmed: 29669415
J Comput Chem. 2016 Nov 5;37(29):2597-605
pubmed: 27634475
J Chem Inf Model. 2020 Nov 23;60(11):5395-5406
pubmed: 32492343
J Chem Phys. 2016 Oct 21;145(15):154114
pubmed: 27782485
J Comput Chem. 2012 Mar 5;33(6):640-51
pubmed: 22228455
J Cheminform. 2019 Apr 2;11(1):26
pubmed: 30941533
J Chem Inf Model. 2020 Nov 23;60(11):5457-5474
pubmed: 32813975
J Chem Inf Model. 2020 Sep 28;60(9):4153-4169
pubmed: 32539386
J Chem Inf Model. 2020 Jan 27;60(1):1-5
pubmed: 31983210
Annu Rev Biophys. 2013;42:121-42
pubmed: 23654303
J Chem Phys. 2008 May 7;128(17):174112
pubmed: 18465915
J Comput Chem. 2020 Jan 30;41(3):247-257
pubmed: 31721260
J Comput Aided Mol Des. 2013 Sep;27(9):755-70
pubmed: 24072356
J Chem Theory Comput. 2011 Oct 11;7(10):3379-90
pubmed: 26598168
J Chem Theory Comput. 2009 Feb 10;5(2):276-86
pubmed: 26610104
J Am Chem Soc. 2015 Feb 25;137(7):2695-703
pubmed: 25625324
J Chem Inf Model. 2021 Feb 22;61(2):560-564
pubmed: 33512157

Auteurs

Benjamin Ries (B)

Laboratory of Physical Chemistry, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zürich, Switzerland.

Karl Normak (K)

Laboratory of Physical Chemistry, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zürich, Switzerland.

R Gregor Weiß (RG)

Laboratory of Physical Chemistry, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zürich, Switzerland.

Salomé Rieder (S)

Laboratory of Physical Chemistry, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zürich, Switzerland.

Emília P Barros (EP)

Laboratory of Physical Chemistry, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zürich, Switzerland.

Candide Champion (C)

Laboratory of Physical Chemistry, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zürich, Switzerland.

Gerhard König (G)

Laboratory of Physical Chemistry, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zürich, Switzerland.

Sereina Riniker (S)

Laboratory of Physical Chemistry, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zürich, Switzerland. sriniker@ethz.ch.

Articles similaires

Photosynthesis Ribulose-Bisphosphate Carboxylase Carbon Dioxide Molecular Dynamics Simulation Cyanobacteria
Fucosyltransferases Drug Repositioning Molecular Docking Simulation Molecular Dynamics Simulation Humans
Receptor, Cannabinoid, CB1 Ligands Molecular Dynamics Simulation Protein Binding Thermodynamics

Amyloid accelerator polyphosphate fits as the mystery density in α-synuclein fibrils.

Philipp Huettemann, Pavithra Mahadevan, Justine Lempart et al.
1.00
Polyphosphates alpha-Synuclein Humans Amyloid Molecular Dynamics Simulation

Classifications MeSH