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Tytuł pozycji:

Binding Thermodynamics of Host-Guest Systems with SMIRNOFF99Frosst 1.0.5 from the Open Force Field Initiative.

Tytuł:
Binding Thermodynamics of Host-Guest Systems with SMIRNOFF99Frosst 1.0.5 from the Open Force Field Initiative.
Autorzy:
Slochower DR; Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California, San Diego , La Jolla , California 92093 , United States.
Henriksen NM; Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California, San Diego , La Jolla , California 92093 , United States.
Wang LP; Department of Chemistry , University of California , Davis , California 95616 , United States.
Chodera JD; Computational and Systems Biology Program, Sloan Kettering Institute , Memorial Sloan Kettering Cancer Center , New York , New York 10065 , United States.
Mobley DL; Department of Pharmaceutical Sciences and Department of Chemistry , University of California , Irvine , California 92697 , United States.
Gilson MK; Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California, San Diego , La Jolla , California 92093 , United States.
Źródło:
Journal of chemical theory and computation [J Chem Theory Comput] 2019 Nov 12; Vol. 15 (11), pp. 6225-6242. Date of Electronic Publication: 2019 Oct 25.
Typ publikacji:
Journal Article
Język:
English
Imprint Name(s):
Original Publication: Washington, D.C. : American Chemical Society, c2005-
MeSH Terms:
Ligands*
Models, Molecular*
Thermodynamics ; alpha-Cyclodextrins/chemistry ; beta-Cyclodextrins/chemistry
References:
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Grant Information:
P30 CA008748 United States CA NCI NIH HHS; R01 GM061300 United States GM NIGMS NIH HHS; R01 GM121505 United States GM NIGMS NIH HHS; R01 GM124270 United States GM NIGMS NIH HHS
Substance Nomenclature:
0 (Ligands)
0 (alpha-Cyclodextrins)
0 (beta-Cyclodextrins)
JV039JZZ3A (betadex)
Z1LH97KTRM (alpha-cyclodextrin)
Entry Date(s):
Date Created: 20191012 Date Completed: 20191120 Latest Revision: 20240329
Update Code:
20240329
PubMed Central ID:
PMC7328435
DOI:
10.1021/acs.jctc.9b00748
PMID:
31603667
Czasopismo naukowe
Designing ligands that bind their target biomolecules with high affinity and specificity is a key step in small-molecule drug discovery, but accurately predicting protein-ligand binding free energies remains challenging. Key sources of errors in the calculations include inadequate sampling of conformational space, ambiguous protonation states, and errors in force fields. Noncovalent complexes between a host molecule with a binding cavity and a druglike guest molecule have emerged as powerful model systems. As model systems, host-guest complexes reduce many of the errors in more complex protein-ligand binding systems, as their small size greatly facilitates conformational sampling, and one can choose systems that avoid ambiguities in protonation states. These features, combined with their ease of experimental characterization, make host-guest systems ideal model systems to test and ultimately optimize force fields in the context of binding thermodynamics calculations. The Open Force Field Initiative aims to create a modern, open software infrastructure for automatically generating and assessing force fields using data sets. The first force field to arise out of this effort, named SMIRNOFF99Frosst, has approximately one tenth the number of parameters, in version 1.0.5, compared to typical general small molecule force fields, such as GAFF. Here, we evaluate the accuracy of this initial force field, using free energy calculations of 43 α and β-cyclodextrin host-guest pairs for which experimental thermodynamic data are available, and compare with matched calculations using two versions of GAFF. For all three force fields, we used TIP3P water and AM1-BCC charges. The calculations are performed using the attach-pull-release (APR) method as implemented in the open source package, pAPRika. For binding free energies, the root-mean-square error of the SMIRNOFF99Frosst calculations relative to experiment is 0.9 [0.7, 1.1] kcal/mol, while the corresponding results for GAFF 1.7 and GAFF 2.1 are 0.9 [0.7, 1.1] kcal/mol and 1.7 [1.5, 1.9] kcal/mol, respectively, with 95% confidence ranges in brackets. These results suggest that SMIRNOFF99Frosst performs competitively with existing small molecule force fields and is a parsimonious starting point for optimization.

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