Evidence map›Paper›PMID 31603667›Full record

ArticleJournal of chemical theory and computation2019

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

David R Slochower, Niel M Henriksen, Lee-Ping Wang, John D Chodera, David L Mobley, Michael K Gilson

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Tuning Potential Functions to Host-Guest Binding Data.Journal of chemical theory and computation · 2024
    Article
  3. Article
  4. Review
  5. Article
  6. An overview of the SAMPL8 host-guest binding challenge.Journal of computer-aided molecular design · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

David R SlochowerSkaggs School of Pharmacy and Pharmaceutical Sciences , University of California, San Diego , La Jolla , California 92093 , United States.ORCID http://orcid.org/0000-0003-3928-5050
Niel M HenriksenSkaggs School of Pharmacy and Pharmaceutical Sciences , University of California, San Diego , La Jolla , California 92093 , United States.ORCID http://orcid.org/0000-0002-7916-0757
Lee-Ping WangDepartment of Chemistry , University of California , Davis , California 95616 , United States.ORCID http://orcid.org/0000-0003-3072-9946
John D ChoderaComputational and Systems Biology Program, Sloan Kettering Institute , Memorial Sloan Kettering Cancer Center , New York , New York 10065 , United States.ORCID http://orcid.org/0000-0003-0542-119X
David L MobleyDepartment of Pharmaceutical Sciences and Department of Chemistry , University of California , Irvine , California 92697 , United States.ORCID http://orcid.org/0000-0002-1083-5533
Michael K GilsonSkaggs School of Pharmacy and Pharmaceutical Sciences , University of California, San Diego , La Jolla , California 92093 , United States.ORCID http://orcid.org/0000-0002-3375-1738

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
THEORY AND MODELING OF NONCOVALENT BINDINGR01GM061300 · NIGMS · UNIVERSITY OF MD BIOTECHNOLOGY INSTITUTE · PI GILSON, MICHAEL K. · 2000 to 2021
$7.2M
The role of reorganization energy in achieving selective kinase inhibition"R01GM121505 · NIGMS · SLOAN-KETTERING INST CAN RESEARCH · PI CHODERA, JOHN DAMON · 2017 to 2021
$1.8M
Advancing predictive physical modeling through focused development of model systems to drive new modeling innovationsR01GM124270 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI MOBLEY, DAVID LOWELL · 2018 to 2021
$1.5M
NCI NIH HHS P30 CA008748NIGMS NIH HHS R01 GM061300NIGMS NIH HHS R01 GM121505NIGMS NIH HHS R01 GM124270
6 · The paper itself

Abstract

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.

Indexed as

LigandsModels, Molecularalpha-Cyclodextrinsbeta-CyclodextrinsThermodynamicsalpha-cyclodextrinalpha-Cyclodextrinsbeta-CyclodextrinsbetadexLigands

Identifiers

PMID31603667
PMCPMC7328435

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.