Evidence map›Paper›PMID 33528251›Full record

ArticleJournal of chemical theory and computation2021

Variational Method for Networkwide Analysis of Relative Ligand Binding Free Energies with Loop Closure and Experimental Constraints.

Timothy J Giese, Darrin M York

Open access · greenAbstract read
In one paragraph

Article in Journal of chemical theory and computation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
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

20 citing papers in PubMed, 35 citations in OpenAlex.

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  11. Alchemical Enhanced Sampling with Optimized Phase Space Overlap.Journal of chemical theory and computation · 2024
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  14. AmberTools.Journal of chemical information and modeling · 2023
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  15. ACES: Optimized Alchemically Enhanced Sampling.Journal of chemical theory and computation · 2023
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  18. Accurate Binding Free Energy Method from End-State MD Simulations.Journal of chemical information and modeling · 2022
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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

2 authors at 1 institution in 1 country.

Timothy J GieseLaboratory for Biomolecular Simulation Research, Center for Integrative Proteomics Research and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854-8087 United States.
Darrin M YorkLaboratory for Biomolecular Simulation Research, Center for Integrative Proteomics Research and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854-8087 United States.ORCID http://orcid.org/0000-0002-9193-7055
Rutgers, The State University of New Jersey · US

Funding

Next-generation integrated quantum force fields for biomedical applicationsR01GM107485 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI Darrin M York · 2015 to 2026
$3.8M
Supercomputing: Rutgers' Catalyst for Discovery at the Frontiers of MedicineS10OD012346 · OD · RBHS-NEW JERSEY MEDICAL SCHOOL · PI MICHELSON, LESLIE PAUL · 2015 to 2015
$1.7M
NIGMS NIH HHS R01 GM107485NIH HHS S10 OD012346
6 · The paper itself

Abstract

We describe an efficient method for the simultaneous solution of all free energies within a relative binding free-energy (RBFE) network with cycle closure and experimental/reference constraint conditions using Bennett Acceptance Ratio (BAR) and Multistate BAR (MBAR) analysis. Rather than solving the BAR or MBAR equations for each transformation independently, the simultaneous solution of all transformations are obtained by performing a constrained minimization of a global objective function. The nonlinear optimization of the objective function is subjected to affine linear constraints that couple the free energies between the network edges. The constraints are used to enforce the closure of thermodynamic cycles within the RBFE network, and to enforce an additional set of linear constraint conditions demonstrated here to be subsets of (1 or 2) experimental values. We describe details of the practical implementation of the network BAR/MBAR procedure, including use of generalized coordinates in the minimization of the free-energy objective function, propagation of bootstrap errors from those coordinates, and performance and memory optimization. In some cases it is found that use of restraints in the optimization is more practical than use of generalized coordinates for enforcing constraint conditions. The fast BARnet and MBARnet methods are used to analyze the RBFEs of six prototypical protein-ligand systems, and it is shown that enforcement of cycle closure conditions reduces the error in the predictions only modestly, and further reduction in errors can be achieved when one or two experimental RBFEs are included in the optimization procedure. These methods have been implemented into FE-ToolKit, a new free-energy analysis toolkit. The BARnet/MBARnet framework presented here opens the door to new, more efficient and robust free-energy analysis with enhanced predictive capability for drug discovery applications.

Identifiers

PMID33528251
PMCPMC8011336
OpenAlexW3126967313

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Registered trials

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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.