Evidence map›Paper›PMID 41931571›Full record

ArticlePloS one2026

Benchmarking free energy calculations: Analysis of single and double mutations across two simulation software platforms for two protein systems.

Shivani Gupta, Qinfang Sun, Ronald M Levy

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Shivani GuptaDepartment of Chemistry, Temple University, Philadelphia, Pennsylvania, United States of America.ORCID https://orcid.org/0000-0001-5212-1996
Qinfang SunCenter for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania, United States of America.
Ronald M LevyCenter for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania, United States of America.ORCID https://orcid.org/0000-0001-8696-5177

Funding

Mapping Fitness & Free Energy Landscapes of ProteinsR35GM132090 · NIGMS · TEMPLE UNIV OF THE COMMONWEALTH · PI Ronald Levy · 2019 to 2026
$3.2M
Mechanisms of HIV fitness and drug resistance inferred from high-resolution molecular dynamics and sequence co-variation modelsR01AI178849 · NIAID · TEMPLE UNIV OF THE COMMONWEALTH · PI Ronald Levy · 2023 to 2026
$2.7M
Computer Cluster for Computational Biology and BiophysicsS10OD020095 · OD · TEMPLE UNIV OF THE COMMONWEALTH · PI LEVY, RONALD · 2015 to 2015
$442k
NIAID NIH HHS R01 AI178849NIGMS NIH HHS R35 GM132090NIH HHS S10 OD020095
6 · The paper itself

Abstract

Mutation analysis of single and double mutations of proteins including the two widely studied proteins: Staphylococcus nuclease (S. nuclease) and T4 lysozyme, provides critical insights into their stability and fitness. Furthermore, such analysis facilitates a deeper understanding of the complex interplay between a protein's sequence, structural conformation, and functional output. Free Energy Perturbation (FEP) is an alchemical, all-atom molecular dynamics based computational approach that determines the free energy change ([Formula: see text] from wild type to mutant states. Two widely adopted software platforms used for this purpose are Schrödinger and GROMACS. We have compared the results of FEP simulations for mutations using these platforms, employing the OPLS4 force field implemented in Schrödinger, and the Amber99SB-ILDN force field implemented in GROMACS for this work. For the 38 single mutants of S. nuclease, the Pearson r between the experimental and the calculated free energy change [Formula: see text] was 0.86 using Schrödinger and 0.87 using GROMACS. The reliability of the FEP method using the two software platforms with the specified force fields was further demonstrated by its performance on 24 single mutants of T4 lysozyme, yielding strong correlation between predicted and experimental [Formula: see text] values, with Pearson r of 0.80 for Schrödinger and 0.85 for GROMACS. Additionally, the computed folding free energy changes for 45 double mutations in S. nuclease [Formula: see text] using Schrödinger correlated well with both experimental measurements (Pearson r = 0.74) and previously reported GROMACS values (Pearson r = 0.71). Correspondingly, the nonadditivities [Formula: see text] of the double mutations derived using Schrödinger for these 45 double mutants of S. nuclease were also found to be in good agreement with the experimental values (Pearson r = 0.79), as well as with the previously reported GROMACS results (Pearson r = 0.61). A good correlation was also observed between computed values from Schrödinger and GROMACS, with a Pearson r of 0.71 for double mutants and 0.61 for their nonadditivities. Collectively, these findings establish the efficiency, accuracy, and reliability of Schrödinger FEP+ and GROMACS in predicting mutation-induced free energy changes in S. nuclease and T4 lysozyme. The integration of FEP based computational methodologies with experimental validation provides a framework for quantifying mutation-induced changes in protein thermostability, which can be used as a tool for protein engineering and design.

Indexed as

Micrococcal NucleaseMolecular Dynamics SimulationMuramidaseMutationSoftwareBacteriophage T4BenchmarkingThermodynamicsMicrococcal NucleaseMuramidase

Identifiers

PMID41931571
PMCPMC13048485

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.