Evidence map›Paper›PMID 31714766›Full record

ArticleJournal of chemical theory and computation2020

ff19SB: Amino-Acid-Specific Protein Backbone Parameters Trained against Quantum Mechanics Energy Surfaces in Solution.

Chuan Tian, Koushik Kasavajhala, Kellon A A Belfon, Lauren Raguette, He Huang, Angela N Migues, John Bickel, Yuzhang Wang, Jorge Pincay, Qin Wu and 1 more

Open access · greenAbstract read
In one paragraph

Article in Journal of chemical theory and computation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,267 papers.

0numbers the graph read from it
0cells of the map it votes in
1,267citing papers in PubMed
34.5field-weighted citation impact, top 1% 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

1,267 citing papers in PubMed, 2,186 citations in OpenAlex.

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  19. Antibody-drug conjugate engineering: from design to efficacy and safety.Signal transduction and targeted therapy · 2026
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1,207 more citing papers are in PubMed but not listed here.

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

11 authors at 2 institutions in 1 country.

Chuan TianDepartment of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.ORCID http://orcid.org/0000-0002-3518-7237
Koushik KasavajhalaDepartment of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.
Kellon A A BelfonDepartment of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.
Lauren RaguetteDepartment of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.
He HuangDepartment of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.ORCID http://orcid.org/0000-0002-2299-5243
Angela N MiguesLaufer Center for Physical and Quantitative Biology , Stony Brook University , Stony Brook , New York 11794 , United States.
John BickelDepartment of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.
Yuzhang WangDepartment of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.
Jorge PincayDepartment of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.
Qin WuCenter for Functional Nanomaterials , Brookhaven National Laboratory , Upton , New York 11973 , United States.ORCID http://orcid.org/0000-0001-6350-6672
Carlos SimmerlingDepartment of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.ORCID http://orcid.org/0000-0002-7252-4730
Stony Brook University · USBrookhaven National Laboratory · US

Funding

Characterization of a potential allosteric target in the dimer interface of retroviral proteasesF31GM123767 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI BELFON, KELLON ASIM AUGUSTINE · 2018 to 2019
$71k
NIGMS NIH HHS F31 GM123767
6 · The paper itself

Abstract

Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the molecular mechanics (MM) force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. However, the overall quality of the FF, such as our previously published ff99SB and ff14SB, can be limited by assumptions that were made years ago. In the updated model presented here (ff19SB), we have significantly improved the backbone profiles for all 20 amino acids. We fit coupled φ/ψ parameters using 2D φ/ψ conformational scans for multiple amino acids, using as reference data the entire 2D quantum mechanics (QM) energy surface. We address the polarization inconsistency during dihedral parameter fitting by using both QM and MM in aqueous solution. Finally, we examine possible dependency of the backbone fitting on side chain rotamer. To extensively validate ff19SB parameters, and to compare to results using other Amber models, we have performed a total of ∼5 ms MD simulations in explicit solvent. Our results show that after amino-acid-specific training against QM data with solvent polarization, ff19SB not only reproduces the differences in amino-acid-specific Protein Data Bank (PDB) Ramachandran maps better but also shows significantly improved capability to differentiate amino-acid-dependent properties such as helical propensities. We also conclude that an inherent underestimation of helicity is present in ff14SB, which is (inexactly) compensated for by an increase in helical content driven by the TIP3P bias toward overly compact structures. In summary, ff19SB, when combined with a more accurate water model such as OPC, should have better predictive power for modeling sequence-specific behavior, protein mutations, and also rational protein design. Of the explicit water models tested here, we recommend use of OPC with ff19SB.

Indexed as

Amino AcidsMolecular Dynamics SimulationPeptidesProtein ConformationProteinsProtein StabilityQuantum TheoryThermodynamicsWaterAmino AcidsPeptidesProteinsWater

Identifiers

PMID31714766
PMCPMC13071887
OpenAlexW2989052455

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.