Evidence map›Paper›PMID 29186229›Full record

ArticlePhysical chemistry chemical physics : PCCP2017

HyRes: a coarse-grained model for multi-scale enhanced sampling of disordered protein conformations.

Xiaorong Liu, Jianhan Chen

Abstract read
In one paragraph

Article in Physical chemistry chemical physics : PCCP, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

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0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

  1. Review
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  8. Driving forces of RNA condensation revealed through coarse-grained modeling with explicit MgProceedings of the National Academy of Sciences of the United States of America · 2025
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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.

Xiaorong LiuDepartment of Chemistry, University of Massachusetts Amherst, Amherst, MA 01003, USA. jianhanc@umass.edu.
Jianhan Chen

Funding

Multi-scale enhanced sampling of disordered proteins: Admin Supplement InstrumentationR01GM114300 · NIGMS · UNIVERSITY OF MASSACHUSETTS AMHERST · PI CHEN, JIANHAN · 2016 to 2020
$1.5M
NIGMS NIH HHS R01 GM114300
6 · The paper itself

Abstract

Efficient coarse-grained (CG) models can be coupled with atomistic force fields to accelerate the sampling of atomistic energy landscapes in the multi-scale enhanced sampling (MSES) framework. This approach may be particularly suitable for generating atomistic conformational ensembles of intrinsically disordered proteins (IDPs). While MSES is relatively robust to inherent CG artifacts, achieving optimal sampling efficiency requires CG modeling to generate the local and long-range fluctuations that are largely consistent with those at the atomistic level. Here, we describe a new hybrid resolution CG model (HyRes) for MSES simulations of disordered protein states, which is specifically designed to provide semi-quantitative secondary structure propensities together with a qualitative description of long-range nonspecific interactions. The HyRes model contains an atomistic description of the backbone with intermediate resolution side chains. The secondary structure propensities are tuned by adjusting the backbone hydrogen-bonding strength and the ϕ/ψ torsion profile. The sizes and covalent geometries of the side chains are parameterized to reproduce distributions derived from atomistic simulations. Lennard-Jones parameters for sidechain beads are assigned to reproduce statistical potentials derived from the protein structural database, and then globally parameterized with nonspecific electrostatic interactions to reproduce the free energy profiles of pair wise interactions and the key conformational properties of model peptides. Application of HyRes to MSES simulations of small IDPs suggests that it is capable of driving faster structural transitions at the atomistic level and increasing the convergence rate compared to the Cα-only Gō-like models previously utilized. With further optimization, we believe that the new CG model could greatly improve the efficiency of MSES simulations of the larger and more complex IDPs frequently involved in cellular signalling and regulation.

Indexed as

Models, MolecularHydrogen BondingIntrinsically Disordered ProteinsProtein Structure, SecondaryStatic ElectricityThermodynamicsIntrinsically Disordered Proteins

Identifiers

PMID29186229
PMCPMC5729119

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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.