» Articles » PMID: 37504674

Toward a Benchmark for Markov State Models: The Folding of HP35

Overview
Specialty Chemistry
Date 2023 Jul 28
PMID 37504674
Authors
Affiliations
Soon will be listed here.
Abstract

Adopting a 300 μs long MD trajectory of the folding of villin headpiece (HP35) by D. E. Shaw Research, we recently constructed a Markov state model (MSM) based on inter-residue contacts. The model reproduces the folding time and predicts that the native basin and unfolded region consist of metastable substates that are structurally well-characterized. Recognizing the need to establish well-defined benchmark problems, we study to what extent and in what sense this MSM can be employed as a reference model. Hence, we test the robustness of the MSM by comparing it to models that use alternative combinations of features, dimensionality reduction methods, and clustering schemes. The study suggests some main characteristics of the folding of HP35 that should be reproduced by other competitive models. Moreover, the discussion reveals which parts of the MSM workflow matter most for the considered problem and illustrates the promises and pitfalls of state-based models for the interpretation of biomolecular simulations.

Citing Articles

Using pretrained graph neural networks with token mixers as geometric featurizers for conformational dynamics.

Pengmei Z, Lorpaiboon C, Guo S, Weare J, Dinner A J Chem Phys. 2025; 162(4).

PMID: 39873278 PMC: 11779506. DOI: 10.1063/5.0244453.


Using pretrained graph neural networks with token mixers as geometric featurizers for conformational dynamics.

Pengmei Z, Lorpaiboon C, Guo S, Weare J, Dinner A ArXiv. 2025; .

PMID: 39801625 PMC: 11722521.


Kemeny Constant-Based Optimization of Network Clustering Using Graph Neural Networks.

Martino S, Morado J, Li C, Lu Z, Rosta E J Phys Chem B. 2024; 128(34):8103-8115.

PMID: 39145603 PMC: 11367579. DOI: 10.1021/acs.jpcb.3c08213.


An Information Bottleneck Approach for Markov Model Construction.

Wang D, Qiu Y, Beyerle E, Huang X, Tiwary P ArXiv. 2024; .

PMID: 38947932 PMC: 11213129.


Information Bottleneck Approach for Markov Model Construction.

Wang D, Qiu Y, Beyerle E, Huang X, Tiwary P J Chem Theory Comput. 2024; 20(12):5352-5367.

PMID: 38859575 PMC: 11199095. DOI: 10.1021/acs.jctc.4c00449.