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Determining Optimal Coarse‐Grained Representation for Biomolecules Using Internal Cluster Validation Indexes
Author(s) -
Wu Zhenliang,
Zhang Yuwei,
Zhang John Zenghui,
Xia Kelin,
Xia Fei
Publication year - 2020
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.26070
Subject(s) - granularity , representation (politics) , maxima and minima , computer science , cluster (spacecraft) , range (aeronautics) , stability (learning theory) , algorithm , mathematics , biological system , materials science , machine learning , mathematical analysis , politics , political science , law , composite material , biology , programming language , operating system
The development of ultracoarse‐grained models for large biomolecules needs to derive the optimal number of coarse‐grained (CG) sites to represent the targets. In this work, we propose to use the statistical internal cluster validation indexes to determine the optimal number of CG sites that are optimized based on the essential dynamics coarse‐graining method. The calculated curves of Calinski‐Harabasz and Silhouette Coefficient indexes exhibit the extrema corresponding to the similar CG numbers. The calculated ratios of the optimal CG numbers to the residue numbers of fine‐grained models are in the range from 4 to 2. The comparison of the stability of index results indicates that Calinski‐Harabasz index is the better choice to determine the optimal CG representation in coarse‐graining. © 2019 Wiley Periodicals, Inc.