Premium
A new computational model for protein folding based on atomic solvation
Author(s) -
Wang Yuhong,
Zhang Hui,
Scott Robert A.
Publication year - 1995
Publication title -
protein science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.353
H-Index - 175
eISSN - 1469-896X
pISSN - 0961-8368
DOI - 10.1002/pro.5560040714
Subject(s) - solvation , implicit solvation , globular protein , folding (dsp implementation) , protein folding , native state , chemical physics , protein structure prediction , set (abstract data type) , chemistry , computational chemistry , protein structure , computer science , statistical physics , physics , biological system , crystallography , molecule , biology , biochemistry , engineering , programming language , electrical engineering , organic chemistry
A new model for calculating the solvation energy of proteins is developed and tested for its ability to identify the native conformation as the global energy minimum among a group of thousands of computationally generated compact non‐native conformations for a series of globular proteins. In the model (called the WZS model), solvation preferences for a set of 17 chemically derived molecular fragments of the 20 amino acids are learned by a training algorithm based on maximizing the solvation energy difference between native and non‐native conformations for a training set of proteins. The performance of the WZS model confirms the success of this learning approach; the WZS model misrecognizes (as more stable than native) only 7 of 8,200 non‐native structures. Possible applications of this model to the prediction of protein structure from sequence are discussed.