Journal ArticleDOI
Empirical scale of side-chain conformational entropy in protein folding.
TLDR
An empirical scale for the loss of side-chain conformational entropy during protein folding is obtained and the stability of site-directed mutations is discussed in terms of conformational Entropy.About:
This article is published in Journal of Molecular Biology.The article was published on 1993-06-05. It has received 259 citations till now. The article focuses on the topics: Conformational entropy & Contact order.read more
Citations
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Journal ArticleDOI
The proteasome - paradigm of a self-compartmentalizing protease
TL;DR: The work of one of us (W. B.) was supported by a grant of the Human Frontiers Science Program and the wish to thank Drs.
Journal ArticleDOI
Principles of protein folding--a perspective from simple exact models.
Ken A. Dill,Sarina Bromberg,Kaizhi Yue,Klaus M. Fiebig,David P. Yee,Paul Thomas,Hue Sun Chan +6 more
TL;DR: These studies suggest the possibility of creating “foldable” chain molecules other than proteins, and can account for the properties that characterize protein folding: two‐state cooperativity, secondary and tertiary structures, and multistage folding kinetics.
Journal ArticleDOI
Coupling of local folding to site-specific binding of proteins to DNA
Spolar Rs,Record Mt +1 more
TL;DR: Estimates of the number of residues that fold on binding obtained from this analysis agree with structural data, and structural comparisons indicate that these local folding transitions create key parts of the protein-DNA interface.
Journal ArticleDOI
Insights into Protein-Protein Binding by Binding Free Energy Calculation and Free Energy Decomposition for the Ras-Raf and Ras-RalGDS Complexes
TL;DR: This study investigates the capability of the molecular mechanics-generalized Born surface area (GBSA) approach to estimate absolute binding free energies for the protein-protein complexes and finds hotspot residues experience a significantly larger-than-average decrease in local fluctuations upon complex formation.
Journal ArticleDOI
Knowledge-based scoring function to predict protein-ligand interactions
TL;DR: The development and validation of a new knowledge-based scoring function (DrugScore) to describe the binding geometry of ligands in proteins is presented and is superior to the "chemical scoring" implemented into this tool, while comparable results are obtained using the "energy scoring" in DOCK.
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