Bioinformatics Approaches for Understanding and Predicting Protein Folding Rates

Title: Bioinformatics Approaches for Understanding and Predicting Protein Folding Rates

Volume: 3 Issue: 1

Author(s): M. Michael Gromiha and S. Selvaraj

Affiliation:

Keywords: Folding rate, contact order, long-range order, LRO, prediction, Φ value analysis, amino acid properties, regression technique

Abstract: Understanding the relationship between amino acid sequences and protein folding rates is a challenging task similar to the protein folding problem. In this review, after a brief definition of protein folding rates, we describe various methods including contact order, long-range order, total contact distance etc. for understanding/predicting protein folding rates from three-dimensional structures of proteins. In addition, the applications of secondary structure content, length of secondary structures and solvent accessibility for understanding protein folding rates will be discussed. Further, the methods based on amino acid properties, composition, long-range contacts etc. for predicting protein folding rates from amino acid sequences will be discussed. The importance of amino acid properties, hydrophobic cluster formation and long-range contact network for understanding the transition state structures of proteins, which are related to protein folding rates, will be outlined.

Cite this article as:

Gromiha Michael M. and Selvaraj S., Bioinformatics Approaches for Understanding and Predicting Protein Folding Rates, Current Bioinformatics 2008; 3 (1) . https://dx.doi.org/10.2174/157489308783329832