Protein flexibility, manifested by local and global changes in conformation, is an essential component of protein function. Conformational flexibility is involved in fundamental biological activities, such as intermolecular interactions, and in a variety of human diseases, such as transmissible encephalopathies and synucleinopathies. Our long-term goal is to incorporate the dynamic properties of proteins into computational analyses of functional sites and disease-related conformational transitions. However, progress in the important area of protein flexibility has long been hampered by the absence of reliable and efficient computational methodology that could be used to perform systematic large-scale studies of flexible protein segments. The main goal of this proposal is to circumvent this problem by developing accurate high-throughput computational methods for predicting dynamic properties of protein segments using their sequence properties. Protein flexibility can be classified into two broad categories: (1) disordered flexibility observed in disordered segments that completely lack detectable structure and (2) ordered flexibility observed in segments that undergo conformational transition from one detectable ordered structure to another. We will address the least studied category of ordered flexibility. First, we will use a combination of supervised pattern-recognition and statistical methods to develop high-throughput methodology that can be used to quantify and predict ordered conformational flexibility from local sequence and has a low rate of false positive predictions. Second, we will create an independent test set of proteins that can be used to assess ? the performance of computational methods designed for the analysis of conformational changes in proteins. Computational methodology developed as an outcome of this proposal will facilitate progress in many areas of basic and applied protein research directly related to human health, including protein structure modeling, studies of protein functional sites and a variety of protein flexibility-related human diseases. ? ?
| Kuznetsov, Igor B (2008) Ordered conformational change in the protein backbone: prediction of conformationally variable positions from sequence and low-resolution structural data. Proteins 72:74-87 |
| Gou, Zhenkun; Kuznetsov, Igor B (2008) On the Accuracy of Sequence-Based Computational Inference of Protein Residues Involved in Interactions with DNA. Trends Appl Sci Res 3:285-291 |
| Hwang, Seungwoo; Gou, Zhenkun; Kuznetsov, Igor B (2007) DP-Bind: a web server for sequence-based prediction of DNA-binding residues in DNA-binding proteins. Bioinformatics 23:634-6 |
