題 目： Exploring preferred driver and passenger mutations in cancer genes: Applications to identify potential drug targets
The substitution of amino acid residues in a protein alters its structure, stability and function (1). In our earlier works, we have developed computational models for understanding the effect of mutations on protein folding and stability (2,3). On the other hand, somatic mutations such as missense, silent, insertions and deletions cause several diseases including the development of cancer. We have systematically analyzed the effect of these mutations at protein level in 41 different cancer types from COSMIC database on different perspectives (4): (i) preference of residues at the mutant positions, (ii) probability of substitutions, (iii) influence of neighboring residues in driver and passenger mutations and (iv) distribution of driver and passenger mutations around hotspot sites. We observed that R→H substitution is dominant in drivers followed by R→Q and R→C whereas E→K has the highest preference in passenger mutations. Further, we have developed a method for distinguishing between driver and passenger mutations in epidermal growth factor receptor in cancer, which showed an accuracy of 85% (5). The method has been utilized for identifying the potential driver and passenger mutations, which could be used for experiments. The salient features of the results will be discussed.
(1) M.M. Gromiha (2010) Protein Bioinformatics: From Sequence to Function, Elsevier/Academic Press.
(2) M.M. Gromiha and L-T. Huang (2011) Curr. Prot. Pept. Sci. 12:490-502.
(3) P. Chaudhary, A. Naganathan and M.M. Gromiha (2015) Bioinformatics 31, 2091-2097.
(4) P. Anoosha, R. Sakthivel, M.M. Gromiha (2016) Biochim. Biophys. Acta - Molecular Basis of Disease, 1862, 155-165
(5) P. Anoosha, L-T. Huang, R. Sakthivel, D. Karunagaran, M.M. Gromiha (2015) Mutation Res. 780, 24-34.
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