Current Synthetic and Systems Biology
Open Access

Structural mapping of protein network aids us to unleash their evolutionary links and to design accurate drugs

International Conference on Synthetic Biology

September 28-29, 2015 Houston, USA

Ashish Runthala

Birla Institute of Technology and Science, India

Posters-Accepted Abstracts: Curr Synthetic Sys Biol

Abstract :

Functional annotation of a protein sequence and that too precisely for its every single encoded domain is challenging. As the number of protein sequences is rapidly growing, the overwhelming count of proteins can only be annotated computationally, although a high accuracy is always expected. Decade is gone when the protein sequence could be annotated through the statistical scoring of its similarity with the existing database of functionally understood protein sequences. A protein structure is naturally too robust over its primary sequence information. To decode the functional attributes of a protein, the task of modeling, assessing and comparing a best predicted protein model with the functionally understood protein or domain conformations becomes a promising exercise. Majority of these protein structure prediction algorithms fail to construct the accurate near-native model with the correct structural topology of each of the encoded domain and with an acceptable mutual orientation of these domains in the overall protein model. The improved protein modeling algorithm is hereby first presented to bridge the sequence-structure gap and the challenge of predicting the functional detail of a protein sequence is further resolved. Smooth mapping of the evolutionary link and biochemical network of protein sequences in a cell is thereby emphasized to develop the best set of composite drugs for effectively curing even the currently unresolved deadly diseases.

Biography :

Email: ashishr@pilani.bits-pilani.ac.in