Structural Bioinformatics and Enzyme Engineering
...............................
Structural Bioinformatics
...............................
A Residue Interaction Graph
Protein structures can be studied as complex networks of interacting amino acids. I have studied proteins of different structural classes from the network perspective. The results of this study indicate that proteins, regardless of their structural class, show small-world network property. I discovered that contrary to most other complex networks protein contact networks are of assortative nature. Moreover I was able to associate the observed assortative nature to kinetics of folding. I am pondering on the possible implications of these results and the questions that they pose.
Ganesh Bagler and Somdatta Sinha, “Assortative mixing in protein Contact Networks and protein folding kinetics”, Bioinformatics, 23, 14, 1760—1767 (2007). Bioinformatics | PDF | arxiv.org/abs/0711.2723
Ganesh Bagler and Somdatta Sinha, "Network properties of protein Structures", Physica A, 346, 27-33 (2005). Physica A | arXiv:q-bio.MN/0408009
Enzyme Engineering
We recently published a research reporting graph theoretical studies of a plant Cu,Zn SOD structure and engineering a thermostable enzyme by mutagenesis that were predicted by computational modeling. This study suggests the importance of increased monomer to dimer ratio to enhance thermostability of Cu,Zn SOD, wherein mutation of a free cysteine (Cys-95) played a central role. The results were supported by in silico as well as other biochemical parameters. The engineered SOD can be used for developing transgenic plants tolerant to abiotic stresses, particularly for high temperature and drought stress, where the temperature can rise to as high as 50–60°C.
Arun Kumar, Som Dutt, Ganesh Bagler, Paramvir Singh Ahuja and Sanjay Kumar, "Engineering a thermo-stable superoxide dismutase functional at sub-zero to 50°C, which also tolerates autoclaving." Scientific Reports (Nature Publication Group), 2, 387 (2012). DOI:10.1038/srep00387
Residue Interaction Graphs (RIG)
Proteins are important biomolecules as they are the facilitators of cellular functions. They can be modeled as complex adaptive systems, whose structure-function relationship and the process of folding pose fundamental problems of immense application value.
Structure-Function Relation
The structural details of proteins have evolved for their functions. Identifying structural keys could lead to answers to proteins' functions. While there are many ways of characterizing and enumerating the structure, coarse-grained modeling is preferred as large amount of structural data available could be processed with this paradigm. It has been recently shown that for many pertinent questions that one may ask about proteins' structure, function and kinetics, fine-grained models may not be needed. Interestingly, it has also observed that the signature/imprint of the dynamical events in the folding process may be left on the native-state structures, which could be decrypted with the help of coarse-grained models. I am interested in studying structure, function, dynamics, kinetics of proteins and eventually, design of macromolecules of desired properties.
Protein Folding: Statistical Force-Fields Design
The idea of physics-based as well as knowledge-based or statistical force-fields has been extensively used for creation of many potentials for ab initio protein structure prediction. With my present mentor, I have been working on the statistical force-fields design based on coarse-grained models of protein structures, and construction of novel potentials with the help of a computational framework.
Michael Lappe, Ganesh Bagler, Ioannis Fillipis, Henning Stehr, Jose M Duarte, and Sathyapriya Rajagopal, “Designing evolvable libraries using multi-body potentials”, Current Opinion in Biotechnology, 20, 437—446 (2009).