- Computational Structural Biology
My main research interests involve application of
computational geometry and data-mining tools in structural biology. The objectives
include the understanding of evolutionary relationship between proteins, gleaning
information about active sites in proteins, discovery of novel secondary structures,
fragment-based protein modeling and new drug design based on geometric concepts.
We attempt to combine knowledge from three different fields; viz, biology,
computational geometry and data-mining.
- Physiologically Based Pharmacokinetic Modeling
Physiologically based pharmacokinetic (PBPK) models
describe how foreign substances (e.g. drugs and toxins) are processed in the body by absorption,
distribution, metabolism, and excretion (ADME). The tremendous growth of computational
power and biological knowledge create the context for innovative multi-scale modeling
solutions that can substantially improve guidance in toxicology and drug development.
In our modeling, we incorporate different scales ranging from the molecular level to the
fluid flow level to the physiological system level. Our research consists of the following
key sub-goals: (1) Molecular Level Models to predict physicochemical and biochemical
characteristics of drug molecules; (2) Fluid Flow Models to account for variability due
to blood perfusion in various sub-populations. (3) System Level Models and Integration:
We plan to model whole-body physiological level phenomena and also account for the genetic
variability in different subpopulation types (e.g. SNPs affecting transporters).
The molecular level and fluid dynamics level information will be integrated into
the physiological level model using systems and feedback control theory.
- Fermentation Modeling, monitoring and control
Our current work is based on experimental and
theoretical analysis of rifamycin production using Amycolatopsis medittriane.
The work involves development of a kinetic model for growth, product formation
and substrate uptake. Model is being developed for fermentation in a complex
media that offers multiple choices of carbon and nitrogen sources. The model
parameters are determined via a specially designed experimental plan. Further,
the model is being applied in model based optimization, monitoring and control
of the fermentation process. This is with academic as well as potential commercial
interest in the production technology for rifamycin. We have been applying several
novel optimization techniques for optimal productivity at the flask as well as
fermentor level. A similar strategy is being applied to the fermentation of
D-ribose using a transketolase deficient strain of B. subtilis. The modeling
and optimization strategy being developed is general and can be applied to any
industrial fermentation process.
- Bapat, P. M., Bhartiya, S., Venkatesh, K. V., Wangikar
P. P. (2006) A structured kinetic model to represent the utilization of multiple substrates
in complex media during rifamycin B fermentation. Biotechnol. Bioeng., 93, 779-790.
- Tendulkar, A. V., Sohoni, M. A., Ogunnaike, B. and Wangikar,
P. P. (2005) “A geometric invariant-based framework for the analysis of protein conformational
space” Bioinformatics, 21, 3622-3628
- Tendulkar, A. V., Joshi, A A., Sohoni, M. A., Wangikar,
P. P. (2004) Clustering of protein structural fragments reveals modular building block
approach of nature. J. Mol. Biol., in press.
- Tendulkar, A. V., Wangikar, P.P., Sohoni, M. A., Samant,
V. V., Mone, C. Y. (2003) “Parameterization and Classification of Protein Universe via
Geometric Techniques”. J. Mol. Biol., 334, 157-172
- Wangikar, P.P., Tendulkar, A. V., Ramya, S., Mali, D., Sarawagi,
S. (2003) “Functional Sites in Protein Families uncovered via an Automated and Objective
Graph Theoretic Approach”. J. Mol. Biol., 326, 955-978.