Research Interest

Genome-scale community metabolic modelling of Human gut microbiota:

Metabolic Flux Analysis (MFA) is an important method for the quantitative estimation of intracellular metabolic flows through metabolic pathways in a variety of cellular metabolism of relevance to medicine and biotechnology. Our current efforts are to identify the altered metabolic profile of the human gut microbiota in different diseases. To achieve this we are constructing the genome-scale metabolic model of human gut microbiota and allowing them to grow in a community. This community model will explore the metabolic interplay and its impact on the biochemical pathway of target cell/tissue.

Tissue/cell-specific Genome-scale metabolic modelling:

Tissue-specific genome-scale modelling is a computational approach used to understand the metabolic behaviour of specific tissues within an organism. It involves tailoring a generic genome-scale metabolic model (GEM) to reflect the metabolic network specific to a given tissue, integrating tissue-specific data such as gene expression, proteomics, and metabolomics. These models can predict metabolic fluxes, understand disease mechanisms, and identify potential therapeutic targets. In our study, we aim to reconstruct the condition-specific model of type 2 diabetic beta cells and compare metabolic alterations with respect to healthy cells. 

Differential gene expression analysis :

Differential gene expression analysis (DGEA) is a key method used to identify genes that show significant differences in expression levels between two or more conditions, such as healthy versus diseased states, different treatments, and various time points. This analysis is crucial for understanding biological responses and uncovering biomarkers or therapeutic targets. 

Protein Dynamics:

We focus on understanding the relationship between protein structure, function, and dynamics. Research is focused on two major sub-groups: 1) molecular modeling of enzyme-substrate / enzyme-inhibitor interactions and 2) structure-based drug discovery. Studies are performed using computer simulation methods ranging from molecular dynamics simulations, Monte Carlo simulations, and Brownian dynamics simulations. General properties that we address include changes in protein structure and dynamics upon binding inhibitors and with mutations, ligand binding affinity and specificity, and bound water structure.

Beura et al., Journal of Molecular Structure, 2022

Beura et al., Journal of Molecular Structure, 2020

Beura et al., Journal of Biomolecular Structure and Dynamics, 2020