Biology subjects

Bhattacharjee, K.

Publications and source records attributed to Bhattacharjee, K..

3 recordsLinked to original sources

bioRxiv2026

Constraint Network Analysis of Global and Local Rigidity in Wild-Type EGFR: Apo vs Gefitinib-Bound States

The mechanical rigidity-flexibility architecture of protein kinases play a critical role in regulating conformational stability and inhibitor response, yet remains insufficiently quantified for Epidermal Growth Factor Receptor (EGFR). Here, we apply Constraint Network Analysis (CNA) to systematically characterize the global and local mechanical properties of wild-type EGFR in its apo state and when bound to the ATP-competitive inhibitor gefitinib. Analysis of multiple global rigidity indices reveal a well-defined rigidity percolation transition in apo EGFR at an energy cutoff of approximately -2.0 kcal mol-1, indicative of an intrinsically stable mechanical framework. Gefitinib binding shifts this transition slightly to higher energies and sharpens the percolation behavior, accompanied by enhanced long-range mechanical coupling, increased rigidity order parameters, and reduced configurational entropy. Importantly, residue-level rigidity and percolation profiles remain largely conserved between the two states, demonstrating that ligand binding does not induce large-scale reorganization of the EGFR mechanical network. Instead, inhibition arises from subtle, localized rigidification within functionally relevant regions, consistent with stabilization of an inactive conformational ensemble. Collectively, this work establishes the first CNA-based mechanical reference state for wild-type EGFR and underscores the utility of network rigidity analysis for resolving ligand-induced effects that are structurally subtle yet mechanistically significant. This framework provides a quantitative baseline for future studies of oncogenic mutations and drug-resistant EGFR variants.

biophysics↗

bioRxiv2024

Identification of Key Regulators in Pancreatic Ductal Adenocarcinoma using Network theoretical Approach

Pancreatic Ductal Adenocarcinoma (PDAC) is a devastating disease with poor clinical outcomes, which is mainly because of delayed disease detection, resistance to chemotherapy, and lack of specific targeted therapies. The diseases development involves complex interactions among immunological, genetic, and environmental factors, yet its molecular mechanism remains elusive. A major challenge in understanding PDAC etiology lies in unraveling the genetic profiling that governs the PDAC network. To address this, we examined the gene expression profile of PDAC and compared it with that of healthy controls, identifying differentially expressed genes (DEGs). These DEGs formed the basis for constructing the PDAC protein interaction network, and their network topological properties were calculated. It was found that the PDAC network self-organizes into a scale-free fractal state with weakly hierarchical organization. Newman and Girvans algorithm (leading eigenvector (LEV) method) of community detection enumerated four communities leading to at least one motif defined by G (3,3). Our analysis revealed 33 key regulators were predominantly enriched in neuroactive ligand-receptor interaction, Cell adhesion molecules, Leukocyte transendothelial migration pathways; positive regulation of cell proliferation, positive regulation of protein kinase B signaling biological functions; G-protein beta-subunit binding, receptor binding molecular functions etc. Transcription Factor and mi-RNA of the key regulators were obtained. Recognizing the therapeutic potential and biomarker significance of PDAC Key regulators, we also identified approved drugs for specific genes. However, it is imperative to subject Key regulators to experimental validation to establish their efficacy in the context of PDAC.

systems biology↗

bioRxiv2020

Structural and dynamical heterogeneity of water trapped inside Na+-pumping KR2 rhodopsin in the dark state

Photoisomerisation in retinal leads to a channel opening in the rhodopsins that triggers translocation or pumping of an ion/proton. Crystal structures of rhodopsins contain several structurally conserved water molecules. It has been suggested that water plays an active role in facilitating the ion pumping/translocation process by acting as a lubricant in these systems. In this work, we systematically investigate the localisation, structure, dynamics and energetics of the water molecules along the channel for the resting/dark state of KR2 rhodopsin. Employing several microseconds long atomistic molecular dynamics (MD) simulation of this trans-membrane protein system, we demonstrate the presence of five distinct water containing pockets/cavities separated by gateways controlled by the protein side-chains. There exists a strong hydrogen bonded network involving these buried water molecules and functionally important key residues. We present evidence of significant structural and dynamical heterogeneity in the water molecules present in these cavities with very rare exchange between them. The exchange time-scale of these buried water with bulk has an extremely wide range from tens of nanoseconds to > 1.5s! The translational and rotational dynamics of buried water are found to be strongly dependent on the protein cavity size and local interactions with classic signature of trapped diffusion and rotational anisotropy.

biophysics↗