Biology subjects

Kumawat, A.

Publications and source records attributed to Kumawat, A..

5 recordsLinked to original sources

bioRxiv2026

Mapping binding landscape of allosteric inhibitor G6PDi-1 on human G6PD

Targeting the oxidative pentose phosphate pathway by inhibiting glucose-6-phosphate dehydrogenase (G6PD), is a promising anticancer strategy, yet clinically useful inhibitors remain unavailable. A key limitation is the lack of molecular insight into how allosteric and non-competitive inhibitors perturb enzymatic activity, limiting rational optimization. Here, we investigated the mechanism of G6PDi-1, a potent, reversible, non-competitive G6PD inhibitor, by combining biochemical assays with molecular dynamics simulations, Markov state model and MM/PBSA binding energy calculations. Experimentally, G6PDi-1 reduced active dimer formation in hepatoblastoma HepG2 cells and increased the inactive monomer fraction, linking inhibition to disrupted oligomerization. Computationally, we identified multiple sites on the enzyme surface, with preferential binding at dimer interface that sterically blocks oligomerization. Importantly, additional distal sites showed enhanced inter-residue correlations, suggesting secondary allosteric effects that shift G6PD toward monomeric states less competent for oligomerization. These findings provide a molecular basis for structure-based development of improved strategies for G6PD inhibition suited for cancer therapy.

biophysics↗

bioRxiv2025

Structural bases for Nuclear Factor 1-X activation and DNA recognition. Prototypic insight into the NFI transcription factor family

Nuclear Factor I (NFI) proteins were first identified in adenovirus DNA replication and later as regulators of gene transcription, stem cell proliferation, and differentiation. They play key roles in development, cancer and congenital disorders. Within the NFI family, NFI-X is critical for neural stem cell biology, hematopoiesis, muscle development, muscular dystrophies and oncogenesis. Here, we present the first structural characterization of the NFI transcription factor, NFI-X, both alone and bound to its consensus palindromic DNA site. Our analyses reveal a novel, MH1-like fold within NFI-X DNA-binding domain (DBD) and identify crucial structural determinants for activity, such as a Zn{superscript 2} binding site, dimeric assembly, activation mechanism and DNA-binding specificity. Given the >95% sequence identity within the NFI DBDs, our structural data are prototypic for the entire family; a NFI Rosetta Stone that allows decoding a wealth of biochemical and functional data and provides a precise target for drug design in a wider disease context.

biochemistry↗

bioRxiv2024

Molecular Insights into the Rescue Mechanism of an hERG Activator Against Severe LQT2 Mutations.

BackgroundMutations in the HERG potassium channel are a major cause of long QT syndrome type 2 (LQT2), which can lead to sudden cardiac death. The HERG channel plays a critical role in the repolarization of the myocardial action potential, and loss-of-function mutations prolong cardiac repolarization. MethodsIn this study, we investigated the efficacy and underlying molecular mechanism of ICA-105574, an HERG activator, in shortening the duration of cardiac repolarization in severe LQT2 variants. We characterized the efficacy of ICA-105574 in vivo, using an animal model to assess its ability to shorten the QT interval and in vitro, in cellular models mimicking severe HERG channel mutations (A561V, G628S, and L779P) to evaluate its impact in enhancing IKr current. Additionally, molecular dynamics simulations were used to investigate the molecular mechanism of ICA-105574 action. ResultsIn vivo, ICA-105574 significantly shortened the QT interval. LQT2 mutations drastically reduced IKr amplitude and suppressed tail currents in cellular models. ICA-105574 restored IKr in A561V and G628S. Finally, in silico data showed that ICA-105574 stabilizes a pattern of interactions similar to gain-of-function SQT1 mutations and can reverse the G628S modifications, through an allosteric network linking the binding site to the selectivity filter and the S5P turret helix, thereby restoring its K+ ion permeability. ConclusionsOur results support the development of HERG activators like ICA-105574 as promising pharmacological molecules against some severe LQT2 mutations and suggest that molecular dynamics simulations can be used to test the ability of molecules to modulate HERG function in silico, paving the way for the rational design of new HERG activators.

biophysics↗

bioRxiv2023

Molecular Mechanism of Regulation of RhoA GTPase by Phosphorylation of RhoGDI

Rho-specific guanine dissociation inhibitors (RhoGDIs) play a crucial role in the regulation of Rho family GTPases. They act as negative regulators that prevent the activation of Rho GTPases by forming complexes with the inactive GDP-bound state of GTPase. Release of Rho GTPase from the RhoGDI-bound complex is necessary for Rho GTPase activation. Biochemical studies provide evidence of a "phosphorylation code", where phosphorylation of some specific residues of RhoGDI selectively releases its GTPase partner (RhoA, Rac1, Cdc42 etc.). This work attempts to understand the molecular mechanism behind this phosphorylation code. Using several microseconds long atomistic molecular dynamics (MD) simulations of the wild-type and phosphorylated states of the RhoA-RhoGDI complex, we propose a molecular-interaction-based mechanistic model for the dissociation of the complex. Phosphorylation induces major structural changes, particularly in the positively charged polybasic region (PBR) of RhoA and the negatively charged N-terminal region of RhoGDI that contribute most to the binding affinity. MM-PBSA binding free energy calculations show a significant weakening of interaction on phosphorylation at the RhoA-specific site of RhoGDI. In contrast, phosphorylation at a Rac1-specific site leads to the strengthening of the interaction confirming the presence of a phosphorylation code. RhoA-specific phosphorylation leads to a reduction in the number of contacts between the PBR of RhoA and the N-terminal region of RhoGDI, which manifests reduction of the binding affinity. Using hydrogen bond occupancy analysis and energetic perturbation network, we propose a mechanistic model for the allosteric response, i.e., long range signal propagation from the site of phosphorylation to the PBR and buried geranylgeranyl group in the form of rearrangement and rewiring of hydrogen bonds and salt bridges. Our results highlight the crucial role of specific electrostatic interactions in manifestation of the phosphorylation code.

biophysics↗

bioRxiv2021

Searching sequence databases for functional homologs using profile HMMs: how to set bit score thresholds?

MotivationUniProt and BFD databases together have 2.5 billion protein sequences. A large majority of these proteins have been electronically annotated. Automated annotation pipelines, vis-a-vis manual curation, have the advantage of scale and speed but are fraught with relatively higher error rates. This is because sequence homology does not necessarily translate to functional homology, molecular function specification is hierarchic and not all functional families have the same amount of experimental data that one can exploit for annotation. Consequently, customization of annotation workflow is inevitable to minimize annotation errors. ResultsWe discuss possible ways of customizing the search of sequence databases for functional homologs using profile HMMs. Choosing an optimal bit score threshold is a critical step in the application of HMMs, which is illustrated using four Case Studies; the single domain nucleotide sugar 6-dehydrogenase and lysozyme-C families, and SH3 and GT-A domains which are typically found as a part of multi-domain proteins. We also discuss the limitations of using profile HMMs for functional annotation and suggests some possible ways to partially overcome such limitations. Supplementary informationSupplementary_material containing Figures S1-S7 and Tables S1 and S2 Supplementary_dataset.xlsx

bioinformatics↗