Biology subjects

Kapoor, J.

Publications and source records attributed to Kapoor, J..

4 recordsLinked to original sources

bioRxiv2025

Personalized real-time inference of momentary excitability from human EEG

The efficacy of transcranial magnetic stimulation (TMS) is often limited by non-adaptive protocols that disregard instantaneous brain states, potentially constraining therapeutic outcomes. Current EEG-guided approaches are hindered by their reliance on motor-evoked potentials (MEPs), which confound cortical and spinal excitability and restrict applications to the motor cortex, and a dependence on static biomarkers that cannot adapt to changing neurophysiological patterns. We introduce PRIME (Personalized Real-time Inference of Momentary Excitability), a deep learning framework that predicts cortical excitability, quantified by TMS-evoked potential (TEP) amplitude, from raw EEG signals. By targeting cortical excitability directly, PRIME enables brain state-dependent stimulation across any cortical region. PRIME incorporates transfer learning and continual adaptation to automatically identify personalized biomarkers, allowing stimulation timing to be adapted across individuals and sessions. PRIME successfully predicts cortical excitability with minimal latency, providing a computational foundation for next-generation, personalized closed-loop TMS interventions.

neuroscience↗

bioRxiv2025

Identification and Characterization of Outer Membrane Proteins and Membrane Spanning Protein Complexes in Brucella melitensis

Brucellosis (Malta fever) is a zoonotic disease that affects both humans and animals, including cattle, sheep, and goats. Brucella melitensis is the most virulent and clinically significant species in humans. It is a Gram-negative bacterium with three groups of outer membrane proteins (OMPs): minor OMPs (Group 1), and major OMPs (Groups 2 and 3). OMPs with {beta}-barrel architecture play important roles in nutrient transport, efflux, adhesion, and membrane biogenesis. Despite their importance, the structure, function, and interaction dynamics of several B. melitensis {beta}-barrel OMPs and associated protein complexes remain mostly unexplored. In this study, we conducted a comprehensive in silico analysis to characterize known outer membrane {beta}-barrel (OMBB) proteins and identify novel OMBBs in B. melitensis 16M. Proteins were modelled using five computational tools: AlphaFold 3, ESMFold, SWISS-MODEL, RoseTTAFold, and TrRosetta. Outer-membrane insertion of the novel OMBBs was confirmed using PPM 3.0, Protein GRAVY, DREAMM, and MemProtMD_Insane. Putative functions were predicted using structure- and sequence-based annotations. Sequence variation across 46 B. melitensis strains were identified and mapped onto the structural models. OMBB-associated protein complexes - the RND (Resistance-Nodulation-Division) efflux pumps, the lipopolysaccharide transport (Lpt) complex, and the {beta}-barrel assembly machinery (BAM) complex - were modelled, and protein-protein interactions (PPIs) were analyzed to confirm thermodynamically stable assemblies. This study presents a robust in silico strategy for exploring OMP architecture and provides valuable structural insights to support the development of diagnostics, targeted therapeutics, and vaccines against B. melitensis.

bioinformatics↗

bioRxiv2025

Design of a Multi-Epitope Vaccine using β-barrel Outer Membrane Proteins Identified in Chlamydia trachomatis

Chlamydia trachomatis is an obligate intracellular Gram-negative pathogen responsible for causing sexually transmitted infections (STIs) and trachoma. Current interventions, including screening and antibiotics, are limited due to the widespread nature of asymptomatic infections, and the absence of licensed vaccine exacerbates the challenge. In this study, we predicted outer membrane {beta}-barrel (OMBB) proteins and designed a multi-epitope vaccine (MEV) construct using identified proteins. We employed a consensus-based computational framework on the C. trachomatis D/UW-3/CX proteome and identified 17 OMBB proteins, including well-known Pmp family members and MOMP. Eight OMBB proteins were computationally characterized, which showed significant structural homology with known outer membrane proteins from other bacteria. Sequence-based annotation tools were used to determine their putative functions. B-cell and T-cell epitopes were predicted from the selected proteins. The MEV construct was designed using four cytotoxic T lymphocyte (CTL) epitopes and 29 helper T lymphocyte (HTL) epitopes predicted from six OMBB proteins, which were conserved across 106 C. trachomatis serovars. The vaccine was supplemented at the N-terminus with Cholera enterotoxin subunit B and PADRE sequence to enhance its immunogenicity. The MEV construct of 780 amino acids was antigenic, non-allergenic, non-toxic, and soluble. Secondary structure analysis revealed 95% random coils. The 3D structural model of MEV was generated and validated, confirming its structural reliability. Molecular docking between MEV and Toll-like receptor 4 (TLR4) revealed strong and stable binding interactions, supporting its potential to elicit a strong immune response. This study highlights OMBB proteins as promising immunogenic targets and presents a computationally designed MEV candidate for C. trachomatis infection.

bioinformatics↗

bioRxiv2025

Identification and Characterization of Novel Outer Membrane Proteins of Brachyspira pilosicoli

Brachyspira pilosicoli is a pathogenic, Gram-negative, spirochete bacterium that causes intestinal spirochetosis (IS) in birds, pigs, and humans and is distributed worldwide. This anaerobic intestinal bacterium colonizes the large intestine, potentially leading to colitis, diarrhoea, and decreased growth rate. Outer membrane proteins of Gram-negative bacteria play crucial roles in adhesion and host-pathogen interaction, helping the bacteria to evade the host immune system, and enhancing their virulence. However, B. pilosicoli outer membrane proteins are yet to be identified and characterized. Here, we report the computational discovery of 42 outer membrane {beta}-barrel (OMBB) proteins in B. pilosicoli proteome predicted using a consensus-based computational framework. {beta}-barrel architectures of the predicted proteins were confirmed by generating AlphaFold 3-based structural models. Structure-based functional annotation predicted putative functions for the identified OMBB proteins, including BamA homolog involved in folding and membrane insertion of OMPs, LptD homolog involved in transport of lipopolysaccharides into the OM, efflux pumps, transporters, enzymes, diffusion channels, and porins. Sequence variations across nine strains of B. pilosicoli were identified and mapped onto structural models, revealing that many of the variations were present on the surface exposed loop regions of the {beta}-barrel structures. Our in-silico analysis has identified 42 OMBB proteins, including homologs of BamA, LptD, TolC, TonB-dependent receptors, CsgG. Seven of these were identified as hypothetical proteins. Computational characterization of the predicted OMBB proteins offer insights into their potential roles in physiology, virulence, and disease pathogenesis, highlighting their potential for applications in diagnostics, vaccine development, or therapeutic interventions.

bioinformatics↗