Biology subjects

Bansia, H.

Publications and source records attributed to Bansia, H..

6 recordsLinked to original sources

bioRxiv2026

Structural basis for direct NGF/TrkA blockade by an analgesic antibody

The NGF/TrkA signaling axis is a central mediator of inflammatory and chronic pain, where injury-induced NGF binds and activates TrkA on nociceptive neurons to drive peripheral sensitization and persistent pain states. Despite its therapeutic promise, targeting this pathway is limited by adverse effects of systemic NGF sequestration such as rapidly progressive osteoarthritis and poor isoform selectivity of Trk kinase inhibitors leading to off-target neurological effects. Targeting the TrkA extracellular domain (TrkAECD) offers a pathway to achieve high isoform selectivity while avoiding these complications. However, the precise structural basis for selective TrkA neutralization remains poorly understood. Monoclonal antibody (mAb) 42F5-15 inhibits TrkA-mediated signaling and increases pain threshold. Here, we report the high-resolution (2.60 [A]) cryo-EM structure of the TrkAECD in complex with the Fab region of the TrkA-neutralizing mAb 42F5-15. Structural analysis reveals that the antibody epitope overlaps the NGF-binding interface, consistent with orthosteric inhibition and distinct from previously proposed allosteric mechanisms. The epitope includes residues conserved in TrkA but divergent in TrkB and TrkC, providing a structural basis for receptor isoform selectivity. Furthermore, we demonstrate in vivo that the mAb 42F5-15 potently mitigates mechanical allodynia and nociceptive sensitization. These findings establish a structural framework for the development of selective extracellular TrkA-targeted therapies for safer, non-opioid chronic pain management.

neuroscience↗

bioRxiv2026

Structural basis of the lobster carapace blue colour mediated by an HPR protein

The chemical basis underlying the striking blue hue of live H. americanus, known as American lobster, are studied in evolutionary biology and in polyene physical chemistry. Carapace colouration is generated by the antioxidant astaxanthin bound within the carotenoprotein crustacyanin complexes. Here, we present the ex vivo structure of the most abundant -crustacyanin and {beta}-crustacyanin forms, determined respectively by cryo-electron microscopy and X-ray crystallography to a resolution of 2.75 [A]. Our structural analysis reveals -crustacyanin as an elongated arrangement of {beta}-crustacyanin heterodimers tethered by an heptatricopeptide repeat (HPR) protein. In vitro complex formation between the {beta}-crustacyanin unit with a synthetic heptatricopeptide reproduces the observed blue colour of -crustacyanin, identifying the HPR protein, in concert with crustacyanins, as contributor in tuning carapace colour. Overall, these results explain how nature adjusts the colour across the entire visible spectrum by exploiting the bathochromic shift of astaxanthin from its unbound red form ({lambda}max = 472 nm) firstly to the {beta}-crustacyanin violet bound form ({lambda}max = 591 nm), and then to the -crustacyanin bound blue form ({lambda}max = 631 nm).

biochemistry↗

bioRxiv2025

Connecting the dots: deep learning-based automated model building methods in cryo-EM

The resolution revolution in single particle cryo-electron microscopy (cryo-EM) has dramatically expanded our structural knowledge of large biomolecular complexes. While high-resolution cryo-EM density maps enable atomic model building, lower-resolution maps can still reveal secondary structures, folds, and domains. When combined with integrative modeling approaches, such data can provide meaningful insights into biomolecular structure and function. Constructing accurate models, however, remains challenging: at low resolutions it is difficult to interpret density maps features reliably, and at high resolutions traditional model-building workflows can become a time-consuming bottleneck. Deep learning, which is transforming problem-solving across scientific domains, offers powerful new tools to automate and accelerate this process. In this review, we discuss deep learning-based methods developed to automate model building in cryo-EM density maps, assessing their impact on streamlining structure determination. Recognizing that biomacromolecular structures exhibit hierarchical organization, we classify these methods according to their ability to model primary, secondary, tertiary, and quaternary structures of biomolecules. Deep learning tools for building atomic models in cryo-EM density maps are further grouped as de novo, where the model is predicted directly from features learned from the cryo-EM density, or hybrid, where it is derived by integrating structural templates with these features. We outline current limitations, including the challenge of obtaining sufficiently large and diverse datasets for training networks to model different types of biomolecules in the cryo-EM density maps, and the open challenge of constructing training sets that capture the conformational heterogeneity often observed in the cryo-EM maps. We conclude by highlighting emerging directions for this rapidly advancing field, which promise to make automated, data-driven model building an integral part of structural biology.

bioinformatics↗

bioRxiv2024

Beta-arrestin 1 mediated Src activation via Src SH3 domain revealed by cryo-electron microscopy

Beta-arrestins ({beta}arrs) are key regulators and transducers of G-protein coupled receptor signaling; however, little is known of how {beta}arrs communicate with their downstream effectors. Here, we report the first structural insights into the fundamental mechanisms driving {beta}arr-mediated signal transduction. Using cryo-electron microscopy, we elucidate how {beta}arr1 recruits and activates the non-receptor tyrosine kinase Src, the first identified signaling partner of {beta}arrs. {beta}arr1 engages Src SH3 through two distinct sites, each employing a different recognition mechanism: a polyproline motif in the N-domain and a non-proline-based interaction in the central crest region. At both sites {beta}arr1 interacts with the aromatic surface of SH3, disrupting the autoinhibited conformation of Src and directly triggering its allosteric activation. This structural evidence establishes {beta}arr1 as an active regulatory protein rather than a passive scaffold and suggests a potentially general mechanism for {beta}arr-mediated signaling across diverse effectors.

biochemistry↗

bioRxiv2020

A multifunctional Type1A DNA/RNA topoisomerase with RNA hydrolysis activity from Mycobacterium smegmatis and Mycobacterium tuberculosis

Topoisomerases maintain topological homeostasis of bacterial chromosomes by catalysing changes in DNA linking number. The resolution of RNA entanglements occurring in the cell would also require catalytic action of topoisomerases. We describe RNA topoisomerase and hydrolysis activities in DNA topoisomerase I (topo I) from mycobacteria. The interaction of topo I with mRNA, tRNA and rRNA suggested its role in some aspect of RNA metabolism; the enzyme participates in rRNA maturation via its RNA hydrolysis activity. Accumulation of rRNA precursors in a topo I knockdown strain and the rescue of rRNA processing deficiency in RNaseE knockdown cells by topo I expression, indicated the enzymes back-up support to RNases involved in rRNA processing. We demonstrate that the active site tyrosine of the enzyme mediates catalytic reactions with both DNA/RNA substrates, and RNA topoisomerase activity can follow two reaction paths in contrast to its DNA topoisomerase activity. Mutation in the canonical proton relay pathway impacts DNA topoisomerase activity while retaining activity on RNA substrates. The mycobacterial topo I thus exemplifies the resourcefulness and parsimony of biological catalysis in harnessing the limited chemical repertoire at its disposal to find common solutions to mechanistically-related challenges of phosphodiester breakage/exchange reactions in DNA and RNA that are essential for cell survival.

biochemistry↗

bioRxiv2019

Structural excavation of cryptic sites in proteins using glycol decoys: implications in drug-design

Cryptic pockets are visible in ligand-bound protein structures but are occluded in unbound structures. Utilizing these pockets in fragment-based drug-design provides an attractive option for proteins not tractable by classical binding sites. However, owing to their hidden nature, they are difficult to identify. Here, we show that small glycols find cryptic pockets on diverse set of proteins. Initial crystallography experiments serendipitously revealed the ability of ethylene glycol, a small glycol, to identify a cryptic pocket on W6A mutant of RBSX protein (RBSX-W6A). Explicit-solvent molecular dynamics (MD) simulations of RBSX-W6A with exposed-state of the cryptic pocket (ethylene glycol removed) revealed closure of the pocket reiterating that cryptic pockets in general prefer to stay in closed-state in absence of the ligands. Also, no change in the pocket was observed for simulations of RBSX-W6A with occluded-state of the cryptic pocket, suggesting that water molecules are not able to open the cryptic pocket. "Cryptic-pocket finding" potential of small glycols was then supported and generalized through additional crystallography experiments, explicit-cosolvent MD simulations, protein dataset construction and analysis. The cryptic pocket on RBSX-W6A was found again upon repeating the crystallography experiments with another small glycol, propylene glycol. Use of ethylene glycol as probe molecule in cosolvent MD simulations led to the enhanced sampling of the exposed-state of experimentally observed cryptic sites on test set of two proteins (Niemann-Pick C2, Interleukin-2). Further, analyses of protein structures with validated cryptic sites showed that ethylene glycol molecules binds to sites on proteins (G-actin, Myosin II, Bcl-xL, Glutamate receptor 2) which become apparent upon binding of biologically relevant ligands. Our study thus suggests potential application of the small glycols in experimental and computational fragment-based approaches to identify cryptic pockets in apparently undruggable and/or difficult targets, making these proteins amenable to drug-design strategies.

biophysics↗