Biology subjects

Bahadur, R. P.

Publications and source records attributed to Bahadur, R. P..

7 recordsLinked to original sources

bioRxiv2026

Sequence architecture of RNA reveals key molecular signatures driving RNA phase separation

Biomolecular condensates are dynamic membraneless assemblies that organize various cellular processes through liquid-liquid phase separation (LLPS). RNA is an active regulator of biomolecular condensates and influence their formation through sequence-encoded features. Despite its established role in condensate formation, no computational framework exists to identify underlying signatures to predict LLPS-associated RNAs. We develop an interpretable hybrid framework to distinguish reviewed, experimentally supported LLPS-associated RNAs from background RNAs. We uncover biologically meaningful sequence properties associated with condensate participation. Each RNA is represented by 167 handcrafted descriptors capturing composition, k-mer usage, sequence complexity, repeat organization and dinucleotide autocorrelation together with 640-dimensional contextual embeddings from RNA-FM. These representations are integrated through cross-validated stacking with neural-network meta-learner. The framework achieves an AUC-ROC of 0.935, AUC-PR of 0.944 and MCC of 0.782. Feature statistics, ablation analysis and SHAP interpretation reveal a distributed sequence architecture dominated by altered local k-mer usage with additional contributions from low-complexity burden, repeat-associated organization and long-range dinucleotide pattern. Biological case studies including MALAT1 and TMPO-AS1 further connect these patterns with experimentally characterized modes of multivalent RNA-protein assembly. Together, the results show how interpretable machine learning can move beyond prediction to identify sequence features that generate mechanistic hypotheses for RNA-mediated condensation.

bioinformatics↗

bioRxiv2026

Competitive Inhibition of the Nipah Virus Matrix Protein by Conivaptan: From Binding Pocket Dynamics to Protein-Membrane Interactions

The recurrent outbreaks of Nipah virus since its first emergence have intensified efforts to identify effective antiviral therapeutics. The matrix protein is a key structural protein that maintains virion architecture and plays a crucial role in anchoring the virus to the host plasma membrane. Binding of phosphatidylinositol-4,5-bisphosphate (PIP2) to the matrix protein promotes conformational changes that facilitate membrane association and initiate viral assembly. Therefore, an effective small-molecule inhibitor should not only compete with PIP2 for binding to the Nipah virus matrix protein (NiVM) but also disrupt its interaction with the host membrane. Using virtual screening of FDA-approved drugs combined with ensemble docking, we identified Conivaptan as a potential inhibitor of the Nipah virus matrix protein. The multivalent interactions of Conivaptan establish stable binding within the PIP2-binding pocket while simultaneously rewiring protein-membrane interactions. In the presence of PIP2, NiVM anchors to the membrane through multiple charged residues, resulting in pronounced local bilayer deformation, an early signature of membrane remodeling. In contrast, Conivaptan binding weakens membrane anchoring and preserves a more ordered and compact bilayer, thereby suppressing membrane deformation. Together, these findings identify Conivaptan as a promising repurposable inhibitor of the Nipah virus matrix protein and provide a mechanistic framework for targeting virus-membrane interactions during viral assembly.

biophysics↗

bioRxiv2026

Deciphering the role of intrinsically disordered regions of FUS in recognizing U1 snRNA

Fused in Sarcoma (FUS) is an RNA-binding protein associated with neurodegenerative disorders such as amyotrophic lateral sclerosis and frontotemporal dementia. Along with its structured RNA recognition motif, FUS contains two intrinsically disordered regions (IDRs) that play important roles in RNA recognition. However, structural mechanism and dynamics of these IDRs in recognizing RNA remain elusive. We have used molecular dynamics simulations to investigate the structure and dynamics of the two IDRs, flanking the RRM domain of human FUS, in both Apo and U1 snRNA-bound states. Comparison of structural parameters and molecular interactions reveals that RNA binding stabilizes the IDRs and reduces their conformational flexibility through reorganization of intra-protein contacts and correlated movements. RNA binding also causes rearrangement of backbone dihedral angles of the IDRs and limits the formation of secondary structures such as -helices and 310 helices. Interestingly, the two IDRs exhibit distinct modes of RNA recognition. The N-terminal IDR interacts mainly with the nucleotides located near the terminal regions of the stem-loop snRNA. On the other hand, the C-terminal IDR preferentially associates with the central double-stranded region through extensive interactions with the minor groove of the snRNA. Even within IDRs, we identify specific residues that associate with the snRNA more frequently than others by forming persistent hydrogen bonds. Overall, our findings suggest that the flanking disordered regions of FUS are not merely flexible linkers, but actively participate in RNA recognition through distinct interaction mechanisms. These results provide molecular-level insights into the functional roles of IDRs in recognizing stem-loop RNA.

biophysics↗

bioRxiv2026

Deciphering conformational preferences of RNA in protein-RNA recognition

Conformational plasticity of RNAs plays important roles in recognizing RNA-binding proteins, and is often modulated by their binding partners. Here, we investigate RNA conformational preferences in a non-redundant dataset of 263 protein-RNA complexes to characterize the structural landscape associated with protein recognition. RNA dinucleotide segments are analyzed using seven backbone torsion angles ({delta}1, {varepsilon}1, {zeta}1, 2, {beta}2, {gamma}2, and {delta}2), two glycosidic torsion angles ({chi}1 and {chi}2) and the pseudo-torsion angle . Focusing on dinucleotide steps present in both interface and non-interface regions, we performed density-based clustering using selected backbone torsion angles to identify recurrent conformational states. We identify 28 distinct RNA dinucleotide conformers containing at least ten members each. Among these, eight conformers represent previously unreported nucleotide conformers (NtCs), including the transitional and the non-canonical states AB06, AB07, BB21, BB22, OP32, OP33, IC08 and IC09. Several of these conformers are preferentially enriched at protein-binding interfaces, suggesting their involvement in local conformational adaptation during protein-RNA recognition. The newly identified conformers span transitional A-B geometries, distorted B-like states, open conformations and compact intercalated structures, highlighting the remarkable structural plasticity of RNA in ribonucleoprotein complexes. Overall, this study expands the current understanding of RNA conformational space and provides a refined RNA dinucleotide conformer library for protein-RNA complexes. These findings will facilitate the identification of novel RNA structural motifs and improved RNA structural modeling, docking protein-RNA complexes and deep learning-based prediction frameworks for describing RNA tertiary structures.

biophysics↗

bioRxiv2026

Decoding Mutually Induced Conformational Changes in Non-Canonical Recognition of U1 SL4 snRNA by ULD of SF3A1 during Early Spliceosome Assembly

A crucial step in early spliceosome assembly is the interaction between splicing factor 3A1 (SF3A1) of U2 snRNP and stem-loop 4 (SL4) of U1 snRNA. This interaction facilitates the spatial alignment of the 5' and the 3' splice sites, leading to the formation of the pre-spliceosomal A complex. In this study, we investigate the structural and dynamic basis of non-canonical recognition between ubiquitin-like domain (ULD) of SF3A1 and SL4 of U1 snRNA. Extensive all-atom molecular dynamics simulations reveal a dual recognition mechanism involving sequence-specific interactions mediated by the C-terminal RGGR motif and structural recognition governed by the UUCG tetraloop of SL4 snRNA. The RGGR motif primarily engages the duplex region of the snRNA, whereas the stem-loop nucleotides interact with the globular region of the ULD. Mutations of key residues R788 and R791 result in a significant loss of protein-RNA interactions, as reflected in the reduced binding affinities and altered conformational stability. Nucleotides C6 to C9 in the duplex region, stabilized by strong base-pairing and backbone-mediated interactions with SF3A1, exhibit constrained torsional distributions and minimal sensitivity to mutation. In contrast, nucleotides G10 to C15 in the tetraloop exhibit broader torsional distributions with moderate occupancy, consistent with weaker base-pairing but stronger protein-RNA interactions. Mutations significantly alter torsional distribution, enabling the nucleotides to adopt alternate conformations that preserve interactions with the globular domain of SF3A1. These findings provide a mechanistic insight into non-canonical RNA recognition and highlight the role of coupled sequence and structural determinants in stabilizing early spliceosomal assembly.

biophysics↗

bioRxiv2021

NCodR: A multi-class SVM classification to distinguish between non-coding RNAs in Viridiplantae

Non-coding RNAs (ncRNAs) are major players in the regulation of gene expression. This study analyses seven classes of ncRNAs in plants using sequence and secondary structure-based RNA folding measures. We observe distinct regions in the distribution of AU content along with overlapping regions for different ncRNA classes. Additionally, we find similar averages for minimum folding energy index across various ncRNAs classes except for pre-miRNAs and lncRNAs. Various RNA folding measures show similar trends among the different ncRNA classes except for pre-miRNAs and lncRNAs. We observe different k-mer repeat signatures of length three among various ncRNA classes. However, in pre-miRs and lncRNAs, a diffuse pattern of k-mers is observed. Using these attributes, we train eight different classifiers to discriminate various ncRNA classes in plants. Support-vector machines employing radial basis function show the highest accuracy (average F1 of ~91%) in discriminating ncRNAs, and the classifier is implemented as a web server, NCodR.

plant biology↗

bioRxiv2018

Elucidating the functional role of predicted miRNAs in post-transcriptional gene regulation along with symbiosis in Medicago truncatula

Non-coding RNAs (ncRNAs) are found to be important regulator of gene expression because of their ability to modulate post-transcriptional processes. microRNAs are small ncRNAs which inhibit translational and post-transcriptional processes whereas long ncRNAs are found to regulate both transcriptional and post-transcriptional gene expression. Medicago truncatula is a well-known model plant for studying legume biology and is also used as a forage crop. In spite of its importance in nitrogen fixation and soil fertility improvement, little information is available about Medicago ncRNAs that play important role in symbiosis. To understand the role of Medicago ncRNAs in symbiosis and regulation of transcription factors, we have identified novel miRNAs and tried to establish an interaction model with their targets. 149 novel miRNAs are predicted along with their 770 target proteins. We have shown that 51 of these novel miRNAs are targeting 282 lncRNAs. We have analyzed the interactions between miRNAs and their target mRNAs as well as their targets on lncRNAs. Role of Medicago miRNAs in the regulation of various transcription factors were also elucidated. Knowledge gained from this study will have a positive impact on the nitrogen fixing ability of this important model plant, which in turn will improve the soil fertility.

genomics↗