Biology subjects

Vijayan, R.

Publications and source records attributed to Vijayan, R..

7 recordsLinked to original sources

bioRxiv2026

NON-NUCLEOSIDE REVERSE TRANSCRIPTASE INHIBITORS BLOCK THE INCORPORATION OF VIRAL GLYCOPROTEINS INTO HIV-1 VIRIONS

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are a key component of antiretroviral therapy that block reverse transcription in newly infected cells. NNRTIs have also been reported to induce premature activation of the HIV-1 protease in virus-producing cells, an activity that has been optimized in a class of NNRTIs known as targeted activators of cell kill (TACK). In this study, we used the TACK compound Pyr01 to investigate how NNRTI-induced premature protease activation affects virion composition and infectivity. We found that Pyr01 treatment markedly reduces the incorporation of the HIV-1 envelope (Env) glycoprotein into virus particles in an Env cytoplasmic tail-independent manner. Pyr01 treatment also disrupts the virion incorporation of foreign viral glycoproteins and causes a substantial loss of the viral enzymes from virions. Virions produced from NNRTI-treated cells exhibit reduced membrane order. The defect in viral glycoprotein incorporation requires an active protease, implicating premature protease-mediated disruption of the Gag lattice and resulting changes in membrane properties as the primary mechanism underlying these effects. These findings reveal that NNRTI-induced premature protease activation during virus assembly fundamentally changes the protein composition and membrane order of HIV-1 virions to markedly reduce particle infectivity. These results have implications for the use of TACK compounds therapeutically and provide basic insights into the properties of the viral membrane that promote viral glycoprotein incorporation.

microbiology↗

bioRxiv2026

Intraspecific trait variation shapes macro-scale patterns ofniche breadth and range size

Morphological variation within species may promote adaptation across ecological and geographic space, perhaps reflecting evolutionary plasticity and adaptability. Based on this concept, species with greater intraspecific variation in morphological traits may be expected to occupy broader ecological niches and larger geographic ranges. However, even in the age of global trait datasets, intraspecific morphological variation remains poorly quantified at broad taxonomic and geographic scales, limiting our understanding of how trait flexibility shapes ecological and biogeographic patterns. Focusing on 161 species of bulbuls, a widespread avian family containing some of the most abundant bird species in the world, along with some of the rarest and most restricted in range, we conducted global-scale sampling of morphological traits. These included beak shape, tarsus length and wing length, associated with dietary niche, foraging strategy and dispersal, respectively. Using phylogenetic models, we tested whether ecological niche breadth and geographical range size are predicted by intraspecific morphological variation quantified from 8,251 museum specimens and 5,627 live captures. Our results demonstrate that morphological trait variation predicts both ecological niche breadth and geographic range size. Furthermore, widespread species exhibit greater morphological variation than restricted-range species even when comparisons are constrained to equivalent geographic extents, consistent with the hypothesis that intraspecific trait variation facilitates range expansion rather than simply accumulating as a consequence of occupying a larger range. These results identify intraspecific morphological variation as a potentially important, yet largely overlooked, predictor of ecological traits and biogeographic distributions in birds.

ecology↗

bioRxiv2026

Female song and breeding phenology of the Nilgiri Flycatcher (Eumyias albicaudatus) in the Shola Sky Islands

Assessing breeding phenology using singing intensity can potentially provide insights into a species' responses to climate or habitat change. Although male passerines are known to sing elaborate songs during the breeding season, females of several tropical passerines also sing. The Nilgiri Flycatcher (Eumyias albicaudatus) is an endemic dimorphic songbird found in the southern Western Ghats of India. Despite its limited distribution and its ecological significance as an indicator species of cloud forests, very little is known about its vocal behaviour and breeding ecology. To examine sex-specific differences in vocalisation patterns, we analysed 294 male and 102 female focal songs from two pairs of birds. We then used data from a year-long automated recorder placed near a breeding pair to study the species' singing phenology using the BirdNET Analyser. The two sexes broadly produced similar songs, although males' songs included more notes at a faster pace. The sex-specific detectors failed due to this high similarity among songs of the two sexes, but we were able to automate species-level detection (F1-score = 0.795 at a confidence threshold of 0.1). We found strong seasonality in vocal activity, with peaks in singing during the breeding season, and identified a diurnal peak at dawn. More data are required to parameterise differences in annual vocal activity between the sexes. These detection patterns provide a framework for a landscape-wide examination of Nilgiri Flycatcher phenology and occurrence. This study suggests that automatic detectors can be a reliable tool for assessing singing phenology in birds and provide insights into breeding periods.

ecology↗

bioRxiv2025

Using Large Language Models to Assemble, Audit, and Prioritize the Therapeutic Landscape

1We present an AI-assisted pipeline for disease-specific drug landscape analysis. Given a disease name, the system assembles a comprehensive, evidence-based view of therapeutic assets by integrating structured sources (such as ClinicalTrials.gov and ChEMBL) and unstructured sources (such as publications, press releases, and patents). Large language models are used in a constrained, auditable mode to normalize drug aliases, resolve drug-target/mechanism of action annotations, and harmonize program status across records. The output is a disease-centric map that spans preclinical assets, not-yet-approved assets (both active and discontinued/shelved), and FDA-approved drugs suitable for re-purposing. Assets are ranked using interpretable, evidence-based scoring heuristics that combine trial volume and clinical phase, endpoint outcomes, biomarker support, recency of activity, and regulatory designations, along with penalties for safety signals and non-pharmaceutical interventions, as well as proportional adjustments for operational versus scientific discontinuations. Case studies in Alzheimers disease, pancreatic cancer, and cystic fibrosis demonstrate generality, coverage, and discrimination across mechanisms and stages. This framework provides a transparent method to assemble and prioritize the therapeutic landscape for any disease, unifying disparate data into a coherent and analyzable representation.

bioinformatics↗

bioRxiv2025

Antifungal therapeutic potential of Candida albicans Fun30: screening and validation of novel inhibitors against Candida albicans

WHO has listed Candida albicans as a fungal pathogen of priority. With the increasing incidence of C. albicans infection and limited treatment strategies, the identification of new drug targets and inhibitor molecules is of global concern. ATP-dependent chromatin remodelling proteins play a crucial role in regulating gene expression. Fun30 from C. albicans (CaFun30) mediates DNA end-resection during DNA double-strand break repair. It also transcriptionally co-regulates the expression of DNA damage response genes and genes involved in white-opaque switching. The gene is not essential for viability; however, the null mutant shows increased sensitivity to genotoxic agents. We hypothesised that the protein could be a potential therapeutic target against C. albicans. The structural model of CaFun30 was generated using homology modelling. Screening of a small molecule library identified 10 potential molecules, of which F1853-0039 was found as the lead inhibitor candidate. In vitro studies showed that the molecule had an MIC in the micromolar range against C. albicans with minimal effect on human THP-1 cells. Finally, coculture experiments showed that the inhibitor molecule prevented the formation of hyphae of C. albicans upon infecting THP-1 cells leading us to conclude that CaFun30 could potentially be developed as a therapeutic target against C. albicans.

pharmacology and toxicology↗

bioRxiv2022

Novel Master Regulators of Microglial Phagocytosis and Repurposed FDA-approved Drug for Treatment of Alzheimer Disease

Microglia, the innate immune cells of the brain, are essential determinants of late-onset Alzheimers Disease (LOAD) neuropathology. Here, we developed an integrative computational systems biology approach to construct causal network models of genetic regulatory programs for microglia in Alzheimers Disease (AD). This model enabled us to identify novel key driver (KDs) genes for microglial functions that can be targeted for AD pharmacotherapy. We prioritized FCER1G, HCK, LAPTM5, ITGB2, SLC1A2, PAPLN, GSAP, NTRK2, and CIRBP as KDs of microglial phagocytosis promoting neuroprotection and/or neural repair. In vitro, shRNA knockdown of each KD significantly reduced microglial phagocytosis. We repurposed riluzole, an FDA-approved ALS drug that upregulates SLC1A2 activity, and discovered that it stimulated phagocytosis of A{beta}1-42 in human primary microglia and decreased hippocampal amyloid plaque burden/phosphorylated tau levels in the brain of aged 3xTg-AD mice. Taken together, these data emphasize the utlility of our integrative approach for repurposing drugs for AD therapy.

neuroscience↗

bioRxiv2020

Dynamics of the ACE2 - SARS-CoV/SARS-CoV-2 spike protein interface reveal unique mechanisms

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major public health concern. A handful of static structures now provide molecular insights into how SARS-CoV-2 and SARS-CoV interact with its host target, which is the angiotensin converting enzyme 2 (ACE2). Molecular recognition, binding and function are dynamic processes. To evaluate this, multiple all atom molecular dynamics simulations of at least 500 ns each were performed to better understand the structural stability and interfacial interactions between the receptor binding domain of the spike protein of SARS-CoV-2 and SARS-CoV bound to ACE2. Several contacts were observed to form, break and reform in the interface during the simulations. Our results indicate that SARS-CoV and SARS-CoV-2 utilizes unique strategies to achieve stable binding to ACE2. Several differences were observed between the residues of SARS-CoV-2 and SARS-CoV that consistently interacted with ACE2. Notably, a stable salt bridge between Lys417 of SARS-CoV-2 spike protein and Asp30 of ACE2 as well as three stable hydrogen bonds between Tyr449, Gln493, and Gln498 of SARS-CoV-2 and Asp38, Glu35, and Lys353 of ACE2 were observed, which were absent in the SARS-CoV-ACE2 interface. Some previously reported residues, which were suggested to enhance the binding affinity of SARS-CoV-2, were not observed to form stable interactions in these simulations. Stable binding to the host receptor is crucial for virus entry. Therefore, special consideration should be given to these stable interactions while designing potential drugs and treatment modalities to target or disrupt this interface.

molecular biology↗