Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2023.01.13.523909

Computational study of Piper betle L. phytocompounds by insilico and ADMET analysis for prediction of potential xanthine oxidase inhibitory activity

Chakravarthi, V.·Karthikeyan, M.·Lakshmanan, L.·Murugesan, S.·Arivuchelvan, A.·Sukumar, K.·Arulmozhi, A.·Jagadeeswaran, A.
View original source ↗Export metadata ↓

Abstract

BackgroundXanthine oxidase (XO) enzyme is directly associated with pathogenesis of gout and indirectly with cancer, diabetes and metabolic syndromes. Allopurinol is a xanthine oxidase inhibitor which is useful in the treatment of gout but it causes side effects in humans and birds. Therefore, this study sought to identify the alternative compound from the natural resources with fewer side effects than the conventional ones. ObjectivesThe present study was designed to findout the xanthine oxidase inhibitory activity of Piper betle phytocompounds in comparison with Allopurinol. MethodsThe detection of phytocompounds present in the P. betle L. extract was identified through Gas Chromatography Mass Spectrometry (GC-MS) analysis. The insilico analysis and ADMET properties were evaluated for the GC-MS derived P.betle phytocompounds. Among the 32 phyto compounds of P.betle, 18 were showed favourable affinity with xanthine oxidase and their different conformational structures were docked in schrodinger module with xanthine oxidase enzyme structure. The interpretation of results was carried out through GLIDE XP Scoring, GLIDE Energy, MM-GBSA energy and hydrogen bond and Pi-Pi interactions. Further the absorption, distribution, metabolism, excretion and toxicity (ADMET) analysis were also carriedout using QIKPRO programme. ResultsThe results revealed that, the twelve phytocompounds of P.betle showed GLIDE XP docking score (-6.881 to - 4.766 Kcal/mol) higher than allopurinol (-4.535 Kcal/mol) and 11 phytocompounds showed higher GLIDE energy (-42.822 Kcal/mol to - 36.706 Kcal/mol) than allopurinol (-32.676 Kcal/mol). Chromonol and eugenol were the most potential compounds of P.betle which showed both hydrogen bond and Pi-Pi interactions with the target xanthine oxidase as that of standard drug allopurinol. The selected phytocompounds satisfied the ADME descriptors and have no violation of Lipinskis rule of five. ConclusionsThe insilico and ADMET profile study on the phytocompounds of P.betle predicted their promising potential xanthine oxidase inhibition activity and they could be developed as alternate molecules against synthetic agents by invivo experiments for the treatment of xanthine oxidase associated diseases like hyperuricimia and cardiovascular disorders.

Explore related subjects

bioinformaticsPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Chakravarthi, V., Karthikeyan, M., Lakshmanan, L., Murugesan, S., Arivuchelvan, A., Sukumar, K., Arulmozhi, A., Jagadeeswaran, A.. 2023-01-16. Computational study of Piper betle L. phytocompounds by insilico and ADMET analysis for prediction of potential xanthine oxidase inhibitory activity. https://doi.org/10.1101/2023.01.13.523909

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

StableProt: Structure-Aware Deep Learning for Protein Thermostability (Tm) and Environmental Adaptation (OGT) Prediction

Predicting protein melting temperature (Tm) and organismal optimal growth temperature (OGT) is essential for enzyme engineering, biocatalyst design, and metagenomic bioprospecting, yet computational prediction faces several fundamental bottlenecks: sequence-only representations miss tertiary packing; dual-task coupling induces destructive gradient conflict; natural database skew (>87% mesophiles) drives mesophilic collapse; and existing tools produce uncalibrated point predictions. To address these challenges, we present StableProt, a structure-aware framework that couples amino acid sequences with Foldseek 3Di structural tokens via a frozen SaProt backbone to capture 3D contacts. Disjoint heads condition thermodynamic stability on ecological context without gradient conflict, while targeted 14% mesophilic subsampling expands thermophile representation to eliminate mesophilic collapse. Calibrated ensemble modeling reduces calibration error to 1.92%, providing dependable 95% confidence intervals. Evaluating models across 10{degrees}C temperature intervals reveals severe baseline collapse at thermal extremes, whereas StableProt maintains robust accuracy across regimes. On ProThermDB and zero-shot FireProtDB, StableProt achieves state-of-the-art probabilistic accuracy (CRPS = 4.52{degrees}C and 8.71{degrees}C) while recovering 92.0% of hyperthermophiles ([≥]80{degrees}C), and in prospective validation, its calibrated intervals capture both enzyme stability (75.3% coverage) and host environmental growth temperatures (78.1% coverage). StableProt is freely accessible as an interactive web server at https://stableprot.dixitlab.org/.

bioinformatics↗
bioRxiv2026

RoDPAA: A Robust Dissimilarity-Based Principal Angle Analysis Framework for Multi-View Microbiome Data Integration

Multiview microbiome studies profile the same participants across body sites or molecular layers, but integration is hampered by sparse, compositional data, modest sample sizes and methods that recognize only exact sharing. We present RoDPAA (Robust Dissimilarity-based Principal Angle Analysis), a framework that represents each view through any data-appropriate dissimilarity, such as Bray--Curtis, without log-ratio transformation or likelihood assumptions. RoDPAA aligns view-specific signal subspaces through principal angles, captures complete and partial sharing, and tests by permutation how many components are shared, using only eigendecomposition and little tuning. In Gaussian simulations, RoDPAA matched JIVE and MOFA given true ranks, ran faster and alone recovered the shared dimension in every replicate. In two inflammatory bowel disease (IBD) cohorts with sparse, zero-inflated data, Bray--Curtis-based RoDPAA recovered shared structure that was stable to prevalence filtering, whereas log-ratio-based alternatives were not. Its leading microbiome--metabolome factors, learned without disease labels, were the only ones associated with IBD.

bioinformatics↗
bioRxiv2026

Deducing splicing events from transcript sets with splicelogic

Long-read RNA sequencing captures a greater proportion of full-length transcripts, enabling more accurate isoform identification, discovery of novel isoforms, and more precise differential transcript usage analysis. However, comparing transcripts, whether between conditions or between sets such as novel and annotated isoforms, yields complex isoform changes that are hard to manipulate, summarize, and visualize. This is compounded by vertical integration of some tools, where downstream analysis depends on the specific output of a particular upstream tool. To address this gap, we have developed splicelogic, an R/Bioconductor package that makes transcript-set comparisons biologically interpretable by turning them into discrete splicing events, such as exon skipping, alternative splice sites, intron retention, and alternative transcription start and end sites. We designed splicelogic to integrate easily with existing RNA-seq workflows and tools. The splicelogic functions are modular, readable, and extensible, making it easy for users to adapt core logic to their own custom scientific questions or novel splicing definitions. By obtaining interpretable splicing events from transcript changes, splicelogic enables downstream analyses, including annotation of RNA-binding protein recognition sites, alongside summary statistics and visualization. The splicelogic package is publicly available and distributed through Bioconductor.

bioinformatics↗