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bioRxiv · 10.1101/2024.12.26.630381

EVOLVE: A Web Platform for Evolutionary Phase Analysis and New Variant Exploration from Multi-Sequence Data

Sangeet, S.·Sinha, A.·Nair, M. B.·Mahata, A.·Sarkar, R.·Roy, S.
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Abstract

Recurrent updates from the World Health Organization (WHO) on refining definitions for Variants of Concern (VOCs), Variants of Interest (VOIs), and Variants Under Monitoring (VUMs) underscore the need for systematic investigations to develop quantifiable metrics that differentiate critical phases of variant evolution. This study illustrates how protein data can be systematically analyzed by applying phase transition principles from statistical mechanics, where quantifying mutational response function (MRF) helps identify concerning variants along evolutionary paths. To support the exploration of metrics like mutational entropy, MRF, and other relevant indicators for novel or uncharacterized viruses and pathogenic bacteria, we introduce EVOLVE--a web platform that empowers researchers across diverse fields to access sequence-based analyses. EVOLVE streamlines data upload and analysis with a user-friendly interface and comprehensive tutorials. Overcoming the challenges with large sequence-space analysis its AI-driven data-learning module integrates evolutionary dynamics with microscopic mutational information, enabling the prediction of future site-specific mutations in prospective missense variants. Access EVOLVE for free at https://www.evolve-0fm3.onrender.com.

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Sangeet, S., Sinha, A., Nair, M. B., Mahata, A., Sarkar, R., Roy, S.. 2024-12-26. EVOLVE: A Web Platform for Evolutionary Phase Analysis and New Variant Exploration from Multi-Sequence Data. https://doi.org/10.1101/2024.12.26.630381

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