Integrative Bioinformatics for Natural Products Linking Chemical Profiles, Bioactivity, and Predictive Modeling

Natural products remain an important source of chemically diverse molecules with potential biological and pharmacological activities. Advances in analytical platforms, including LC-MS, GC-MS, metabolomics, and high-throughput bioactivity screening, have generated increasingly complex datasets that require robust computational approaches for their analysis and interpretation. Integrative bioinformatics provides a means of linking chemical composition, molecular features, biological responses, and predictive models within a common analytical framework.This Research Topic focuses on the application of bioinformatics, cheminformatics, machine learning, artificial intelligence, and related computational methods to natural product research. Particular interest is given to approaches that link chemical profiles with experimentally determined biological activities, identify bioactive compounds and molecular signatures, predict structure–activity relationships, and support the prioritization of natural products for further investigation. Studies integrating metabolomic or phytochemical data with antioxidant, antimicrobial, enzyme inhibitory, cytotoxic, antiproliferative, anti-inflammatory, or other biologically relevant endpoints are especially encouraged when supported by appropriate computational analysis.The Research Topic also covers methodological approaches including predictive modeling, feature selection, data integration, network-based analysis, molecular docking, molecular dynamics, multi-omics integration, explainable artificial intelligence, and computational optimization. Studies involving plants, fungi, microorganisms, marine organisms, isolated natural compounds, and complex extracts are within scope.By integrating chemical, biological, and computational data, this Research Topic will highlight approaches for improving the identification and characterization of bioactive natural products, as well as their prediction and prioritization for further experimental investigation. Topic editors: Tetiana Krupodorova, Mustafa Sevindik Source: https://www.frontiersin.org/research-topics/85934/integrative-bioinformatics-for-natural-products-linking-chemical-profiles-bioactivity-and-predictive-modeling