INTEGRATED COMPUTATIONAL APPROACH FOR ANALYZING BIOACTIVE COMPOUNDS IN CARDIOVASCULAR DISEASES

Rufat ASLANOV, Moldova State University

Abstract

We propose a step-by-step methodological approach for computational analysis of bioactive compounds in cardiovascular diseases (CVD) that integrates network medicine/systems biology, multi-omics integration, AI/ML, QSAR, molecular docking/AlphaFold 3, and chemogenomic resources. The workflow aligns with contemporary clinical stratification (HFrEF/HFmrEF/HFpEF; dyslipidemia; hypertension; coronary artery disease; pulmonary hypertension) and drug classes (statins/ezetimibe/PCSK9 inhibitors and siRNA; SGLT2 inhibitors; ARNI; vericiguat; targeted anti-inflammatories; ATTR-specific therapy). Projects under development include: virtual library, QSAR/early tox filters, target position/affinity (docking), including AlphaFold 3 complex prediction (AF3 for joint complex prediction), network proximity, multi-omics signature matching, prioritized hit list. Representative studies (2014–2025) are synthesized, the effects presented, and a methodological scheme for further research developed.

Keywords: cardiovascular, bioactive, network medicine, multi-omics, ML, QSAR, molecular docking, drug-repositioning, AlphaFold 3.

DOI:https://doi.org/10.59295/sum6(186)2025_09