IN SILICO DRUG REPURPOSING FOR INFLAMMATORY DISEASES: A SYSTEMATIC REVIEW OF MOLECULAR DOCKING AND VIRTUAL SCREENING STUDIES

Abstract

The escalating global burden of inflammatory diseases—marked by persistent immune dysregulation, multisystem involvement, and complex molecular etiologies—has intensified the need for innovative therapeutic strategies that minimize cost, reduce development timelines, and increase success rates. Drug repurposing, the practice of identifying new therapeutic uses for existing drugs, has emerged as a strategic alternative to de novo drug discovery, particularly through in silico methodologies such as molecular docking, virtual screening, and cheminformatics-guided candidate selection. This systematic review synthesizes and evaluates recent advancements in computational repurposing approaches aimed at inflammatory disorders, including rheumatoid arthritis, inflammatory bowel disease, psoriasis, and systemic lupus erythematosus. Following the PRISMA 2020 guidelines, a comprehensive literature search was conducted across multiple scientific databases—including PubMed, Scopus, Web of Science, Embase, and IEEE Xplore—to identify peer-reviewed studies published between January 2010 and April 2022. A total of 65 articles met the inclusion criteria, encompassing diverse in silico workflows that examined drug-target interactions using molecular docking platforms such as AutoDock, AutoDock Vina, Schrödinger’s Glide, MOE, and GOLD, often combined with ADMET profiling tools (e.g., SwissADME, pkCSM) and molecular dynamics simulations to validate binding stability. Target proteins of interest commonly included pro-inflammatory mediators such as TNF-α, IL-6, IL-1β, JAK1/2, and NF-κB, with FDA-approved kinase inhibitors and anti-cancer drugs frequently emerging as high-affinity binders suitable for cross-disease application. In addition, the review documents methodological convergence in scoring thresholds, ligand library design, and reproducibility standards across computational studies. Several case studies demonstrate successful downstream validation of in silico predictions via in vitro or in vivo assays, reinforcing the translational potential of these approaches. However, key challenges persist, including lack of consensus on docking protocol standardization, limited exploration of off-target toxicities, and insufficient integration with systems pharmacology and biological network modeling. This review concludes that in silico drug repurposing represents a rapidly evolving, resource-efficient approach for identifying new treatments in immunopathology, but emphasizes the need for hybrid computational-experimental pipelines and improved benchmarking to realize its full clinical utility.