Human Biology Open Access Pre-Prints

Document Type

Article

Anticipated Volume

96

Anticipated Issue

4

Abstract

Background: India harbors remarkable genetic diversity shaped by geographical isolation, endogamy, and distinct evolutionary histories. Such diversity contributes to population-specific disease susceptibility and therapeutic responses. However, systematic integration of comparative population genomics with computational drug discovery remains limited.

Methods: Comparative genomic datasets representing five populations (Kapu, Irula, Relli, Brahmin, and Yadav) were analyzed to identify population-specific genes. Functional annotation was performed to determine their biological relevance. Candidate proteins were subjected to structure-based virtual screening against libraries of approved drugs and bioactive compounds. The highest-ranking protein–ligand complexes were subsequently evaluated through molecular dynamics simulations to assess structural stability and binding behavior.

Results: Distinct population-specific molecular signatures were identified across all study populations. PRSS2 (c.166C>T; c.200+1G>A) was uniquely associated with the Kapu population, MYO15B (c.3294_3297del; c.4241+2T>C) with the Irula population, MUC4 (c.9784_9785insGG; c.9781_9782delGA) with the Relli population, HLA-DRB5 (c.764–2A>G;c.763+1G>C; c.658C>T; c.640_641insTG; c.100+1G>A; c.97C>T) with the Yadav population, and CELA1 (c.12_15delTTAT; c.7_8insCT; c.6_7insC) with the Brahmin population. Functional analysis of several of the prioritized variants revealed potentially disruptive consequences including splice-site and frameshift variants on transcript processing or protein coding sequences. We performed molecular docking selectively for PRSS2 and MUC4, since the functional implications of late MUC4 coding variants and the PRSS2

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