COMPASS employs a multi-step methodology to analyze coding variants:
Revolutionizing Genetic Variant Analysis for Precision Medicine.
COMPASS is an advanced computational pipeline designed to systematically evaluate the functional and structural consequences of disease-associated coding variants. By integrating genetic association analysis with AI-predicted protein structures, this innovative approach bridges the gap between genetic variation and phenotypic outcomes, offering new insights into disease mechanisms and potential therapeutic targets.
Our goal is to enhance the understanding of how genetic variants contribute to complex diseases and traits, ultimately accelerating the discovery of drug targets. By leveraging large-scale genomic data, such as the UK Biobank 500K whole-genome sequencing dataset, COMPASS provides a scalable and comprehensive framework to uncover actionable genetic insights for precision medicine.
Our pipeline has been applied to study rare coding variants associated with lipid traits, revealing structural hotspot such as PCSK9 missense variants linked to LDL cholesterol (P = 3.19E-161). The identified hotspot includes critical functional interface, such as the LDL receptor (LDLR) binding site targeted by monoclonal antibodies Alirocumab and Evolocumab. These results highlight COMPASS’s ability to pinpoint potential functional hotspots and druggable targets.
COMPASS employs a multi-step methodology to analyze coding variants:
Sequence-based Selection: Identifies disease-associated coding variants based on statistical significance from whole-genome sequencing studies. These variants are then mapped to transcript-based amino acid sequences and selects a representative amino acid sequence.
Structure-based patch scanning: Uses a structure-based patch scanning approach to pinpoint disease-relevant protein subregions.
Therapeutic Insights: By integrating structural and functional analyses of disease-associated variants, COMPASS pinpoints regions of potential therapeutic relevance.