Recent advances in AI-based methods have revolutionized the field of structural biology. Concomitantly, high-throughput sequencing and functional genomics have generated genetic variants at an unprecedented scale. However, efficient tools and resources are needed to link disparate data types-to 'map' variants onto protein structures, to better understand how the variation causes disease, and thereby design therapeutics. Here we present the Genomics 2 Proteins portal ( https://g2p.broadinstitute.org/ ): a human proteome-wide resource that maps 20,076,998 genetic variants onto 42,413 protein sequences and 77,923 structures, with a comprehensive set of structural and functional features. Additionally, the Genomics 2 Proteins portal allows users to interactively upload protein residue-wise annotations (for example, variants and scores) as well as the protein structure beyond databases to establish the connection between genomics to proteins. The portal serves as an easy-to-use discovery tool for researchers and scientists to hypothesize the structure-function relationship between natural or synthetic variations and their molecular phenotypes.

• MeSH
• Databases, Protein * MeSH
• Genetic Variation MeSH
• Genetic Testing methods   MeSH
• Genomics * methods   MeSH
• Protein Conformation MeSH
• Humans MeSH
• Proteins genetics   chemistry   MeSH
• Proteome genetics   MeSH
• Amino Acid Sequence MeSH
• Software MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Proteins MeSH
• Proteome MeSH

Interpretation of the colossal number of genetic variants identified from sequencing applications is one of the major bottlenecks in clinical genetics, with the inference of the effect of amino acid-substituting missense variations on protein structure and function being especially challenging. Here we characterize the three-dimensional (3D) amino acid positions affected in pathogenic and population variants from 1,330 disease-associated genes using over 14,000 experimentally solved human protein structures. By measuring the statistical burden of variations (i.e., point mutations) from all genes on 40 3D protein features, accounting for the structural, chemical, and functional context of the variations' positions, we identify features that are generally associated with pathogenic and population missense variants. We then perform the same amino acid-level analysis individually for 24 protein functional classes, which reveals unique characteristics of the positions of the altered amino acids: We observe up to 46% divergence of the class-specific features from the general characteristics obtained by the analysis on all genes, which is consistent with the structural diversity of essential regions across different protein classes. We demonstrate that the function-specific 3D features of the variants match the readouts of mutagenesis experiments for BRCA1 and PTEN, and positively correlate with an independent set of clinically interpreted pathogenic and benign missense variants. Finally, we make our results available through a web server to foster accessibility and downstream research. Our findings represent a crucial step toward translational genetics, from highlighting the impact of mutations on protein structure to rationalizing the variants' pathogenicity in terms of the perturbed molecular mechanisms.

• Keywords
• 3D mutational hotspot, disease variation effect, machine learning, missense variant interpretation, protein structure and function,
• MeSH
• PTEN Phosphohydrolase chemistry   genetics   MeSH
• Protein Conformation MeSH
• Humans MeSH
• Mutation, Missense genetics   physiology   MeSH
• Models, Molecular MeSH
• BRCA1 Protein chemistry   genetics   MeSH
• Proteins chemistry   genetics   physiology   MeSH
• Amino Acid Sequence MeSH
• Machine Learning MeSH
• Computational Biology methods   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• BRCA1 protein, human MeSH Browser
• PTEN Phosphohydrolase MeSH
• BRCA1 Protein MeSH
• Proteins MeSH
• PTEN protein, human MeSH Browser