ADDRESS: A Database of Disease-associated Human Variants Incorporating Protein Structure and Folding Stabilities

Numerous human diseases are caused by mutations in genomic sequences. Since amino acid changes affect protein function through mechanisms often predictable from protein structure, the integration of structural and sequence data enables us to estimate with greater accuracy whether and how a given mutation will lead to disease. Publicly available annotated databases enable hypothesis assessment and benchmarking of prediction tools. However, the results are often presented as summary statistics or black box predictors, without providing full descriptive information. We developed a new semi-manually curated human variant database presenting information on the protein contact-map, sequence-to-structure mapping, amino acid identity change, and stability prediction for the popular Uni-Prot database. We found that the profiles of pathogenic and benign missense polymorphisms can be effectively deduced using decision trees and comparative analyses based on the presented dataset. (C) 2021 Elsevier Ltd. All rights reserved.

Automated summary

The article discusses how mutations in genomic sequences can lead to human diseases, and how combining structural and sequence data can help accurately predict disease outcomes. The research shows that using decision trees and comparative analysis can effectively deduce the characteristics of pathogenic and benign missense polymorphisms.