ADDRESS: A database of disease-associated human variants incorporating protein structure and folding stabilities
| Autor: | Yang Zhang, Jaie Woodard, Chengxin Zhang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Protein Folding
Computer science Stability (learning theory) Decision tree Single-nucleotide polymorphism Disease computer.software_genre Polymorphism Single Nucleotide Article 03 medical and health sciences User-Computer Interface 0302 clinical medicine Protein structure Structural Biology Missense mutation Humans Amino Acids Databases Protein Molecular Biology 030304 developmental biology 0303 health sciences Database Protein Stability Genetic Variation Proteins Mutation (genetic algorithm) UniProt computer 030217 neurology & neurosurgery |
| Zdroj: | J Mol Biol |
| Popis: | 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 UniProt 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. The database is made publicly available through https://zhanglab.ccmb.med.umich.edu/ADDRESS. |
| Databáze: | OpenAIRE |
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