부산대학교 도서관

The assembly of proteins into complexes and their interactions with other biomolecules are often vital for their biological function. While it is known that mutations at protein interfaces have a high potential to be damaging and cause human genetic disease, there has been relatively little consideration for how this varies between different types of interfaces. Here we investigate the properties of human pathogenic and putatively benign missense variants at homomeric (isologous and heterologous), heteromeric, DNA, RNA and other ligand interfaces, and at different regions in proteins with respect to those interfaces. We find that different types of interfaces vary greatly in their propensity to be associated with pathogenic mutations, with homomeric heterologous and DNA interfaces being particularly enriched in disease. We also find that residues that do not directly participate in an interface, but are close in three-dimensional space, show a significant disease enrichment. Finally, we observe that mutations at different types of interfaces tend to have distinct property changes when undergoing amino acid substitutions associated with disease, and that this is linked to substantial variability in their identification by computational variant effect predictors. Author summary: Nearly all proteins interact with other molecules as part of their biological function. For example, proteins can interact with other copies of the same type of protein, with different proteins, with DNA, or with small ligand molecules. Many mutations at protein interfaces, the regions of proteins that interact with other molecules, are known to cause human genetic disease. In this study, we first investigate how different types of protein interfaces have different tendencies to be associated with disease. We also show that the closer a mutation is to an interface, the more likely it is to cause disease. Finally, we study how mutations at different types of interfaces tend to be associated with different changes in amino acid properties, which appears to influence our ability to computationally predict the effects of mutations. Ultimately, we hope that consideration of protein interface properties will eventually improve our ability to identify new disease-causing mutations. [ABSTRACT FROM AUTHOR]