Assessment of community efforts to advance network-based prediction of protein-protein interactions.

Comprehensive understanding of the human protein-protein interaction (PPI) network, aka the human interactome, can provide important insights into the molecular mechanisms of complex biological processes and diseases. Despite the remarkable experimental efforts undertaken to date to determine the structure of the human interactome, many PPIs remain unmapped. Computational approaches, especially network-based methods, can facilitate the identification of previously uncharacterized PPIs. Many such methods have been proposed. Yet, a systematic evaluation of existing network-based methods in predicting PPIs is still lacking. Here, we report community efforts initiated by the International Network Medicine Consortium to benchmark the ability of 26 representative network-based methods to predict PPIs across six different interactomes of four different organisms: A. thaliana, C. elegans, S. cerevisiae, and H. sapiens. Through extensive computational and experimental validations, we found that advanced similarity-based methods, which leverage the underlying network characteristics of PPIs, show superior performance over other general link prediction methods in the interactomes we considered.

Multimodal assessment of protein functional deficiency supports pathogenicity of BRCA1 p.V1688del.

Unequivocal discrimination between neutral variants and deleterious mutations is crucial for appropriate counseling of individuals with a BRCA1 or BRCA2 sequence change. An increasing number of variants of uncertain significance (VUS) are being identified, the unclassified biological effect of which poses clinical concerns. A multifactorial likelihood-based approach recently suggested disease causality for BRCA1 p.V1688del, a VUS recurrent in Italian breast/ovarian cancer families. Whether and how this single amino acid deletion in the BRCA1 COOH terminus (BRCT) domain affects the function of the mutant protein (DeltaValBRCA1) has not been elucidated. We undertook comprehensive functional characterization of DeltaValBRCA1, comprising comparative structural modeling, analysis of protein stability and associations, and analysis of DNA repair function. Our model predicted BRCT domain destabilization and folding disruption caused by BRCA1 p.V1688del. Consistently, the recombinant DeltaValBRCA1 was less stable than wild-type BRCA1 and, unlike the latter, failed to associate with BRIP1, CtIP, and Rap80 and to relocalize to sites of DNA damage. Yeast two-hybrid analysis revealed a compromised interaction with FHL2 and KPNA2, which is likely responsible for improper subcellular localization of DeltaValBRCA1. In addition, we found four new breast/ovarian cancer families of Italian ancestry who carried this sequence alteration. These results provide the first evidence of the effect of BRCA1 p.V1688del on protein stability and function, supporting the view that it is a deleterious mutation. Multimodal analyses like ours could advance understanding of tumor suppression by BRCA1 and ultimately contribute to developing efficient strategies for screening and characterization of VUS.