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Comprehensive analysis of co-occurring domain sets in yeast proteins.

ABSTRACT: Protein domains are fundamental evolutionary units of protein architecture, composing proteins in a modular manner. Combinations of two or more, possibly non-adjacent, domains are thought to play specific functional roles within proteins. Indeed, while the number of potential co-occurring domain sets (CDSs) is very large, only a few of these occur in nature. Here we study the principles governing domain content of proteins, using yeast as a model species.We design a novel representation of proteins and their constituent domains as a protein-domain network. An analysis of this network reveals 99 CDSs that occur in proteins more than expected by chance. The identified CDSs are shown to preferentially include ancient domains that are conserved from bacteria or archaea. Moreover, the protein sets spanned by these combinations were found to be highly functionally coherent, significantly match known protein complexes, and enriched with protein-protein interactions. These observations serve to validate the biological significance of the identified CDSs.Our work provides a comprehensive list of co-occurring domain sets in yeast, and sheds light on their function and evolution.

SUBMITTER: Cohen-Gihon I

PROVIDER: S-EPMC1919370 | biostudies-literature | 2007 Jun

REPOSITORIES: biostudies-literature

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Comprehensive analysis of co-occurring domain sets in yeast proteins.

Cohen-Gihon Inbar I Nussinov Ruth R Sharan Roded R

BMC genomics 20070611

<h4>Background</h4>Protein domains are fundamental evolutionary units of protein architecture, composing proteins in a modular manner. Combinations of two or more, possibly non-adjacent, domains are thought to play specific functional roles within proteins. Indeed, while the number of potential co-occurring domain sets (CDSs) is very large, only a few of these occur in nature. Here we study the principles governing domain content of proteins, using yeast as a model species.<h4>Results</h4>We des ...[more]

PMID: 17562021

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Project description:IntroductionEGFR exon 20 insertions (EGFRex20ins) comprise an uncommon subset of EGFR-activating alterations relatively insensitive to first- and second-generation EGFR tyrosine kinase inhibitors (TKIs). However, recent early clinical data suggests these patients may benefit from newer-generation EGFR-TKIs. Comprehensive genomic profiling (CGP) identifies a broad spectrum of EGFRex20ins and associated co-occurring genomic alterations (GAs) present in NSCLC.MethodsHybrid capture-based CGP was performed prospectively on 14,483 clinically annotated consecutive NSCLC specimens to a mean coverage depth of greater than 650X for 236 or 315 cancer-related genes.ResultsOf 14,483 NSCLC cases, CGP identified 263 (1.8%) cases with EGFRex20ins, representing 12% (263 of 2251) of cases with EGFR mutations. Sixty-four unique EGFRex20ins were identified, most commonly D770_N771>ASVDN (21%) and N771_P772>SVDNP (20%). EGFR amplification occurred in 22% (57 of 263). The most common co-occurring GAs effected tumor protein p53 (TP53) (56%), cyclin dependent kinase inhibitor 2A (CDKN2A) (22%), cyclin dependent kinase inhibitor 2B (CDKN2B) (16%), NK2 homeobox 1 (NKX2-1) (14%) and RB transcriptional corepressor 1 (RB1) (11%); co-occurring GAs in other known lung cancer drivers were rare (5%). Average tumor mutational burden was low (mean 4.3, range 0 to 40.3 mutations/Mb). Clinical outcomes to first- and second-generation EGFR TKIs were obtained for five patients and none responded.ConclusionsIn the largest series of EGFRex20ins NSCLC, diverse EGFRex20ins were detected in 12% of EGFR-mutant NSCLC, a higher frequency than previously reported in smaller single-institution studies. Clinical outcomes showed lack of response to EGFR TKIs. Tumor mutational burden was low, consistent with non-smoking associated NSCLC. Comprehensive sequencing revealed increased proportion and wide variety of EGFRex20ins, representing a population of patients significant enough for focused efforts on effective interventions.

Dataset Information

Comprehensive analysis of co-occurring domain sets in yeast proteins.

Publications

Comprehensive analysis of co-occurring domain sets in yeast proteins.

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