An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences

S, Lam; Das, Sayoni; Sillitoe, Ian; Orengo, Christine A.

doi:10.1107/s2059798317008920

Cited by 52 publications

(39 citation statements)

References 146 publications

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“…catalytic residues in CSA 26 . They have also been shown to be structurally coherent 64,70 . Highly conserved sites within CATH-FunFams (also described as FunSites) are found by analysing sequence conservation in a multiple sequence alignment of the FunFam, using the scorecons algorithm 71 .…”

Section: Cath-funfams Are Sets Of Evolutionary Related Domains Clustementioning

confidence: 97%

A CATH domain functional family based approach to identify putative cancer driver genes and driver mutations

Ashford

Pang

Moya‐García

et al. 2018

Preprint

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Tumour sequencing identifies highly recurrent point mutations in cancer driver genes, but rare functional mutations are hard to distinguish from large numbers of passengers. We developed a novel computational platform applying a multi-modal approach to filter out passengers and more robustly identify putative driver genes. The primary filter identifies enrichment of cancer mutations in CATH functional families (CATH-FunFams) -structurally and functionally coherent sets of evolutionary related domains. Using structural representatives from CATH-FunFams, we subsequently seek enrichment of mutations in 3D and show that these mutation clusters have a very significant tendency to lie close to known functional sites or conserved sites predicted using CATH-FunFams. Our third filter identifies enrichment of putative driver genes in functionally coherent protein network modules confirmed by literature analysis to be cancer associated.Our approach is complementary to other domain enrichment approaches exploiting Pfam families, but benefits from more functionally coherent groupings of domains. Using a set of mutations from 22 cancers we detect 151 putative cancer drivers, of which 79 are not listed in cancer resources and include recently validated cancer genes EPHA7, DCC netrin-1 receptor and zinc-finger protein ZNF479. Table 1 Summary of protein functions and cancers for the top mutated MutFam genes having some other supporting evidence. Genes in bold were also identified in either CGC or Miller.

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Section: Cath-funfams Are Sets Of Evolutionary Related Domains Clustementioning

confidence: 97%

A CATH domain functional family based approach to identify putative cancer driver genes and driver mutations

Ashford

Pang

Moya‐García

et al. 2018

Preprint

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“…For FunFams that had a known domain structure, we annotated the splice events using the FlyBase/Ensembl to PDB mapping. For FunFams that had no relative of known structure, we used the FunMod modelling pipeline (29,30) which exploits the MODELLER (42) algorithm to build structural models. We used normalised DOPE (43) and GA341 (44) to assess the quality of the models.…”

Section: Annotating Mxe Events With Structural Informationmentioning

confidence: 99%

“…Relatives in FunFams have highly similar structures and functions (27,28). Splice regions were mapped to known structures where available, or homology models built using the in-house FunMod modelling pipeline (29,30). If no model could be built, splice events were aligned to known structures using an in-house HMMbased protocol.…”

Section: Introductionmentioning

confidence: 99%

Protein structure and function analyses to understand the implication of mutually exclusive splicing

Orengo

Lees

2018

Preprint

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Alternative splicing (AS) has been suggested as one of the major processes expanding the diversity of proteomes in multicellular organisms. Mutually exclusive exons (MXE) provide one form of AS that is less likely to disrupt protein structure and is over-represented in the proteome compared to other forms of AS. We used domain structure information from the CATH classification to perform a systematic structural analysis of the effects of MXE splicing in high quality animal genomes (e.g. human, fly, mouse and 2 fishes) and we were able to annotate approximately 50% of MXE events with structural information. For those MXE events which can be mapped to a structure, we found that although embedded in domains, they were strongly enriched in surface exposed residues. We also demonstrated that the variable residues between splicing events lie close to known and/or predicted functional sites. We present some examples of MXE events in proteins that have important roles in cells. This work presents the first large scale systematic study of the structural/functional effects of MXE splicing using predominantly domain based modelling and functional annotation tools. Our study supports and expands on previous work in this field and helps to build a picture of how MXE events facilitate evolution of new functions.

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“…choosing the most relevant enzymeligand complex for their analyses in structure-based drug design applications but will also help the structural bioinformatics community in selecting suitable structural representatives for protein family-based studies on ligand diversity (Najmanovich, 2017), function evolution (Das et al, 2015), and structural modeling (Lam et al, 2017), among others. For example, the carbonic anhydrase superfamily in CATH (Dawson et al, 2017) contains many carbonic anhydrase enzyme structures with different ligands bound in different parts of the structure (Figure 2A).…”

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confidence: 99%

Unexpected Specificity of a Trypsin-like Enzyme

Dauter

Wlodawer

2018

Structure

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An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences

Cited by 52 publications

References 146 publications

A CATH domain functional family based approach to identify putative cancer driver genes and driver mutations

A CATH domain functional family based approach to identify putative cancer driver genes and driver mutations

Protein structure and function analyses to understand the implication of mutually exclusive splicing

Unexpected Specificity of a Trypsin-like Enzyme

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