Deriving a mutation index of carcinogenicity using protein structure and protein interfaces

With the advent of Next Generation Sequencing the identification of mutations in the genomes of healthy and diseased tissues has become commonplace. While much progress has been made to elucidate the aetiology of disease processes in cancer, the contributions to disease that many individual mutations make remain to be characterised and their downstream consequences on cancer phenotypes remain to be understood. Missense mutations commonly occur in cancers and their consequences remain challenging to predict. However, this knowledge is becoming more vital, for both assessing disease progression and for stratifying drug treatment regimes. Coupled with structural data, comprehensive genomic databases of mutations such as the 1000 Genomes project and COSMIC give an opportunity to investigate general principles of how cancer mutations disrupt proteins and their interactions at the molecular and network level. We describe a comprehensive comparison of cancer and neutral missense mutations; by combining features derived from structural and interface properties we have developed a carcinogenicity predictor, InCa (Index of Carcinogenicity). Upon comparison with other methods, we observe that InCa can predict mutations that might not be detected by other methods. We also discuss general limitations shared by all predictors that attempt to predict driver mutations and discuss how this could impact high-throughput predictions. A web interface to a server implementation is publicly available at http://inca.icr.ac.uk/

Beyond the Binding Site: The Role of the β2 – β3 Loop and Extra-Domain Structures in PDZ Domains

A general paradigm to understand protein function is to look at properties of isolated well conserved domains, such as SH3 or PDZ domains. While common features of domain families are well understood, the role of subtle differences among members of these families is less clear. Here, molecular dynamics simulations indicate that the binding mechanism in PSD95-PDZ3 is critically regulated via interactions outside the canonical binding site, involving both the poorly conserved loop and an extra-domain helix. Using the CRIPT peptide as a prototypical ligand, our simulations suggest that a network of salt-bridges between the ligand and this loop is necessary for binding. These contacts interconvert between each other on a time scale of a few tens of nanoseconds, making them elusive to X-ray crystallography. The loop is stabilized by an extra-domain helix. The latter influences the global dynamics of the domain, considerably increasing binding affinity. We found that two key contacts between the helix and the domain, one involving the loop, provide an atomistic interpretation of the increased affinity. Our analysis indicates that both extra-domain segments and loosely conserved regions play critical roles in PDZ binding affinity and specificity

A Dynamic View of Domain-Motif Interactions

Many protein-protein interactions are mediated by domain-motif interaction, where a domain in one protein binds a short linear motif in its interacting partner. Such interactions are often involved in key cellular processes, necessitating their tight regulation. A common strategy of the cell to control protein function and interaction is by post-translational modifications of specific residues, especially phosphorylation. Indeed, there are motifs, such as SH2-binding motifs, in which motif phosphorylation is required for the domain-motif interaction. On the contrary, there are other examples where motif phosphorylation prevents the domain-motif interaction. Here we present a large-scale integrative analysis of experimental human data of domain-motif interactions and phosphorylation events, demonstrating an intriguing coupling between the two. We report such coupling for SH3, PDZ, SH2 and WW domains, where residue phosphorylation within or next to the motif is implied to be associated with switching on or off domain binding. For domains that require motif phosphorylation for binding, such as SH2 domains, we found coupled phosphorylation events other than the ones required for domain binding. Furthermore, we show that phosphorylation might function as a double switch, concurrently enabling interaction of the motif with one domain and disabling interaction with another domain. Evolutionary analysis shows that co-evolution of the motif and the proximal residues capable of phosphorylation predominates over other evolutionary scenarios, in which the motif appeared before the potentially phosphorylated residue, or vice versa. Our findings provide strengthening evidence for coupled interaction-regulation units, defined by a domain-binding motif and a phosphorylated residue

Identification of amino acids essential for the antiangiogenic activity of tumstatin and its use in combination antitumor activity

Tumstatin is an angiogenesis inhibitor that binds to αvβ3 integrin and suppresses tumor growth. Previous deletion mutagenesis studies identified a 25-aa fragment of tumstatin (tumstatin peptide) with in vitro antiangiogenic activity. Here, we demonstrate that systemic administration of this tumstatin peptide inhibits tumor growth and angiogenesis. Site-directed mutagenesis identified amino acids L, V, and D as essential for the antiangiogenic activity of tumstatin. The tumstatin peptide binds to αvβ3 integrin on proliferating endothelial cells and localizes to select tumor endothelium in vivo. Using 3D molecular modeling, we identify a putative interaction interface for tumstatin peptide on αvβ3 integrin. The antitumor activity of the tumstatin peptide, in combination with bevacizumab (anti-VEGF antibody), displays significant improvement in efficacy against human renal cell carcinoma xenografts when compared with the single-agent use. Collectively, our results demonstrate that tumstatin peptide binds specifically to the tumor endothelium, and its antiangiogenic action is mediated by αvβ3 integrin, and, in combination with an anti-VEGF antibody it exhibits enhanced tumor suppression of renal cell carcinoma

Genome-Wide Analysis of PDZ Domain Binding Reveals Inherent Functional Overlap within the PDZ Interaction Network

Binding selectivity and cross-reactivity within one of the largest and most abundant interaction domain families, the PDZ family, has long been enigmatic. The complete human PDZ domain complement (the PDZome) consists of 267 domains and we applied here a Bayesian selectivity model to predict hundreds of human PDZ domain interactions, using target sequences of 22,997 non-redundant proteins. Subsequent analysis of these binding scores shows that PDZs can be divided into two genome-wide clusters that coincide well with the division between canonical class 1 and 2 PDZs. Within the class 1 PDZs we observed binding overlap at unprecedented levels, mediated by two residues at positions 1 and 5 of the second ahelix of the binding pocket. Eight PDZ domains were subsequently selected for experimental binding studies and to verify the basics of our predictions. Overall, the PDZ domain class 1 cross-reactivity identified here implies that auxiliary mechanisms must be in place to overcome this inherent functional overlap and to minimize cross-selectivity within the living cell. Indeed, when we superimpose PDZ domain binding affinities with gene ontologies, network topology data and the domain position within a PDZ superfamily protein, functional overlap is minimized and PDZ domains position optimally in the binding space. We therefore propose that PDZ domain selectivity is achieved through cellular context rather than inherent binding specificity.BionanoscienceApplied Science