COSMIC: the Catalogue Of Somatic Mutations In Cancer.

COSMIC, the Catalogue Of Somatic Mutations In Cancer (https://cancer.sanger.ac.uk) is the most detailed and comprehensive resource for exploring the effect of somatic mutations in human cancer. The latest release, COSMIC v86 (August 2018), includes almost 6 million coding mutations across 1.4 million tumour samples, curated from over 26 000 publications. In addition to coding mutations, COSMIC covers all the genetic mechanisms by which somatic mutations promote cancer, including non-coding mutations, gene fusions, copy-number variants and drug-resistance mutations. COSMIC is primarily hand-curated, ensuring quality, accuracy and descriptive data capture. Building on our manual curation processes, we are introducing new initiatives that allow us to prioritize key genes and diseases, and to react more quickly and comprehensively to new findings in the literature. Alongside improvements to the public website and data-download systems, new functionality in COSMIC-3D allows exploration of mutations within three-dimensional protein structures, their protein structural and functional impacts, and implications for druggability. In parallel with COSMIC's deep and broad variant coverage, the Cancer Gene Census (CGC) describes a curated catalogue of genes driving every form of human cancer. Currently describing 719 genes, the CGC has recently introduced functional descriptions of how each gene drives disease, summarized into the 10 cancer Hallmarks.

COSMIC: somatic cancer genetics at high-resolution.

COSMIC, the Catalogue of Somatic Mutations in Cancer (http://cancer.sanger.ac.uk) is a high-resolution resource for exploring targets and trends in the genetics of human cancer. Currently the broadest database of mutations in cancer, the information in COSMIC is curated by expert scientists, primarily by scrutinizing large numbers of scientific publications. Over 4 million coding mutations are described in v78 (September 2016), combining genome-wide sequencing results from 28 366 tumours with complete manual curation of 23 489 individual publications focused on 186 key genes and 286 key fusion pairs across all cancers. Molecular profiling of large tumour numbers has also allowed the annotation of more than 13 million non-coding mutations, 18 029 gene fusions, 187 429 genome rearrangements, 1 271 436 abnormal copy number segments, 9 175 462 abnormal expression variants and 7 879 142 differentially methylated CpG dinucleotides. COSMIC now details the genetics of drug resistance, novel somatic gene mutations which allow a tumour to evade therapeutic cancer drugs. Focusing initially on highly characterized drugs and genes, COSMIC v78 contains wide resistance mutation profiles across 20 drugs, detailing the recurrence of 301 unique resistance alleles across 1934 drug-resistant tumours. All information from the COSMIC database is available freely on the COSMIC website.

Understanding the impacts of missense mutations on structures and functions of human cancer-related genes: A preliminary computational analysis of the COSMIC Cancer Gene Census.

Genomics and genome screening are proving central to the study of cancer. However, a good appreciation of the protein structures coded by cancer genes is also invaluable, especially for the understanding of functions, for assessing ligandability of potential targets, and for designing new drugs. To complement the wealth of information on the genetics of cancer in COSMIC, the most comprehensive database for cancer somatic mutations available, structural information obtained experimentally has been brought together recently in COSMIC-3D. Even where structural information is available for a gene in the Cancer Gene Census, a list of genes in COSMIC with substantial evidence supporting their impacts in cancer, this information is quite often for a single domain in a larger protein or for a single protomer in a multiprotein assembly. Here, we show that over 60% of the genes included in the Cancer Gene Census are predicted to possess multiple domains. Many are also multicomponent and membrane-associated molecular assemblies, with mutations recorded in COSMIC affecting such assemblies. However, only 469 of the gene products have a structure represented in the PDB, and of these only 87 structures have 90-100% coverage over the sequence and 69 have less than 10% coverage. As a first step to bridging gaps in our knowledge in the many cases where individual protein structures and domains are lacking, we discuss our attempts of protein structure modelling using our pipeline and investigating the effects of mutations using two of our in-house methods (SDM2 and mCSM) and identifying potential driver mutations. This allows us to begin to understand the effects of mutations not only on protein stability but also on protein-protein, protein-ligand and protein-nucleic acid interactions. In addition, we consider ways to combine the structural information with the wealth of mutation data available in COSMIC. We discuss the impacts of COSMIC missense mutations on protein structure in order to identify and assess the molecular consequences of cancer-driving mutations.

Arpeggio: A Web Server for Calculating and Visualising Interatomic Interactions in Protein Structures.

Interactions between proteins and their ligands, such as small molecules, other proteins, and DNA, depend on specific interatomic interactions that can be classified on the basis of atom type and distance and angle constraints. Visualisation of these interactions provides insights into the nature of molecular recognition events and has practical uses in guiding drug design and understanding the structural and functional impacts of mutations. We present Arpeggio, a web server for calculating interactions within and between proteins and protein, DNA, or small-molecule ligands, including van der Waals', ionic, carbonyl, metal, hydrophobic, and halogen bond contacts, and hydrogen bonds and specific atom-aromatic ring (cation-π, donor-π, halogen-π, and carbon-π) and aromatic ring-aromatic ring (π-π) interactions, within user-submitted macromolecule structures. PyMOL session files can be downloaded, allowing high-quality publication images of the interactions to be generated. Arpeggio is implemented in Python and available as a user-friendly web interface at http://structure.bioc.cam.ac.uk/arpeggio/ and as a downloadable package at https://bitbucket.org/harryjubb/arpeggio.

Mutations at protein-protein interfaces: Small changes over big surfaces have large impacts on human health.

Many essential biological processes including cell regulation and signalling are mediated through the assembly of protein complexes. Changes to protein-protein interaction (PPI) interfaces can affect the formation of multiprotein complexes, and consequently lead to disruptions in interconnected networks of PPIs within and between cells, further leading to phenotypic changes as functional interactions are created or disrupted. Mutations altering PPIs have been linked to the development of genetic diseases including cancer and rare Mendelian diseases, and to the development of drug resistance. The importance of these protein mutations has led to the development of many resources for understanding and predicting their effects. We propose that a better understanding of how these mutations affect the structure, function, and formation of multiprotein complexes provides novel opportunities for tackling them, including the development of small-molecule drugs targeted specifically to mutated PPIs.

Phosphopeptide interactions with BRCA1 BRCT domains: More than just a motif.

BRCA1 BRCT domains function as phosphoprotein-binding modules for recognition of the phosphorylated protein-sequence motif pSXXF. While the motif interaction interface provides strong anchor points for binding, protein regions outside the motif have recently been found to be important for binding affinity. In this review, we compare the available structural data for BRCA1 BRCT domains in complex with phosphopeptides in order to gain a more complete understanding of the interaction between phosphopeptides and BRCA1-BRCT domains.

Flexibility and small pockets at protein-protein interfaces: New insights into druggability.

The transient assembly of multiprotein complexes mediates many aspects of cell regulation and signalling in living organisms. Modulation of the formation of these complexes through targeting protein-protein interfaces can offer greater selectivity than the inhibition of protein kinases, proteases or other post-translational regulatory enzymes using substrate, co-factor or transition state mimetics. However, capitalising on protein-protein interaction interfaces as drug targets has been hindered by the nature of interfaces that tend to offer binding sites lacking the well-defined large cavities of classical drug targets. In this review we posit that interfaces formed by concerted folding and binding (disorder-to-order transitions on binding) of one partner and other examples of interfaces where a protein partner is bound through a continuous epitope from a surface-exposed helix, flexible loop or chain extension may be more tractable for the development of "orthosteric", competitive chemical modulators; these interfaces tend to offer small-volume but deep pockets and/or larger grooves that may be bound tightly by small chemical entities. We discuss examples of such protein-protein interaction interfaces for which successful chemical modulators are being developed.

TIMBAL v2: update of a database holding small molecules modulating protein-protein interactions.

TIMBAL is a database holding molecules of molecular weight <1200 Daltons that modulate protein-protein interactions. Since its first release, the database has been extended to cover 50 known protein-protein interactions drug targets, including protein complexes that can be stabilized by small molecules with therapeutic effect. The resource contains 14 890 data points for 6896 distinct small molecules. UniProt codes and Protein Data Bank entries are also included. Database URL: http://www-cryst.bioc.cam.ac.uk/timbal

Protein-protein interactions as druggable targets: recent technological advances.

Classical target-based drug discovery, where large chemical libraries are screened using inhibitory assays for a single target, has struggled to find ligands that inhibit protein-protein interactions (PPI). Nevertheless, in the past decade there have been successes that have demonstrated that PPI can be useful drug targets, and the field is now evolving fast. This review focuses on the new approaches and concepts that are being developed to tackle these challenging targets: the use of fragment based methods to explore the chemical space, stapled peptides to regulate intracellular PPI, alternatives to competitive inhibition and the use of antibodies to enable small molecule discovery for these targets.

Structural biology and drug discovery for protein-protein interactions.

Although targeting protein-protein interfaces of regulatory multiprotein complexes has become a significant focus in drug discovery, it continues to pose major challenges. Most interfaces would be classed as 'undruggable' by conventional analyses, as they tend to be large, flat and featureless. Over the past decade, encouragement has come from the discovery of hotspots that contribute much of the free energy of interaction, and this has led to the development of tethering methods that target small molecules to these sites, often inducing adaptive changes. Equally important has been the recognition that many protein-protein interactions involve a continuous epitope of one partner and a well-defined groove or series of specific small pockets. These observations have stimulated the development of stapled α-helical peptides and other proteomimetic approaches. They have also led to the realisation that fragments might gain low-affinity 'footholds' on some protein-protein interfaces, and that these fragments might be elaborated to useful modulators of the interactions.