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/

Elevated neoantigen levels in tumors with somatic mutations in the HLA-A, HLA-B, HLA-C and B2M genes.

BackgroundThe major histocompatibility complex class I (MHC-I) molecule is a protein complex that displays intracellular peptides to T cells, allowing the immune system to recognize and destroy infected or cancerous cells. MHC-I is composed of a highly polymorphic HLA-encoded alpha chain that binds the peptide and a Beta-2-microglobulin (B2M) protein that acts as a stabilizing scaffold. HLA mutations have been implicated as a mechanism of immune evasion during tumorigenesis, and B2M is considered a tumor suppressor gene. However, the implications of somatic HLA and B2M mutations have not been fully explored in the context of antigen presentation via the MHC-I molecule during tumor development. To understand the effect that B2M and HLA MHC-I molecule mutations have on mutagenesis, we analyzed the accumulation of mutations in patients from The Cancer Genome Atlas according to their MHC-I molecule mutation status.ResultsSomatic B2M and HLA mutations in microsatellite stable tumors were associated with higher overall mutation burden and a larger fraction of HLA-binding neoantigens when compared to B2M and HLA wild type tumors. B2M and HLA mutations were highly enriched in patients with microsatellite instability. B2M mutations tended to occur relatively early during patients' respective tumor development, whereas HLA mutations were either early or late events. In addition, B2M and HLA mutated patients had higher levels of immune infiltration by natural killer and CD8+ T cells and higher levels of cytotoxicity.ConclusionsOur findings add to a growing body of evidence that somatic B2M and HLA mutations are a mechanism of immune evasion by demonstrating that such mutations are associated with a higher load of neoantigens that should be presented via MHC-I

Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems

A huge amount of genetic information is available thanks to the recent advances in sequencing technologies and the larger computational capabilities, but the interpretation of such genetic data at phenotypic level remains elusive. One of the reasons is that proteins are not acting alone, but are specifically interacting with other proteins and biomolecules, forming intricate interaction networks that are essential for the majority of cell processes and pathological conditions. Thus, characterizing such interaction networks is an important step in understanding how information flows from gene to phenotype. Indeed, structural characterization of protein–protein interactions at atomic resolution has many applications in biomedicine, from diagnosis and vaccine design, to drug discovery. However, despite the advances of experimental structural determination, the number of interactions for which there is available structural data is still very small. In this context, a complementary approach is computational modeling of protein interactions by docking, which is usually composed of two major phases: (i) sampling of the possible binding modes between the interacting molecules and (ii) scoring for the identification of the correct orientations. In addition, prediction of interface and hot-spot residues is very useful in order to guide and interpret mutagenesis experiments, as well as to understand functional and mechanistic aspects of the interaction. Computational docking is already being applied to specific biomedical problems within the context of personalized medicine, for instance, helping to interpret pathological mutations involved in protein–protein interactions, or providing modeled structural data for drug discovery targeting protein–protein interactions.Spanish Ministry of Economy grant number BIO2016-79960-R; D.B.B. is supported by a predoctoral fellowship from CONACyT; M.R. is supported by an FPI fellowship from the Severo Ochoa program. We are grateful to the Joint BSC-CRG-IRB Programme in Computational Biology.Peer ReviewedPostprint (author's final draft

Aqueous Amino Acids and Proteins Near the Surface of Gold in Hydrophilic and Hydrophobic Force Fields

We calculate potentials of the mean force for twenty amino acids in the vicinity of the (111) surface of gold, for several dipeptides, and for some analogs of the side chains, using molecular dynamics simulations and the umbrella sampling method. We compare results obtained within three different force fields: one hydrophobic (for a contaminated surface) and two hydrophilic. All of these fields lead to good binding with very different specificities and different patterns in the density and polarization of water. The covalent bond with the sulfur atom on cysteine is modeled by the Morse potential. We demonstrate that binding energies of dipeptides are different than the combined binding energies of their amino-acidic components. For the hydrophobic gold, adsorption events of a small protein are driven by attraction to the strongest binding amino acids. This is not so in the hydrophilic cases - a result of smaller specificities combined with the difficulty for proteins, but not for single amino acids, to penetrate the first layer of water. The properties of water near the surface sensitively depend on the force field

Allo-network drugs: Extension of the allosteric drug concept to protein-protein interaction and signaling networks

Allosteric drugs are usually more specific and have fewer side effects than orthosteric drugs targeting the same protein. Here, we overview the current knowledge on allosteric signal transmission from the network point of view, and show that most intra-protein conformational changes may be dynamically transmitted across protein-protein interaction and signaling networks of the cell. Allo-network drugs influence the pharmacological target protein indirectly using specific inter-protein network pathways. We show that allo-network drugs may have a higher efficiency to change the networks of human cells than those of other organisms, and can be designed to have specific effects on cells in a diseased state. Finally, we summarize possible methods to identify allo-network drug targets and sites, which may develop to a promising new area of systems-based drug design

The Many Faces of Protein–Protein Interactions: A Compendium of Interface Geometry

A systematic classification of protein–protein interfaces is a valuable resource for understanding the principles of molecular recognition and for modelling protein complexes. Here, we present a classification of domain interfaces according to their geometry. Our new algorithm uses a hybrid approach of both sequential and structural features. The accuracy is evaluated on a hand-curated dataset of 416 interfaces. Our hybrid procedure achieves 83% precision and 95% recall, which improves the earlier sequence-based method by 5% on both terms. We classify virtually all domain interfaces of known structure, which results in nearly 6,000 distinct types of interfaces. In 40% of the cases, the interacting domain families associate in multiple orientations, suggesting that all the possible binding orientations need to be explored for modelling multidomain proteins and protein complexes. In general, hub proteins are shown to use distinct surface regions (multiple faces) for interactions with different partners. Our classification provides a convenient framework to query genuine gene fusion, which conserves binding orientation in both fused and separate forms. The result suggests that the binding orientations are not conserved in at least one-third of the gene fusion cases detected by a conventional sequence similarity search. We show that any evolutionary analysis on interfaces can be skewed by multiple binding orientations and multiple interaction partners. The taxonomic distribution of interface types suggests that ancient interfaces common to the three major kingdoms of life are enriched by symmetric homodimers. The classification results are online at http://www.scoppi.org

Uncovering Amino Acids Patterns At The Membrane-Binding Interfaces Of Peripheral Proteins

Masteroppgave i informatikkINF399MAMN-INFMAMN-PRO

The complete mitochondrial genome of Yarrowia lipolytica

We here report the complete nucleotide sequence of the 47.9 kb mitochondrial (mt) genome from the obligate aerobic yeast Yarrowia lipolytica. It encodes, all on the same strand, seven subunits of NADH: ubiquinone oxidoreductase (ND1-6, ND4L), apocytochrome b (COB), three subunits of cytochrome oxidase (COX1, 2, 3), three subunits of ATP synthetase (ATP6, 8 and 9), small and large ribosomal RNAs and an incomplete set of tRNAs. The Y. lipolytica mt genome is very similar to the Hansenula wingei mt genome, as judged from blocks of conserved gene order and from sequence homology. The extra DNA in the Y. lipolytica mt genome consists of 17 group 1 introns and stretches of A+Trich sequence, interspersed with potentially transposable GC clusters. The usual mould mt genetic code is used. Interestingly, there is no tRNA able to read CGN (arginine) codons. CGN codons could not be found in exonic open reading frames, whereas they do occur in intronic open reading frames. However, several of the intronic open reading frames have accumulated mutations and must be regarded as pseudogenes. We propose that this may have been triggered by the presence of untranslatable CGN codons. This sequence is available under EMBL Accession No. AJ307410

V_H replacement in rearranged immunoglobulin genes

Examples suggesting that all or part of the V<sub>H</sub> segment of a rearranged V<sub>H</sub>DJ<sub>H</sub> may be replaced by all or part of another V<sub>H</sub> have been appearing since the 1980s. Evidence has been presented of two rather different types of replacement. One of these has gained acceptance and has now been clearly demonstrated to occur. The other, proposed more recently, has not yet gained general acceptance because the same effect can be produced by polymerase chain reaction artefact. We review both types of replacement including a critical examination of evidence for the latter. The first type involves RAG proteins and recombination signal sequences (RSS) and occurs in immature B cells. The second was also thought to be brought about by RAG proteins and RSS. However, it has been reported in hypermutating cells which are not thought to express RAG proteins but in which activation-induced cytidine deaminase (AID) has recently been shown to initiate homologous recombination. Re-examination of the published sequences reveals AID target sites in V<sub>H</sub>-V<sub>H</sub> junction regions and examples that resemble gene conversion