SDM--a server for predicting effects of mutations on protein stability and malfunction

Large scale analysis of the mutational landscape in β-glucuronidase: A major player of mucopolysaccharidosis type VII

The lysosomal storage disorders are a group of 50 unique inherited diseases characterized by unseemly lipid storage in lysosomes. These malfunctions arise due to genetic mutations that result in deficiency or reduced activities of the lysosomal enzymes, which are responsible for catabolism of biological macromolecules. Sly syndrome or mucopolysaccharidosis type VII is a lysosomal storage disorder associated with the deficiency of β-glucuronidase (EC 3.2.1.31) that catalyzes the hydrolysis of β-D-glucuronic acid residues from the non-reducing terminal of glycosaminoglycan. The effects of the disease causing mutations on the framework of the sequences and structure of β-glucuronidase (GUSBp) were analyzed utilizing a variety of bioinformatic tools. These analyses showed that 211 mutations may result in alteration of the biological activity of GUSBp, including previously experimentally validated mutations. Finally, we refined 90 disease causing mutations, which presumably cause a significant impact on the structure, function, and stability of GUSBp. Stability analyses showed that mutations p.Phe208Pro, p.Phe539Gly, p.Leu622Gly, p.Ile499Gly and p.Ile586Gly caused the highest impact on GUSBp stability and function because of destabilization of the protein structure. Furthermore, structures of wild type and mutant GUSBp were subjected to molecular dynamics simulation to examine the relative structural behaviors in the explicit conditions of water. In a broader view, the use of in silico approaches provided a useful understanding of the effect of single point mutations on the structure-function relationship of GUSBp.

Effects of Non-Natural Amino Acid Incorporation into the Enzyme Core Region on Enzyme Structure and Function

Techniques to incorporate non-natural amino acids (NNAAs) have enabled biosynthesis of proteins containing new building blocks with unique structures, chemistry, and reactivity that are not found in natural amino acids. It is crucial to understand how incorporation of NNAAs affects protein function because NNAA incorporation may perturb critical function of a target protein. This study investigates how the site-specific incorporation of NNAAs affects catalytic properties of an enzyme. A NNAA with a hydrophobic and bulky sidechain, 3-(2-naphthyl)-alanine (2Nal), was site-specifically incorporated at six different positions in the hydrophobic core of a model enzyme, murine dihydrofolate reductase (mDHFR). The mDHFR variants with a greater change in van der Waals volume upon 2Nal incorporation exhibited a greater reduction in the catalytic efficiency. Similarly, the steric incompatibility calculated using RosettaDesign, a protein stability calculation program, correlated with the changes in the catalytic efficiency.

Can template-based protein models guide the design of sequence fitness for enhanced thermal stability of single domain antibodies?

We investigate the practical use of comparative (template-based) protein models in replica-exchange simulations of single-domain antibody (sdAb) chains to evaluate if the models can correctly predict in rank order the thermal susceptibility to unfold relative to experimental melting temperatures. The baseline model system is the recently determined crystallographic structure of a llama sdAb (denoted as A3), which exhibits an unusually high thermal stability. An evaluation of the simulation results for the A3 comparative model and crystal structure shows that, despite the overall low Cα root-mean-square deviation between the two structures, the model contains misfolded regions that yields a thermal profile of unraveling at a lower temperature. Yet comparison of the simulations of four different comparative models for sdAb A3, C8, A3C8 and E9, where A3C8 is a design of swapping the sequence of the complementarity determining regions of C8 onto the A3 framework, discriminated among the sequences to detect the highest and lowest experimental melting transition temperatures. Further structural analysis of A3 for selected alanine substitutions by a combined computational and experimental study found unexpectedly that the comparative model performed admirably in recognizing substitution 'hot spots' when using a support-vector machine algorithm.

Structure Based Thermostability Prediction Models for Protein Single Point Mutations with Machine Learning Tools

Thermostability issue of protein point mutations is a common occurrence in protein engineering. An application which predicts the thermostability of mutants can be helpful for guiding decision making process in protein design via mutagenesis. An in silico point mutation scanning method is frequently used to find “hot spots” in proteins for focused mutagenesis. ProTherm (http://gibk26.bio.kyutech.ac.jp/jouhou/Protherm/protherm.html) is a public database that consists of thousands of protein mutants’ experimentally measured thermostability. Two data sets based on two differently measured thermostability properties of protein single point mutations, namely the unfolding free energy change (ddG) and melting temperature change (dTm) were obtained from this database. Folding free energy change calculation from Rosetta, structural information of the point mutations as well as amino acid physical properties were obtained for building thermostability prediction models with informatics modeling tools. Five supervised machine learning methods (support vector machine, random forests, artificial neural network, naïve Bayes classifier, K nearest neighbor) and partial least squares regression are used for building the prediction models. Binary and ternary classifications as well as regression models were built and evaluated. Data set redundancy and balancing, the reverse mutations technique, feature selection, and comparison to other published methods were discussed. Rosetta calculated folding free energy change ranked as the most influential features in all prediction models. Other descriptors also made significant contributions to increasing the accuracy of the prediction models.

Structural and functional impact of missense mutations in TPMT: An integrated computational approach

BACKGROUND

Thiopurine S-methyltransferase (TPMT) detoxifies thiopurine drugs which are used for treatment of various diseases including inflammatory bowel disease (IBD), and hematological malignancies. Individual variation in TPMT activity results from mutations in TPMT gene. In this study, the effects of all the known missense mutations in TPMT enzyme were studied at the sequence and structural level

METHODS

A broad set of bioinformatic tools was used to assess all the known missense mutations affecting enzyme activity. The effects of these mutations on protein stability, aggregation propensity, and residue interaction network were analyzed.

RESULTS

Our results indicate that the missense mutations have diverse effects on TPMT structure and function. Stability and aggregation propensities are affected by various mutations. Several mutations also affect residues in ligand binding site.

CONCLUSIONS

In vitro study of missense mutation is laborious and time-consuming. However, computational methods can be used to obtain information about effects of missense mutations on protein structure. In this study, the effects of most of the mutations on enzyme activity could be explained by computational methods. Thus, the present approach can be used for understanding the protein structure-function relationships.

A non-foaming proteosurfactant engineered from Ranaspumin-2

Advances in biological surfactant proteins have already yielded a diverse range of benefits from dramatically improved survival rates for premature births to artificial photosynthesis. Presented here is the design, development, and analysis of a novel biosurfactant protein we call Surfactant Resisting Foam formatioN (SRFN). Starting with the Tungara frog's foam forming protein Ranaspumin-2, we have engineered a new surfactant protein with a destabilized hinge region to alter the kinetics and equilibrium of the protein structural transition from aqueous globular form to an extended surfactant structure at the air/water interface. SRFN is capable of approximately the same total surface tension reduction, but with the unique property of forming quickly collapsible foams. The difference in foam formation is attributed to the destabilizing glycine substitutions engineered into the hinge region. Surfactants used specifically to increase wettability, such as those used in agricultural applications would benefit from this new proteosurfactant since foamed liquid has greater wind resistance and decreased dispersal. Indeed, given growing concern of organsilicone surfactant effects on declining bee populations, biological surfactant proteins have several unique advantages over more common amphiphiles in that they can be renewably sourced, are environmentally friendly, degrade readily into non-toxic byproducts, and reduce surface tension without deleterious effects on cell membranes.

Value of predictive bioinformatics in inherited metabolic diseases

Typically, inherited metabolic diseases arise from point mutations in genes encoding metabolic enzymes. Although some of these mutations directly affect amino acid residues in the active sites of these enzymes, the majority do not. It is now well accepted that the majority of these disease-associated mutations exert their effects through alteration of protein stability, which causes a reduction in enzymatic activity. This finding suggests a way to predict the severity of newly discovered mutations. In silico prediction of the effects of amino acid sequence alterations on protein stability often correlates with disease severity. However, no stability prediction tool is perfect and, in general, better results are obtained if the predictions from a variety of tools are combined and then interpreted. In addition to predicted alterations to stability, the degree of conservation of a particular residue can also be a factor which needs to be taken into account: alterations to highly conserved residues are more likely to be associated with severe forms of the disease. The approach has been successfully applied in a variety of inherited metabolic diseases, but further improvements are necessary to enable robust translation into clinically useful tools.

A novel mutation in the TMC1 gene causes non-syndromic hearing loss in a Moroccan family

Autosomal recessive non-syndromic hearing loss (ARNSHL) is one of the most common genetic diseases in human and is subject to important genetic heterogeneity, rendering molecular diagnosis difficult. Whole-exome sequencing is thus a powerful strategy for this purpose. After excluding GJB2 mutation and other common mutations associated with hearing loss in Morocco, whole-exome sequencing was performed to study the genetic causes of one sibling with ARSHNL in a consanguineous Moroccan family. After filtering data and Sanger sequencing validation, one novel pathogenic homozygous mutation c.1810C>G (p.Arg604Gly) was identified in TMC1, a gene reported to cause deafness in various populations. Thus, we identified here the first mutation in the TMC1 gene in the Moroccan population causing non-syndromic hearing loss.

Computational analyses and prediction of guanylin deleterious SNPs

Human guanylin, coded by the GUCA2A gene, is a member of a peptide family that activates intestinal membrane guanylate cyclase, regulating electrolyte and water transport in intestinal and renal epithelia. Deregulation of guanylin peptide activity has been associated with colon adenocarcinoma, adenoma and intestinal polyps. Besides, it is known that mutations on guanylin receptors could be involved in meconium ileus. However, there are no previous works regarding the alterations driven by single nucleotide polymorphisms in guanylin peptides. A comprehensive in silico analysis of missense SNPs present in the GUCA2A gene was performed taking into account 16 prediction tools in order to select the deleterious variations for further evaluation by molecular dynamics simulations (50 ns). Molecular dynamics data suggest that the three out of five variants (Cys104Arg, Cys112Ser and Cys115Tyr) have undergone structural modifications in terms of flexibility, volume and/or solvation. In addition, two nonsense SNPs were identified, both preventing the formation of disulfide bonds and resulting in the synthesis of truncated proteins. In summary the structural analysis of missense SNPs is important to decrease the number of potential mutations to be in vitro evaluated for associating them with some genetic diseases. In addition, data reported here could lead to a better understanding of structural and functional aspects of guanylin peptides.

Serine 350 of human pregnane X receptor is crucial for its heterodimerization with retinoid X receptor alpha and transactivation of target genes in vitro and in vivo

The human pregnane X receptor (hPXR), a member of the nuclear receptor superfamily, senses xenobiotics and controls the transcription of genes encoding drug-metabolizing enzymes and transporters. The regulation of hPXR's transcriptional activation of its target genes is important for xenobiotic detoxification and endobiotic metabolism, and hPXR dysregulation can cause various adverse drug effects. Studies have implicated the putative phosphorylation site serine 350 (Ser(350)) in regulating hPXR transcriptional activity, but the mechanism of regulation remains elusive. Here we investigated the transactivation of hPXR target genes in vitro and in vivo by hPXR with a phosphomimetic mutation at Ser(350) (hPXR(S350D)). The S350D phosphomimetic mutation reduced the endogenous expression of cytochrome P450 3A4 (an hPXR target gene) in HepG2 and LS180 cells. Biochemical assays and structural modeling revealed that Ser(350) of hPXR is crucial for formation of the hPXR-retinoid X receptor alpha (RXRα) heterodimer. The S350D mutation abrogated heterodimerization in a ligand-independent manner, impairing hPXR-mediated transactivation. Further, in a novel humanized transgenic mouse model expressing the hPXR(S350D) transgene, we demonstrated that the S350D mutation alone is sufficient to impair hPXR transcriptional activity in mouse liver. This transgenic mouse model provides a unique tool to investigate the regulation and function of hPXR, including its non-genomic function, in vivo. Our finding that phosphorylation regulates hPXR activity has implications for development of novel hPXR antagonists and for safety evaluation during drug development.

Towards a "Golden Standard" for computing globin stability: Stability and structure sensitivity of myoglobin mutants

Fast and accurate computation of protein stability is increasingly important for e.g. protein engineering and protein misfolding diseases, but no consensus methods exist for important proteins such as globins, and performance may depend on the type of structural input given. This paper reports benchmarking of six protein stability calculators (POPMUSIC 2.1, I-Mutant 2.0, I-Mutant 3.0, CUPSAT, SDM, and mCSM) against 134 experimental stability changes for mutations of sperm-whale myoglobin. Six different high-resolution structures were used to test structure sensitivity that may impair protein calculations. The trend accuracy of the methods decreased as I-Mutant 2.0 (R=0.64-0.65), SDM (R=0.57-0.60), POPMUSIC2.1 (R=0.54-0.57), I-Mutant 3.0 (R=0.53-0.55), mCSM (R=0.35-0.47), and CUPSAT (R=0.25-0.48). The mean signed errors increased as SDM<CUPSAT<I-Mutant 2.0<I-Mutant 3.0<POPMUSIC 2.1<mCSM. Mean absolute errors increased as I-Mutant 2.0<I-Mutant 3.0<POPMUSIC 2.1<CUPSAT<SDM<mCSM. Structural sensitivity increased as I-Mutant 3.0 (0.05)<I-Mutant 2.0 (0.09)<POPMUSIC 2.1 (0.12)<SDM (0.18)<mCSM (0.27)<CUPSAT (0.58). Leaving out heterogeneous experimental data did not change conclusions. The distinct performances reveal room for improvement, but I-Mutant 2.0 is proficient for this purpose, as further validated against a data set of related cytochrome c like proteins. The results also emphasize the importance of high-quality crystal structures and reveal structure-dependent effects even in the near-atomic resolution limit.

A novel pathogenic variant in PRF1 associated with hemophagocytic lymphohistiocytosis

Familial Hemophagocytic Lymphohistiocytosis type 2 (FHL2) results from mutations in PRF1. We described two unrelated individuals who presented with FHL, in whom severely impaired NK cytotoxicity and decrease perforin expression was observed. DNA sequencing of PRF1 demonstrated that both were not only heterozygous for the p.54R > C/91A > V haplotype but also presented with the novel variant p.47G > V at the perforin protein. Perforin mRNA was found to be increased in a individual with that genotype. A carrier of the novel variant also demonstrated altered perforin mRNA and protein expression. Phylogenetic analysis and multiple alignments with perforin orthologous demonstrated a high level of conservation at Gly47. PolyPhen-2 and PROVEAN predicted p.47G > V to be "probably damaging" and "deleterious", respectively. A thermodynamic analysis showed that this variant was highly stabilizing, decreasing the protein internal energy. The ab initio perforin molecular modeling indicated that Gly47 is buried inside the hydrophobic core of the MACPF domain, which is crucial for the lytic pore formation and protein oligomerization. After the in silico induction of the p.47G > V mutation, Val47 increased the interactions with the surrounding amino acids due to its size and physical properties, avoiding a proper conformational change of the domain. To our knowledge, this is the first description supporting that p.47G > V is a pathogenic variant that in conjunction with p.54R > C/91A > V might result in the clinical phenotype of FHL2.

Functional Validation of Rare Human Genetic Variants Involved in Homologous Recombination Using Saccharomyces cerevisiae

Systems for the repair of DNA double-strand breaks (DSBs) are necessary to maintain genome integrity and normal functionality of cells in all organisms. Homologous recombination (HR) plays an important role in repairing accidental and programmed DSBs in mitotic and meiotic cells, respectively. Failure to repair these DSBs causes genome instability and can induce tumorigenesis. Rad51 and Rad52 are two key proteins in homologous pairing and strand exchange during DSB-induced HR; both are highly conserved in eukaryotes. In this study, we analyzed pathogenic single nucleotide polymorphisms (SNPs) in human RAD51 and RAD52 using the Polymorphism Phenotyping (PolyPhen) and Sorting Intolerant from Tolerant (SIFT) algorithms and observed the effect of mutations in highly conserved domains of RAD51 and RAD52 on DNA damage repair in a Saccharomyces cerevisiae-based system. We identified a number of rad51 and rad52 alleles that exhibited severe DNA repair defects. The functionally inactive SNPs were located near ATPase active site of Rad51 and the DNA binding domain of Rad52. The rad51-F317I, rad52-R52W, and rad52-G107C mutations conferred hypersensitivity to methyl methane sulfonate (MMS)-induced DNA damage and were defective in HR-mediated DSB repair. Our study provides a new approach for detecting functional and loss-of-function genetic polymorphisms and for identifying causal variants in human DNA repair genes that contribute to the initiation or progression of cancer.

Thermal stabilization of dihydrofolate reductase using monte carlo unfolding simulations and its functional consequences

Design of proteins with desired thermal properties is important for scientific and biotechnological applications. Here we developed a theoretical approach to predict the effect of mutations on protein stability from non-equilibrium unfolding simulations. We establish a relative measure based on apparent simulated melting temperatures that is independent of simulation length and, under certain assumptions, proportional to equilibrium stability, and we justify this theoretical development with extensive simulations and experimental data. Using our new method based on all-atom Monte-Carlo unfolding simulations, we carried out a saturating mutagenesis of Dihydrofolate Reductase (DHFR), a key target of antibiotics and chemotherapeutic drugs. The method predicted more than 500 stabilizing mutations, several of which were selected for detailed computational and experimental analysis. We find a highly significant correlation of r = 0.65–0.68 between predicted and experimentally determined melting temperatures and unfolding denaturant concentrations for WT DHFR and 42 mutants. The correlation between energy of the native state and experimental denaturation temperature was much weaker, indicating the important role of entropy in protein stability. The most stabilizing point mutation was D27F, which is located in the active site of the protein, rendering it inactive. However for the rest of mutations outside of the active site we observed a weak yet statistically significant positive correlation between thermal stability and catalytic activity indicating the lack of a stability-activity tradeoff for DHFR. By combining stabilizing mutations predicted by our method, we created a highly stable catalytically active E. coli DHFR mutant with measured denaturation temperature 7.2°C higher than WT. Prediction results for DHFR and several other proteins indicate that computational approaches based on unfolding simulations are useful as a general technique to discover stabilizing mutations.

All-atom molecular simulations have provided valuable insight into the workings of molecular machines and the folding and unfolding of proteins. However, commonly employed molecular dynamics simulations suffer from a limitation in accessible time scale, making it difficult to model large-scale unfolding events in a realistic amount of simulation time without employing unrealistically high temperatures. Here, we describe a rapid all-atom Monte Carlo simulation approach to simulate unfolding of the essential bacterial enzyme Dihydrofolate Reductase (DHFR) and all possible single point-mutants. We use these simulations to predict which mutants will be more thermodynamically stable (i.e., reside more often in the native folded state vs. the unfolded state) than the wild-type protein, and we confirm our predictions experimentally, creating several highly stable and catalytically active mutants. Thermally stable active engineered proteins can be used as a starting point in directed evolution experiments to evolve new functions on the background of this additional “reservoir of stability.” The stabilized enzyme may be able to accumulate a greater number of destabilizing yet functionally important mutations before unfolding, protease digestion, and aggregation abolish its activity.

Two conserved amino acids of juxtaposed domains of a ribosomal maturation protein CgtA sustain its optimal GTPase activity

CgtA is a highly conserved ribosome binding protein involved in ribosome biogenesis and associated with stringent response. It is a 55 KDa GTPase protein consisting of GTPase, Obg and C-terminal domains. The function of the latter two domains was not clear and despite the importance, the mode of action of CgtA is still largely unknown. Knocking out of CgtA gene is lethal and mutations lead to growth, sporulation and developmental defects in bacteria. It was found that a growth defect and pinhole size colony morphology of Bacillus subtilis was associated with a Gly92Asp point mutation on the Obg domain of its CgtA protein, instead of its GTPase domain. CgtA is an important and essential protein of the deadly diarrhea causing bacteria Vibrio cholerae and in order to investigate the mode of action of the V. cholerae CgtA we have utilized this information. We measured the GTPase activity of V. cholerae CgtA (CgtAvc) protein in the presence of purified ribosome. Our results showed 5-fold increased GTP hydrolysis activity compared to its intrinsic activity. Then we explored the GTPase activity of the mutated CgtAvc (Gly98Asp) located at the Obg domain, which reduced the GTP hydrolysis rate to half. The double point mutations (Gly98Asp, and Tyr194Gly) encompassing another conserved residue, Tyr194, located at the diagonally opposite position in the GTPase domain largely restored (about 82%) the reduced GTPase activity, revealing a fine-tuned inter-domain movement readily associated with the GTPase activity of CgtA and thus maintaining the proper functioning of the CgtA protein.

MAESTRO--multi agent stability prediction upon point mutations

BACKGROUND

Point mutations can have a strong impact on protein stability. A change in stability may subsequently lead to dysfunction and finally cause diseases. Moreover, protein engineering approaches aim to deliberately modify protein properties, where stability is a major constraint. In order to support basic research and protein design tasks, several computational tools for predicting the change in stability upon mutations have been developed. Comparative studies have shown the usefulness but also limitations of such programs.

RESULTS

We aim to contribute a novel method for predicting changes in stability upon point mutation in proteins called MAESTRO. MAESTRO is structure based and distinguishes itself from similar approaches in the following points: (i) MAESTRO implements a multi-agent machine learning system. (ii) It also provides predicted free energy change (Δ ΔG) values and a corresponding prediction confidence estimation. (iii) It provides high throughput scanning for multi-point mutations where sites and types of mutation can be comprehensively controlled. (iv) Finally, the software provides a specific mode for the prediction of stabilizing disulfide bonds. The predictive power of MAESTRO for single point mutations and stabilizing disulfide bonds is comparable to similar methods.

CONCLUSIONS

MAESTRO is a versatile tool in the field of stability change prediction upon point mutations. Executables for the Linux and Windows operating systems are freely available to non-commercial users from http://biwww.che.sbg.ac.at/MAESTRO.

Structural and functional influences of coagulation factor XIII subunit B heterozygous missense mutants

The coagulation factor XIII(FXIII) is a plasma circulating heterotetrameric protransglutaminase that acts at the end of the coagulation cascade by covalently cross-linking preformed fibrin clots (to themselves and to fibrinolytic inhibitors) in order to stabilize them against fibrinolysis. It circulates in the plasma as a heterotetramer composed of two homomeric catalytic Factor XIIIA₂ (FXIIIA₂) and two homomeric protective/carrier Factor XIIIB₂ subunit (FXIIIB₂). Congenital deficiency of FXIII is of two types: severe homozygous/compound heterozygous FXIII deficiency which results in severe bleeding symptoms and mild heterozygous FXIII deficiency which is associated with mild bleeding (only upon trauma) or an asymptomatic phenotype. Defects in the F13B gene (Factor XIIIB subunit) occur more frequently in mild FXIII deficiency patients than in severe FXIII deficiency. We had recently reported secretion-related defects for seven previously reported F13B missense mutations. In the present study we further analyze the underlying molecular pathological mechanisms as well as the heterozygous expression phenotype for these mutations using a combination of in vitro heterologous expression (in HEK293T cells) and confocal microscopy. In combination with the in vitro work we have also performed an in silico solvated molecular dynamic simulation study on previously reported FXIIIB subunit sushi domain homology models in order to predict the putative structure-functional impact of these mutations. We were able to categorize the mutations into the following functional groups that: (1) affect antigenic stability as well as binding to FXIIIA subunit, that is, Cys5Arg, Cys316Phe, and Pro428Ser (2) affect binding to FXIIIA subunit with little or no influence on antigenic stability, that is, Ile81Asn and Val401Gln c) influence neither aspects and are most likely causality linked polymorphisms or functional polymorphisms, that is, Leu116Phe and Val217Ile. The Cys5Arg mutation was the only mutation to show a direct secretion-based defect since the mutated protein was observed to accumulate in the endoplasmic reticulum.

CHOPIN: a web resource for the structural and functional proteome of Mycobacterium tuberculosis

Tuberculosis kills more than a million people annually and presents increasingly high levels of resistance against current first line drugs. Structural information about Mycobacterium tuberculosis (Mtb) proteins is a valuable asset for the development of novel drugs and for understanding the biology of the bacterium; however, only about 10% of the ∼4000 proteins have had their structures determined experimentally. The CHOPIN database assigns structural domains and generates homology models for 2911 sequences, corresponding to ∼73% of the proteome. A sophisticated pipeline allows multiple models to be created using conformational states characteristic of different oligomeric states and ligand binding, such that the models reflect various functional states of the proteins. Additionally, CHOPIN includes structural analyses of mutations potentially associated with drug resistance. Results are made available at the web interface, which also serves as an automatically updated repository of all published Mtb experimental structures. Its RESTful interface allows direct and flexible access to structures and metadata via intuitive URLs, enabling easy programmatic use of the models.

Database URL: http://structure.bioc.cam.ac.uk/chopin

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the 'search space' of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the 'best' amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.

Analysis of HGD Gene Mutations in Patients with Alkaptonuria from the United Kingdom: Identification of Novel Mutations

Alkaptonuria (AKU) is a rare autosomal recessive disorder with incidence ranging from 1:100,000 to 1:250,000. The disorder is caused by a deficiency of the enzyme homogentisate 1,2-dioxygenase (HGD), which results from defects in the HGD gene. This enzyme converts homogentisic acid to maleylacetoacetate and has a major role in the catabolism of phenylalanine and tyrosine. To elucidate the mutation spectrum of the HGD gene in patients with alkaptonuria from 42 patients attending the National Alkaptonuria Centre, 14 exons of the HGD gene and the intron-exon boundaries were analysed by PCR-based sequencing. A total of 34 sequence variants was observed, confirming the genetic heterogeneity of AKU. Of these mutations, 26 were missense substitutions and four splice site mutations. There were two deletions and one duplication giving rise to frame shifts and one substitution abolishing the translation termination codon (no stop). Nine of the mutations were previously unreported novel variants. Using computational approaches based on the 3D structure, these novel mutations are predicted to affect the activity of the protein complex through destabilisation of the individual protomer structure or through disruption of protomer-protomer interactions.

Mutagenesis and functional analysis of the pore-forming toxin HALT-1 from Hydra magnipapillata

Actinoporins are small 18.5 kDa pore-forming toxins. A family of six actinoporin genes has been identified in the genome of Hydra magnipapillata, and HALT-1 (Hydra actinoporin-like toxin-1) has been shown to have haemolytic activity. In this study, we have used site-directed mutagenesis to investigate the role of amino acids in the pore-forming N-terminal region and the conserved aromatic cluster required for cell membrane binding. A total of 10 mutants of HALT-1 were constructed and tested for their haemolytic and cytolytic activity on human erythrocytes and HeLa cells, respectively. Insertion of 1–4 negatively charged residues in the N-terminal region of HALT-1 strongly reduced haemolytic and cytolytic activity, suggesting that the length or charge of the N-terminal region is critical for pore-forming activity. Moreover, substitution of amino acids in the conserved aromatic cluster reduced haemolytic and cytolytic activity by more than 80%, suggesting that these aromatic amino acids are important for attachment to the lipid membrane as shown for other actinoporins. The results suggest that HALT-1 and other actinoporins share similar mechanisms of pore formation and that it is critical for HALT-1 to maintain an amphipathic helix at the N-terminus and an aromatic amino acid-rich segment at the site of membrane binding.

A TMC1 (transmembrane channel-like 1) mutation (p.S320R) in a Polish family with hearing impairment

After excluding frequent mutations in common genes like GJB2, SLC26A4 and MT-RNR1 by straightforward Sanger sequencing in about 20 Polish families with hearing impairment, new and possibly pathogenic mutations were searched for by next-generation sequencing (NGS) screening using a specialised panel including more than 80 genes connected with hearing disorders. Due to high rates of false-positive pathogen predictions for newly discovered single-nucleotide polymorphisms (SNPs), different prediction models were combined to enhance the prediction power. In one family with a record of over four generations, II,3 and II,4 were suspected of hearing impairment without medical records. A male person (III,2) displayed hearing loss of 40 dB hearing level (HL) and his two sons, IV,1 and IV,2, were both affected; one with 90 dB HL and the other with 40 dB HL. Here, one heterozygous, non-synonymous variant was detected, with the SNP causing an amino acid substitution in TMC1 (transmembrane channel-like 1), a gene reported with many mutations in DFNA36 and DFNB7/11 (OMIM #606705 and #600974, respectively). Until now, the substitution p.S320R has not been described in any database. Instead of the significance of this mutation by bioinformatics tools, we confirmed the genotype-phenotype co-segregation in family members. The involvement of TMC1 in hereditary hearing impairment has not been observed in the Polish population so far.

Weak association of glyoxalase 1 (GLO1) variants with autism spectrum disorder

The prevalence of the autism spectrum disorder (ASD) was recently estimated to 1 in 88 children by the CDC MMWR. In up to 25 % of the cases, the genetic cause can be identified. Past studies identified increased level of advanced glycation end products (AGE) in the brain samples of ASD patients. The methylglyoxal (MG) is one of the main precursors for AGE formation. Humans developed effective mechanism of the MG metabolism involving two enzymes glyoxalase 1 (GLO1) and hydroxyacylglutathione hydrolase (HAGH). Our aim was to analyse genetic variants of GLO1 and HAGH in population of 143 paediatric participants with ASD. We detected 7 genetic variants in GLO1 and 16 variants in HAGH using high-resolution melting (HRM) analysis. A novel association between variant rs1049346 and ASD [OR (allele C)] = 1.5; 95 % CI = 1.1-2.2 and p < 0.05) was identified, and weak association between ASD and variant rs2736654 [OR (allele A)] = 2.2; 95 % CI = 0.99-4.9; p = 0.045) was confirmed. Additionally, a novel genetic variant (GLO1 c.484G > A, p.Ala161Thr) with predicted potentially damaging effect on the activity of the glyoxalase 1 that may contribute to the aetiology of ASD was identified in one participant with ASD. No association between genetic variants of the HAGH gene and ASD was found. Increased level of MG and, consequently, AGEs can induce oxidative stress, mitochondrial dysfunction and inflammation all of which have been implicated to act in the aetiology of the ASD. Our results indicate potential importance of MG metabolism in ASD. However, these results must be interpreted with caution until a causative relation is demonstrated.

A Micropolymorphism Altering the Residue Triad 97/114/156 Determines the Relative Levels of Tapasin Independence and Distinct Peptide Profiles for HLA-A(*)24 Allotypes

While many HLA class I molecules interact directly with the peptide loading complex (PLC) for conventional loading of peptides certain class I molecules are able to present peptides in a way that circumvents the PLC components. We investigated micropolymorphisms at position 156 of HLA-A(*)24 allotypes and their effects on PLC dependence for assembly and peptide binding specificities. HLA-A(*)24:06(156Trp) and HLA-A(*)24:13(156Leu) showed high levels of cell surface expression while HLA-A(*)24:02(156Gln) was expressed at low levels in tapasin deficient cells. Peptides presented by these allelic variants showed distinct differences in features and repertoire. Immunoprecipitation experiments demonstrated all the HLA-A(*)24/156 variants to associate at similar levels with tapasin when present. Structurally, HLA-A(*)24:02 contains the residue triad Met97/His114/Gln156 and a Trp156 or Leu156 polymorphism provides tapasin independence by stabilizing these triad residues, thus generating an energetically stable and a more peptide receptive environment. Micropolymorphisms at position 156 can influence the generic peptide loading pathway for HLA-A(*)24 by altering their tapasin dependence for peptide selection. The trade-off for this tapasin independence could be the presentation of unusual ligands by these alleles, imposing significant risk following hematopoietic stem cell transplantation (HSCT).

Tri-peptide reference structures for the calculation of relative solvent accessible surface area in protein amino acid residues

Relative amino acid residue solvent accessibility values allow the quantitative comparison of atomic solvent-accessible surface areas in different residue types and physical environments in proteins and in protein structural alignments. Geometry-optimised tri-peptide structures in extended solvent-exposed reference conformations have been obtained for 43 amino acid residue types at a high level of quantum chemical theory. Significant increases in side-chain solvent accessibility, offset by reductions in main-chain atom solvent exposure, were observed for standard residue types in partially geometry-optimised structures when compared to non-minimised models built from identical sets of proper dihedral angles abstracted from the literature. Optimisation of proper dihedral angles led most notably to marked increases of up to 54% in proline main-chain atom solvent accessibility compared to literature values. Similar effects were observed for fully-optimised tri-peptides in implicit solvent. The relief of internal strain energy was associated with systematic variation in N, C(α) and C(β) atom solvent accessibility across all standard residue types. The results underline the importance of optimisation of 'hard' degrees of freedom (bond lengths and valence bond angles) and improper dihedral angle values from force field or other context-independent reference values, and impact on the use of standardised fixed internal co-ordinate geometry in sampling approaches to the determination of absolute values of protein amino acid residue solvent accessibility. Quantum chemical methods provide a useful and accurate alternative to molecular mechanics methods to perform energy minimisation of peptides containing non-standard (chemically modified) amino acid residues frequently present in experimental protein structure data sets, for which force field parameters may not be available. Reference tri-peptide atomic co-ordinate sets including hydrogen atoms are made freely available.

An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma

Mutations in the von Hippel-Lindau (VHL) gene are pathogenic in VHL disease, congenital polycythaemia and clear cell renal carcinoma (ccRCC). pVHL forms a ternary complex with elongin C and elongin B, critical for pVHL stability and function, which interacts with Cullin-2 and RING-box protein 1 to target hypoxia-inducible factor for polyubiquitination and proteasomal degradation. We describe a comprehensive database of missense VHL mutations linked to experimental and clinical data. We use predictions from in silico tools to link the functional effects of missense VHL mutations to phenotype. The risk of ccRCC in VHL disease is linked to the degree of destabilization resulting from missense mutations. An optimized binary classification system (symphony), which integrates predictions from five in silico methods, can predict the risk of ccRCC associated with VHL missense mutations with high sensitivity and specificity. We use symphony to generate predictions for risk of ccRCC for all possible VHL missense mutations and present these predictions, in association with clinical and experimental data, in a publically available, searchable web server.

A sialoreceptor binding motif in the Mycoplasma synoviae adhesin VlhA

Mycoplasma synoviae depends on its adhesin VlhA to mediate cytadherence to sialylated host cell receptors. Allelic variants of VlhA arise through recombination between an assemblage of promoterless vlhA pseudogenes and a single transcription promoter site, creating lineages of M. synoviae that each express a different vlhA allele. The predicted full-length VlhA sequences adjacent to the promoter of nine lineages of M. synoviae varying in avidity of cytadherence were aligned with that of the reference strain MS53 and with a 60-a.a. hemagglutinating VlhA C-terminal fragment from a Tunisian lineage of strain WVU1853^T. Seven different sequence variants of an imperfectly conserved, single-copy, 12-a.a. candidate cytadherence motif were evident amid the flanking variable residues of the 11 total sequences examined. The motif was predicted to adopt a short hairpin structure in a low-complexity region near the C-terminus of VlhA. Biotinylated synthetic oligopeptides representing four selected variants of the 12-a.a. motif, with the whole synthesized 60-a.a. fragment as a positive control, differed (P<0.01) in the extent they bound to chicken erythrocyte membranes. All bound to a greater extent (P<0.01) than scrambled or irrelevant VlhA domain negative control peptides did. Experimentally introduced branched-chain amino acid (BCAA) substitutions Val3Ile and Leu7Ile did not significantly alter binding, whereas fold-destabilizing substitutions Thr4Gly and Ala9Gly tended to reduce it (P<0.05). Binding was also reduced to background levels (P<0.01) when the peptides were exposed to desialylated membranes, or were pre-saturated with free sialic acid before exposure to untreated membranes. From this evidence we conclude that the motif P-X-(BCAA)-X-F-X-(BCAA)-X-A-K-X-G binds sialic acid and likely mediates VlhA-dependent M. synoviae attachment to host cells. This conserved mechanism retains the potential for fine-scale rheostasis in binding avidity, which could be a general characteristic of pathogens that depend on analogous systems of antigenically variable adhesins. The motif may be useful to identify previously unrecognized adhesins.

Platinum: a database of experimentally measured effects of mutations on structurally defined protein-ligand complexes

Drug resistance is a major challenge for the treatment of many diseases and a significant concern throughout the drug development process. The ability to understand and predict the effects of mutations on protein–ligand affinities and their roles in the emergence of resistance would significantly aid treatment and drug design strategies. In order to study and understand the impacts of missense mutations on the interaction of ligands with the proteome, we have developed Platinum (http://structure.bioc.cam.ac.uk/platinum). This manually curated, literature-derived database, comprising over 1000 mutations, associates for the first time experimental information on changes in affinity with three-dimensional structures of protein–ligand complexes. To minimize differences arising from experimental techniques and to directly compare binding affinities, Platinum considers only changes measured by the same group and with the same amino-acid sequence used for structure determination, providing a direct link between protein structure, how a ligand binds and how mutations alter the affinity of the ligand of the protein. We believe Platinum will be an invaluable resource for understanding the effects of mutations that give rise to drug resistance, a major problem emerging in pandemics including those caused by the influenza virus, in infectious diseases such as tuberculosis, in cancer and in many other life-threatening illnesses.

Functional characterisation of a novel mutation affecting the catalytic domain of MMP2 in siblings with multicentric osteolysis, nodulosis and arthropathy

Multicentric osteolysis, nodulosis and arthropathy (MONA) is a rare autosomal recessive disorder. To date, 13 mutations of the matrix metalloproteinase 2 (MMP2) gene have been detected in 26 patients with MONA and other osteolytic syndromes. Here, we describe the molecular and functional analysis of a novel MMP2 mutation in two adult Italian siblings with MONA. Both siblings displayed palmar-plantar subcutaneous nodules, tendon retractions, limb arthropathies, osteolysis in the toes and pigmented fibrous skin lesions. Molecular analysis identified a homozygous MMP2 missense mutation in exon 8 c.1228G>C (p.G410R), not detected in 260 controls and predicted by several bioinformatic tools to be pathogenic. By protein modelling, the mutant residue was predicted to affect the main chain conformation of the catalytic domain. Gelatin zymography, the gold standard test for MMP2 function, of serum-free conditioned medium from G410R-MMP2-expressing human embryonic kidney (HEK) cells, showed a complete loss of gelatinolytic activity. The novel mutation is located in the catalytic domain, as are 3 (p.E404K, p.V400del and p.G406D) of the other 13 MMP2 mutations described to date; however, p.G410R underlies a phenotype that is only partially overlapping that of other MMP2 exon 8 mutation carriers. Our results further delineate the complexity of genotype-phenotype correlations in MONA, broaden the repertoire of reported MMP2 mutation and enhance the comprehension of the protein motifs crucial for MMP2 catalytic activity.

The role of the interactome in the maintenance of deleterious variability in human populations

Recent genomic projects have revealed the existence of an unexpectedly large amount of deleterious variability in the human genome. Several hypotheses have been proposed to explain such an apparently high mutational load. However, the mechanisms by which deleterious mutations in some genes cause a pathological effect but are apparently innocuous in other genes remain largely unknown. This study searched for deleterious variants in the 1,000 genomes populations, as well as in a newly sequenced population of 252 healthy Spanish individuals. In addition, variants causative of monogenic diseases and somatic variants from 41 chronic lymphocytic leukaemia patients were analysed. The deleterious variants found were analysed in the context of the interactome to understand the role of network topology in the maintenance of the observed mutational load. Our results suggest that one of the mechanisms whereby the effect of these deleterious variants on the phenotype is suppressed could be related to the configuration of the protein interaction network. Most of the deleterious variants observed in healthy individuals are concentrated in peripheral regions of the interactome, in combinations that preserve their connectivity, and have a marginal effect on interactome integrity. On the contrary, likely pathogenic cancer somatic deleterious variants tend to occur in internal regions of the interactome, often with associated structural consequences. Finally, variants causative of monogenic diseases seem to occupy an intermediate position. Our observations suggest that the real pathological potential of a variant might be more a systems property rather than an intrinsic property of individual proteins.

Computational and experimental approaches to reveal the effects of single nucleotide polymorphisms with respect to disease diagnostics

DNA mutations are the cause of many human diseases and they are the reason for natural differences among individuals by affecting the structure, function, interactions, and other properties of DNA and expressed proteins. The ability to predict whether a given mutation is disease-causing or harmless is of great importance for the early detection of patients with a high risk of developing a particular disease and would pave the way for personalized medicine and diagnostics. Here we review existing methods and techniques to study and predict the effects of DNA mutations from three different perspectives: in silico, in vitro and in vivo. It is emphasized that the problem is complicated and successful detection of a pathogenic mutation frequently requires a combination of several methods and a knowledge of the biological phenomena associated with the corresponding macromolecules.

DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach

Cancer genome and other sequencing initiatives are generating extensive data on non-synonymous single nucleotide polymorphisms (nsSNPs) in human and other genomes. In order to understand the impacts of nsSNPs on the structure and function of the proteome, as well as to guide protein engineering, accurate in silicomethodologies are required to study and predict their effects on protein stability. Despite the diversity of available computational methods in the literature, none has proven accurate and dependable on its own under all scenarios where mutation analysis is required. Here we present DUET, a web server for an integrated computational approach to study missense mutations in proteins. DUET consolidates two complementary approaches (mCSM and SDM) in a consensus prediction, obtained by combining the results of the separate methods in an optimized predictor using Support Vector Machines (SVM). We demonstrate that the proposed method improves overall accuracy of the predictions in comparison with either method individually and performs as well as or better than similar methods. The DUET web server is freely and openly available at http://structure.bioc.cam.ac.uk/duet.

The spatial organization of non-homologous end joining: from bridging to end joining

Non-homologous end joining (NHEJ) repairs DNA double-strand breaks generated by DNA damage and also those occurring in V(D)J recombination in immunoglobulin and T cell receptor production in the immune system. In NHEJ DNA-PKcs assembles with Ku heterodimer on the DNA ends at double-strand breaks, in order to bring the broken ends together and to assemble other proteins, including DNA ligase IV (LigIV), required for DNA repair. Here we focus on structural aspects of the interactions of LigIV with XRCC4, XLF, Artemis and DNA involved in the bridging and end-joining steps of NHEJ. We begin with a discussion of the role of XLF, which interacts with Ku and forms a hetero-filament with XRCC4; this likely forms a scaffold bridging the DNA ends. We then review the well-defined interaction of XRCC4 with LigIV, and discuss the possibility of this complex interrupting the filament formation, so positioning the ligase at the correct positions close to the broken ends. We also describe the interactions of LigIV with Artemis, the nuclease that prepares the ends for ligation and also interacts with DNA-PK. Lastly we review the likely affects of Mendelian mutations on these multiprotein assemblies and their impacts on the form of inherited disease.

SDS, a structural disruption score for assessment of missense variant deleteriousness

We have developed a novel structure-based evaluation for missense variants that explicitly models protein structure and amino acid properties to predict the likelihood that a variant disrupts protein function. A structural disruption score (SDS) is introduced as a measure to depict the likelihood that a case variant is functional. The score is constructed using characteristics that distinguish between causal and neutral variants within a group of proteins. The SDS score is correlated with standard sequence-based deleteriousness, but shows promise for improving discrimination between neutral and causal variants at less conserved sites. The prediction was performed on 3-dimentional structures of 57 gene products whose homozygous SNPs were identified as case-exclusive variants in an exome sequencing study of epilepsy disorders. We contrasted the candidate epilepsy variants with scores for likely benign variants found in the EVS database, and for positive control variants in the same genes that are suspected to promote a range of diseases. To derive a characteristic profile of damaging SNPs, we transformed continuous scores into categorical variables based on the score distribution of each measurement, collected from all possible SNPs in this protein set, where extreme measures were assumed to be deleterious. A second epilepsy dataset was used to replicate the findings. Causal variants tend to receive higher sequence-based deleterious scores, induce larger physico-chemical changes between amino acid pairs, locate in protein domains, buried sites or on conserved protein surface clusters, and cause protein destabilization, relative to negative controls. These measures were agglomerated for each variant. A list of nine high-priority putative functional variants for epilepsy was generated. Our newly developed SDS protocol facilitates SNP prioritization for experimental validation.

Modulation of protein stability and aggregation properties by surface charge engineering

An attempt to alter protein surface charges through traditional protein engineering approaches often affects the native protein structure significantly and induces misfolding. This limitation is a major hindrance in modulating protein properties through surface charge variations. In this study, as a strategy to overcome such a limitation, we attempted to co-introduce stabilizing mutations that can neutralize the destabilizing effect of protein surface charge variation. Two sets of rational mutations were designed; one to increase the number of surface charged amino acids and the other to decrease the number of surface charged amino acids by mutating surface polar uncharged amino acids and charged amino acids, respectively. These two sets of mutations were introduced into Green Fluorescent Protein (GFP) together with or without stabilizing mutations. The co-introduction of stabilizing mutations along with mutations for surface charge modification allowed us to obtain functionally active protein variants (s-GFP(+15-17) and s-GFP(+5-6)). When the protein properties such as fluorescent activity, folding rate and kinetic stability were assessed, we found the possibility that the protein stability can be modulated independently of activity and folding by engineering protein surface charges. The aggregation properties of GFP could also be altered through the surface charge engineering.

Strigolactone promotes degradation of DWARF14, an α/β hydrolase essential for strigolactone signaling in Arabidopsis

Strigolactones (SLs) are phytohormones that play a central role in regulating shoot branching. SL perception and signaling involves the F-box protein MAX2 and the hydrolase DWARF14 (D14), proposed to act as an SL receptor. We used strong loss-of-function alleles of the Arabidopsis thaliana D14 gene to characterize D14 function from early axillary bud development through to lateral shoot outgrowth and demonstrated a role of this gene in the control of flowering time. Our data show that D14 distribution in vivo overlaps with that reported for MAX2 at both the tissue and subcellular levels, allowing physical interactions between these proteins. Our grafting studies indicate that neither D14 mRNA nor the protein move over a long range upwards in the plant. Like MAX2, D14 is required locally in the aerial part of the plant to suppress shoot branching. We also identified a mechanism of SL-induced, MAX2-dependent proteasome-mediated degradation of D14. This negative feedback loop would cause a substantial drop in SL perception, which would effectively limit SL signaling duration and intensity.

Computing stability effects of mutations in human superoxide dismutase 1

Protein stability is affected in several diseases and is of substantial interest in efforts to correlate genotypes to phenotypes. Superoxide dismutase 1 (SOD1) is a suitable test case for such correlations due to its abundance, stability, available crystal structures and thermochemical data, and physiological importance. In this work, stability changes of SOD1 mutations were computed with five methods, CUPSAT, I-Mutant2.0, I-Mutant3.0, PoPMuSiC, and SDM, with emphasis on structural sensitivity as a potential issue in structure-based protein calculation. The large correlation between experimental literature data of SOD1 dimers and monomers (r = 0.82) suggests that mutations in separate protein monomers are mostly additive. PoPMuSiC was most accurate (typical MAE ~ 1 kcal/mol, r ~ 0.5). The relative performance of the methods was not very structure-dependent, and the more accurate methods also displayed less structural sensitivity, with the standard deviation from different high-resolution structures down to ~0.2 kcal/mol. Structures of variable resolution and number of protein copies locally affected specific sites, emphasizing the use of state-relevant crystal structures when such sites are of interest, but had little impact on overall batch estimates. Protein-interaction effects (as a mimic of crystal packing) were small for the more accurate methods. Thus, batch computations, relevant to, e.g., comparisons of disease/nondisease mutant sets or different clades in phylogenetic trees, are much more significant than single mutant calculations and may be the only meaningful way to computationally bridge the genotype-phenotype gap of proteomics. Finally, mutations involving glycine were most difficult to model, of relevance to future method improvement. This could be due to structure changes (glycine has a low structural propensity) or water colocalization with glycine.

Recurrent mutations in epigenetic regulators, RHOA and FYN kinase in peripheral T cell lymphomas

Peripheral T cell lymphomas (PTCLs) are a heterogeneous and poorly understood group of non-Hodgkin lymphomas. Here we combined whole-exome sequencing of 12 tumor-normal DNA pairs, RNA sequencing analysis and targeted deep sequencing to identify new genetic alterations in PTCL transformation. These analyses identified highly recurrent epigenetic factor mutations in TET2, DNMT3A and IDH2 as well as a new highly prevalent RHOA mutation encoding a p.Gly17Val alteration present in 22 of 35 (67%) angioimmunoblastic T cell lymphoma (AITL) samples and in 8 of 44 (18%) PTCL, not otherwise specified (PTCL-NOS) samples. Mechanistically, the RHOA Gly17Val protein interferes with RHOA signaling in biochemical and cellular assays, an effect potentially mediated by the sequestration of activated guanine-exchange factor (GEF) proteins. In addition, we describe new and recurrent, albeit less frequent, genetic defects including mutations in FYN, ATM, B2M and CD58 implicating SRC signaling, impaired DNA damage response and escape from immune surveillance mechanisms in the pathogenesis of PTCL.