Protein binding specificity versus promiscuity

Interactions between macromolecules in general, and between proteins in particular, are essential for any life process. Examples include transfer of information, inhibition or activation of function, molecular recognition as in the immune system, assembly of macromolecular structures and molecular machines, and more. Proteins interact with affinities ranging from millimolar to femtomolar and, because affinity determines the concentration required to obtain 50% binding, the amount of different complexes formed is very much related to local concentrations. Although the concentration of a specific binding partner is usually quite low in the cell (nanomolar to micromolar), the total concentration of other macromolecules is very high, allowing weak and non-specific interactions to play important roles. In this review we address the question of binding specificity, that is, how do some proteins maintain monogamous relations while others are clearly polygamous. We examine recent work that addresses the molecular and structural basis for specificity versus promiscuity. We show through examples how multiple solutions exist to achieve binding via similar interfaces and how protein specificity can be tuned using both positive and negative selection (specificity by demand). Binding of a protein to numerous partners can be promoted through variation in which residues are used for binding, conformational plasticity and/or post-translational modification. Natively unstructured regions represent the extreme case in which structure is obtained only upon binding. Many natively unstructured proteins serve as hubs in protein–protein interaction networks and such promiscuity can be of functional importance in biology.National Institutes of Health (U.S.) (Award GM084181)National Institutes of Health (U.S.) (Award GM067681

The evolution of protein kinase specificity

All research conducted at EMBL-EBI under the supervision of Dr. Pedro Beltrao. Work on the PhD project was paused temporarily in the Spring of 2017 for me to undertake a 3-month internship at EMBO Press (in Heidelberg).Protein phosphorylation represents one of the most important post-translational modifica- tions (PTMs) for cell signalling, and is is catalysed by a group of enzymes called protein kinases. Through this activity they serve as key regulators of almost all cellular processes. This is achieved at any time by a network of different kinases that are transiently active. The fidelity of cell systems control therefore requires that each kinase targets only a restricted set of substrates. This specificity is achieved partly by contextual factors that separate kinases spatially and temporally, but also by sequence features that are encoded in the kinase domain itself. For this thesis I focus on elements of kinase specificity that are encoded in the the active site of the enzyme. During these investigations I have tried to address three main questions: 1) How is specificity for residues surrounding the phosphorylation site determined in the kinase? 2) How did these specificities evolve? and 3) To what extent does kinase evolution correlate with the evolution of its substrates? First, I developed a sequence-based method for the automated detection of kinase speci- ficity determining residues (SDRs). The putative determinants were then rationalised using available structural data, and in two specific cases were validated experimentally. I also used mutation data from The Cancer Genome Atlas (TCGA) to demonstrate that kinase SDRs are often targeted during cancer. Second, a global analysis of SDR evolution was performed for kinases following gene duplication and speciation, revealing that SDRs often diverge between paralogues but not between orthologues. This global analysis is followed by a detailed case study of G-protein coupled receptor kinase (GRKs) evolution using ancestral sequence reconstructions. Third, I inferred global substrate preferences in a taxonomically broad range of species using phosphoproteome data. I then related the evolution of substrate motif sequences to that of their cognate effector kinases where possible. The results strongly suggest that many of the motifs emerged in a universal eukaryotic ancestor. I finish by summarising the major findings of this doctoral research, which to my knowl- edge represents the most comprehensive analysis to date of protein kinase specificity and its evolution.BBSR

High-throughput profiling of sequence recognition by phosphotyrosine signaling proteins

Protein tyrosine kinase and phosphatase domains have binding specificities that depend on the amino acid sequence surrounding the target (phospho)tyrosine residue on their substrates. Although the preferred recognition motifs of many kinase and phosphatase domains have been characterized, we lack a quantitative description of sequence specificity that could guide predictions about signaling pathways or be used to design sequences for biomedical applications. Here, we present a platform that combines genetically-encoded peptide libraries and deep sequencing to profile sequence recognition by tyrosine kinases. We screened several tyrosine kinases against a million-peptide random library and used the resulting profiles to design high-activity sequences and predict phosphorylation efficiencies of substrates. We then screened several kinases against a library containing thousands of human proteome-derived peptides and their naturally-occurring variants. These screens recapitulated independently measured phosphorylation rates and revealed hundreds of phosphosite-proximal mutations that impact phosphosite recognition by tyrosine kinases. Finally, we have made progress towards extending this platform to the analysis of tyrosine phosphatase domains, by optimizing methods to produce tyrosine-phosphorylated bacterial display libraries and implementing methods to detect peptide dephosphorylation on the cell surface. Collectively, these experiments demonstrate the utility of our platform for rapid profiling of sequence specificity by tyrosine kinases and will shed new light on phosphotyrosine signaling

Developing a computational approach to investigate the impacts of disease-causing mutations on protein function

This project uses bioinformatics protocols to explore the impacts of non-synonymous mutations (nsSNPs) in proteins associated with diseases, including germline, rare diseases and somatic diseases such as cancer. New approaches were explored for determining the impacts of disease-associated mutations on protein structure and function. Whilst this work has mainly concentrated on the analysis of cancer mutations, the methods developed are generic and could be applied to analysing other types of disease mutations. Different types of disease-causing mutations have been studied including germline diseases, somatic cancer mutations in oncogenes and tumour-suppressors, along with known activating and inactivating mutations in kinases. The proximity of disease-associated mutations has been analysed with respect to known functional sites reported by CSA, IBIS, along with predicted functional sites derived from the CATH classification of domain structure superfamilies. The latter are called FunSites, and are highly conserved residues within a CATH functional family (FunFam) – which is a functionally coherent subset of a CATH superfamily. Such sites include key catalytic residues as well as specificity determining residues and interface residues. Clear differences were found between oncogenes, tumour suppressor and germ-line mutations with oncogene mutations more likely to locate close to FunSites. Functional families that are highly enriched in disease mutations were identified and exploited structural data to identify clusters within proteins in these families that are enriched in mutations (using our MutClust program). We examined the tendencies of these clusters to lie close to the functional sites discussed above. For selected genes, the stability effects of disease mutations in cancer have also been investigated with a particular focus on activating mutations in FGFR3. These studies, which were supported by experimental validation, showed that activating mutations implicated in cancer tend to cause stabilisation of the active FGFR3 form, leading to its abnormal activity and oncogenesis. Mutationally enriched CATH FunFams were also used in the identification of cancer driver genes, which were then subjected to pathway and GO biological process analysis

Comprehensively Surveying Structure and Function of RING Domains from Drosophila melanogaster

Using a complete set of RING domains from Drosophila melanogaster, all the solved RING domains and cocrystal structures of RING-containing ubiquitin-ligases (RING-E3) and ubiquitin-conjugating enzyme (E2) pairs, we analyzed RING domains structures from their primary to quarternary structures. The results showed that: i) putative orthologs of RING domains between Drosophila melanogaster and the human largely occur (118/139, 84.9%); ii) of the 118 orthologous pairs from Drosophila melanogaster and the human, 117 pairs (117/118, 99.2%) were found to retain entirely uniform domain architectures, only Iap2/Diap2 experienced evolutionary expansion of domain architecture; iii) 4 evolutionary structurally conserved regions (SCRs) are responsible for homologous folding of RING domains at the superfamily level; iv) besides the conserved Cys/His chelating zinc ions, 6 equivalent residues (4 hydrophobic and 2 polar residues) in the SCRs possess good-consensus and conservation- these 4 SCRs function in the structural positioning of 6 equivalent residues as determinants for RING-E3 catalysis; v) members of these RING proteins located nucleus, multiple subcellular compartments, membrane protein and mitochondrion are respectively 42 (42/139, 30.2%), 71 (71/139, 51.1%), 22 (22/139, 15.8%) and 4 (4/139, 2.9%); vi) CG15104 (Topors) and CG1134 (Mul1) in C3HC4, and CG3929 (Deltex) in C3H2C3 seem to display broader E2s binding profiles than other RING-E3s; vii) analyzing intermolecular interfaces of E2/RING-E3 complexes indicate that residues directly interacting with E2s are all from the SCRs in RING domains. Of the 6 residues, 2 hydrophobic ones contribute to constructing the conserved hydrophobic core, while the 2 hydrophobic and 2 polar residues directly participate in E2/RING-E3 interactions. Based on sequence and structural data, SCRs, conserved equivalent residues and features of intermolecular interfaces were extracted, highlighting the presence of a nucleus for RING domain fold and formation of catalytic core in which related residues and regions exhibit preferential evolutionary conservation

Computational Reconstruction of Enhancer-Gene Regulatory Networks Altered in Cancer

Enhancers are cis-acting non-coding regulatory elements that regulate the transcriptional output of target genes. Their dysregulation has been associated with various diseases including cancer. However, identification and characterisation of non-coding mutations that are relevant for tumorigenesis and prognosis remains a major challenge. We hypothesised that non-coding mutations in enhancers could significantly influence cancer prognosis and patient survival and thus can be exploited as novel prognostic biomarkers for better patient stratification and targeted therapy in lung cancer. Here we present the detection and characterisation of enhancer mutations in a genome-wide analysis of 159 lung cancer samples. To define enhancers across the genome we leverage the epigenomic signatures incorporating histone marks (H3K27ac) and chromatin accessibility (DNase I sensitivity or ATAC-seq) from 8 lung cell lines and primary tissue. We observe that the mutation burden at enhancers, promoters and exons is similar, whereas the mutation signature at these genomic locations varies significantly. We observe recurrent mutations in enhancers at base pair level and show their impact on target genes. We also demonstrate that genes have more than one enhancer and when they are mutated, the gene expression is altered. We also observe pathway-level aggregated enhancer mutations in cancer patients. These results contribute to a new approach towards the functional validation of non-coding mutations in cancer

Molecular Genetic and DNA Methylation Profiling of Chronic Lymphocytic Leukaemia: a Focus on Divergent Prognostic Subgroups and Subsets

Advancements in prognostication have improved the subdivision of chronic lymphocytic leukaemia (CLL) into diverse prognostic subgroups. In CLL, IGHV unmutated and IGHV3-21 genes are associated with a poor-prognosis, conversely, IGHV mutated genes with a favourable outcome. The finding of multiple CLL subsets expressing ‘stereotyped’ B-cell receptors (BCRs) has suggested a role for antigen(s) in leukemogenesis. Patients belonging to certain stereotyped subsets share clinical and biological characteristics, yet limited knowledge exists regarding the genetic and epigenetic events that may influence their clinical behaviour. This thesis aimed to, further investigate Swedish IGHV3-21-utilising patients, screen for genetic and DNA methylation events in CLL subgroups/subsets and study DNA methylation over time and within different CLL compartments. In paper I, IGHV gene sequencing of 337 CLL patients from a Swedish population-based cohort revealed a lower (6.5%) IGHV3-21 frequency relative to previous Swedish hospital-based studies (10.1-12.7%). Interestingly, this frequency remained higher compared to other Western CLL (2.6-4.1%) hospital-based cohorts. Furthermore, we confirmed the poor-outcome for IGHV3-21 patients to be independent of mutational and stereotypy status. In paper II, genomic events in stereotyped IGHV3-21-subset #2, IGHV4-34- subset #4 and subset #16 and their non-stereotyped counterparts were investigated via SNP arrays (n=101). Subset #2 and non-subset #2 carried a higher frequency of V events compared to subset #4. A high frequency of del(11q) was evident in IGHV3- 21 patients particularly subset #2 cases, which may partially explain their poorprognosis. In contrast, the lower prevalence of aberrations and absence of poorprognostic alterations may reflect the inherent low-proliferative disease seen in subset #4 cases. In papers III and IV, differential methylation profiles in IGHV mutated and IGHV unmutated patients were identified using DNA-methylation microarrays. CLL prognostic genes (CLLU1, LPL), tumor-suppressor genes (TSGs) (ABI3, WISP3) and genes belonging to TGF-ß and NFkB/ TNFR1 pathways were differentially methylated between the subgroups. Additionally, the re-expression of methylated TSGs by use of methyl and deacetyl inhibitors was demonstrated. Interestingly, analysis of patient-paired diagnostic/follow-up samples and patient-matched lymph node (LN) and peripheral blood (PB) cases revealed global DNA methylation to be relatively stable over time and remarkably similar within the different compartments. Altogether, this thesis provides insight into the aberrant genomic and DNA methylation events in divergent CLL subgroups. Moreover this thesis helps distinguish the extent to which DNA methylation changes with respect to time and microenvironment in CLL

Hereditable variants of classical protein tyrosine phosphatase genes: Will they prove innocent or guilty?

Protein tyrosine phosphatases, together with protein tyrosine kinases, control many molecular signaling steps that control life at cellular and organismal levels. Impairing alterations in the genes encoding the involved proteins is expected to profoundly affect the quality of life—if compatible with life at all. Here, we review the current knowledge on the effects of germline variants that have been reported for genes encoding a subset of the protein tyrosine phosphatase superfamily; that of the thirty seven classical members. The conclusion must be that the newest genome research tools produced an avalanche of data that suggest ‘guilt by association’ for individual genes to specific disorders. Future research should face the challenge to investigate these accusations thoroughly and convincingly, to reach a mature genotype-phenotype map for this intriguing protein family