Catherine L. Worth

Structural biology and bioinformatics in drug design: opportunities and challenges for target identification and lead discovery

Impressive progress in genome sequencing, protein expression and high-throughput crystallography and NMR has radically transformed the opportunities to use protein three-dimensional structures to accelerate drug discovery, but the quantity and complexity of the data have ensured a central place for informatics. Structural biology and bioinformatics have assisted in lead optimization and target identification where they have well established roles; they can now contribute to lead discovery, exploiting high-throughput methods of structure determination that provide powerful approaches to screening of fragment binding.

Structural and functional constraints in the evolution of protein families

High-throughput genomic sequencing has focused attention on understanding differences between species and between individuals. When this genetic variation affects protein sequences, the rate of amino acid substitution reflects both Darwinian selection for functionally advantageous mutations and selectively neutral evolution operating within the constraints of structure and function. During neutral evolution, whereby mutations accumulate by random drift, amino acid substitutions are constrained by factors such as the formation of intramolecular and intermolecular interactions and the accessibility to water or lipids surrounding the protein. These constraints arise from the need to conserve a specific architecture and to retain interactions that mediate functions in protein families and superfamilies.

Comparative Sequence and Structural Analyses of G-Protein-Coupled Receptor Crystal Structures and Implications for Molecular Models

Background Up until recently the only available experimental (high resolution) structure of a G-protein-coupled receptor (GPCR) was that of bovine rhodopsin. In the past few years the determination of GPCR structures has accelerated with three new receptors, as well as squid rhodopsin, being successfully crystallized. All share a common molecular architecture of seven transmembrane helices and can therefore serve as templates for building molecular models of homologous GPCRs. However, despite the common general architecture of these structures key differences do exist between them. The choice of which experimental GPCR structure(s) to use for building a comparative model of a particular GPCR is unclear and without detailed structural and sequence analyses, could be arbitrary. The aim of this study is therefore to perform a systematic and detailed analysis of sequence-structure relationships of known GPCR structures. Methodology We analyzed in detail conserved and unique sequence motifs and structural features in experimentally-determined GPCR structures. Deeper insight into specific and important structural features of GPCRs as well as valuable information for template selection has been gained. Using key features a workflow has been formulated for identifying the most appropriate template(s) for building homology models of GPCRs of unknown structure. This workflow was applied to a set of 14 human family A GPCRs suggesting for each the most appropriate template(s) for building a comparative molecular model. Conclusions The available crystal structures represent only a subset of all possible structural variation in family A GPCRs. Some GPCRs have structural features that are distributed over different crystal structures or which are not present in the templates suggesting that homology models should be built using multiple templates. This study provides a systematic analysis of GPCR crystal structures and a consistent method for identifying suitable templates for GPCR homology modelling that will help to produce more reliable three-dimensional models.

A STRUCTURAL BIOINFORMATICS APPROACH TO THE ANALYSIS OF NONSYNONYMOUS SINGLE NUCLEOTIDE POLYMORPHISMS (nsSNPs) AND THEIR RELATION TO DISEASE

The prediction of the effects of nonsynonymous single nucleotide polymorphisms (nsSNPs) on function depends critically on exploiting all information available on the three-dimensional structures of proteins. We describe software and databases for the analysis of nsSNPs that allow a user to move from SNP to sequence to structure to function. In both structure prediction and the analysis of the effects of nsSNPs, we exploit information about protein evolution, in particular, that derived from investigations on the relation of sequence to structure gained from the study of amino acid substitutions in divergent evolution. The techniques developed in our laboratory have allowed fast and automated sequence-structure homology recognition to identify templates and to perform comparative modeling; as well as simple, robust, and generally applicable algorithms to assess the likely impact of amino acid substitutions on structure and interactions. We describe our strategy for approaching the relationship between SNPs and disease, and the results of benchmarking our approach -- human proteins of known structure and recognized mutation.

Structural bioinformatics mutation analysis reveals genotype-phenotype correlations in von Hippel-Lindau disease and suggests molecular mechanisms of tumorigenesis.

Mutations in the VHL gene lead to von Hippel‐Lindau (VHL) disease, a clinically heterogeneous cancer syndrome. Here, we use software and database tools to understand and predict the phenotypes associated with missense mutations in the VHL gene product, pVHL. The protein product pVHL is known to interact with elongin B, elongin C, and the HIF substrate. By analyzing known and predicted interaction sites and predictions of thermodynamic stability change upon mutation, we generate new hypotheses regarding the molecular etiology of renal cell carcinoma (RCC) and pheochromocytoma (PCC) in VHL disease. We find that the molecular causes of RCC and PCC appear to be decoupled. RCC may arise through two distinct mechanisms: disruption of HIF interactions or binding at the elongin B interface. PCC is triggered by mutations which disrupt interactions at the elongin C binding site. These findings have important implications for VHL disease and for nonfamilial RCC, because most cases of clear cell RCC are linked with VHL inactivation. Additionally, predicting effects of genetic variation will be critical as genetic sequencing accelerates; the analytical strategy presented here may elucidate other systems as further data on genetic variation become available. Proteins 2009.

Genome bioinformatic analysis of nonsynonymous SNPs

BackgroundGenome-wide association studies of common diseases for common, low penetrance causal variants are underway. A proportion of these will alter protein sequences, the most common of which is the non-synonymous single nucleotide polymorphism (nsSNP). It would be an advantage if the functional effects of an nsSNP on protein structure and function could be predicted, both for the final identification process of a causal variant in a disease-associated chromosome region, and in further functional analyses of the nsSNP and its disease-associated protein.ResultsIn the present report we have compared and contrasted structure- and sequence-based methods of prediction to over 5500 genes carrying nearly 24,000 nsSNPs, by employing an automatic comparative modelling procedure to build models for the genes. The nsSNP information came from two sources, the OMIM database which are rare (minor allele frequency, MAF, < 0.01) and are known to cause penetrant, monogenic diseases. Secondly, nsSNP information came from dbSNP125, for which the vast majority of nsSNPs, mostly MAF > 0.05, have no known link to a disease. For over 40% of the nsSNPs, structure-based methods predicted which of these sequence changes are likely to either disrupt the structure of the protein or interfere with the function or interactions of the protein. For the remaining 60%, we generated sequence-based predictions.ConclusionWe show that, in general, the prediction tools are able distinguish disease causing mutations from those mutations which are thought to have a neutral affect. We give examples of mutations in genes that are predicted to be deleterious and may have a role in disease. Contrary to previous reports, we also show that rare mutations are consistently predicted to be deleterious as often as commonly occurring nsSNPs.

Principles and Determinants of G-Protein Coupling by the Rhodopsin-Like Thyrotropin Receptor

In this study we wanted to gain insights into selectivity mechanisms between G-protein-coupled receptors (GPCR) and different subtypes of G-proteins. The thyrotropin receptor (TSHR) binds G-proteins promiscuously and activates both Gs (cAMP) and Gq (IP). Our goal was to dissect selectivity patterns for both pathways in the intracellular region of this receptor. We were particularly interested in the participation of poorly investigated receptor parts. We systematically investigated the amino acids of intracellular loop (ICL) 1 and helix 8 using site-directed mutagenesis alongside characterization of cAMP and IP accumulation. This approach was guided by a homology model of activated TSHR in complex with heterotrimeric Gq, using the X-ray structure of opsin with a bound G-protein peptide as a structural template. We provide evidence that ICL1 is significantly involved in G-protein activation and our model suggests potential interactions with subunits Gα as well as Gβγ. Several amino acid substitutions impaired both IP and cAMP accumulation. Moreover, we found a few residues in ICL1 (L440, T441, H443) and helix 8 (R687) that are sensitive for Gq but not for Gs activation. Conversely, not even one residue was found that selectively affects cAMP accumulation only. Together with our previous mutagenesis data on ICL2 and ICL3 we provide here the first systematically completed map of potential interfaces between TSHR and heterotrimeric G-protein. The TSHR/Gq-heterotrimer complex is characterized by more selective interactions than the TSHR/Gs complex. In fact the receptor interface for binding Gs is a subset of that for Gq and we postulate that this may be true for other GPCRs coupling these G-proteins. Our findings support that G-protein coupling and preference is dominated by specific structural features at the intracellular region of the activated GPCR but is completed by additional complementary recognition patterns between receptor and G-protein subtypes.

Signaling-sensitive amino acids surround the allosteric ligand binding site of the thyrotropin receptor

The thyrotropin receptor [thyroidstimulating hormone receptor (TSHR)], a G‐proteincoupled receptor (GPCR), is endogenously activated by thyrotropin, which binds to the extracellular region of the receptor. We previously identified a low‐molecular‐weight (LMW) agonist of the TSHR and predicted its allosteric binding pocket within the receptors transmembrane domain. Because binding of the LMW agonist probably disrupts interactions or leads to formation of new interactions among amino acid residues surrounding the pocket, we tested whether mutation of residues at these positions would lead to constitutive signaling activity. Guided by molecular modeling, we performed site‐directed mutagenesis of 24 amino acids in this spatial region, followed by functional characterization of the mutant receptors in terms of expression and signaling, measured as cAMP accumulation. We found that mutations V421I, Y466A, T501A, L587V, M637C, M637W, S641A, Y643F, L645V, and Y667A located in several helices exhibit constitutive activity. Of note is mutation M637W at position 6.48 in transmembrane helix 6, which has a significant effect on the interaction of the receptor with the LMW agonist. In summary, we found that a high proportion of residues in several helices surrounding the allosteric binding site of LMW ligands in the TSHR when mutated lead to constitutively active receptors. Our findings of signaling‐sensitive residues in this region of the transmembrane bundle may be of general importance as this domain appears to be evolutionarily retained among GPCRs.—Kleinau, G., Haas, A.‐K., Neumann, S., Worth, C. L., Hoyer, I., Furkert, J., Rutz, Gershengorn, M. C, Schülein, R., Krause, G. Signalingsensitive amino acids surround the allosteric ligand binding site of the thyrotropin receptor. FASEBJ. 24, 2347–2354 (2010). www.fasebj.org

Structural and functional restraints in the evolution of protein families and superfamilies.

Divergent evolution of proteins reflects both selectively advantageous and neutral amino acid substitutions. In the present article, we examine restraints on sequence, which arise from selectively advantageous roles for structure and function and which lead to the conservation of local sequences and structures in families and superfamilies. We analyse structurally aligned members of protein families and superfamilies in order to investigate the importance of the local structural environment of amino acid residues in the acceptance of amino acid substitutions during protein evolution. We show that solvent accessibility is the most important determinant, followed by the existence of hydrogen bonds from the side-chain to main-chain functions and the nature of the element of secondary structure to which the amino acid contributes. Polar side chains whose hydrogen-bonding potential is satisfied tend to be more conserved than their unsatisfied or non-hydrogen-bonded counterparts, and buried and satisfied polar residues tend to be significantly more conserved than buried hydrophobic residues. Finally, we discuss the importance of functional restraints in the form of interactions of proteins with other macromolecules in assemblies or with substrates, ligands or allosteric regulators. We show that residues involved in such functional interactions are significantly more conserved and have differing amino acid substitution patterns.

From Molecular Details of the Interplay between Transmembrane Helices of the Thyrotropin Receptor to General Aspects of Signal Transduction in Family A G-protein-coupled Receptors (GPCRs)

Transmembrane helices (TMHs) 5 and 6 are known to be important for signal transduction by G-protein-coupled receptors (GPCRs). Our aim was to characterize the interface between TMH5 and TMH6 of the thyrotropin receptor (TSHR) to gain molecular insights into aspects of signal transduction and regulation. A proline at TMH5 position 5.50 is highly conserved in family A GPCRs and causes a twist in the helix structure. Mutation of the TSHR-specific alanine (Ala-5935.50) at this position to proline resulted in a 20-fold reduction of cell surface expression. This indicates that TMH5 in the TSHR might have a conformation different from most other family A GPCRs by forming a regular α-helix. Furthermore, linking our own and previous data from directed mutagenesis with structural information led to suggestions of distinct pairs of interacting residues between TMH5 and TMH6 that are responsible for stabilizing either the basal or the active state. Our insights suggest that the inactive state conformation is constrained by a core set of polar interactions among TMHs 2, 3, 6, and 7 and in contrast that the active state conformation is stabilized mainly by non-polar interactions between TMHs 5 and 6. Our findings might be relevant for all family A GPCRs as supported by a statistical analysis of residue properties between the TMHs of a vast number of GPCR sequences.