Missense3D-TM: Predicting the Effect of Missense Variants in Helical Transmembrane Protein Regions Using 3D Protein Structures.

Variant effect predictors assess if a substitution is pathogenic or benign. Most predictors, including those that are structure-based, are designed for globular proteins in aqueous environments and do not consider that the variant residue is located within the membrane. We report Missense3D-TM that provides a structure-based assessment of the impact of a missense variant located within a membrane. On a dataset of 2,078 pathogenic and 1,060 benign variants, spanning 711 proteins from 706 structures, Missense3D-TM achieved an accuracy of 66%, Mathews correlation coefficient of 0.37, sensitivity of 58% and specificity of 81%. Missense3D-TM performed similarly to mCSM-membrane: accuracy 66% vs 61% (p = 0.02) on an unbalanced test set and 70% vs 67% (p = 0.20) on a balanced test set. The Missense3D-TM website provides an analysis of the structural effects of the variant along with its predicted position within the membrane. The web server is available at http://missense3d.bc.ic.ac.uk/.

Mutations in a Sar1 GTPase of COPII vesicles are associated with lipid absorption disorders.

Dietary fat is an important source of nutrition. Here we identify eight mutations in SARA2 that are associated with three severe disorders of fat malabsorption. The Sar1 family of proteins initiates the intracellular transport of proteins in COPII (coat protein)-coated vesicles. Our data suggest that chylomicrons, which vastly exceed the size of typical COPII vesicles, are selectively recruited by the COPII machinery for transport through the secretory pathways of the cell.

Missense3D-PPI: A Web Resource to Predict the Impact of Missense Variants at Protein Interfaces Using 3D Structural Data.

In 2019, we released Missense3D which identifies stereochemical features that are disrupted by a missense variant, such as introducing a buried charge. Missense3D analyses the effect of a missense variant on a single structure and thus may fail to identify as damaging surface variants disrupting a protein interface i.e., a protein-protein interaction (PPI) site. Here we present Missense3D-PPI designed to predict missense variants at PPI interfaces. Our development dataset comprised of 1,279 missense variants (pathogenic n = 733, benign n = 546) in 434 proteins and 545 experimental structures of PPI complexes. Benchmarking of Missense3D-PPI was performed after dividing the dataset in training (320 benign and 320 pathogenic variants) and testing (226 benign and 413 pathogenic). Structural features affecting PPI, such as disruption of interchain bonds and introduction of unbalanced charged interface residues, were analysed to assess the impact of the variant at PPI. The performance of Missense3D-PPI was superior to that of Missense3D: sensitivity 44 % versus 8% and accuracy 58% versus 40%, p = 4.23 × 10-16. However, the specificity of Missense3D-PPI was lower compared to Missense3D (84% versus 98%). On our dataset, Missense3D-PPI's accuracy was superior to BeAtMuSiC (p = 3.4 × 10-5), mCSM-PPI2 (p = 1.5 × 10-12) and MutaBind2 (p = 0.0025). Missense3D-PPI represents a valuable tool for predicting the structural effect of missense variants on biological protein networks and is available at the Missense3D web portal (http://missense3d.bc.ic.ac.uk).

GWYRE: A Resource for Mapping Variants onto Experimental and Modeled Structures of Human Protein Complexes.

Rapid progress in structural modeling of proteins and their interactions is powered by advances in knowledge-based methodologies along with better understanding of physical principles of protein structure and function. The pool of structural data for modeling of proteins and protein-protein complexes is constantly increasing due to the rapid growth of protein interaction databases and Protein Data Bank. The GWYRE (Genome Wide PhYRE) project capitalizes on these developments by advancing and applying new powerful modeling methodologies to structural modeling of protein-protein interactions and genetic variation. The methods integrate knowledge-based tertiary structure prediction using Phyre2 and quaternary structure prediction using template-based docking by a full-structure alignment protocol to generate models for binary complexes. The predictions are incorporated in a comprehensive public resource for structural characterization of the human interactome and the location of human genetic variants. The GWYRE resource facilitates better understanding of principles of protein interaction and structure/function relationships. The resource is available at http://www.gwyre.org.

Promyelocytic leukemia nuclear bodies associate with transcriptionally active genomic regions.

The promyelocytic leukemia (PML) protein is aggregated into nuclear bodies that are associated with diverse nuclear processes. Here, we report that the distance between a locus and its nearest PML body correlates with the transcriptional activity and gene density around the locus. Genes on the active X chromosome are more significantly associated with PML bodies than their silenced homologues on the inactive X chromosome. We also found that a histone-encoding gene cluster, which is transcribed only in S-phase, is more strongly associated with PML bodies in S-phase than in G0/G1 phase of the cell cycle. However, visualization of specific RNA transcripts for several genes showed that PML bodies were not themselves sites of transcription for these genes. Furthermore, knock-down of PML bodies by RNA interference did not preferentially change the expression of genes closely associated with PML bodies. We propose that PML bodies form in nuclear compartments of high transcriptional activity, but they do not directly regulate transcription of genes in these compartments.

Can Predicted Protein 3D Structures Provide Reliable Insights into whether Missense Variants Are Disease Associated?

Knowledge of protein structure can be used to predict the phenotypic consequence of a missense variant. Since structural coverage of the human proteome can be roughly tripled to over 50% of the residues if homology-predicted structures are included in addition to experimentally determined coordinates, it is important to assess the reliability of using predicted models when analyzing missense variants. Accordingly, we assess whether a missense variant is structurally damaging by using experimental and predicted structures. We considered 606 experimental structures and show that 40% of the 1965 disease-associated missense variants analyzed have a structurally damaging change in the mutant structure. Only 11% of the 2134 neutral variants are structurally damaging. Importantly, similar results are obtained when 1052 structures predicted using Phyre2 algorithm were used, even when the model shares low (<40%) sequence identity to the template. Thus, structure-based analysis of the effects of missense variants can be effectively applied to homology models. Our in-house pipeline, Missense3D, for structurally assessing missense variants was made available at http://www.sbg.bio.ic.ac.uk/~missense3d.

PhyreRisk: A Dynamic Web Application to Bridge Genomics, Proteomics and 3D Structural Data to Guide Interpretation of Human Genetic Variants.

PhyreRisk is an open-access, publicly accessible web application for interactively bridging genomic, proteomic and structural data facilitating the mapping of human variants onto protein structures. A major advance over other tools for sequence-structure variant mapping is that PhyreRisk provides information on 20,214 human canonical proteins and an additional 22,271 alternative protein sequences (isoforms). Specifically, PhyreRisk provides structural coverage (partial or complete) for 70% (14,035 of 20,214 canonical proteins) of the human proteome, by storing 18,874 experimental structures and 84,818 pre-built models of canonical proteins and their isoforms generated using our in house Phyre2. PhyreRisk reports 55,732 experimentally, multi-validated protein interactions from IntAct and 24,260 experimental structures of protein complexes. Another major feature of PhyreRisk is that, rather than presenting a limited set of precomputed variant-structure mapping of known genetic variants, it allows the user to explore novel variants using, as input, genomic coordinates formats (Ensembl, VCF, reference SNP ID and HGVS notations) and Human Build GRCh37 and GRCh38. PhyreRisk also supports mapping variants using amino acid coordinates and searching for genes or proteins of interest. PhyreRisk is designed to empower researchers to translate genetic data into protein structural information, thereby providing a more comprehensive appreciation of the functional impact of variants. PhyreRisk is freely available at http://phyrerisk.bc.ic.ac.uk.

Quantitative analysis of cell nucleus organisation.

There are almost 1,300 entries for higher eukaryotes in the Nuclear Protein Database. The proteins' subcellular distribution patterns within interphase nuclei can be complex, ranging from diffuse to punctate or microspeckled, yet they all work together in a coordinated and controlled manner within the three-dimensional confines of the nuclear volume. In this review we describe recent advances in the use of quantitative methods to understand nuclear spatial organisation and discuss some of the practical applications resulting from this work.

EzMol: A Web Server Wizard for the Rapid Visualization and Image Production of Protein and Nucleic Acid Structures.

EzMol is a molecular visualization Web server in the form of a software wizard, located at http://www.sbg.bio.ic.ac.uk/ezmol/. It is designed for easy and rapid image manipulation and display of protein molecules, and is intended for users who need to quickly produce high-resolution images of protein molecules but do not have the time or inclination to use a software molecular visualization system. EzMol allows the upload of molecular structure files in PDB format to generate a Web page including a representation of the structure that the user can manipulate. EzMol provides intuitive options for chain display, adjusting the color/transparency of residues, side chains and protein surfaces, and for adding labels to residues. The final adjusted protein image can then be downloaded as a high-resolution image. There are a range of applications for rapid protein display, including the illustration of specific areas of a protein structure and the rapid prototyping of images.

The transcriptional regulator CBP has defined spatial associations within interphase nuclei.

It is becoming increasingly clear that nuclear macromolecules and macromolecular complexes are compartmentalized through binding interactions into an apparent three-dimensionally ordered structure. This ordering, however, does not appear to be deterministic to the extent that chromatin and nonchromatin structures maintain a strict 3-D arrangement. Rather, spatial ordering within the cell nucleus appears to conform to stochastic rather than deterministic spatial relationships. The stochastic nature of organization becomes particularly problematic when any attempt is made to describe the spatial relationship between proteins involved in the regulation of the genome. The CREB-binding protein (CBP) is one such transcriptional regulator that, when visualised by confocal microscopy, reveals a highly punctate staining pattern comprising several hundred individual foci distributed within the nuclear volume. Markers for euchromatic sequences have similar patterns. Surprisingly, in most cases, the predicted one-to-one relationship between transcription factor and chromatin sequence is not observed. Consequently, to understand whether spatial relationships that are not coincident are nonrandom and potentially biologically important, it is necessary to develop statistical approaches. In this study, we report on the development of such an approach and apply it to understanding the role of CBP in mediating chromatin modification and transcriptional regulation. We have used nearest-neighbor distance measurements and probability analyses to study the spatial relationship between CBP and other nuclear subcompartments enriched in transcription factors, chromatin, and splicing factors. Our results demonstrate that CBP has an order of spatial association with other nuclear subcompartments. We observe closer associations between CBP and RNA polymerase II-enriched foci and SC35 speckles than nascent RNA or specific acetylated histones. Furthermore, we find that CBP has a significantly higher probability of being close to its known in vivo substrate histone H4 lysine 5 compared with the closely related H4 lysine 12. This study demonstrates that complex relationships not described by colocalization exist in the interphase nucleus and can be characterized and quantified. The subnuclear distribution of CBP is difficult to reconcile with a model where chromatin organization is the sole determinant of the nuclear organization of proteins that regulate transcription but is consistent with a close link between spatial associations and nuclear functions.

The role of sequence and structure in protein folding kinetics; the diffusion-collision model applied to proteins L and G.

The diffusion-collision model (DCM) is applied to the folding kinetics of protein L and protein G. In the DCM, the two proteins are treated as consisting of two beta-hairpins and one alpha-helix, so that they are isomorphous with the three-helix bundle DCM model. In the absence of sequence dependent factors, both proteins would fold in the same way in the DCM, with the coalescence of the N-terminal hairpin and the helix slightly favored over the C-terminal hairpin and the helix because the former are closer together than the latter. However, sequence dependent factors make the N-terminal hairpin of protein L and the C-terminal hairpin of protein G more stable in the ensemble of unfolded conformations. This difference in the stabilities gives rise to the difference in the calculated folding behavior, in agreement with experiment.

Protein-protein docking using 3D-Dock in rounds 3, 4, and 5 of CAPRI.

In rounds 3-5 of CAPRI, the community-wide experiment on the comparative evaluation of protein-protein docking for structure prediction, we applied the 3D-Dock software package to predict the atomic structures of nine biophysical interactions. This approach starts with an initial grid-based shape complementarity search. The product of this is a large number of potential interacting conformations that are subsequently ranked by interface residue propensities and interaction energies. Refinement through detailed energetics and optimization of side-chain positions using a rotamer library is also performed. For rounds 3, 4, and 5 of the CAPRI evaluation, where possible, we clustered functional residues on the surfaces of the monomers as an indication of binding sites, using sequence based evolutionary conservations. In certain targets this provided a very useful tool for identifying the areas of interaction. During round 5, we also applied the techniques of side-chain trimming and geometrical clustering described in the literature. Of the nine target complexes in rounds 3-5, we predicted conformations that contained at least some correct contact residues for seven of these systems. For two of the targets, we submitted predictions that were considered as medium-quality. These were a nidogen-laminin complex for target 8 (T08) and a serine-threonine phosphatase bound to a targeting subunit (T14). For a further three target systems, we produced models that were rated as acceptable predictions.

Application of the diffusion-collision model to the folding of three-helix bundle proteins.

The diffusion-collision model has been successful in explaining many features of protein folding kinetics, particularly for helical proteins. In the model the folding reaction is described in terms of coupled chemical kinetic (Master) equations of coarse grained entities, called microdomains. Here, the diffusion-collision model is applied to compute the folding kinetics of four three-helix bundle proteins, all of which fold on a time scale of tens of microseconds and appear to have two-state folding. The native structure and the stability of the helical microdomains are used to determine the parameters of the model. The formulation allows computation of the overall rate and determination of the importance of kinetic intermediates. The proteins considered are the B domain of protein A (1BDC), the Engrailed Homeodomain (1ENH), the peripheral sub-unit-binding domain (1EBD C-chain) and the villin headpiece subdomain (1VII). The results for the folding time of protein A, the Engrailed Homeodomain, and 1EBD C-chain are in agreement with experiment, while 1VII is not stable in the present model. In the three proteins that are stable, two-state folding is predicted by the diffusion-collision model. This disagrees with published assertions that multistate kinetics would be obtained from the model. The contact order prediction agrees with experiment for protein A, but yields values that are a factor of 40, 30 and 15 too slow for 1ENH, 1EBD C-chain and 1VII. The effect of mutants on folding is described for protein A and it is demonstrated that significant intermediate concentrations (i.e. deviation from two-state folding) can occur if the stability of some of the helical microdomains is increased. A linear relationship between folding time and the length of the loop between helices B and C in protein A is demonstrated; this is not evident in the contact order description.

The Discovery of Novel 10,11-Dihydro-5H-dibenz[b,f]azepine SIRT2 Inhibitors.

Isoform selective inhibitors of the sirtuins (NAD+-dependent histone deacetylases) should enable an in depth study of the molecular biology underpinning these targets and how they are deregulated in diseases such as cancer and neurodegeneration. Herein, we present the discovery of structurally novel SIRT2 inhibitors. Hit molecule 8 was discovered through the chemical synthesis and biological characterization of a small-molecule compound library based around the 10,11-dihydro-5H-dibenz[b,f]azepine scaffold. In vitro screening assays revealed compound 8 to have an IC50 of 18 µM against SIRT2 and to exhibit more than 30-fold selectivity compared to SIRT1. Cellular assays, performed on MCF-7 cells, confirmed the in vitro selectivity and showed hit 8 to have antiproliferative activity at a concentration of 30 µM. Computational studies were performed to predict the SIRT2 binding mode and to rationalise the observed selectivity.

The proteome: structure, function and evolution.

This paper reports two studies to model the inter-relationships between protein sequence, structure and function. First, an automated pipeline to provide a structural annotation of proteomes in the major genomes is described. The results are stored in a database at Imperial College, London (3D-GENOMICS) that can be accessed at www.sbg.bio.ic.ac.uk. Analysis of the assignments to structural superfamilies provides evolutionary insights. 3D-GENOMICS is being integrated with related proteome annotation data at University College London and the European Bioinformatics Institute in a project known as e-protein (http://www.e-protein.org/). The second topic is motivated by the developments in structural genomics projects in which the structure of a protein is determined prior to knowledge of its function. We have developed a new approach PHUNCTIONER that uses the gene ontology (GO) classification to supervise the extraction of the sequence signal responsible for protein function from a structure-based sequence alignment. Using GO we can obtain profiles for a range of specificities described in the ontology. In the region of low sequence similarity (around 15%), our method is more accurate than assignment from the closest structural homologue. The method is also able to identify the specific residues associated with the function of the protein family.