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     

Role for protein–protein interaction databases in human genetics

Proteomics and the study of protein–protein interactions are becoming increasingly important in our effort to understand human diseases on a system-wide level. Thanks to the development and curation of protein-interaction databases, up-to-date information on these interaction networks is accessible and publicly available to the scientific community. As our knowledge of protein–protein interactions increases, it is important to give thought to the different ways that these resources can impact biomedical research. In this article, we highlight the importance of protein–protein interactions in human genetics and genetic epidemiology. Since protein–protein interactions demonstrate one of the strongest functional relationships between genes, combining genomic data with available proteomic data may provide us with a more in-depth understanding of common human diseases. In this review, we will discuss some of the fundamentals of protein interactions, the databases that are publicly available and how information from these databases can be used to facilitate genome-wide genetic studies.     

Can We AlphaFold Our Way Out of the Next Pandemic?

The announcement of the outstanding performance of AlphaFold 2 in the CASP 14 protein structure prediction competition came at the end of a long year defined by the COVID-19 pandemic. With an infectious organism dominating the world stage, the developers of Alphafold 2 were keen to play their part, accurately predicting novel structures of two proteins from SARS-CoV-2. In their blog post of December 2020, they highlighted this contribution, writing “we’ve also seen signs that protein structure prediction could be useful in future pandemic response efforts”. So, what role does structural biology play in guiding vaccine immunogen design and what might be the contribution of AlphaFold 2?     

The legacy of pharmacogenetics and potential applications

Some 40 years of pharmacogenetic research indicates that knowledge of human genetic diversity is essential to a broader understanding of variation in human drug response, and suggests that drug therapy tailored to the genetic characteristics of the individual may be a realistic goal. Aided by new technologies, molecular studies of genetic polymorphisms of many human enzymes, receptors, and other proteins indicate that only a limited number of important protein variants account for the diversity in drug response, raising the prospect that these variants may be cataloged relatively soon for many human populations. The next great challenge of pharmacogenetics is to pin down the cellular location and effect of these variant proteins on the pathways and networks that govern individual variation in responses to drugs and other exogenous chemicals. In this paper, we will discuss some the current challenges to progress in pharmacogenetics and newer strategies that might be used to improve prospects of drug design and personalized therapy.     

Utilizing Ethnic-Specific Differences in Minor Allele Frequency to Recategorize Reported Pathogenic Deafness Variants

Ethnic-specific differences in minor allele frequency impact variant categorization for genetic screening of nonsyndromic hearing loss (NSHL) and other genetic disorders. We sought to evaluate all previously reported pathogenic NSHL variants in the context of a large number of controls from ethnically distinct populations sequenced with orthogonal massively parallel sequencing methods. We used HGMD, ClinVar, and dbSNP to generate a comprehensive list of reported pathogenic NSHL variants and re-evaluated these variants in the context of 8,595 individuals from 12 populations and 6 ethnically distinct major human evolutionary phylogenetic groups from three sources (Exome Variant Server, 1000 Genomes project, and a control set of individuals created for this study, the OtoDB). Of the 2,197 reported pathogenic deafness variants, 325 (14.8%) were present in at least one of the 8,595 controls, indicating a minor allele frequency (MAF) >0.00006. MAFs ranged as high as 0.72, a level incompatible with pathogenicity for a fully penetrant disease like NSHL. Based on these data, we established MAF thresholds of 0.005 for autosomal-recessive variants (excluding specific variants in GJB2) and 0.0005 for autosomal-dominant variants. Using these thresholds, we recategorized 93 (4.2%) of reported pathogenic variants as benign. Our data show that evaluation of reported pathogenic deafness variants using variant MAFs from multiple distinct ethnicities and sequenced by orthogonal methods provides a powerful filter for determining pathogenicity. The proposed MAF thresholds will facilitate clinical interpretation of variants identified in genetic testing for NSHL. All data are publicly available to facilitate interpretation of genetic variants causing deafness.     

VarSite: Disease variants and protein structure

VarSite is a web server mapping known disease‐associated variants from UniProt and ClinVar, together with natural variants from gnomAD, onto protein 3D structures in the Protein Data Bank. The analyses are primarily image‐based and provide both an overview for each human protein, as well as a report for any specific variant of interest. The information can be useful in assessing whether a given variant might be pathogenic or benign. The structural annotations for each position in the protein include protein secondary structure, interactions with ligand, metal, DNA/RNA, or other protein, and various measures of a given variant's possible impact on the protein's function. The 3D locations of the disease‐associated variants can be viewed interactively via the 3dmol.js JavaScript viewer, as well as in RasMol and PyMOL. Users can search for specific variants, or sets of variants, by providing the DNA coordinates of the base change(s) of interest. Additionally, various agglomerative analyses are given, such as the mapping of disease and natural variants onto specific Pfam or CATH domains. The server is freely accessible to all at: https://www.ebi.ac.uk/thornton-srv/databases/VarSite .     

Evidence of colorectal cancer risk associated variant Lys25Ser in the proximity of human bone morphogenetic protein 2

Colorectal cancer (CRC) is the third most prevalent cancer and fourth leading cause of cancer-related deaths globally. It has been shown that the nsSNP variants play an important role in diseases, however it remained unclear how these variants are associated with the disease. Recently, several CRC risk associated SNPs have been discovered, however rs961253 (Lys25Arg at 20p12.3) located in the proximity of bone morphogenetic protein 2 (Bmp2) and fermitin family homolog 1 Fermt1 genes have been reported to be highly associated with the CRC risk. Here we provide evidence for the first time in silico biological functional and structural implications of non-synonymous (nsSNPs) CRC disease-associated variant Lys25Arg via molecular dynamic (MD) simulation. Protein structural analysis was performed with a particular variant allele (A/C, Lys25Arg) and compared with the predicted native protein structure. Our results showed that this nsSNP will cause changes in the protein structure and as a result is associated with the disease. In addition to the native and mutant 3D structures of CRC associated risk allele protein domain (CRAPD), they were also analyzed using solvent accessibility models for further protein stability confirmation. Taken together, this study confirmed that this variant has functional effect and structural impact on the CRAPD and may play an important role in CRC disease progression; hence it could be a reasonable approach for studying the effect of other deleterious variants in future studies.     

SPEACH_AF: Sampling protein ensembles and conformational heterogeneity with Alphafold2

The unprecedented performance of Deepmind’s Alphafold2 in predicting protein structure in CASP XIV and the creation of a database of structures for multiple proteomes and protein sequence repositories is reshaping structural biology. However, because this database returns a single structure, it brought into question Alphafold’s ability to capture the intrinsic conformational flexibility of proteins. Here we present a general approach to drive Alphafold2 to model alternate protein conformations through simple manipulation of the multiple sequence alignment via in silico mutagenesis. The approach is grounded in the hypothesis that the multiple sequence alignment must also encode for protein structural heterogeneity, thus its rational manipulation will enable Alphafold2 to sample alternate conformations. A systematic modeling pipeline is benchmarked against canonical examples of protein conformational flexibility and applied to interrogate the conformational landscape of membrane proteins. This work broadens the applicability of Alphafold2 by generating multiple protein conformations to be tested biologically, biochemically, biophysically, and for use in structure-based drug design.     

Simultaneous characterization of SNPs and N-glycans from multiple glycosylation sites of intact β-2-glycoprotein-1 (B2GP1) by ESI-qTOF-MS

The highly glycosylated ß-2-glycoprotein-1 (B2GP1), also called apolipoprotein H, is a 50 kDa human plasma protein with four or five N-glycosylation sites. Glycosylation of B2GP1 can impact auto antibody recognition leading to the development of antiphospholipid syndrome (APS), which can result in miscarriages or thrombosis. Next to its glycosylation different genetic variants are known to increase the risk of suffering from APS. Here we show that ESI-q/TOF-MS of intact B2GP1 can be used to analyze genetic variants and glycosylation simultaneously. After enrichment of B2GP1 from 16 different plasma samples and subsequent ESI-MS measurement of the intact protein, we detected five different SNPs in our samples either homozygous or heterozygous. The dominant glycan composition shows four biantennary, fully sialylated glycan structures, with a relative proportion of about 30%. We also detected compositions with one or two triantennary glycan structures in lower amounts and fucosylated species with one or two fucosyl residues. Two of our samples showed an unreported partially occupied fifth glycosylation site presumably arising from the presence of SNP variant S88N. Our method allows a fast determination of genetic variants and glycan compositions of human B2GP1 to be potentially used as diagnostic marker.     

Many amino acid substitution variants identified in DNA repair genes during human population screenings are predicted to impact protein function

Over 520 different amino acid substitution variants have been previously identified in the systematic screening of 91 human DNA repair genes for sequence variation. Two algorithms were employed to predict the impact of these amino acid substitutions on protein activity. Sorting Intolerant from Tolerant (SIFT) classified 226 of 508 variants (44%) as "Intolerant." Polymorphism Phenotyping (PolyPhen) classed 165 of 489 amino acid substitutions (34%) as "Probably or possibly damaging." Another 9-15% of the variants were classed as "Potentially intolerant or damaging." The results from the two algorithms are highly associated, with concordance in predicted impact observed for approximately 62% of the variants. Twenty-one to thirty-one percent of the variant proteins are predicted to exhibit reduced activity by both algorithms. These variants occur at slightly lower individual allele frequency than do the variants classified as "Tolerant" or "Benign." Both algorithms correctly predicted the impact of 26 functionally characterized amino acid substitutions in the APE1 protein on biochemical activity, with one exception. It is concluded that a substantial fraction of the missense variants observed in the general human population are functionally relevant. These variants are expected to be the molecular genetic and biochemical basis for the associations of reduced DNA repair capacity phenotypes with elevated cancer risk.     

The human histone H3 complement anno 2011

Histones are highly basic, relatively small proteins that complex with DNA to form higher order structures that underlie chromosome topology. Of the four core histones H2A, H2B, H3 and H4, it is H3 that is most heavily modified at the post-translational level. The human genome harbours 16 annotated bona fide histone H3 genes which code for four H3 protein variants. In 2010, two novel histone H3.3 protein variants were reported, carrying over twenty amino acid substitutions. Nevertheless, they appear to be incorporated into chromatin. Interestingly, these new H3 genes are located on human chromosome 5 in a repetitive region that harbours an additional five H3 pseudogenes, but no other core histone ORFs. In addition, a human-specific novel putative histone H3.3 variant located at 12p11.21 was reported in 2011. These developments raised the question as to how many more human histone H3 ORFs there may be. Using homology searches, we detected 41 histone H3 pseudogenes in the current human genome assembly. The large majority are derived from the H3.3 gene H3F3A, and three of those may code for yet more histone H3.3 protein variants. We also identified one extra intact H3.2-type variant ORF in the vicinity of the canonical HIST2 gene cluster at chromosome 1p21.2. RNA polymerase II occupancy data revealed heterogeneity in H3 gene expression in human cell lines. None of the novel H3 genes were significantly occupied by RNA polymerase II in the data sets at hand, however. We discuss the implications of these recent developments.     

An Integrated Approach for Analyzing Clinical Genomic Variant Data from Next-Generation Sequencing

Next-generation sequencing (NGS) technologies provide the potential for developing high-throughput and low-cost platforms for clinical diagnostics. A limiting factor to clinical applications of genomic NGS is downstream bioinformatics analysis for data interpretation. We have developed an integrated approach for end-to-end clinical NGS data analysis from variant detection to functional profiling. Robust bioinformatics pipelines were implemented for genome alignment, single nucleotide polymorphism (SNP), small insertion/deletion (InDel), and copy number variation (CNV) detection of whole exome sequencing (WES) data from the Illumina platform. Quality-control metrics were analyzed at each step of the pipeline by use of a validated training dataset to ensure data integrity for clinical applications. We annotate the variants with data regarding the disease population and variant impact. Custom algorithms were developed to filter variants based on criteria, such as quality of variant, inheritance pattern, and impact of variant on protein function. The developed clinical variant pipeline links the identified rare variants to Integrated Genome Viewer for visualization in a genomic context and to the Protein Information Resource’s iProXpress for rich protein and disease information. With the application of our system of annotations, prioritizations, inheritance filters, and functional profiling and analysis, we have created a unique methodology for downstream variant filtering that empowers clinicians and researchers to interpret more effectively the relevance of genomic alterations within a rare genetic disease.     

Expansion of the genetic code enables design of a novel "gold" class of green fluorescent proteins

Much effort has been dedicated to the design of significantly red shifted variants of the green fluorescent protein (GFP) from Aequoria victora (av). These approaches have been based on classical engineering with the 20 canonical amino acids. We report here an expansion of these efforts by incorporation of an amino substituted variant of tryptophan into the "cyan" GFP mutant, which turned it into a "gold" variant. This variant possesses a red shift in emission unprecedented for any avFP, similar to "red" FPs, but with enhanced stability and a very low aggregation tendency. An increasing number of non-natural amino acids are available for chromophore redesign (by engineering of the genetic code) and enable new general strategies to generate novel classes of tailor-made GFP proteins.     

Robust classification of protein variation using structural modelling and large-scale data integration

Existing methods for interpreting protein variation focus on annotating mutation pathogenicity rather than detailed interpretation of variant deleteriousness and frequently use only sequence-based or structure-based information. We present VIPUR, a computational framework that seamlessly integrates sequence analysis and structural modelling (using the Rosetta protein modelling suite) to identify and interpret deleterious protein variants. To train VIPUR, we collected 9477 protein variants with known effects on protein function from multiple organisms and curated structural models for each variant from crystal structures and homology models. VIPUR can be applied to mutations in any organism''s proteome with improved generalized accuracy (AUROC .83) and interpretability (AUPR .87) compared to other methods. We demonstrate that VIPUR''s predictions of deleteriousness match the biological phenotypes in ClinVar and provide a clear ranking of prediction confidence. We use VIPUR to interpret known mutations associated with inflammation and diabetes, demonstrating the structural diversity of disrupted functional sites and improved interpretation of mutations associated with human diseases. Lastly, we demonstrate VIPUR''s ability to highlight candidate variants associated with human diseases by applying VIPUR to de novo variants associated with autism spectrum disorders.     

Changes in expression and microheterogeneity of the genetic variants of human α1-acid glycoprotein in malignant mesothelioma

Human α₁-acid glycoprotein (AAG), an acute-phase plasma protein, is heterogeneous in the native state and polymorphic in the desialylated state. The AAG heterogeneity is mainly explained by a variable glycan chain composition in its five glycosylation sites. The AAG polymorphism is due to the presence of genetic variants. Three main variants are observed for AAG, ORM1 F1, ORM1 S and ORM2 A, which have a separate genetic origin. In this paper, we have used different isoelectric focusing (IEF) methods and chromatography on immobilized metal affinity adsorbent to study the relative occurrence of the genetic variants of AAG in relation to changes in microheterogeneity, in plasma and pleural effusions of patients with malignant mesothelioma (MM). The results were compared to those obtained with the variants in plasma of healthy individuals. Significant changes in variant distribution were observed in the MM samples, that corresponded to a rise in the proportion of the ORM1 variants and a fall in that of the ORM2 variant. However, the concentration in MM plasma increased for both variants. The AAG in MM plasma and effusion fluids was found to be more heterogeneous on IEF than AAG of healthy plasma. The evidence of stronger concentrations of both the high and low pI forms of AAG in the MM samples suggested two kinds of changes in charge heterogeneity. These two changes were shown to be attributed to different variants — i.e. the high pI forms to ORM1 F1 and S and the low pI forms to ORM2 A, after fractionation of AAG by chromatography on immobilized copper(II) ions. These results indicate specific changes in both the expression and glycosylation for each AAG variant, according to its separate genetic origin, in MM.     

Protein dynamics in a family of laboratory evolved thermophilic enzymes

Molecular dynamics simulations were employed to study how protein solution structure and dynamics are affected by adaptation to high temperature. Simulations were carried out on a para-nitrobenzyl esterase (484 residues) and two thermostable variants that were generated by laboratory evolution. Although these variants display much higher melting temperatures than wild-type (up to 18 degrees C higher) they are both >97% identical in sequence to the wild-type. In simulations at 300 K the thermostable variants remain closer to their crystal structures than wild-type. However, they also display increased fluctuations about their time-averaged structures. Additionally, both variants show a small but significant increase in radius of gyration relative to wild-type. The vibrational density of states was calculated for each of the esterases. While the density of states profiles are similar overall, both thermostable mutants show increased populations of the very lowest frequency modes (<10 cm(-1)), with the more stable mutant showing the larger increase. This indicates that the thermally stable variants experience increased concerted motions relative to wild-type. Taken together, these data suggest that adaptation for high temperature stability has resulted in a restriction of large deviations from the native state and a corresponding increase in smaller scale fluctuations about the native state. These fluctuations contribute to entropy and hence to the stability of the native state. The largest changes in localized dynamics occur in surface loops, while other regions, particularly the active site residues, remain essentially unchanged. Several mutations, most notably L313F and H322Y in variant 8G8, are in the region showing the largest increase in fluctuations, suggesting that these mutations confer more flexibility to the loops. As a validation of our simulations, the fluctuations of Trp102 were examined in detail, and compared with Trp102 phosphorescence lifetimes that were previously measured. Consistent with expectations from the theory of phosphorescence, an inverse correlation between out-of-plane fluctuations on the picosecond time scale and phosphorescence lifetime was observed.     

Protein structure-based evaluation of missense variants: Resources,challenges and future directions

We provide an overview of the methods that can be used for protein structure-based evaluation of missense variants. The algorithms can be broadly divided into those that calculate the difference in free energy (ΔΔG) between the wild type and variant structures and those that use structural features to predict the damaging effect of a variant without providing a ΔΔG. A wide range of machine learning approaches have been employed to develop those algorithms. We also discuss challenges and opportunities for variant interpretation in view of the recent breakthrough in three-dimensional structural modelling using deep learning.