Biology subjects

Vranken, W.

Publications and source records attributed to Vranken, W..

12 recordsLinked to original sources

bioRxiv2024

Critical assessment of missense variant effect predictors on disease-relevant variant data

Regular, systematic, and independent assessment of computational tools used to predict the pathogenicity of missense variants is necessary to evaluate their clinical and research utility and suggest directions for future improvement. Here, as part of the sixth edition of the Critical Assessment of Genome Interpretation (CAGI) challenge, we assess missense variant effect predictors (or variant impact predictors) on an evaluation dataset of rare missense variants from disease-relevant databases. Our assessment evaluates predictors submitted to the CAGI6 Annotate-All-Missense challenge, predictors commonly used by the clinical genetics community, and recently developed deep learning methods for variant effect prediction. To explore a variety of settings that are relevant for different clinical and research applications, we assess performance within different subsets of the evaluation data and within high-specificity and high-sensitivity regimes. We find strong performance of many predictors across multiple settings. Meta-predictors tend to outperform their constituent individual predictors; however, several individual predictors have performance similar to that of commonly used meta-predictors. The relative performance of predictors differs in high-specificity and high-sensitivity regimes, suggesting that different methods may be best suited to different use cases. We also characterize two potential sources of bias. Predictors that incorporate allele frequency as a predictive feature tend to have reduced performance when distinguishing pathogenic variants from very rare benign variants, and predictors supervised on pathogenicity labels from curated variant databases often learn label imbalances within genes. Overall, we find notable advances over the oldest and most cited missense variant effect predictors and continued improvements among the most recently developed tools, and the CAGI Annotate-All-Missense challenge (also termed the Missense Marathon) will continue to assess state-of-the-art methods as the field progresses. Together, our results help illuminate the current clinical and research utility of missense variant effect predictors and identify potential areas for future development.

genetics↗

bioRxiv2022

MIADE metadata guidelines: Minimum Information About a Disorder Experiment

An unambiguous description of an experimental setup and analysis, and the subsequent biological observation is vital for accurate data interpretation and reproducible results. Consequently, experimental analyses should be described in a concise, unequivocal, and digestible manner. The aim of minimum information guidelines is to define the fundamental complement of data that can support an unambiguous conclusion on experimental observations. In this document, we present the Minimum Information About Disorder Experiments (MIADE) guidelines to define the minimal fundamental parameters required for non-experts to understand the key findings of an experiment studying intrinsically disordered proteins (IDPs) or intrinsically disordered protein regions (IDRs). MIADE guidelines provide recommendations for data producers to describe the results of their experiments at source, for curators to annotate experimental data to community resources and for database developers maintaining community resources to disseminate the data. We give examples of the application of these guidelines in common use cases and describe the implementation of an update to the DisProt IDP database to allow MIADE-compliant annotation. The MIADE guidelines will improve the interpretability of experimental results for data consumers, facilitate direct data submission, simplify data curation, improve data exchange among repositories and standardise the dissemination of the key metadata on an IDP experiment by IDP data sources.

scientific communication and education↗

bioRxiv2022

Deep mutational scanning of essential bacterial proteins can guide antibiotic development

Deep mutational scanning is a powerful approach to investigate a wide variety of research questions including protein function and stability. We performed deep mutational scanning on three essential E. coli proteins (FabZ, LpxC and MurA) involved in cell envelope synthesis using high-throughput CRISPR genome editing. This allowed us to study the effect of the introduced mutations in their original genomic context. Using more than 17,000 variants of FabZ, LpxC and MurA from the saturation editing libraries constructed here, we have interrogated protein function and the importance of individual amino acids in supporting viability. Additionally, we have exploited these libraries to study resistance development against antimicrobial compounds that target the selected proteins. Our results show that, among the three proteins studied, MurA is the superior antimicrobial target due to its low mutational flexibility which decreases the chance of acquiring resistance-conferring mutations that simultaneously preserve MurA function. Additionally, we were able to rank anti-LpxC lead compounds for further development guided by the number of resistance-conferring mutations against each compound. Our results show that deep mutational scanning studies can be used to guide drug development, which we hope will contribute towards the development of urgently needed novel antimicrobial therapies.

microbiology↗

bioRxiv2022

Evolutionary adaptation of the folding pathway for secretability

Secretory preproteins of the Sec pathway bear signal peptides and are targeted post-translationally to cross the plasma membrane or ER through translocases. After translocation and signal peptide cleavage, mature domains fold to native states in the bacterial periplasm or after further trafficking. During cytoplasmic transit, mature domains must remain non-folded for translocase recognition and translocation. Here, we sought the structural basis for the delayed folding mechanism of mature domains and how this is regulated by signal peptides. To address this, we compared how evolution diversified a periplasmic peptidyl-prolyl isomerase PpiA mature domain from its structural twin cytoplasmic PpiB. Using global and local hydrogen deuterium exchange mass spectrometry we showed that PpiA is a slower folder. We defined at near-residue resolution hierarchical folding initiated by similar foldons in the twins, that displayed different order and rates. Folding is delayed in PpiA by less hydrophobic/bulky native contacts, frustrated residues and a critical {beta} -turn in the early folding region and by signal peptide-driven disorder, which disrupts foldon hierarchy. When selected PpiA residues and its signal peptide were grafted onto PpiB they converted it into a slow folder with enhanced in vivo secretion. These data reveal the structural basis of non-folding in a secretory protein, that allows its trafficking.

biochemistry↗

bioRxiv2022

Evolution of CRISPR-associated Endonucleases as Inferred from Resurrected Proteins

Clustered regularly interspaced short palindromic repeats (CRISPR)-associated Cas9 protein is an effector that plays a major role in a prokaryotic adaptive immune system, by which invading DNA can be targeted and cut for inactivation. The Cas9 endonuclease is directed to target sites by a guide RNA (gRNA) where Cas9 can recognize specific sequences (PAMs) in foreign DNA, which then serve as an anchoring point for cleavage of the adjacent RNA-matching DNA region. Although the CRISPR-Cas9 system has been widely studied and repurposed for diverse applications (notably, genome editing), its origin and evolution remain to be elucidated. Here, we investigate the evolution of Cas9 from resurrected ancient nucleases (anCas) in extinct firmicutes species as old as 2600 myr to the current day. Surprisingly, we demonstrate that these ancient forms were much more flexible in their PAM and gRNA scaffold requirements compared to modern day Cas9 enzymes. In addition, anCas portrays a gradual paleoenzymatic adaptation from nickase to double-strand break activity, suggesting a mechanism by which ancient CRISPR systems could propagate when harboring Cas enzymes with minimal PAMs. The oldest anCas also exhibit high levels of activity with ssDNA and ssRNA targets, resembling Cas nucleases in related system types. Finally, we illustrate editing activity of the anCas enzymes in human cells. The prediction and characterization of anCas proteins uncovers an unexpected evolutionary trajectory leading to ancient enzymes with extraordinary properties.

evolutionary biology↗

bioRxiv2022

What stabilizes pre-folded structures in the intrinsically disordered α-helical binding motifs?

Many examples are known of regions of intrinsically disordered proteins (IDPs) that fold into -helices upon binding their globular protein targets. In their unbound state these regions possess a small amount of residual helicity, referred to as pre-folded structure, which has been studied on case by case basis. In order to investigate what determines these pre-folded structures we compiled a database of peptides that fold-upon-binding, and experimentally characterized their helicity in the unbound and target-bound state. These regions are more hydrophobic and lack proline residues compared to IDPs in general. On average they possess about 17% helicity in the pre-folded state and gain 40% of helicity upon target binding. We observe that the locations of pre-folded helical regions strongly overlap with those in the targetbound IDPs. To understand this correlation, we analyzed per-residue energetic contributions stabilizing helical structure and found that target-interacting IDP have higher helix propensity. Notably, leucine is the most common residue involved in IDP-target interactions and, due to its high helix propensity, it strongly stabilizes pre-folded helical structures. For many IDP binding motifs, particularly those enriched in leucine, we observe that they not only mediate target-interactions but also confer stability to the pre-folded structure. Collectively, this shows that the formation of pre-folded helical elements is coupled to the IDP-target interactions, explaining why such elements are a common feature of -helical binding motifs. Moreover, it probably explains the preference for leucine among IDP-target hotspots, even though this residue is underrepresented among hotspots in the interfaces between globular proteins.

bioinformatics↗

bioRxiv2021

MutaFrame - an interpretative visualization framework for deleteriousness prediction of missense variants in the human exome

MotivationHigh-throughput experiments are generating ever increasing amounts of various -omics data, so shedding new light on the link between human disorders, their genetic causes, and the related impact on protein behavior and structure. While numerous bioinformatics tools now exist that predict which variants in the human exome cause diseases, few tools predict the reasons why they might do so. Yet, understanding the impact of variants at the molecular level is a prerequisite for the rational development of targeted drugs or personalized therapies. ResultsWe present the updated MutaFrame webserver, which aims to meet this need. It offers two deleteriousness prediction softwares, DEOGEN2 and SNPMuSiC, and is designed for bioinformaticians and medical researchers who want to gain insights into the origins of monogenic diseases. It contains information at two levels for each human protein: its amino acid sequence and its 3-dimensional structure; we used the experimental structures whenever available, and modeled structures otherwise. MutaFrame also includes higher-level information, such as protein essentiality and protein-protein interactions. It has a user-friendly interface for the interpretation of results and a convenient visualization system for protein structures, in which the variant positions introduced by the user and other structural information are shown. In this way, MutaFrame aids our understanding of the pathogenic processes caused by single-site mutations and their molecular and contextual interpretation. AvailabilityMutaframe webserver at http://mutaframe.com

bioinformatics↗

bioRxiv2020

Prediction of disordered regions in proteins with recurrent Neural Networks and protein dynamics

The role of intrinsically disordered protein regions (IDRs) in cellular processes has become increasingly evident over the last years. These IDRs continue to challenge structural biology experiments because they lack a well-defined conformation, and bioinformatics approaches that accurately delineate disordered protein regions remain essential for their identification and further investigation. Typically, these predictors use only the protein amino acid sequence, without taking into account likely emergent properties that are sequence context dependent, such as protein backbone dynamics. The DisoMine method predicts protein disorder with recurrent neural networks not directly from the amino acid sequence, but instead from more generic predictions of key biophysical properties, here protein dynamics, secondary structure and early folding. The tool is fast and requires only a single sequence, making it applicable for large-scale screening, including poorly studied and orphan proteins. DisoMine compares well to 10 state of the art predictors, also if these use evolutionary information. DisoMine is freely available through an interactive webserver at http://bio2byte.com/disomine/

bioinformatics↗

bioRxiv2020

Distance-based metrics for comparing conformational ensembles of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are proteins whose native functional states represent ensembles of highly diverse conformations. Such ensembles are a challenge for quantitative structure comparisons as their conformational diversity precludes optimal superimposition of the atomic coordinates, necessary for deriving common similarity measures such as the root-mean-square deviation (RMSD) of these coordinates. Here we introduce superimposition-free metrics, which are based on computing matrices of C-C distance distributions within ensembles and comparing these matrices between ensembles. Differences between two matrices yield information on the similarity between specific regions of the polypeptide, whereas the global structural similarity is captured by the ens_dRMS, defined as the root-mean-square difference between the medians of the C-Cdistance distributions of two ensembles. Together, our metrics enable rigorous investigations of structure-function relationships in conformational ensembles of IDPs derived using experimental restraints or by molecular simulations, and for proteins containing both structured and disordered regions. Statement of SignificanceImportant biological insight is obtained from comparing the high-resolution structures of proteins. Such comparisons commonly involve superimposing two protein structures and computing the residual root-mean-square deviation of the atomic positions. This approach cannot be applied to intrinsically disordered proteins (IDPs) because IDPs do not adopt well-defined 3D structures, rather, their native functional state is defined by ensembles of heterogeneous conformations that cannot be meaningfully superimposed. We report new measures that quantify the local and global similarity between different conformational ensembles by evaluating differences between the distributions of residue-residue distances and their statistical significance. Applying these measures to IDP ensembles and to a protein containing both structured and intrinsically disordered domains provides deeper insights into how structural features relate to function.

bioinformatics↗

bioRxiv2019

Megabodies expand the nanobody toolkit for protein structure determination by single-particle cryo-EM

Nanobodies (Nbs) are popular and versatile tools for structural biology because they have a compact single immunoglobulin domain organization. Nbs bind their target proteins with high affinities while reducing their conformational heterogeneity, and they stabilize multi-protein complexes. Here we demonstrate that engineered Nbs can also help overcome two major obstacles that limit the resolution of single-particle cryo-EM reconstructions: particle size and preferential orientation at the water-air interface. We have developed and characterised novel constructs, termed megabodies, by grafting Nbs into selected protein scaffolds to increase their molecular weight while retaining the full antigen binding specificity and affinity. We show that the megabody design principles are applicable to different scaffold proteins and recognition domains of compatible geometries and are amenable for efficient selection from yeast display libraries. Moreover, we used a megabody to solve the 2.5 [A] resolution cryo-EM structure of a membrane protein that suffers from severe preferential orientation, the human GABAA {beta}3 homopentameric receptor bound to its small-molecule agonist histamine.

biochemistry↗

bioRxiv2019

Scop3P: a comprehensive resource of human phosphosites within their full context

Protein phosphorylation is a key post-translational modification (PTM) in many biological processes and is associated to human diseases such as cancer and metabolic disorders. The accurate identification, annotation and functional analysis of phosphosites is therefore crucial to understand their various roles. Phosphosites (P-sites) are mainly analysed through phosphoproteomics, which has led to increasing amounts of publicly available phosphoproteomics data. Several resources have been built around the resulting phosphosite information, but these are usually restricted to protein sequence and basic site metadata. What is often missing from these resources, however, is context, including protein structure mapping, experimental provenance information, and biophysical predictions. We therefore developed Scop3P: a comprehensive database of human phosphosites within their full context. Scop3P integrates sequences (UniProtKB/Swiss-Prot), structures (PDB), and uniformly reprocessed phosphoproteomics data (PRIDE) to annotate all known human phosphosites. Furthermore, these sites are put into biophysical context by annotating each phosphoprotein with perresidue structural propensity, solvent accessibility, disordered probability, and early folding information. Scop3P, available at https://iomics.ugent.be/scop3p, presents a unique resource for visualization and analysis of phosphosites, and for understanding of phosphosite structure-function relationships.

bioinformatics↗

bioRxiv2018

Beyond the ribosome: proteome-wide secretability studies using SECRiFY

While transcriptome- and proteome-wide technologies to assess processes in protein biogenesis are now widely available, we still lack global approaches to assay post-ribosomal biogenesis events, in particular those occurring in the eukaryotic secretory system. We here developed a method, SECRiFY, to simultaneously assess the secretability of >105 protein fragments by two yeast species, S. cerevisiae and P. pastoris, using custom fragment libraries, surface display and a sequencing-based readout. Screening human proteome fragments with a median size of 50 - 100 amino acids, we generated datasets that enable datamining into protein features underlying secretability, revealing a striking role for intrinsic disorder and chain flexibility. SECRiFY is the first methodology that generates sufficient amounts of annotated data for advanced machine learning methods to deduce secretability predictors. The finding that secretability is indeed a learnable feature of protein sequences is of significant impact in the broad area of recombinant protein expression and de novo protein design.

molecular biology↗