ATLAS: protein flexibility description from atomistic molecular dynamics simulations.

Dynamical behaviour is one of the most crucial protein characteristics. Despite the advances in the field of protein structure resolution and prediction, analysis and prediction of protein dynamic properties remains a major challenge, mostly due to the low accessibility of data and its diversity and heterogeneity. To address this issue, we present ATLAS, a database of standardised all-atom molecular dynamics simulations, accompanied by their analysis in the form of interactive diagrams and trajectory visualisation. ATLAS offers a large-scale view and valuable insights on protein dynamics for a large and representative set of proteins, by combining data obtained through molecular dynamics simulations with information extracted from experimental structures. Users can easily analyse dynamic properties of functional protein regions, such as domain limits (hinge positions) and residues involved in interaction with other biological molecules. Additionally, the database enables exploration of proteins with uncommon dynamic properties conditioned by their environment such as chameleon subsequences and Dual Personality Fragments. The ATLAS database is freely available at https://www.dsimb.inserm.fr/ATLAS.

Poincaré maps for visualization of large protein families.

In the era of constantly increasing amounts of the available protein data, a relevant and interpretable visualization becomes crucial, especially for tasks requiring human expertise. Poincaré disk projection has previously demonstrated its important efficiency for visualization of biological data such as single-cell RNAseq data. Here, we develop a new method PoincaréMSA for visual representation of complex relationships between protein sequences based on Poincaré maps embedding. We demonstrate its efficiency and potential for visualization of protein family topology as well as evolutionary and functional annotation of uncharacterized sequences. PoincaréMSA is implemented in open source Python code with available interactive Google Colab notebooks as described at https://www.dsimb.inserm.fr/POINCARE_MSA.

Intergenic ORFs as elementary structural modules of de novo gene birth and protein evolution.

The noncoding genome plays an important role in de novo gene birth and in the emergence of genetic novelty. Nevertheless, how noncoding sequences' properties could promote the birth of novel genes and shape the evolution and the structural diversity of proteins remains unclear. Therefore, by combining different bioinformatic approaches, we characterized the fold potential diversity of the amino acid sequences encoded by all intergenic open reading frames (ORFs) of S. cerevisiae with the aim of (1) exploring whether the structural states' diversity of proteomes is already present in noncoding sequences, and (2) estimating the potential of the noncoding genome to produce novel protein bricks that could either give rise to novel genes or be integrated into pre-existing proteins, thus participating in protein structure diversity and evolution. We showed that amino acid sequences encoded by most yeast intergenic ORFs contain the elementary building blocks of protein structures. Moreover, they encompass the large structural state diversity of canonical proteins, with the majority predicted as foldable. Then, we investigated the early stages of de novo gene birth by reconstructing the ancestral sequences of 70 yeast de novo genes and characterized the sequence and structural properties of intergenic ORFs with a strong translation signal. This enabled us to highlight sequence and structural factors determining de novo gene emergence. Finally, we showed a strong correlation between the fold potential of de novo proteins and one of their ancestral amino acid sequences, reflecting the relationship between the noncoding genome and the protein structure universe.

ICARUS: flexible protein structural alignment based on Protein Units.

MOTIVATION: Alignment of protein structures is a major problem in structural biology. The first approach commonly used is to consider proteins as rigid bodies. However, alignment of protein structures can be very complex due to conformational variability, or complex evolutionary relationships between proteins such as insertions, circular permutations or repetitions. In such cases, introducing flexibility becomes useful for two reasons: (i) it can help compare two protein chains which adopted two different conformational states, such as due to proteins/ligands interaction or post-translational modifications, and (ii) it aids in the identification of conserved regions in proteins that may have distant evolutionary relationships. RESULTS: We propose ICARUS, a new approach for flexible structural alignment based on identification of Protein Units, evolutionarily preserved structural descriptors of intermediate size, between secondary structures and domains. ICARUS significantly outperforms reference methods on a dataset of very difficult structural alignments. AVAILABILITY AND IMPLEMENTATION: Code is freely available online at https://github.com/DSIMB/ICARUS.

SWORD2: hierarchical analysis of protein 3D structures.

Understanding the functions and origins of proteins requires splitting these macromolecules into fragments that could be independent in terms of folding, activity, or evolution. For that purpose, structural domains are the typical level of analysis, but shorter segments, such as subdomains and supersecondary structures, are insightful as well. Here, we propose SWORD2, a web server for exploring how an input protein structure may be decomposed into 'Protein Units' that can be hierarchically assembled to delimit structural domains. For each partitioning solution, the relevance of the identified substructures is estimated through different measures. This multilevel analysis is achieved by integrating our previous work on domain delineation, 'protein peeling' and model quality assessment. We hope that SWORD2 will be useful to biologists searching for key regions in their proteins of interest and to bioinformaticians building datasets of protein structures. The web server is freely available online: https://www.dsimb.inserm.fr/SWORD2.

Molecular and structural characterization of a novel high-prevalence antigen of the Augustine blood group system.

BACKGROUND: An antibody directed against a high-prevalence red blood cell (RBC) antigen was detected in a 67-year-old female patient of North African ancestry with a history of a single pregnancy and blood transfusion. So far, the specificity of the proband's alloantibody remained unknown in our immunohematology reference laboratory. STUDY DESIGN AND METHODS: Whole-exome sequencing (WES) was performed on the proband's DNA. The reactivity to the SLC29A1-encoded ENT1 adenosine transporter was investigated by flow cytometry analyses of ENT1-expressing HEK293 cells, and RBCs from Augustine-typed individuals. Erythrocyte protein expression level, nucleoside-binding capacity, and molecular structure of the proband's ENT1 variant were further explored by western blot, flow cytometry, and molecular dynamics calculations, respectively. RESULTS: A missense variant was identified in the SLC29A1 gene, which encodes the Augustine blood group system. It arises from homozygosity for a rare c.242A > G missense mutation that results in a nonsynonymous p.Asn81Ser substitution within the large extracellular loop of ENT1. Flow cytometry analyses demonstrated that the proband's antibody was reactive against HEK-293 cells transfected with control but not proband's SLC29A1 cDNA. Consistent with this finding, proband's antibody was found to be reactive with At(a-) (AUG:-2), but not AUG:-1 (null phenotype) RBCs. Data from structural analysis further supported that the proband's p.Asn81Ser variation does not alter ENT1 binding of its specific inhibitor NBMPR. CONCLUSION: Our study provides evidence for a novel high-prevalence antigen, AUG4 (also called ATAM after the proband's name) in the Augustine blood group system, encoded by the rare SLC29A1 variant allele AUG*04 (c.242A > G, p.Asn81Ser).

Insights into Comparative Modeling of VHH Domains.

In the particular case of the Camelidae family, immunoglobulin proteins have evolved into a unique and more simplified architecture with only heavy chains. The variable domains of these chains, named VHHs, have a number of Complementary Determining Regions (CDRs) reduced by half, and can function as single domains making them good candidates for molecular tools. 3D structure prediction of these domains is a beneficial and advantageous step to advance their developability as molecular tools. Nonetheless, the conformations of CDRs loops in these domains remain difficult to predict due to their higher conformational diversity. In addition to CDRs loop diversity, our earlier study has established that Framework Regions (FRs) are also not entirely conformationally conserved which establishes a need for more rigorous analyses of these regions that could assist in template selection. In the current study, VHHs models using different template selection strategies for comparative modeling using Modeller have been extensively assessed. This study analyses the conformational changes in both CDRs and FRs using an original strategy of conformational discretization based on a structural alphabet. Conformational sampling in selected cases is precisely reported. Some interesting outcomes of the structural analyses of models also draw attention towards the distinct difficulty in 3D structure prediction of VHH domains.

PYTHIA: Deep Learning Approach for Local Protein Conformation Prediction.

Protein Blocks (PBs) are a widely used structural alphabet describing local protein backbone conformation in terms of 16 possible conformational states, adopted by five consecutive amino acids. The representation of complex protein 3D structures as 1D PB sequences was previously successfully applied to protein structure alignment and protein structure prediction. In the current study, we present a new model, PYTHIA (predicting any conformation at high accuracy), for the prediction of the protein local conformations in terms of PBs directly from the amino acid sequence. PYTHIA is based on a deep residual inception-inside-inception neural network with convolutional block attention modules, predicting 1 of 16 PB classes from evolutionary information combined to physicochemical properties of individual amino acids. PYTHIA clearly outperforms the LOCUSTRA reference method for all PB classes and demonstrates great performance for PB prediction on particularly challenging proteins from the CASP14 free modelling category.

A structural entropy index to analyse local conformations in intrinsically disordered proteins.

Sequence - structure - function paradigm has been revolutionized by the discovery of disordered regions and disordered proteins more than two decades ago. While the definition of rigidity is simple with X-ray structures, the notion of flexibility is linked to high experimental B-factors. The definition of disordered regions is more complex as in these same X-ray structures; it is associated to the position of missing residues. Thus a continuum so seems to exist between rigidity, flexibility and disorder. However, it had not been precisely described. In this study, we used an ensemble of disordered proteins (or regions) and, we applied a structural alphabet to analyse their local conformation. This structural alphabet, namely Protein Blocks, had been efficiently used to highlight rigid local domains within flexible regions and so discriminates deformability and mobility concepts. Using an entropy index derived from this structural alphabet, we underlined its interest to measure these local dynamics, and to quantify, for the first time, continuum states from rigidity to flexibility and finally disorder. We also highlight non-disordered regions in the ensemble of disordered proteins in our study.

KNOTTIN: the database of inhibitor cystine knot scaffold after 10 years, toward a systematic structure modeling.

Knottins, or inhibitor cystine knots (ICKs), are ultra-stable miniproteins with multiple applications in drug design and medical imaging. These widespread and functionally diverse proteins are characterized by the presence of three interwoven disulfide bridges in their structure, which form a unique pseudoknot. Since 2004, the KNOTTIN database (www.dsimb.inserm.fr/KNOTTIN/) has been gathering standardized information about knottin sequences, structures, functions and evolution. The website also provides access to bibliographic data and to computational tools that have been specifically developed for ICKs. Here, we present a major upgrade of our database, both in terms of data content and user interface. In addition to the new features, this article describes how KNOTTIN has seen its size multiplied over the past ten years (since its last publication), notably with the recent inclusion of predicted ICKs structures. Finally, we report how our web resource has proved usefulness for the researchers working on ICKs, and how the new version of the KNOTTIN website will continue to serve this active community.

OREMPRO web server: orientation and assessment of atomistic and coarse-grained structures of membrane proteins.

UNLABELLED: : The experimental determination of membrane protein orientation within the lipid bilayer is extremely challenging, such that computational methods are most often the only solution. Moreover, obtaining all-atom 3D structures of membrane proteins is also technically difficult, and many of the available data are either experimental low-resolution structures or theoretical models, whose structural quality needs to be evaluated. Here, to address these two crucial problems, we propose OREMPRO, a web server capable of both (i) positioning α-helical and ß-sheet transmembrane domains in the lipid bilayer and (ii) assessing their structural quality. Most importantly, OREMPRO uses the sole alpha carbon coordinates, which makes it the only web server compatible with both high and low structural resolutions. Finally, OREMPRO is also interesting in its ability to process coarse-grained protein models, by using coordinates of backbone beads in place of alpha carbons. AVAILABILITY AND IMPLEMENTATION: http://www.dsimb.inserm.fr/OREMPRO/ CONTACT: : guillaume.postic@univ-paris-diderot.fr or jean-christophe.gelly@univ-paris-diderot.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Recent advances on polyproline II.

About half of the globular proteins are composed of regular secondary structures, α-helices, and ß-sheets, while the rest are constituted of irregular secondary structures, such as turns or coil conformations. Other regular secondary structures are often ignored, despite their importance in biological processes. Among such structures, the polyproline II helix (PPII) has interesting behaviours. PPIIs are not usually associated with conventional stabilizing interactions, and recent studies have observed that PPIIs are more frequent than anticipated. In addition, it is suggested that they may have an important functional role, particularly in protein-protein or protein-nucleic acid interactions and recognition. Residues associated with PPII conformations represent nearly 5% of the total residues, but the lack of PPII assignment approaches prevents their systematic analysis. This short review will present current knowledge and recent research in PPII area. In a first step, the different methodologies able to assign PPII are presented. In the second step, recent studies that have shown new perspectives in PPII analysis in terms of structure and function are underlined with three cases: (1) PPII in protein structures. For instance, the first crystal structure of an oligoproline adopting an all-trans polyproline II (PPII) helix had been presented; (2) the involvement of PPII in different diseases and drug designs; and (3) an interesting extension of PPII study in the protein dynamics. For instance, PPIIs are often linked to disorder region analysis and the precise analysis of a potential PPII helix in hypogonadism shows unanticipated PPII formations in the patient mutation, while it is not observed in the wild-type form of KISSR1 protein.

Improving protein fold recognition with hybrid profiles combining sequence and structure evolution.

MOTIVATION: Template-based modeling, the most successful approach for predicting protein 3D structure, often requires detecting distant evolutionary relationships between the target sequence and proteins of known structure. Developed for this purpose, fold recognition methods use elaborate strategies to exploit evolutionary information, mainly by encoding amino acid sequence into profiles. Since protein structure is more conserved than sequence, the inclusion of structural information can improve the detection of remote homology. RESULTS: Here, we present ORION, a new fold recognition method based on the pairwise comparison of hybrid profiles that contain evolutionary information from both protein sequence and structure. Our method uses the 16-state structural alphabet Protein Blocks, which provides an accurate 1D description of protein structure local conformations. ORION systematically outperforms PSI-BLAST and HHsearch on several benchmarks, including target sequences from the modeling competitions CASP8, 9 and 10, and detects ∼10% more templates at fold and superfamily SCOP levels. AVAILABILITY: Software freely available for download at http://www.dsimb.inserm.fr/orion/. CONTACT: jean-christophe.gelly@univ-paris-diderot.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Bioinformatic analysis of the protein/DNA interface.

To investigate the principles driving recognition between proteins and DNA, we analyzed more than thousand crystal structures of protein/DNA complexes. We classified protein and DNA conformations by structural alphabets, protein blocks [de Brevern, Etchebest and Hazout (2000) (Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks. Prots. Struct. Funct. Genet., 41:271-287)] and dinucleotide conformers [Svozil, Kalina, Omelka and Schneider (2008) (DNA conformations and their sequence preferences. Nucleic Acids Res., 36:3690-3706)], respectively. Assembling the mutually interacting protein blocks and dinucleotide conformers into 'interaction matrices' revealed their correlations and conformer preferences at the interface relative to their occurrence outside the interface. The analyzed data demonstrated important differences between complexes of various types of proteins such as transcription factors and nucleases, distinct interaction patterns for the DNA minor groove relative to the major groove and phosphate and importance of water-mediated contacts. Water molecules mediate proportionally the largest number of contacts in the minor groove and form the largest proportion of contacts in complexes of transcription factors. The generally known induction of A-DNA forms by complexation was more accurately attributed to A-like and intermediate A/B conformers rare in naked DNA molecules.

Local dynamics of proteins and DNA evaluated from crystallographic B factors.

The dynamics of protein and nucleic acid structures is as important as their average static picture. The local molecular dynamics concealed in diffraction images is expressed as so-called B factors. To find out how the crystal-derived B factors represent the dynamic behaviour of atoms and residues of proteins and DNA in their complexes, the distributions of scaled B factors from a carefully curated data set of over 700 protein-DNA crystal structures were analyzed [Schneider et al. (2014), Nucleic Acids Res. 42, 3381-3394]. Amino acids and nucleotides were categorized based on their molecular neighbourhood as solvent-accessible, solvent-inaccessible (i.e. forming the protein core) or lying at protein-protein or protein-DNA interfaces; the backbone and side-chain atoms were analyzed separately. The B factors of two types of crystal-ordered water molecules were also analyzed. The analysis confirmed several expected features of protein and DNA dynamics, but also revealed surprising facts. Solvent-accessible amino acids have B factors that are larger than those of residues at the biomolecular interfaces, and core-forming amino acids are the most restricted in their movement. A unique feature of the latter group is that their side-chain and backbone atoms are restricted in their movement to the same extent; in all other amino-acid groups the side chains are more floppy than the backbone. The low values of the B factors of water molecules bridging proteins with DNA and the very large fluctuations of DNA phosphates are surprising. The features discriminating different types of residues are less pronounced in structures with lower crystallographic resolution. Some of the observed trends are likely to be the consequence of improper refinement protocols that may need to be rectified.

PredyFlexy: flexibility and local structure prediction from sequence.

Protein structures are necessary for understanding protein function at a molecular level. Dynamics and flexibility of protein structures are also key elements of protein function. So, we have proposed to look at protein flexibility using novel methods: (i) using a structural alphabet and (ii) combining classical X-ray B-factor data and molecular dynamics simulations. First, we established a library composed of structural prototypes (LSPs) to describe protein structure by a limited set of recurring local structures. We developed a prediction method that proposes structural candidates in terms of LSPs and predict protein flexibility along a given sequence. Second, we examine flexibility according to two different descriptors: X-ray B-factors considered as good indicators of flexibility and the root mean square fluctuations, based on molecular dynamics simulations. We then define three flexibility classes and propose a method based on the LSP prediction method for predicting flexibility along the sequence. This method does not resort to sophisticate learning of flexibility but predicts flexibility from average flexibility of predicted local structures. The method is implemented in PredyFlexy web server. Results are similar to those obtained with the most recent, cutting-edge methods based on direct learning of flexibility data conducted with sophisticated algorithms. PredyFlexy can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/predyflexy/.

MitoGenesisDB: an expression data mining tool to explore spatio-temporal dynamics of mitochondrial biogenesis.

Mitochondria constitute complex and flexible cellular entities, which play crucial roles in normal and pathological cell conditions. The database MitoGenesisDB focuses on the dynamic of mitochondrial protein formation through global mRNA analyses. Three main parameters confer a global view of mitochondrial biogenesis: (i) time-course of mRNA production in highly synchronized yeast cell cultures, (ii) microarray analyses of mRNA localization that define translation sites and (iii) mRNA transcription rate and stability which characterize genes that are more dependent on post-transcriptional regulation processes. MitoGenesisDB integrates and establishes cross-comparisons between these data. Several model organisms can be analyzed via orthologous relationships between interspecies genes. More generally this database supports the 'post-transcriptional operon' model, which postulates that eukaryotes co-regulate related mRNAs based on their functional organization in ribonucleoprotein complexes. MitoGenesisDB allows identifying such groups of post-trancriptionally regulated genes and is thus a useful tool to analyze the complex relationships between transcriptional and post-transcriptional regulation processes. The case of respiratory chain assembly factors illustrates this point. The MitoGenesisDB interface is available at http://www.dsimb.inserm.fr/dsimb_tools/mitgene/.

iPBA: a tool for protein structure comparison using sequence alignment strategies.

With the immense growth in the number of available protein structures, fast and accurate structure comparison has been essential. We propose an efficient method for structure comparison, based on a structural alphabet. Protein Blocks (PBs) is a widely used structural alphabet with 16 pentapeptide conformations that can fairly approximate a complete protein chain. Thus a 3D structure can be translated into a 1D sequence of PBs. With a simple Needleman-Wunsch approach and a raw PB substitution matrix, PB-based structural alignments were better than many popular methods. iPBA web server presents an improved alignment approach using (i) specialized PB Substitution Matrices (SM) and (ii) anchor-based alignment methodology. With these developments, the quality of ∼88% of alignments was improved. iPBA alignments were also better than DALI, MUSTANG and GANGSTA(+) in >80% of the cases. The webserver is designed to for both pairwise comparisons and database searches. Outputs are given as sequence alignment and superposed 3D structures displayed using PyMol and Jmol. A local alignment option for detecting subs-structural similarity is also embedded. As a fast and efficient 'sequence-based' structure comparison tool, we believe that it will be quite useful to the scientific community. iPBA can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/ipba/.

Quality assessment of VHH models.

Heavy Chain Only Antibodies are specific to Camelid species. Despite the lack of the light chain variable domain, their heavy chain variable domain (VH) domain, named VHH or nanobody, has promising potential applications in research and therapeutic fields. The structural study of VHH is therefore of great interest. Unfortunately, considering the huge amount of sequences that might be produced, only about one thousand of VHH experimental structures are publicly available in the Protein Data Bank, implying that structural model prediction of VHH is a necessary alternative to obtaining 3D information besides its sequence. The present study aims to assess and compare the quality of predictions from different modelling methodologies. Established comparative & homology modelling approaches to recent Deep Learning-based modelling strategies were applied, i.e. Modeller using single or multiple structural templates, ModWeb, SwissModel (with two evaluation schema), RoseTTAfold, AlphaFold 2 and NanoNet. The prediction accuracy was evaluated using RMSD, TM-score, GDT-TS, GDT-HA and Protein Blocks distance metrics. Besides the global structure assessment, we performed specific analyses of Frameworks and CDRs structures. We observed that AlphaFold 2 and especially NanoNet performed better than the other evaluated softwares. Importantly, we performed molecular dynamics simulations of an experimental structure and a NanoNet predicted model of a VHH in order to compare the global structural flexibility and local conformations using Protein Blocks. Despite rather similar structures, substantial differences in dynamical properties were observed, which underlies the complexity of the task of model evaluation.Communicated by Ramaswamy H. Sarma.

Protein Peeling 3D: new tools for analyzing protein structures.

UNLABELLED: We present an improved version of our Protein Peeling web server dedicated to the analysis of protein structure architecture through the identification of protein units produced by an iterative splitting algorithm. New features include identification of structural domains, detection of unstructured terminal elements and evaluation of the stability of protein unit structures. AVAILABILITY: The website is free and open to all users with no login requirements at http://www.dsimb.inserm.fr/dsimb-tools/peeling3.