Evolutionarily conserved protein motifs drive interactions between the plant nucleoskeleton and nuclear pores

The nucleoskeleton forms a filamentous meshwork under the nuclear envelope and contributes to the regulation of nuclear shape and gene expression. To understand how the Arabidopsis (Arabidopsis thaliana) nucleoskeleton physically connects to the nuclear periphery in plants, we investigated the Arabidopsis nucleoskeleton protein KAKU4 and sought for functional regions responsible for its localization at the nuclear periphery. We identified 3 conserved peptide motifs within the N-terminal region of KAKU4, which are required for intermolecular interactions of KAKU4 with itself, interaction with the nucleoskeleton protein CROWDED NUCLEI (CRWN), localization at the nuclear periphery, and nuclear elongation in differentiated tissues. Unexpectedly, we find these motifs to be present also in NUP82 and NUP136, 2 plant-specific nucleoporins from the nuclear pore basket. We further show that NUP82, NUP136, and KAKU4 have a common evolutionary history predating nonvascular land plants with KAKU4 mainly localizing outside the nuclear pore suggesting its divergence from an ancient nucleoporin into a new nucleoskeleton component. Finally, we demonstrate that both NUP82 and NUP136, through their shared N-terminal motifs, interact with CRWN and KAKU4 proteins revealing the existence of a physical continuum between the nuclear pore and the nucleoskeleton in plants.

PEP-FOLD4: a pH-dependent force field for peptide structure prediction in aqueous solution

Accurate and fast structure prediction of peptides of less 40 amino acids in aqueous solution has many biological applications, but their conformations are pH- and salt concentration-dependent. In this work, we present PEP-FOLD4 which goes one step beyond many machine-learning approaches, such as AlphaFold2, TrRosetta and RaptorX. Adding the Debye-Hueckel formalism for charged-charged side chain interactions to a Mie formalism for all intramolecular (backbone and side chain) interactions, PEP-FOLD4, based on a coarse-grained representation of the peptides, performs as well as machine-learning methods on well-structured peptides, but displays significant improvements for poly-charged peptides. PEP-FOLD4 is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD4. This server is free and there is no login requirement.

In Silico and In Vivo Studies of a Tumor-Penetrating and Interfering Peptide with Antitumoral Effect on Xenograft Models of Breast Cancer

The combination of a tumor-penetrating peptide (TPP) with a peptide able to interfere with a given protein-protein interaction (IP) is a promising strategy with potential clinical application. Little is known about the impact of fusing a TPP with an IP, both in terms of internalization and functional effect. Here, we analyze these aspects in the context of breast cancer, targeting PP2A/SET interaction, using both in silico and in vivo approaches. Our results support the fact that state-of-the-art deep learning approaches developed for protein-peptide interaction modeling can reliably identify good candidate poses for the IP-TPP in interaction with the Neuropilin-1 receptor. The association of the IP with the TPP does not seem to affect the ability of the TPP to bind to Neuropilin-1. Molecular simulation results suggest that peptide IP-GG-LinTT1 in a cleaved form interacts with Neuropilin-1 in a more stable manner and has a more helical secondary structure than the cleaved IP-GG-iRGD. Surprisingly, in silico investigations also suggest that the non-cleaved TPPs can bind the Neuropilin-1 in a stable manner. The in vivo results using xenografts models show that both bifunctional peptides resulting from the combination of the IP and either LinTT1 or iRGD are effective against tumoral growth. The peptide iRGD-IP shows the highest stability to serum proteases degradation while having the same antitumoral effect as Lin TT1-IP, which is more sensitive to proteases degradation. Our results support the development of the TPP-IP strategy as therapeutic peptides against cancer.

Binding and Kinetic Analysis of Human Protein Phosphatase PP2A Interactions with Caspase 9 Protein and the Interfering Peptide C9h

The serine/threonine phosphatase PP2A and the cysteine protease Caspase 9 are two proteins involved in physiological and pathological processes, including cancer and apoptosis. We previously demonstrated the interaction between Caspase 9 and PP2A and identified the C9h peptide, corresponding to the binding site of Caspase 9 to PP2A. This interfering peptide can modulate Caspase 9/PP2A interaction leading to a strong therapeutic effect in vitro and in vivo in mouse models of tumor progression. In this manuscript, we investigate (I) the peptide binding to PP2A combining docking with molecular dynamics and (II) the secondary structure of the peptide using CD spectroscopy. Additionally, we compare the binding affinity, using biolayer interferometry, of the wild-type protein PP2A with Caspase 9 and vice versa to that observed between the PP2A protein and the interfering peptide C9h. This result strongly encourages the use of peptides as new therapeutics against cancer, as shown for the C9h peptide already in clinical trial.

A Generalized Attraction-Repulsion Potential and Revisited Fragment Library Improves PEP-FOLD Peptide Structure Prediction

Fast and accurate structure prediction is essential to the study of peptide function, molecular targets, and interactions and has been the subject of considerable efforts in the past decade. In this work, we present improvements to the popular simplified PEP-FOLD technique for small peptide structure prediction. PEP-FOLD originality is threefold: (i) it uses a predetermined structural alphabet, (ii) it uses a sequential algorithm to reconstruct the tridimensional structures of these peptides in a discrete space using a fragment library, and (iii) it assesses the energy of these structures using a coarse-grained representation in which all of the backbone atoms but the α-hydrogen are present, and the side chain corresponds to a unique bead. In former versions of PEP-FOLD, a van der Waals formulation was used for non-bonded interactions, with each side chain being associated with a fixed radius. Here, we explore the relevance of using instead a generalized formulation in which not only the optimal distance of interaction and the energy at this distance are parameters but also the distance at which the potential is zero. This allows each side chain to be associated with a different radius and potential energy shape, depending on its interaction partner, and in principle to make more effective the coarse-grained representation. In addition, the new PEP-FOLD version is associated with an updated library of fragments. We show that these modifications lead to important improvements for many of the problematic targets identified with the former PEP-FOLD version while maintaining already correct predictions. The improvement is in terms of both model ranking and model accuracy. We also compare the PEP-FOLD enhanced version to state-of-the-art techniques for both peptide and structure predictions: APPTest, RaptorX, and AlphaFold2. We find that the new predictions are superior, in particular with respect to the prediction of small β-targets, to those of APPTest and RaptorX and bring, with its original approach, additional understanding on folded structures, even when less precise than AlphaFold2. With their strong physical influence, the revised structural library and coarse-grained potential offer, however, the means for a deeper understanding of the nature of folding and open a solid basis for studying flexibility and other dynamical properties not accessible to IA structure prediction approaches.

Bi-Functional Peptides as a New Therapeutic Tool for Hepatocellular Carcinoma

Background: The interfering peptides that block protein–protein interactions have been receiving increasing attention as potential therapeutic tools. Methods: We measured the internalization and biological effect of four bi-functional tumor-penetrating and interfering peptides into primary hepatocytes isolated from three non-malignant and 11 hepatocellular carcinomas. Results: These peptides are internalized in malignant hepatocytes but not in non-malignant cells. Furthermore, the degree of peptide internalization correlated with receptor expression level and tumor aggressiveness levels. Importantly, penetration of the peptides iRGD-IP, LinTT1-IP, TT1-IP, and RPARPAR-IP induced apoptosis of the malignant hepatocytes without effect on non-malignant cells. Conclusion: Receptor expression levels correlated with the level of peptide internalization and aggressiveness of the tumor. This study highlights the potential to exploit the expression of tumor-penetrating peptide receptors as a predictive marker of liver tumor aggressiveness. These bi-functional peptides could be developed for personalized tumor treatment.

A community proposal to integrate structural bioinformatics activities in ELIXIR (3D-Bioinfo Community)

Structural bioinformatics provides the scientific methods and tools to analyse, archive, validate, and present the biomolecular structure data generated by the structural biology community. It also provides an important link with the genomics community, as structural bioinformaticians also use the extensive sequence data to predict protein structures and their functional sites. A very broad and active community of structural bioinformaticians exists across Europe, and 3D-Bioinfo will establish formal platforms to address their needs and better integrate their activities and initiatives. Our mission will be to strengthen the ties with the structural biology research communities in Europe covering life sciences, as well as chemistry and physics and to bridge the gap between these researchers in order to fully realize the potential of structural bioinformatics. Our Community will also undertake dedicated educational, training and outreach efforts to facilitate this, bringing new insights and thus facilitating the development of much needed innovative applications e.g. for human health, drug and protein design. Our combined efforts will be of critical importance to keep the European research efforts competitive in this respect.

Here we highlight the major European contributions to the field of structural bioinformatics, the most pressing challenges remaining and how Europe-wide interactions, enabled by ELIXIR and its platforms, will help in addressing these challenges and in coordinating structural bioinformatics resources across Europe. In particular, we present recent activities and future plans to consolidate an ELIXIR 3D-Bioinfo Community in structural bioinformatics and propose means to develop better links across the community. These include building new consortia, organising workshops to establish data standards and seeking community agreement on benchmark data sets and strategies. We also highlight existing and planned collaborations with other ELIXIR Communities and other European infrastructures, such as the structural biology community supported by Instruct-ERIC, with whom we have synergies and overlapping common interests.

Coarse-grained and atomic resolution biomolecular docking with the ATTRACT approach

The ATTRACT protein-protein docking program has been employed to predict protein-protein complex structures in CAPRI rounds 38-45. For 11 out of 16 targets acceptable or better quality solutions have been submitted (~70%). It includes also several cases of peptide-protein docking and the successful prediction of the geometry of carbohydrate-protein interactions. The option of combining rigid body minimization and simultaneous optimization in collective degrees of freedom based on elastic network modes was employed and systematically evaluated. Application to a large benchmark set indicates a modest improvement in docking performance compared to rigid docking. Possible further improvements of the docking approach in particular at the scoring and the flexible refinement steps are discussed.

The pepATTRACT web server for blind, large-scale peptide-protein docking

Peptide–protein interactions are ubiquitous in the cell and form an important part of the interactome. Computational docking methods can complement experimental characterization of these complexes, but current protocols are not applicable on the proteome scale. pepATTRACT is a novel docking protocol that is fully blind, i.e. it does not require any information about the binding site. In various stages of its development, pepATTRACT has participated in CAPRI, making successful predictions for five out of seven protein–peptide targets. Its performance is similar or better than state-of-the-art local docking protocols that do require binding site information. Here we present a novel web server that carries out the rigid-body stage of pepATTRACT. On the peptiDB benchmark, the web server generates a correct model in the top 50 in 34% of the cases. Compared to the full pepATTRACT protocol, this leads to some loss of performance, but the computation time is reduced from ∼18 h to ∼10 min. Combined with the fact that it is fully blind, this makes the web server well-suited for large-scale in silico protein–peptide docking experiments. The rigid-body pepATTRACT server is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/services/pepATTRACT.

Probing the quality control mechanism of the Escherichia coli twin-arginine translocase with folding variants of a de novo-designed heme protein

Protein transport across the cytoplasmic membrane of bacterial cells is mediated by either the general secretion (Sec) system or the twin-arginine translocase (Tat). The Tat machinery exports folded and cofactor-containing proteins from the cytoplasm to the periplasm by using the transmembrane proton motive force as a source of energy. The Tat apparatus apparently senses the folded state of its protein substrates, a quality-control mechanism that prevents premature export of nascent unfolded or misfolded polypeptides, but its mechanistic basis has not yet been determined. Here, we investigated the innate ability of the model Escherichia coli Tat system to recognize and translocate de novo–designed protein substrates with experimentally determined differences in the extent of folding. Water-soluble, four-helix bundle maquette proteins were engineered to bind two, one, or no heme b cofactors, resulting in a concomitant reduction in the extent of their folding, assessed with temperature-dependent CD spectroscopy and one-dimensional ¹H NMR spectroscopy. Fusion of the archetypal N-terminal Tat signal peptide of the E. coli trimethylamine-N-oxide (TMAO) reductase (TorA) to the N terminus of the protein maquettes was sufficient for the Tat system to recognize them as substrates. The clear correlation between the level of Tat-dependent export and the degree of heme b–induced folding of the maquette protein suggested that the membrane-bound Tat machinery can sense the extent of folding and conformational flexibility of its substrates. We propose that these artificial proteins are ideal substrates for future investigations of the Tat system's quality-control mechanism.

Interfering peptides targeting protein-protein interactions: the next generation of drugs?

Protein-protein interactions (PPIs) are well recognized as promising therapeutic targets. Consequently, interfering peptides (IPs) - natural or synthetic peptides capable of interfering with PPIs - are receiving increasing attention. Given their physicochemical characteristics, IPs seem better suited than small molecules to interfere with the large surfaces implicated in PPIs. Progress on peptide administration, stability, biodelivery and safety are also encouraging the interest in peptide drug development. The concept of IPs has been validated for several PPIs, generating great expectations for their therapeutic potential. Here, we describe approaches and methods useful for IPs identification and in silico, physicochemical and biological-based strategies for their design and optimization. Selected promising in-vivo-validated examples are described and advantages, limitations and potential of IPs as therapeutic tools are discussed.

A Computational Methodology to Overcome the Challenges Associated With the Search for Specific Enzyme Targets to Develop Drugs Against Leishmania major

We present an approach for detecting enzymes that are specific of Leishmania major compared with Homo sapiens and provide targets that may assist research in drug development. This approach is based on traditional techniques of sequence homology comparison by similarity search and Markov modeling; it integrates the characterization of enzymatic functionality, secondary and tertiary protein structures, protein domain architecture, and metabolic environment. From 67 enzymes represented by 42 enzymatic activities classified by AnEnPi (Analogous Enzymes Pipeline) as specific for L major compared with H sapiens, only 40 (23 Enzyme Commission [EC] numbers) could actually be considered as strictly specific of L major and 27 enzymes (19 EC numbers) were disregarded for having ambiguous homologies or analogies with H sapiens. Among the 40 strictly specific enzymes, we identified sterol 24-C-methyltransferase, pyruvate phosphate dikinase, trypanothione synthetase, and RNA-editing ligase as 4 essential enzymes for L major that may serve as targets for drug development.

A Functional Role for the Monomethylated Gln-51 and Lys-53 Residues of the 49GGQTK53 Motif of eL42 from Human 80S Ribosomes

BACKGROUND

We have previously demonstrated that the eukaryote-specific ribosomal protein eL42 of the human 80S ribosome contains seven monomethylated residues, among which are the Gln-51 and Lys-53 residues contained in the 47GFGGQTK53 sequence conserved in all eukaryotic 80S ribosomes. This sequence contains the methylated and universally conserved GGQ motif common for all class-1 translation termination factors responsible for stop codon recognition and for triggering the hydrolysis of the P site-bound peptidyl-tRNA. We have also recently reported a model of ribosomal ternary eL42-tRNA-eRF1 complex where specific regions of all three macromolecules (the comparably flexible GGQ domains of eRF1 and eL42 and the CCA-arm of tRNA) are involved in interactions.

METHOD

Here, we have studied the interactions between recombinant eL42 and eRF1 proteins and the tRNA substrate by means of the Biacore assay, using the wild-type eL42 protein, the eL42-Δ(GGQTK) mutant (the eL42 protein whose GGQTK motif has been deleted), the single Q51E and K53Q mutants (eL42-Q51E and eL42-K53Q, respectively), as well as the double Q51A/K53A mutant (eL42-Q51A/K53A).

RESULTS

Our results show that the monomethylated Gln-51 and Lys-53 residues contained in the 47GFGGQTK53 sequence of eL42 and the monomethylated GGQ motif of eRF1 represents the sites of interaction between these two proteins through hydrophobic contacts between methyl groups. We also demonstrate that the interactions between eL42 and tRNA or 28S rRNA are characterized by strong binding affinities (KD values in the nanomolar or picomolar range, respectively) which argue for specific interactions. Strong interactions between eL42 and tRNA are likely to be responsible for the decrease in the poly(U)-dependent poly(Phe) synthesis activity of human 80S or E. coli 70S ribosomes in the presence of added human recombinant eL42. It is proposed that the decrease of the activity of the ribosome is caused by the sequestration of the substrate Phe-tRNAPhe by the added eL42 protein.

CONCLUSION

Interactions between the monomethylated Gln-51 and Lys-53 residues of the 49GGQTK53 motif of the human eL42 protein and the methylated GGQ motif of eRF1 are likely to play a functional role on translating human 80S ribosomes.

Peptide Suboptimal Conformation Sampling for the Prediction of Protein-Peptide Interactions

The blind identification of candidate patches of interaction on the protein surface is a difficult task that can hardly be accomplished without a heuristic or the use of simplified representations to speed up the search. The PEP-SiteFinder protocol performs a systematic blind search on the protein surface using a rigid docking procedure applied to a limited set of peptide suboptimal conformations expected to approximate satisfactorily the conformation of the peptide in interaction. All steps rely on a coarse-grained representation of the protein and the peptide. While simple, such a protocol can help to infer useful information, assuming a critical analysis of the results. Moreover, such a protocol can be extended to a semi-flexible protocol where the suboptimal conformations are directly folded in the vicinity of the receptor.

HHalign-Kbest: exploring sub-optimal alignments for remote homology comparative modeling

MOTIVATION

The HHsearch algorithm, implementing a hidden Markov model (HMM)-HMM alignment method, has shown excellent alignment performance in the so-called twilight zone (target-template sequence identity with ∼20%). However, an optimal alignment by HHsearch may contain small to large errors, leading to poor structure prediction if these errors are located in important structural elements.

RESULTS

HHalign-Kbest server runs a full pipeline, from the generation of suboptimal HMM-HMM alignments to the evaluation of the best structural models. In the HHsearch framework, it implements a novel algorithm capable of generating k-best HMM-HMM suboptimal alignments rather than only the optimal one. For large proteins, a directed acyclic graph-based implementation reduces drastically the memory usage. Improved alignments were systematically generated among the top k suboptimal alignments. To recognize them, corresponding structural models were systematically generated and evaluated with Qmean score. The method was benchmarked over 420 targets from the SCOP30 database. In the range of HHsearch probability of 20-99%, average quality of the models (TM-score) raised by 4.1-16.3% and 8.0-21.0% considering the top 1 and top 10 best models, respectively.

AVAILABILITY AND IMPLEMENTATION

http://bioserv.rpbs.univ-paris-diderot.fr/services/HHalign-Kbest/ (source code and server).

CONTACT

guerois@cea.fr.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

De novo peptide structure prediction: an overview

Peptide structure identification is an important contribution to the further characterization of the residues involved in functional interactions. De novo structure peptide prediction has, in the past few years, made significant progresses that make reasonable, for peptides up to 50 amino acids, its use for the fast identification of their structural topologies. Here, we introduce some of the concepts underlying approaches of the field, together with their limits.

BactPepDB: a database of predicted peptides from a exhaustive survey of complete prokaryote genomes

With the recent progress in complete genome sequencing, mining the increasing amount of genomic information available should in theory provide the means to discover new classes of peptides. However, annotation pipelines often do not consider small reading frames likely to be expressed. BactPepDB, available online at http://bactpepdb.rpbs.univ-paris-diderot.fr, is a database that aims at providing an exhaustive re-annotation of all complete prokaryotic genomes—chromosomal and plasmid DNA—available in RefSeq for coding sequences ranging between 10 and 80 amino acids. The identified peptides are classified as (i) previously identified in RefSeq, (ii) entity-overlapping (intragenic) or intergenic, and (iii) potential pseudogenes—intergenic sequences corresponding to a portion of a previously annotated larger gene. Additional information is related to homologs within order, predicted signal sequence, transmembrane segments, disulfide bonds, secondary structure, and the existence of a related 3D structure in the Protein Databank. As a result, BactPepDB provides insights about candidate peptides, and provides information about their conservation, together with some of their expected biological/structural features. The BactPepDB interface allows to search for candidate peptides in the database, or to search for peptides similar to a query, according to the multiple properties predicted or related to genomic localization.

Database URL:http://www.yeastgenome.org/

The CCA-end of P-tRNA Contacts Both the Human RPL36AL and the A-site Bound Translation Termination Factor eRF1 at the Peptidyl Transferase Center of the Human 80S Ribosome

We have demonstrated previously that the E-site specific protein RPL36AL present in human ribosomes can be crosslinked with the CCA-end of a P-tRNA in situ. Here we report the following: (i) We modeled RPL36AL into the structure of the archaeal ortholog RPL44E extracted from the known X-ray structure of the 50S subunit of Haloarcula marismortui. Superimposing the obtained RPL36AL structure with that of P/E tRNA observed in eukaryotic 80S ribosomes suggested that RPL36AL might in addition to its CCA neighbourhood interact with the inner site of the tRNA elbow similar to an interaction pattern known from tRNA•synthetase pairs. (ii) Accordingly, we detected that the isolated recombinant protein RPL36AL can form a tight binary complex with deacylated tRNA, and even tRNA fragments truncated at their CCA end showed a high affinity in the nanomolar range supporting a strong interaction outside the CCA end. (iii) We constructed programmed 80S complexes containing the termination factor eRF1 (stop codon UAA at the A-site) and a 2’,3’-dialdehyde tRNA (tRNAox) analog at the P-site. Surprisingly, we observed a crosslinked ternary complex containing the tRNA, eRF1 and RPL36AL crosslinked both to the aldehyde groups of tRNAox at the 2’- and 3’-positions of the ultimate A. We also demonstrated that, upon binding to the ribosomal A-site, eRF1 induces an alternative conformation of the ribosome and/or the tRNA, leading to a novel crosslink of tRNAox to another large-subunit ribosomal protein (namely L37) rather than to RPL36AL, both ribosomal proteins being labeled in a mutually exclusive fashion. Since the human 80S ribosome in complex with P-site bound tRNAox and A-site bound eRF1 corresponds to the post-termination state of the ribosome, the results represent the first biochemical evidence for the positioning of the CCA-arm of the P-tRNA in close proximity to both RPL36AL and eRF1 at the end of the translation process.

The OPEP protein model: from single molecules, amyloid formation, crowding and hydrodynamics to DNA/RNA systems

The OPEP coarse-grained protein model has been applied to a wide range of applications since its first release 15 years ago. The model, which combines energetic and structural accuracy and chemical specificity, allows the study of single protein properties, DNA-RNA complexes, amyloid fibril formation and protein suspensions in a crowded environment. Here we first review the current state of the model and the most exciting applications using advanced conformational sampling methods. We then present the current limitations and a perspective on the ongoing developments.

Detecting protein candidate fragments using a structural alphabet profile comparison approach

Predicting accurate fragments from sequence has recently become a critical step for protein structure modeling, as protein fragment assembly techniques are presently among the most efficient approaches for de novo prediction. A key step in these approaches is, given the sequence of a protein to model, the identification of relevant fragments - candidate fragments - from a collection of the available 3D structures. These fragments can then be assembled to produce a model of the complete structure of the protein of interest. The search for candidate fragments is classically achieved by considering local sequence similarity using profile comparison, or threading approaches. In the present study, we introduce a new profile comparison approach that, instead of using amino acid profiles, is based on the use of predicted structural alphabet profiles, where structural alphabet profiles contain information related to the 3D local shapes associated with the sequences. We show that structural alphabet profile-profile comparison can be used efficiently to retrieve accurate structural fragments, and we introduce a fully new protocol for the detection of candidate fragments. It identifies fragments specific of each position of the sequence and of size varying between 6 and 27 amino-acids. We find it outperforms present state of the art approaches in terms (i) of the accuracy of the fragments identified, (ii) the rate of true positives identified, while having a high coverage score. We illustrate the relevance of the approach on complete target sets of the two previous Critical Assessment of Techniques for Protein Structure Prediction (CASP) rounds 9 and 10. A web server for the approach is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/SAFrag.

Missense mutations in SLC26A8, encoding a sperm-specific activator of CFTR, are associated with human asthenozoospermia

The cystic fibrosis transmembrane conductance regulator (CFTR) is present in mature sperm and is required for sperm motility and capacitation. Both these processes are controlled by ions fluxes and are essential for fertilization. We have shown that SLC26A8, a sperm-specific member of the SLC26 family of anion exchangers, associates with the CFTR channel and strongly stimulates its activity. This suggests that the two proteins cooperate to regulate the anion fluxes required for correct sperm motility and capacitation. Here, we report on three heterozygous SLC26A8 missense mutations identified in a cohort of 146 men presenting with asthenozoospermia: c.260G>A (p.Arg87Gln), c.2434G>A (p.Glu812Lys), and c.2860C>T (p.Arg954Cys). These mutations were not present in 121 controls matched for ethnicity, and statistical analysis on a control population of 8,600 individuals (from dbSNP and 1000 Genomes) showed them to be associated with asthenozoospermia with a power > 95%. By cotransfecting Chinese hamster ovary (CHO)-K1 cells with SLC26A8 variants and CFTR, we showed that the physical interaction between the two proteins was partly conserved but that the capacity to activate CFTR-dependent anion transport was completely abolished for all mutants. Biochemical studies revealed the presence of much smaller amounts of protein for all variants, but these amounts were restored to wild-type levels upon treatment with the proteasome inhibitor MG132. Immunocytochemistry also showed the amounts of SLC26A8 in sperm to be abnormally small in individuals carrying the mutations. These mutations might therefore impair formation of the SLC26A8-CFTR complex, principally by affecting SLC26A8 stability, consistent with an impairment of CFTR-dependent sperm-activation events in affected individuals.

Protease profiling of liver fibrosis reveals the ADAM metallopeptidase with thrombospondin type 1 motif, 1 as a central activator of transforming growth factor beta

During chronic liver disease, tissue remodeling leads to dramatic changes and accumulation of matrix components. Matrix metalloproteases and their inhibitors have been involved in the regulation of matrix degradation. However, the role of other proteases remains incompletely defined. We undertook a gene-expression screen of human liver fibrosis samples using a dedicated gene array selected for relevance to protease activities, identifying the ADAMTS1 (A Disintegrin And Metalloproteinase [ADAM] with thrombospondin type 1 motif, 1) gene as an important node of the protease network. Up-regulation of ADAMTS1 in fibrosis was found to be associated with hepatic stellate cell (HSC) activation. ADAMTS1 is synthesized as 110-kDa latent forms and is processed by HSCs to accumulate as 87-kDa mature forms in fibrotic tissues. Structural evidence has suggested that the thrombospondin motif-containing domain from ADAMTS1 may be involved in interactions with, and activation of, the major fibrogenic cytokine, transforming growth factor beta (TGF-β). Indeed, we observed direct interactions between ADAMTS1 and latency-associated peptide-TGF-β (LAP-TGF-β). ADAMTS1 induces TGF-β activation through the interaction of the ADAMTS1 KTFR peptide with the LAP-TGF-β LKSL peptide. Down-regulation of ADAMTS1 in HSCs decreases the release of TGF-β competent for transcriptional activation, and KTFR competitor peptides directed against ADAMTS1 block the HSC-mediated release of active TGF-β. Using a mouse liver fibrosis model, we show that carbon tetrachloride treatment induces ADAMTS1 expression in parallel to that of type I collagen. Importantly, concurrent injection of the KTFR peptide prevents liver damage.

CONCLUSION

Our results indicate that up-regulation of ADAMTS1 in HSCs constitutes a new mechanism for control of TGF-β activation in chronic liver disease.

Flexibility and binding affinity in protein-ligand, protein-protein and multi-component protein interactions: limitations of current computational approaches

The recognition process between a protein and a partner represents a significant theoretical challenge. In silico structure-based drug design carried out with nothing more than the three-dimensional structure of the protein has led to the introduction of many compounds into clinical trials and numerous drug approvals. Central to guiding the discovery process is to recognize active among non-active compounds. While large-scale computer simulations of compounds taken from a library (virtual screening) or designed de novo are highly desirable in the post-genomic area, many technical problems remain to be adequately addressed. This article presents an overview and discusses the limits of current computational methods for predicting the correct binding pose and accurate binding affinity. It also presents the performances of the most popular algorithms for exploring binary and multi-body protein interactions.

aes, the gene encoding the esterase B in Escherichia coli, is a powerful phylogenetic marker of the species

Background

Previous studies have established a correlation between electrophoretic polymorphism of esterase B, and virulence and phylogeny of Escherichia coli. Strains belonging to the phylogenetic group B2 are more frequently implicated in extraintestinal infections and include esterase B₂ variants, whereas phylogenetic groups A, B1 and D contain less virulent strains and include esterase B₁ variants. We investigated esterase B as a marker of phylogeny and/or virulence, in a thorough analysis of the esterase B-encoding gene.

Results

We identified the gene encoding esterase B as the acetyl-esterase gene (aes) using gene disruption. The analysis of aes nucleotide sequences in a panel of 78 reference strains, including the E. coli reference (ECOR) strains, demonstrated that the gene is under purifying selection. The phylogenetic tree reconstructed from aes sequences showed a strong correlation with the species phylogenetic history, based on multi-locus sequence typing using six housekeeping genes. The unambiguous distinction between variants B₁ and B₂ by electrophoresis was consistent with Aes amino-acid sequence analysis and protein modelling, which showed that substituted amino acids in the two esterase B variants occurred mostly at different sites on the protein surface. Studies in an experimental mouse model of septicaemia using mutant strains did not reveal a direct link between aes and extraintestinal virulence. Moreover, we did not find any genes in the chromosomal region of aes to be associated with virulence.

Conclusion

Our findings suggest that aes does not play a direct role in the virulence of E. coli extraintestinal infection. However, this gene acts as a powerful marker of phylogeny, illustrating the extensive divergence of B2 phylogenetic group strains from the rest of the species.

Mobyle: a new full web bioinformatics framework

Motivation: For the biologist, running bioinformatics analyses involves a time-consuming management of data and tools. Users need support to organize their work, retrieve parameters and reproduce their analyses. They also need to be able to combine their analytic tools using a safe data flow software mechanism. Finally, given that scientific tools can be difficult to install, it is particularly helpful for biologists to be able to use these tools through a web user interface. However, providing a web interface for a set of tools raises the problem that a single web portal cannot offer all the existing and possible services: it is the user, again, who has to cope with data copy among a number of different services. A framework enabling portal administrators to build a network of cooperating services would therefore clearly be beneficial.

Results: We have designed a system, Mobyle, to provide a flexible and usable Web environment for defining and running bioinformatics analyses. It embeds simple yet powerful data management features that allow the user to reproduce analyses and to combine tools using a hierarchical typing system. Mobyle offers invocation of services distributed over remote Mobyle servers, thus enabling a federated network of curated bioinformatics portals without the user having to learn complex concepts or to install sophisticated software. While being focused on the end user, the Mobyle system also addresses the need, for the bioinfomatician, to automate remote services execution: PlayMOBY is a companion tool that automates the publication of BioMOBY web services, using Mobyle program definitions.

Availability: The Mobyle system is distributed under the terms of the GNU GPLv2 on the project web site (http://bioweb2.pasteur.fr/projects/mobyle/). It is already deployed on three servers: http://mobyle.pasteur.fr, http://mobyle.rpbs.univ-paris-diderot.fr and http://lipm-bioinfo.toulouse.inra.fr/Mobyle. The PlayMOBY companion is distributed under the terms of the CeCILL license, and is available at http://lipm-bioinfo.toulouse.inra.fr/biomoby/PlayMOBY/.

Contact:mobyle-support@pasteur.fr; mobyle-support@rpbs.univ-paris-diderot.fr; letondal@pasteur.fr

Supplementary information:Supplementary data are available at Bioinformatics online.

Ligand scaffold hopping combining 3D maximal substructure search and molecular similarity

BACKGROUND

Virtual screening methods are now well established as effective to identify hit and lead candidates and are fully integrated in most drug discovery programs. Ligand-based approaches make use of physico-chemical, structural and energetics properties of known active compounds to search large chemical libraries for related and novel chemotypes. While 2D-similarity search tools are known to be fast and efficient, the use of 3D-similarity search methods can be very valuable to many research projects as integration of "3D knowledge" can facilitate the identification of not only related molecules but also of chemicals possessing distant scaffolds as compared to the query and therefore be more inclined to scaffolds hopping. To date, very few methods performing this task are easily available to the scientific community.

RESULTS

We introduce a new approach (LigCSRre) to the 3D ligand similarity search of drug candidates. It combines a 3D maximum common substructure search algorithm independent on atom order with a tunable description of atomic compatibilities to prune the search and increase its physico-chemical relevance. We show, on 47 experimentally validated active compounds across five protein targets having different specificities, that for single compound search, the approach is able to recover on average 52% of the co-actives in the top 1% of the ranked list which is better than gold standards of the field. Moreover, the combination of several runs on a single protein target using different query active compounds shows a remarkable improvement in enrichment. Such Results demonstrate LigCSRre as a valuable tool for ligand-based screening.

CONCLUSION

LigCSRre constitutes a new efficient and generic approach to the 3D similarity screening of small compounds, whose flexible design opens the door to many enhancements. The program is freely available to the academics for non-profit research at: http://bioserv.rpbs.univ-paris-diderot.fr/LigCSRre.html.

A coarse-grained protein force field for folding and structure prediction

We have revisited the protein coarse-grained optimized potential for efficient structure prediction (OPEP). The training and validation sets consist of 13 and 16 protein targets. Because optimization depends on details of how the ensemble of decoys is sampled, trial conformations are generated by molecular dynamics, threading, greedy, and Monte Carlo simulations, or taken from publicly available databases. The OPEP parameters are varied by a genetic algorithm using a scoring function which requires that the native structure has the lowest energy, and the native-like structures have energy higher than the native structure but lower than the remote conformations. Overall, we find that OPEP correctly identifies 24 native or native-like states for 29 targets and has very similar capability to the all-atom discrete optimized protein energy model (DOPE), found recently to outperform five currently used energy models.

Fpocket: an open source platform for ligand pocket detection

Background

Virtual screening methods start to be well established as effective approaches to identify hits, candidates and leads for drug discovery research. Among those, structure based virtual screening (SBVS) approaches aim at docking collections of small compounds in the target structure to identify potent compounds. For SBVS, the identification of candidate pockets in protein structures is a key feature, and the recent years have seen increasing interest in developing methods for pocket and cavity detection on protein surfaces.

Results

Fpocket is an open source pocket detection package based on Voronoi tessellation and alpha spheres built on top of the publicly available package Qhull. The modular source code is organised around a central library of functions, a basis for three main programs: (i) Fpocket, to perform pocket identification, (ii) Tpocket, to organise pocket detection benchmarking on a set of known protein-ligand complexes, and (iii) Dpocket, to collect pocket descriptor values on a set of proteins. Fpocket is written in the C programming language, which makes it a platform well suited for the scientific community willing to develop new scoring functions and extract various pocket descriptors on a large scale level. Fpocket 1.0, relying on a simple scoring function, is able to detect 94% and 92% of the pockets within the best three ranked pockets from the holo and apo proteins respectively, outperforming the standards of the field, while being faster.

Conclusion

Fpocket provides a rapid, open source and stable basis for further developments related to protein pocket detection, efficient pocket descriptor extraction, or drugablity prediction purposes. Fpocket is freely available under the GNU GPL license at .

PEP-FOLD: an online resource for de novo peptide structure prediction

Rational peptide design and large-scale prediction of peptide structure from sequence remain a challenge for chemical biologists. We present PEP-FOLD, an online service, aimed at de novo modelling of 3D conformations for peptides between 9 and 25 amino acids in aqueous solution. Using a hidden Markov model-derived structural alphabet (SA) of 27 four-residue letters, PEP-FOLD first predicts the SA letter profiles from the amino acid sequence and then assembles the predicted fragments by a greedy procedure driven by a modified version of the OPEP coarse-grained force field. Starting from an amino acid sequence, PEP-FOLD performs series of 50 simulations and returns the most representative conformations identified in terms of energy and population. Using a benchmark of 25 peptides with 9–23 amino acids, and considering the reproducibility of the runs, we find that, on average, PEP-FOLD locates lowest energy conformations differing by 2.6 Å Cα root mean square deviation from the full NMR structures. PEP-FOLD can be accessed at http://bioserv.rpbs.univ-paris-diderot.fr/PEP-FOLD

wwLigCSRre: a 3D ligand-based server for hit identification and optimization

The wwLigCSRre web server performs ligand-based screening using a 3D molecular similarity engine. Its aim is to provide an online versatile facility to assist the exploration of the chemical similarity of families of compounds, or to propose some scaffold hopping from a query compound. The service allows the user to screen several chemically diversified focused banks, such as Kinase-, CNS-, GPCR-, Ion-channel-, Antibacterial-, Anticancer- and Analgesic-focused libraries. The server also provides the possibility to screen the DrugBank and DSSTOX/Carcinogenic compounds databases. User banks can also been downloaded. The 3D similarity search combines both geometrical (3D) and physicochemical information. Starting from one 3D ligand molecule as query, the screening of such databases can lead to unraveled compound scaffold as hits or help to optimize previously identified hit molecules in a SAR (Structure activity relationship) project. wwLigCSRre can be accessed at http://bioserv.rpbs.univ-paris-diderot.fr/wwLigCSRre.html.

FAF-Drugs: free ADME/tox filtering of compound collections

In silico screening based on the structures of the ligands or of the receptors has become an essential tool to facilitate the drug discovery process but compound collections are needed to carry out such in silico experiments. It has been recognized that absorption, distribution, metabolism, excretion and toxicity (ADME/tox) are key properties that need to be considered early on, even during the database preparation stage. FAF-Drugs is an online service based on Frowns (a chemoinformatics toolkit) that allows users to process their own compound collections via simple ADME/Tox filtering rules such as molecular weight, polar surface area, logP or number of rotatable bonds. SMILES (Simplified Molecular Input Line Entry System), CANSMILES (canonical smiles) or SDF (structure data file) files are required as input and molecules that pass or do not pass the filters are sent back in CANSMILES format. This service should thus help scientists engaging in drug discovery campaigns. Other utilities and several compound collections suitable for in silico screening are available at our site. FAF-Drugs can be accessed at http://bioserv.rpbs.jussieu.fr/FAFDrugs.html.

Dependency between consecutive local conformations helps assemble protein structures from secondary structures using Go potential and greedy algorithm

Discretization of protein conformational space and fragment assembly methods simplify the search of native structures. These methods, mostly of Monte Carlo and genetic-type, do not exploit, however, the fact that short fragments describing consecutive parts of proteins are conformation-dependent. Yet, this information should be useful in improving ab initio and comparative protein structure modeling. In a preliminary study, we have assessed the possibility of using greedy algorithms for protein structure reconstruction based on the assembly of fragments of four-residue length. Greedy algorithms differ from Monte Carlo and genetic approaches in that they grow a polypeptide chain one fragment after another. Here, we move one step further in complexity, and provide strong evidence that the dependence between consecutive local conformations during assembly makes possible the reconstruction of protein structures from their secondary structures using a Go potential. Overall our procedure can reproduce 20 protein structures of 50-164 amino acids within 2.7 to 6.5 A RMSd and is able to identify native topologies for all proteins, although some targets are stabilized by very long-range interactions.

Improved greedy algorithm for protein structure reconstruction

This article concerns the development of an improved greedy algorithm for protein structure reconstruction. Our stochastic greedy algorithm, which attempts to locate the ground state of an approximate energy function, exploits the fact that protein structures consist of overlapping structural building blocks that are not independent. Application of this approach to a series of 16 proteins with 50-250 amino acids leads to predicted models deviating from the experimental structures by 0.5 A RMSD using an RMSD-based energy function and within 1.5 to 4.8 A RMSD using a Go-based energy function. The Go-based results are significant because they illustrate the strength of combining structural fragments and stochastic greedy algorithms in capturing the native structures of proteins stabilized by long-range interactions separated by more than 30 amino acids. These results clearly open the door to less computationally demanding solutions to predict structures from sequences.

A triple-mutated allele of granzyme B incapable of inducing apoptosis

Granzyme B (GzmB) is a serine protease involved in many pathologies, including viral infections, autoimmunity, transplant rejection, and antitumor immunity. To measure the extent of genetic variation in GzmB, we screened the GzmB gene for polymorphisms and defined a frequently represented triple-mutated GzmB allele. In this variant, three amino acids of the mature protein Q(48)P(88)Y(245) are mutated to R(48)A(88)H(245). In CD8(+) cytotoxic T lymphocytes, GzmB was expressed at similar levels in QPY homozygous, QPY/RAH heterozygous, and RAH homozygous individuals, demonstrating that RAH GzmB is a stable protein. Active RAH GzmB expressed in glioblastoma cell lines displayed proteolytic activity, but in contrast to QPY GzmB, it did not accumulate in the nucleus and was unable to induce Bid cleavage, cytochrome c release, or apoptosis. Molecular modeling showed that the three amino acid substitutions clustered near the C-terminal alpha-helix of the protein, indicating that this region of the protein may be involved in the intracellular targeting of GzmB. The triple-mutated GzmB allele that we describe appears to be incapable of inducing apoptosis in tumor cell lines, and its presence could, therefore, influence both the prognosis of cancer patients and the success rates of antitumor cellular immunotherapy.

Hidden Markov model approach for identifying the modular framework of the protein backbone

The hidden Markov model (HMM) was used to identify recurrent short 3D structural building blocks (SBBs) describing protein backbones, independently of any a priori knowledge. Polypeptide chains are decomposed into a series of short segments defined by their inter-alpha-carbon distances. Basically, the model takes into account the sequentiality of the observed segments and assumes that each one corresponds to one of several possible SBBs. Fitting the model to a database of non-redundant proteins allowed us to decode proteins in terms of 12 distinct SBBs with different roles in protein structure. Some SBBs correspond to classical regular secondary structures. Others correspond to a significant subdivision of their bounding regions previously considered to be a single pattern. The major contribution of the HMM is that this model implicitly takes into account the sequential connections between SBBs and thus describes the most probable pathways by which the blocks are connected to form the framework of the protein structures. Validation of the SBBs code was performed by extracting SBB series repeated in recoding proteins and examining their structural similarities. Preliminary results on the sequence specificity of SBBs suggest promising perspectives for the prediction of SBBs or series of SBBs from the protein sequences.

A model for the photosystem II reaction center core including the structure of the primary donor P680

For a detailed understanding of the function of photosystem II (PSII), a molecular structure is needed. The crystal structure has not yet been determined, but the PSII reaction center proteins D1 and D2 show homology with the L and M subunits of the photosynthetic reaction center from purple bacteria. We have modeled important parts of the D1 and D2 proteins on the basis of the crystallographic structure of the reaction center from Rhodopseudomonas viridis. The model contains the central core of the PSII reaction center, including the protein regions for the transmembrane helices B, C, D, and E and loops B-C and C-D connecting the helices. In the model, four chlorophylls, two pheophytins, and the nonheme Fe2+ ion are included. We have applied techniques from computational chemistry that incorporate statistical data on side-chain rotameric states from known protein structure and that describe interactions within the model using an empirical potential energy function. The conformation of chlorophyll pigments in the model was optimized by using exciton interaction calculations in combination with potential energy calculations to find a solution that agrees with experimentally determined exciton interaction energies. The model is analyzed and compared with experimental results for the regions of P680, the redox active pheophytin, the acceptor side Fe2+, and the tyrosyl radicals TyrD and TyrZ. P680 is proposed to be a weakly coupled chlorophyll a pair which makes three hydrogen bonds with residues on the D1 and D2 proteins. In the model the redox-active pheophytin is hydrogen bonded to D1-Glu130 and possibly also to D1-Tyr126 and D1-Tyr147. TyrD is hydrogen bonded to D2-His190 and also interacts with D2-Gln165. TyrZ is bound in a hydrophilic environment which is partially constituted by D1-Gln165, D1-Asp170, D1-Glu189, and D1-His190. These polar residues are most likely involved in proton transfer from oxidized TyrZ or in metal binding.

Prediction of the positioning of the seven transmembrane alpha-helices of bacteriorhodopsin. A molecular simulation study

We have applied a search strategy for determining the optimal packing of protein secondary structure elements to the rotational positioning of the seven transmembrane helices of bacteriorhodopsin. The search is based on the assumption that the relative orientations of the helices within the bundle are conditioned principally by inter-helix side-chain interactions and that the extra-helical parts of the protein have only a minor influence on the bundle conformation. Our approach performs conformational energy optimization using a predetermined set of side-chain rotamers and appropriate methods for sampling the conformational space of peptide fragments with fixed backbone geometries. The final solution obtained for bacteriorhodopsin places each of the seven helices to a precision of a few degrees in rotation around the helical axis and to a few tenths of an ångström in translation along the helical axis with respect to the best experimental structure obtained by electron diffraction, except for helix D, where our results support the suggestion that this helix should be displaced along its axis toward its N terminus. The perspectives of such an approach for the determination of the structures of other transmembrane helical bundles are discussed.

FORME: an interactive package for protein backbone deformation

The FORME package presented herein is designed for modeling purposes: It allows interactive deformation of the protein backbone. General formalism on transformations is introduced and the operators of stretching inside an "acceptance area" and stretching with end-block invariance (i.e., governed by a translational moving) are described. A discussion is presented on the choice of strategy to achieve an interactive deformation tool. Perspectives about complex transformations are presented.

A new approach to the rapid determination of protein side chain conformations

Two efficient algorithms have been developed which allow amino acid side chain conformations to be optimized rapidly for a given peptide backbone conformation. Both these approaches are based on the assumption that each side chain can be represented by a small number of rotameric states. These states have been obtained by a dynamic cluster analysis of a large data base of known crystallographic structures. Successful applications of these algorithms to the prediction of known protein conformations are presented.

Restriction map construction using a 'complete sentences compatibility' algorithm

We have developed a new algorithm 'Complete sentences compatibility' (CSC) which uses single and double digestion fragments to rapidly determine restriction maps of circular DNA. From possible combinations of fragments of each simple digestion, which we call 'sentences of decomposition', we construct a restriction map which combines the sentences while taking into account compatibility rules. The algorithm can also deal with experimental errors of fragment weight and can suggest solutions that account for non-readable bands (fragments of zero length or multiple bands) on the gel. Because experiments using pairs of restrictive enzymes often result in multiple solutions, a complementary algorithm tries to reduce the number of proposed solutions by establishing consensus maps. The restriction map construction algorithm was tested on real cases, some containing more than fifteen fragments. Execution times range from 1-10 s on an IBM PC compatible microcomputer.