Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.

Synthesis and Biological Activity of a New Indenoisoquinoline Copper Derivative as a Topoisomerase I Inhibitor

Topoisomerases are interesting targets in cancer chemotherapy. Here, we describe the design and synthesis of a novel copper(II) indenoisoquinoline complex, WN198. The new organometallic compound exhibits a cytotoxic effect on five adenocarcinoma cell lines (MCF-7, MDA-MB-231, HeLa, HT-29, and DU-145) with the lowest IC50 (0.37 ± 0.04 μM) for the triple-negative MDA-MB-231 breast cancer cell line. Below 5 µM, WN198 was ineffective on non-tumorigenic epithelial breast MCF-10A cells and Xenopus oocyte G2/M transition or embryonic development. Moreover, cancer cell lines showed autophagy markers including Beclin-1 accumulation and LC3-II formation. The DNA interaction of this new compound was evaluated and the dose-dependent topoisomerase I activity starting at 1 μM was confirmed using in vitro tests and has intercalation properties into DNA shown by melting curves and fluorescence measurements. Molecular modeling showed that the main interaction occurs with the aromatic ring but copper stabilizes the molecule before binding and so can putatively increase the potency as well. In this way, copper-derived indenoisoquinoline topoisomerase I inhibitor WN198 is a promising antitumorigenic agent for the development of future DNA-damaging treatments.

New insights into the pathogenicity of TMEM165 variants using structural modeling based on AlphaFold 2 predictions

TMEM165 is a Golgi protein playing a crucial role in Mn²⁺ transport, and whose mutations in patients are known to cause Congenital Disorders of Glycosylation. Some of those mutations affect the highly-conserved consensus motifs E-φ-G-D-[KR]-[TS] characterizing the CaCA2/UPF0016 family, presumably important for the transport of Mn²⁺ which is essential for the function of many Golgi glycosylation enzymes. Others, like the G>R³⁰⁴ mutation, are far away from these motifs in the sequence. Until recently, the classical membrane protein topology prediction methods were unable to provide a clear picture of the organization of TMEM165 inside the cell membrane, or to explain in a convincing manner the impact of patient and experimentally-generated mutations on the transporter function of TMEM165. In this study, AlphaFold 2 was used to build a TMEM165 model that was then refined by molecular dynamics simulation with membrane lipids and water. This model provides a realistic picture of the 3D protein scaffold formed from a two-fold repeat of three transmembrane helices/domains where the consensus motifs face each other to form a putative acidic cation-binding site at the cytosolic side of the protein. It sheds new light on the impact of mutations on the transporter function of TMEM165, found in patients and studied experimentally in vitro, formerly and within this study. More particularly and very interestingly, this model explains the impact of the G>R³⁰⁴ mutation on TMEM165's function. These findings provide great confidence in the predicted TMEM165 model whose structural features are discussed in the study and compared to other structural and functional TMEM165 homologs from the CaCA2/UPF0016 family and the LysE superfamily.

Critical Assessment of Methods for Predicting the 3D Structure of Proteins and Protein Complexes

Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling of complexes, that have over decades emulated this pattern, as monitored by the community-wide blind prediction experiments CASP and CAPRI. However, over the past few years, dramatic advances were observed for the accurate prediction of single protein chains, driven by a surge of deep learning methodologies entering the prediction field. We review the mainscientific developments that enabled these recent breakthroughs and feature the important role of blind prediction experiments in building up and nurturing the structure prediction field. We discuss how the new wave of artificial intelligence-based methods is impacting the fields of computational and experimental structural biology and highlight areas in which deep learning methods are likely to lead to future developments, provided that major challenges are overcome.

What is the potential impact of genetic divergence of plastid ribosomal genes between Silene nutans lineages in hybrids? An in silico approach using the 3D structure of the plastid ribosome

Introduction

Following the integration of cyanobacteria into the eukaryotic cells, many genes were transferred from the plastid to the nucleus. As a result, plastid complexes are encoded both by plastid and nuclear genes. Tight co-adaptation is required between these genes as plastid and nuclear genomes differ in several characteristics, such as mutation rate and inheritance patterns. Among these are complexes from the plastid ribosome, composed of two main subunits: a large and a small one, both composed of nuclear and plastid gene products. This complex has been identified as a potential candidate for sheltering plastid-nuclear incompatibilities in a Caryophyllaceae species, Silene nutans. This species is composed of four genetically differentiated lineages, which exhibit hybrid breakdown when interlineage crosses are conducted. As this complex is composed of numerous interacting plastid-nuclear gene pairs, in the present study, the goal was to reduce the number of gene pairs that could induce such incompatibilities.

Method

We used the previously published 3D structure of the spinach ribosome to further elucidate which of the potential gene pairs might disrupt plastid-nuclear interactions within this complex. After modeling the impact of the identified mutations on the 3D structure, we further focused on one strongly mutated plastid-nuclear gene pair: rps11-rps21. We used the centrality measure of the mutated residues to further understand if the modified interactions and associated modified centralities might be correlated with hybrid breakdown.

Results and discussion

This study highlights that lineage-specific mutations in essential plastid and nuclear genes might disrupt plastid-nuclear protein interactions of the plastid ribosome and that reproductive isolation correlates with changes in residue centrality values. Because of this, the plastid ribosome might be involved in hybrid breakdown in this system.

TRPM8-Rap1A Interaction Sites as Critical Determinants for Adhesion and Migration of Prostate and Other Epithelial Cancer Cells

Emerging evidence indicates that the TRPM8 channel plays an important role in prostate cancer (PCa) progression, by impairing the motility of these cancer cells. Here, we reveal a novel facet of PCa motility control via direct protein-protein interaction (PPI) of the channel with the small GTPase Rap1A. The functional interaction of the two proteins was assessed by active Rap1 pull-down assays and live-cell imaging experiments. Molecular modeling analysis allowed the identification of four putative residues involved in TRPM8-Rap1A interaction. Point mutations of these sites impaired PPI as shown by GST-pull-down, co-immunoprecipitation, and PLA experiments and revealed their key functional role in the adhesion and migration of PC3 prostate cancer cells. More precisely, TRPM8 inhibits cell migration and adhesion by trapping Rap1A in its GDP-bound inactive form, thus preventing its activation at the plasma membrane. In particular, residues E207 and Y240 in the sequence of TRPM8 and Y32 in that of Rap1A are critical for the interaction between the two proteins not only in PC3 cells but also in cervical (HeLa) and breast (MCF-7) cancer cells. This study deepens our knowledge of the mechanism through which TRPM8 would exert a protective role in cancer progression and provides new insights into the possible use of TRPM8 as a new therapeutic target in cancer treatment.

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70-75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70-80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.

Centrality Measures in Residue Interaction Networks to Highlight Amino Acids in Protein–Protein Binding

Residue interaction networks (RINs) describe a protein structure as a network of interacting residues. Central nodes in these networks, identified by centrality analyses, highlight those residues that play a role in the structure and function of the protein. However, little is known about the capability of such analyses to identify residues involved in the formation of macromolecular complexes. Here, we performed six different centrality measures on the RINs generated from the complexes of the SKEMPI 2 database of changes in protein–protein binding upon mutation in order to evaluate the capability of each of these measures to identify major binding residues. The analyses were performed with and without the crystallographic water molecules, in addition to the protein residues. We also investigated the use of a weight factor based on the inter-residue distances to improve the detection of these residues. We show that for the identification of major binding residues, closeness, degree, and PageRank result in good precision, whereas betweenness, eigenvector, and residue centrality analyses give a higher sensitivity. Including water in the analysis improves the sensitivity of all measures without losing precision. Applying weights only slightly raises the sensitivity of eigenvector centrality analysis. We finally show that a combination of multiple centrality analyses is the optimal approach to identify residues that play a role in protein–protein interaction.

O-GlcNAcylation Prediction: An Unattained Objective

BACKGROUND

O-GlcNAcylation is an essential post-translational modification (PTM) in mammalian cells. It consists in the addition of a N-acetylglucosamine (GlcNAc) residue onto serines or threonines by an O-GlcNAc transferase (OGT). Inhibition of OGT is lethal, and misregulation of this PTM can lead to diverse pathologies including diabetes, Alzheimer's disease and cancers. Knowing the location of O-GlcNAcylation sites and the ability to accurately predict them is therefore of prime importance to a better understanding of this process and its related pathologies.

PURPOSE

Here, we present an evaluation of the current predictors of O-GlcNAcylation sites based on a newly built dataset and an investigation to improve predictions.

METHODS

Several datasets of experimentally proven O-GlcNAcylated sites were combined, and the resulting meta-dataset was used to evaluate three prediction tools. We further defined a set of new features following the analysis of the primary to tertiary structures of experimentally proven O-GlcNAcylated sites in order to improve predictions by the use of different types of machine learning techniques.

RESULTS

Our results show the failure of currently available algorithms to predict O-GlcNAcylated sites with a precision exceeding 9%. Our efforts to improve the precision with new features using machine learning techniques do succeed for equal proportions of O-GlcNAcylated and non-O-GlcNAcylated sites but fail like the other tools for real-life proportions where ~1.4% of S/T are O-GlcNAcylated.

CONCLUSION

Present-day algorithms for O-GlcNAcylation prediction narrowly outperform random prediction. The inclusion of additional features, in combination with machine learning algorithms, does not enhance these predictions, emphasizing a pressing need for further development. We hypothesize that the improvement of prediction algorithms requires characterization of OGT's partners.

Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment

We present the results for CAPRI Round 46, the third joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo-oligomers and 6 heterocomplexes. Eight of the homo-oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher-order assemblies. These were more difficult to model, as their prediction mainly involved "ab-initio" docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance "gap" was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template-based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.

Asymmetrical diversification of the receptor-ligand interaction controlling self-incompatibility in Arabidopsis

How two-component genetic systems accumulate evolutionary novelty and diversify in the course of evolution is a fundamental problem in evolutionary systems biology. In the Brassicaceae, self-incompatibility (SI) is a spectacular example of a diversified allelic series in which numerous highly diverged receptor-ligand combinations are segregating in natural populations. However, the evolutionary mechanisms by which new SI specificities arise have remained elusive. Using in planta ancestral protein reconstruction, we demonstrate that two allelic variants segregating as distinct receptor-ligand combinations diverged through an asymmetrical process whereby one variant has retained the same recognition specificity as their (now extinct) putative ancestor, while the other has functionally diverged and now represents a novel specificity no longer recognized by the ancestor. Examination of the structural determinants of the shift in binding specificity suggests that qualitative rather than quantitative changes of the interaction are an important source of evolutionary novelty in this highly diversified receptor-ligand system.

Assembly of B4GALT1/ST6GAL1 heteromers in the Golgi membranes involves lateral interactions via highly charged surface domains

β-1,4-Galactosyltransferase 1 (B4GALT1) and ST6 β-galactoside α-2,6-sialyltransferase 1 (ST6GAL1) catalyze the successive addition of terminal β-1,4-linked galactose and α-2,6-linked sialic acid to N-glycans. Their exclusive interaction in the Golgi compartment is a prerequisite for their full catalytic activity, whereas a lack of this interaction is associated with cancers and hypoxia. To date, no structural information exists that shows how glycosyltransferases functionally assemble with each other. Using molecular docking simulations to predict interaction surfaces, along with mutagenesis screens and high-throughput FRET analyses in live cells to validate these predictions, we show here that B4GALT1 and ST6GAL1 interact via highly charged noncatalytic surfaces, leaving the active sites exposed and accessible for donor and acceptor substrate binding. Moreover, we found that the assembly of ST6GAL1 homomers in the endoplasmic reticulum before ST6GAL1 activation in the Golgi utilizes the same noncatalytic surface, whereas B4GALT1 uses its active-site surface for assembly, which silences its catalytic activity. Last, we show that the homomeric and heteromeric B4GALT1/ST6GAL1 complexes can assemble laterally in the Golgi membranes without forming cross-cisternal contacts between enzyme molecules residing in the opposite membranes of each Golgi cisterna. Our results provide detailed mechanistic insights into the regulation of glycosyltransferase interactions, the transitions between B4GALT1 and ST6GAL1 homo- and heteromers in the Golgi, and cooperative B4GALT1/ST6GAL1 function in N-glycan synthesis.

Identification of Key Residues in Proteins Through Centrality Analysis and Flexibility Prediction with RINspector

Protein structures inherently contain information that can be used to decipher their functions, but the exploitation of this knowledge is not trivial. We recently developed an app for the Cytoscape network visualization and analysis program, called RINspector, the goal of which is to integrate two different approaches that identify key residues in a protein structure or complex. The first approach consists of calculating centralities on a residue interaction network (RIN) generated from the three-dimensional structure; the second consists of predicting backbone flexibility and needs only the primary sequence. The identified residues are highly correlated with functional relevance and constitute a good set of targets for mutagenesis experiments. Here we present a protocol that details in a step-by-step fashion how to create a RIN from a structure and then calculate centralities and predict flexibilities. We also discuss how to understand and use the results of the analyses. © 2018 by John Wiley & Sons, Inc.

The Inclusion of Water Molecules in Residue Interaction Networks Identifies Additional Central Residues

The relevance of water molecules for the recognition and the interaction of biomolecules is widely appreciated. In this paper we address the role that water molecules associated to protein complexes play for the functional relevance of residues by considering their residue interaction networks (RINs). These are commonly defined on the basis of the amino acid composition of the proteins themselves, disregarding the solvation state of the protein. We determine properties of the RINs of two protein complexes, colicin E2/Im2 and barnase/barstar, with and without associated water molecules, using a previously developed methodology and its associated application RINspector. We find that the inclusion of water molecules in RINs leads to an increase in the number of central residues which adds a novel mechanism to the relevance of water molecules for protein function.

Computational characterization of the binding mode between oncoprotein Ets-1 and DNA-repair enzymes

The Ets-1 oncoprotein is a transcription factor that promotes target gene expression in specific biological processes. Typically, Ets-1 activity is low in healthy cells, but elevated levels of expression have been found in cancerous cells, specifically related to tumor progression. Like the vast majority of the cellular effectors, Ets-1 does not act alone but in association with partners. Given the important role that is attributed to Ets-1 in major human diseases, it is crucial to identify its partners and characterize their interactions. In this context, two DNA-repair enzymes, PARP-1 and DNA-PK, have been identified recently as interaction partners of Ets-1. We here identify their binding mode by means of protein docking. The results identify the interacting surface between Ets-1 and the two DNA-repair enzymes centered on the α-helix H1 of the ETS domain, leaving α-helix H3 available to bind DNA. The models highlight a hydrophobic patch on Ets-1 at the center of the interaction interface that includes three tryptophans (Trp338, Trp356, and Trp361). We rationalize the binding mode using a series of computational analyses, including alanine scanning, molecular dynamics simulation, and residue centrality analysis. Our study constitutes a first but important step in the characterization, at the molecular level, of the interaction between an oncoprotein and DNA-repair enzymes.

Targeting Dynamical Binding Processes in the Design of Non-Antibiotic Anti-Adhesives by Molecular Simulation-The Example of FimH

Located at the tip of type I fimbria of Escherichia coli, the bacterial adhesin FimH is responsible for the attachment of the bacteria to the (human) host by specifically binding to highly-mannosylated glycoproteins located on the exterior of the host cell wall. Adhesion represents a necessary early step in bacterial infection and specific inhibition of this process represents a valuable alternative pathway to antibiotic treatments, as such anti-adhesive drugs are non-intrusive and are therefore unlikely to induce bacterial resistance. The currently available anti-adhesives with the highest affinities for FimH still feature affinities in the nanomolar range. A prerequisite to develop higher-affinity FimH inhibitors is a molecular understanding of the FimH-inhibitor complex formation. The latest insights in the formation process are achieved by combining several molecular simulation and traditional experimental techniques. This review summarizes how molecular simulation contributed to the current knowledge of the molecular function of FimH and the importance of dynamics in the inhibitor binding process, and highlights the importance of the incorporation of dynamical aspects in (future) drug-design studies.

Structure and dynamics of a human myelin protein P2 portal region mutant indicate opening of the β barrel in fatty acid binding proteins

Background

Myelin is a multilayered proteolipid sheath wrapped around selected axons in the nervous system. Its constituent proteins play major roles in forming of the highly regular membrane structure. P2 is a myelin-specific protein of the fatty acid binding protein (FABP) superfamily, which is able to stack lipid bilayers together, and it is a target for mutations in the human inherited neuropathy Charcot-Marie-Tooth disease. A conserved residue that has been proposed to participate in membrane and fatty acid binding and conformational changes in FABPs is Phe57. This residue is thought to be a gatekeeper for the opening of the portal region upon ligand entry and egress.

Results

We performed a structural characterization of the F57A mutant of human P2. The mutant protein was crystallized in three crystal forms, all of which showed changes in the portal region and helix α2. In addition, the behaviour of the mutant protein upon lipid bilayer binding suggested more unfolding than previously observed for wild-type P2. On the other hand, membrane binding rendered F57A heat-stable, similarly to wild-type P2. Atomistic molecular dynamics simulations showed opening of the side of the discontinuous β barrel, giving important indications on the mechanism of portal region opening and ligand entry into FABPs. The results suggest a central role for Phe57 in regulating the opening of the portal region in human P2 and other FABPs, and the F57A mutation disturbs dynamic cross-correlation networks in the portal region of P2.

Conclusions

Overall, the F57A variant presents similar properties to the P2 patient mutations recently linked to Charcot-Marie-Tooth disease. Our results identify Phe57 as a residue regulating conformational changes that may accompany membrane surface binding and ligand exchange in P2 and other FABPs.

Electronic supplementary material

The online version of this article (10.1186/s12900-018-0087-2) contains supplementary material, which is available to authorized users.

Comparing protein structures with RINspector automation in Cytoscape

Residue interaction networks (RINs) have been shown to be relevant representations of the tertiary or quaternary structures of proteins, in particular thanks to network centrality analyses. We recently developed the RINspector 1.0.0 Cytoscape app, which couples centrality analyses with backbone flexibility predictions. This combined approach permits the identification of crucial residues for the folding or function of the protein that can constitute good targets for mutagenesis experiments. Here we present an application programming interface (API) for RINspector 1.1.0 that enables interplay between Cytoscape, RINspector and external languages, such as R or Python. This API provides easy access to batch centrality calculations and flexibility predictions, and allows for the easy comparison of results between different structures. These comparisons can lead to the identification of specific and conserved central residues, and show the impact of mutations to these and other residues on the flexibility of the proteins. We give two use cases to demonstrate the interest of these functionalities and provide the corresponding scripts: the first concerns NMR conformers, the second focuses on mutations in a structure.

Coiled-Coil Antagonism Regulates Activity of Venus Flytrap-Domain-Containing Sensor Kinases of the BvgS Family

Bordetella pertussis controls the expression of its virulence regulon through the two-component system BvgAS. BvgS is a prototype for a family of multidomain sensor kinases. In BvgS, helical linkers connect periplasmic Venus flytrap (VFT) perception domains to a cytoplasmic Per-Arnt-Sim (PAS) domain and the PAS domain to the dimerization/histidine phosphotransfer (DHp) domain of the kinase. The two linkers can adopt coiled-coil structures but cannot do so simultaneously. The first linker forms a coiled coil in the kinase mode and the second in the phosphatase mode, with the other linker in both cases showing an increase in dynamic behavior. The intervening PAS domain changes its quaternary structure between the two modes. In BvgS homologues without a PAS domain, a helical "X" linker directly connects the VFT and DHp domains. Here, we used BvgS as a platform to characterize regulation in members of the PAS-less subfamily. BvgS chimeras of homologues with natural X linkers displayed various regulation phenotypes. We identified two distinct coiled-coil registers in the N- and C-terminal portions of the X linkers. Stable coil formation in the C-terminal moiety determines the phosphatase mode, similarly to BvgS; in contrast, coil formation in the N-terminal moiety along the other register leads to the kinase mode. Thus, antagonism between two registers in the VFT-DHp linker forms the basis for activity regulation in the absence of the PAS domain. The N and C moieties of the X linker play roles similar to those played by the two independent linkers in sensor kinases with a PAS domain, providing a unified mechanism of regulation for the entire family.IMPORTANCE The whooping cough agent Bordetella pertussis uses the BvgAS sensory transduction two-component system to regulate production of its virulence factors. BvgS serves as a model for a large family of multidomain bacterial sensor kinases. B. pertussis is virulent when BvgS functions as a kinase and avirulent when it switches to phosphatase activity in response to modulating signals. Understanding the molecular regulation of those proteins might lead to new antibacterial strategies. Here, we show that the linker regions between the perception and the enzymatic domains shift between distinct states of conformation in an alternating manner in response to signals and that their antagonistic changes control sensor kinase activity. These linker regions and mechanistic principles appear to be conserved among BvgS homologues, irrespective of the presence or absence of an intervening domain between the perception and the enzymatic domains. This work has thus uncovered general molecular mechanisms that regulate activity of sensor kinases in the BvgS family.

The challenge of modeling protein assemblies: the CASP12-CAPRI experiment

We present the quality assessment of 5613 models submitted by predictor groups from both CAPRI and CASP for the total of 15 most tractable targets from the second joint CASP-CAPRI protein assembly prediction experiment. These targets comprised 12 homo-oligomers and 3 hetero-complexes. The bulk of the analysis focuses on 10 targets (of CAPRI Round 37), which included all 3 hetero-complexes, and whose protein chains or the full assembly could be readily modeled from structural templates in the PDB. On average, 28 CAPRI groups and 10 CASP groups (including automatic servers), submitted models for each of these 10 targets. Additionally, about 16 groups participated in the CAPRI scoring experiments. A range of acceptable to high quality models were obtained for 6 of the 10 Round 37 targets, for which templates were available for the full assembly. Poorer results were achieved for the remaining targets due to the lower quality of the templates available for the full complex or the individual protein chains, highlighting the unmet challenge of modeling the structural adjustments of the protein components that occur upon binding or which must be accounted for in template-based modeling. On the other hand, our analysis indicated that residues in binding interfaces were correctly predicted in a sizable fraction of otherwise poorly modeled assemblies and this with higher accuracy than published methods that do not use information on the binding partner. Lastly, the strengths and weaknesses of the assessment methods are evaluated and improvements suggested.

RINspector: a Cytoscape app for centrality analyses and DynaMine flexibility prediction

Motivation

Protein function is directly related to amino acid residue composition and the dynamics of these residues. Centrality analyses based on residue interaction networks permit to identify key residues in a protein that are important for its fold or function. Such central residues and their environment constitute suitable targets for mutagenesis experiments. Predicted flexibility and changes in flexibility upon mutation provide valuable additional information for the design of such experiments.

Results

We combined centrality analyses with DynaMine flexibility predictions in a Cytoscape app called RINspector. The app performs centrality analyses and directly visualizes the results on a graph of predicted residue flexibility. In addition, the effect of mutations on local flexibility can be calculated.

Availability and implementation

The app is publicly available in the Cytoscape app store.

Supplementary information

Supplementary data are available at Bioinformatics online.

FlexPepDock lessons from CAPRI peptide-protein rounds and suggested new criteria for assessment of model quality and utility

CAPRI rounds 28 and 29 included, for the first time, peptide-receptor targets of three different systems, reflecting increased appreciation of the importance of peptide-protein interactions. The CAPRI rounds allowed us to objectively assess the performance of Rosetta FlexPepDock, one of the first protocols to explicitly include peptide flexibility in docking, accounting for peptide conformational changes upon binding. We discuss here successes and challenges in modeling these targets: we obtain top-performing, high-resolution models of the peptide motif for cases with known binding sites but there is a need for better modeling of flanking regions, as well as better selection criteria, in particular for unknown binding sites. These rounds have also provided us the opportunity to reassess the success criteria, to better reflect the quality of a peptide-protein complex model. Using all models submitted to CAPRI, we analyze the correlation between current classification criteria and the ability to retrieve critical interface features, such as hydrogen bonds and hotspots. We find that loosening the backbone (and ligand) RMSD threshold, together with a restriction on the side chain RMSD measure, allows us to improve the selection of high-accuracy models. We also suggest a new measure to assess interface hydrogen bond recovery, which is not assessed by the current CAPRI criteria. Finally, we find that surprisingly much can be learned from rather inaccurate models about binding hotspots, suggesting that the current status of peptide-protein docking methods, as reflected by the submitted CAPRI models, can already have a significant impact on our understanding of protein interactions. Proteins 2017; 85:445-462. © 2016 Wiley Periodicals, Inc.

Sites for Dynamic Protein-Carbohydrate Interactions of O- and C-Linked Mannosides on the E. coli FimH Adhesin

Antagonists of the Escherichia coli type-1 fimbrial adhesin FimH are recognized as attractive alternatives for antibiotic therapies and prophylaxes against acute and recurrent bacterial infections. In this study α-d-mannopyranosides O- or C-linked with an alkyl, alkene, alkyne, thioalkyl, amide, or sulfonamide were investigated to fit a hydrophobic substituent with up to two aryl groups within the tyrosine gate emerging from the mannose-binding pocket of FimH. The results were summarized into a set of structure-activity relationships to be used in FimH-targeted inhibitor design: alkene linkers gave an improved affinity and inhibitory potential, because of their relative flexibility combined with a favourable interaction with isoleucine-52 located in the middle of the tyrosine gate. Of particular interest is a C-linked mannoside, alkene-linked to an ortho-substituted biphenyl that has an affinity similar to its O-mannosidic analog but superior to its para-substituted analog. Docking of its high-resolution NMR solution structure to the FimH adhesin indicated that its ultimate, ortho-placed phenyl ring is able to interact with isoleucine-13, located in the clamp loop that undergoes conformational changes under shear force exerted on the bacteria. Molecular dynamics simulations confirmed that a subpopulation of the C-mannoside conformers is able to interact in this secondary binding site of FimH.

Mutation of Tyr137 of the universal Escherichia coli fimbrial adhesin FimH relaxes the tyrosine gate prior to mannose binding

The most prevalent diseases manifested by Escherichia coli are acute and recurrent bladder infections and chronic inflammatory bowel diseases such as Crohn's disease. E. coli clinical isolates express the FimH adhesin, which consists of a mannose-specific lectin domain connected via a pilin domain to the tip of type 1 pili. Although the isolated FimH lectin domain has affinities in the nanomolar range for all high-mannosidic glycans, differentiation between these glycans is based on their capacity to form predominantly hydrophobic interactions within the tyrosine gate at the entrance to the binding pocket. In this study, novel crystal structures of tyrosine-gate mutants of FimH, ligand-free or in complex with heptyl α-d-O-mannopyranoside or 4-biphenyl α-d-O-mannopyranoside, are combined with quantum-mechanical calculations and molecular-dynamics simulations. In the Y48A FimH crystal structure, a large increase in the dynamics of the alkyl chain of heptyl α-d-O-mannopyranoside attempts to compensate for the absence of the aromatic ring; however, the highly energetic and stringent mannose-binding pocket of wild-type FimH is largely maintained. The Y137A mutation, on the other hand, is the most detrimental to FimH affinity and specificity: (i) in the absence of ligand the FimH C-terminal residue Thr158 intrudes into the mannose-binding pocket and (ii) ethylenediaminetetraacetic acid interacts strongly with Glu50, Thr53 and Asn136, in spite of multiple dialysis and purification steps. Upon mutation, pre-ligand-binding relaxation of the backbone dihedral angles at position 137 in the tyrosine gate and their coupling to Tyr48 via the interiorly located Ile52 form the basis of the loss of affinity of the FimH adhesin in the Y137A mutant.

Modeling protein-protein and protein-peptide complexes: CAPRI 6th edition

We present the sixth report evaluating the performance of methods for predicting the atomic resolution structures of protein complexes offered as targets to the community-wide initiative on the Critical Assessment of Predicted Interactions (CAPRI). The evaluation is based on a total of 20,670 predicted models for 8 protein-peptide complexes, a novel category of targets in CAPRI, and 12 protein-protein targets in CAPRI prediction Rounds held during the years 2013-2016. For two of the protein-protein targets, the focus was on the prediction of side-chain conformation and positions of interfacial water molecules. Seven of the protein-protein targets were particularly challenging owing to their multicomponent nature, to conformational changes at the binding site, or to a combination of both. Encouragingly, the very large multiprotein complex with the nucleosome was correctly predicted, and correct models were submitted for the protein-peptide targets, but not for some of the challenging protein-protein targets. Models of acceptable quality or better were obtained for 14 of the 20 targets, including medium quality models for 13 targets and high quality models for 8 targets, indicating tangible progress of present-day computational methods in modeling protein complexes with increased accuracy. Our evaluation suggests that the progress stems from better integration of different modeling tools with docking procedures, as well as the use of more sophisticated evolutionary information to score models. Nonetheless, adequate modeling of conformational flexibility in interacting proteins remains an important area with a crucial need for improvement. Proteins 2017; 85:359-377. © 2016 Wiley Periodicals, Inc.

Introducing a Clustering Step in a Consensus Approach for the Scoring of Protein-Protein Docking Models

Correctly scoring protein-protein docking models to single out native-like ones is an open challenge. It is also an object of assessment in CAPRI (Critical Assessment of PRedicted Interactions), the community-wide blind docking experiment. We introduced in the field the first pure consensus method, CONSRANK, which ranks models based on their ability to match the most conserved contacts in the ensemble they belong to. In CAPRI, scorers are asked to evaluate a set of available models and select the top ten ones, based on their own scoring approach. Scorers’ performance is ranked based on the number of targets/interfaces for which they could provide at least one correct solution. In such terms, blind testing in CAPRI Round 30 (a joint prediction round with CASP11) has shown that critical cases for CONSRANK are represented by targets showing multiple interfaces or for which only a very small number of correct solutions are available. To address these challenging cases, CONSRANK has now been modified to include a contact-based clustering of the models as a preliminary step of the scoring process. We used an agglomerative hierarchical clustering based on the number of common inter-residue contacts within the models. Two criteria, with different thresholds, were explored in the cluster generation, setting either the number of common contacts or of total clusters. For each clustering approach, after selecting the top (most populated) ten clusters, CONSRANK was run on these clusters and the top-ranked model for each cluster was selected, in the limit of 10 models per target. We have applied our modified scoring approach, Clust-CONSRANK, to SCORE_SET, a set of CAPRI scoring models made recently available by CAPRI assessors, and to the subset of homodimeric targets in CAPRI Round 30 for which CONSRANK failed to include a correct solution within the ten selected models. Results show that, for the challenging cases, the clustering step typically enriches the ten top ranked models in native-like solutions. The best performing clustering approaches we tested indeed lead to more than double the number of cases for which at least one correct solution can be included within the top ten ranked models.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323-348. © 2016 Wiley Periodicals, Inc.

Molecular docking as a popular tool in drug design, an in silico travel

New molecular modeling approaches, driven by rapidly improving computational platforms, have allowed many success stories for the use of computer-assisted drug design in the discovery of new mechanism-or structure-based drugs. In this overview, we highlight three aspects of the use of molecular docking. First, we discuss the combination of molecular and quantum mechanics to investigate an unusual enzymatic mechanism of a flavoprotein. Second, we present recent advances in anti-infectious agents' synthesis driven by structural insights. At the end, we focus on larger biological complexes made by protein-protein interactions and discuss their relevance in drug design. This review provides information on how these large systems, even in the presence of the solvent, can be investigated with the outlook of drug discovery.

CLUB-MARTINI: Selecting Favourable Interactions amongst Available Candidates, a Coarse-Grained Simulation Approach to Scoring Docking Decoys

Large-scale identification of native binding orientations is crucial for understanding the role of protein-protein interactions in their biological context. Measuring binding free energy is the method of choice to estimate binding strength and reveal the relevance of particular conformations in which proteins interact. In a recent study, we successfully applied coarse-grained molecular dynamics simulations to measure binding free energy for two protein complexes with similar accuracy to full-atomistic simulation, but 500-fold less time consuming. Here, we investigate the efficacy of this approach as a scoring method to identify stable binding conformations from thousands of docking decoys produced by protein docking programs. To test our method, we first applied it to calculate binding free energies of all protein conformations in a CAPRI (Critical Assessment of PRedicted Interactions) benchmark dataset, which included over 19000 protein docking solutions for 15 benchmark targets. Based on the binding free energies, we ranked all docking solutions to select the near-native binding modes under the assumption that the native-solutions have lowest binding free energies. In our top 100 ranked structures, for the ‘easy’ targets that have many near-native conformations, we obtain a strong enrichment of acceptable or better quality structures; for the ‘hard’ targets without near-native decoys, our method is still able to retain structures which have native binding contacts. Moreover, in our top 10 selections, CLUB-MARTINI shows a comparable performance when compared with other state-of-the-art docking scoring functions. As a proof of concept, CLUB-MARTINI performs remarkably well for many targets and is able to pinpoint near-native binding modes in the top selections. To the best of our knowledge, this is the first time interaction free energy calculated from MD simulations have been used to rank docking solutions at a large scale.

Structures of C-mannosylated anti-adhesives bound to the type 1 fimbrial FimH adhesin

Selective inhibitors of the type 1 fimbrial adhesin FimH are recognized as attractive alternatives for antibiotic therapies and prophylaxes against Escherichia coli infections such as urinary-tract infections. To construct these inhibitors, the α-d-mannopyranoside of high-mannose N-glycans, recognized with exclusive specificity on glycoprotein receptors by FimH, forms the basal structure. A hydrophobic aglycon is then linked to the mannose by the O1 oxygen inherently present in the α-anomeric configuration. Substitution of this O atom by a carbon introduces a C-glycosidic bond, which may enhance the therapeutic potential of such compounds owing to the inability of enzymes to degrade C-glycosidic bonds. Here, the first crystal structures of the E. coli FimH adhesin in complex with C-glycosidically linked mannopyranosides are presented. These findings explain the role of the spacer in positioning biphenyl ligands for interactions by means of aromatic stacking in the tyrosine gate of FimH and how the normally hydrated C-glycosidic link is tolerated. As these new compounds can bind FimH, it can be assumed that they have the potential to serve as potent new antagonists of FimH, paving the way for the design of a new family of anti-adhesive compounds against urinary-tract infections.

The Antiadhesive Strategy in Crohn's Disease: Orally Active Mannosides to Decolonize Pathogenic Escherichia coli from the Gut

Blocking the adherence of bacteria to cells is an attractive complementary approach to current antibiotic treatments, which are faced with increasing resistance. This strategy has been particularly studied in the context of urinary tract infections (UTIs), in which the adhesion of pathogenic Escherichia coli strains to uroepithelial cells is prevented by blocking the FimH adhesin expressed at the tips of bacteria organelles called fimbriae. Recently, we extended the antiadhesive concept, showing that potent FimH antagonists can block the attachment of adherent-invasive E. coli (AIEC) colonizing the intestinal mucosa of patients with Crohn's disease (CD). In this work, we designed a small library of analogues of heptyl mannoside (HM), a previously identified nanomolar FimH inhibitor, but one that displays poor antiadhesive effects in vivo. The anomeric oxygen atom was replaced by a sulfur or a methylene group to prevent hydrolysis by intestinal glycosidases, and chemical groups were attached at the end of the alkyl tail. Importantly, a lead compound was shown to reduce AIEC levels in the feces and in the colonic and ileal mucosa after oral administration (10 mg kg(-1) ) in a transgenic mouse model of CD. The compound showed a low bioavailability, preferable in this instance, thus suggesting the possibility of setting up an innovative antiadhesive therapy, based on the water-soluble and non-cytotoxic FimH antagonists developed here, for the CD subpopulation in which AIEC plays a key role.

Balance between Coiled-Coil Stability and Dynamics Regulates Activity of BvgS Sensor Kinase in Bordetella

The two-component system BvgAS controls the expression of the virulence regulon of Bordetella pertussis. BvgS is a prototype of bacterial sensor kinases with extracytoplasmic Venus flytrap perception domains. Following its transmembrane segment, BvgS harbors a cytoplasmic Per-Arnt-Sim (PAS) domain and then a predicted 2-helix coiled coil that precede the dimerization-histidine-phosphotransfer domain of the kinase. BvgS homologs have a similar domain organization, or they harbor only a predicted coiled coil between the transmembrane and the dimerization-histidine-phosphotransfer domains. Here, we show that the 2-helix coiled coil of BvgS regulates the enzymatic activity in a mechanical manner. Its marginally stable hydrophobic interface enables a switch between a state of great rotational dynamics in the kinase mode and a more rigid conformation in the phosphatase mode in response to signal perception by the periplasmic domains. We further show that the activity of BvgS is controlled in the same manner if its PAS domain is replaced with the natural α-helical sequences of PAS-less homologs. Clamshell motions of the Venus flytrap domains trigger the shift of the coiled coil's dynamics. Thus, we have uncovered a general mechanism of regulation for the BvgS family of Venus flytrap-containing two-component sensor kinases.

IMPORTANCE

The two-component system BvgAS of the whooping cough agent Bordetella pertussis regulates the virulence factors necessary for infection in a coordinated manner. BvgS is the prototype of a family of sensor kinase proteins found in major bacterial pathogens. When BvgS functions as a kinase, B. pertussis is virulent, and the bacterium shifts to an avirulent phase after BvgS senses chemicals that make it switch to phosphatase. Our goal is to decipher the signaling mechanisms of BvgS in order to understand virulence regulation in Bordetella, which may lead to new antimicrobial treatments targeting those two-component systems. We discovered that the activity of BvgS is regulated in a mechanical manner. A short region of the protein that precedes the enzymatic domain switches between two states in response to signal perception by other BvgS domains. This switch region is conserved among BvgS homologs, and thus, the regulation uncovered here will likely be relevant for the family.

Signal Transduction by BvgS Sensor Kinase: BINDING OF MODULATOR NICOTINATE AFFECTS THE CONFORMATION AND DYNAMICS OF THE ENTIRE PERIPLASMIC MOIETY

The two-component sensory transduction system BvgAS controls the virulence regulon of the whooping-cough agent Bordetella pertussis. The periplasmic moiety of the homodimeric sensor kinase BvgS is composed of four bilobed Venus flytrap (VFT) perception domains followed by α helices that extend into the cytoplasmic membrane. In the virulent phase, the default state of B. pertussis, the cytoplasmic enzymatic moiety of BvgS acts as kinase by autophosphorylating and transferring the phosphoryl group to the response regulator BvgA. Under laboratory conditions, BvgS shifts to phosphatase activity in response to modulators, notably nicotinate ions. Here we characterized the effects of nicotinate and related modulators on the BvgS periplasmic moiety by using site-directed mutagenesis and in silico and biophysical approaches. Modulators bind with low affinity to BvgS in the VFT2 cavity. Electron paramagnetic resonance shows that their binding globally affects the conformation and dynamics of the periplasmic moiety. Specific amino acid substitutions designed to slacken interactions within and between the VFT lobes prevent BvgS from responding to nicotinate, showing that BvgS shifts from kinase to phosphatase activity in response to this modulator via a tense transition state that involves a large periplasmic structural block. We propose that this transition enables the transmembrane helices to adopt a distinct conformation that sets the cytoplasmic enzymatic moiety in the phosphatase mode. The bona fide, in vivo VFT ligands that remain to be identified are likely to trigger similar effects on the transmembrane and cytoplasmic moieties. This mechanism may be relevant to the other VFT-containing sensor kinases homologous to BvgS.

Virulence regulation with Venus flytrap domains: structure and function of the periplasmic moiety of the sensor-kinase BvgS

Two-component systems (TCS) represent major signal-transduction pathways for adaptation to environmental conditions, and regulate many aspects of bacterial physiology. In the whooping cough agent Bordetella pertussis, the TCS BvgAS controls the virulence regulon, and is therefore critical for pathogenicity. BvgS is a prototypical TCS sensor-kinase with tandem periplasmic Venus flytrap (VFT) domains. VFT are bi-lobed domains that typically close around specific ligands using clamshell motions. We report the X-ray structure of the periplasmic moiety of BvgS, an intricate homodimer with a novel architecture. By combining site-directed mutagenesis, functional analyses and molecular modeling, we show that the conformation of the periplasmic moiety determines the state of BvgS activity. The intertwined structure of the periplasmic portion and the different conformation and dynamics of its mobile, membrane-distal VFT1 domains, and closed, membrane-proximal VFT2 domains, exert a conformational strain onto the transmembrane helices, which sets the cytoplasmic moiety in a kinase-on state by default corresponding to the virulent phase of the bacterium. Signaling the presence of negative signals perceived by the periplasmic domains implies a shift of BvgS to a distinct state of conformation and activity, corresponding to the avirulent phase. The response to negative modulation depends on the integrity of the periplasmic dimer, indicating that the shift to the kinase-off state implies a concerted conformational transition. This work lays the bases to understand virulence regulation in Bordetella. As homologous sensor-kinases control virulence features of diverse bacterial pathogens, the BvgS structure and mechanism may pave the way for new modes of targeted therapeutic interventions.

Regulatory motifs on ISWI chromatin remodelers: molecular mechanisms and kinetic proofreading

Recently, kinetic proofreading scenarios have been proposed for the regulation of chromatin remodeling, first on purely theoretical grounds (Blossey and Schiessel 2008 HFSP J. 2 167-70) and deduced from experiments on the ISWI/ACF system (Narlikar 2010 Curr. Opin. Chem. Biol. 14 660). In the kinetic proofreading scenario of chromatin remodeling, the combination of the recognition of a histone tail state and ATP-hydrolysis in the remodeler motor act together to select (i.e. proofread) a nucleosomal substrate. ISWI remodelers have recently been shown to have an additional level of regulation as they contain auto-inhibitory motifs which need to be inactivated through an interaction with the nucleosome. In this paper we show that the auto-regulatory effect enhances substrate recognition in kinetic proofreading. We further report some suggestive additional insights into the molecular mechanism underlying ISWI-autoregulation.

Blind prediction of interfacial water positions in CAPRI

We report the first assessment of blind predictions of water positions at protein-protein interfaces, performed as part of the critical assessment of predicted interactions (CAPRI) community-wide experiment. Groups submitting docking predictions for the complex of the DNase domain of colicin E2 and Im2 immunity protein (CAPRI Target 47), were invited to predict the positions of interfacial water molecules using the method of their choice. The predictions-20 groups submitted a total of 195 models-were assessed by measuring the recall fraction of water-mediated protein contacts. Of the 176 high- or medium-quality docking models-a very good docking performance per se-only 44% had a recall fraction above 0.3, and a mere 6% above 0.5. The actual water positions were in general predicted to an accuracy level no better than 1.5 Å, and even in good models about half of the contacts represented false positives. This notwithstanding, three hotspot interface water positions were quite well predicted, and so was one of the water positions that is believed to stabilize the loop that confers specificity in these complexes. Overall the best interface water predictions was achieved by groups that also produced high-quality docking models, indicating that accurate modelling of the protein portion is a determinant factor. The use of established molecular mechanics force fields, coupled to sampling and optimization procedures also seemed to confer an advantage. Insights gained from this analysis should help improve the prediction of protein-water interactions and their role in stabilizing protein complexes.

On the molecular basis of D-bifunctional protein deficiency type III

Molecular basis of D-bifunctional protein (D-BP) deficiency was studied with wild type and five disease-causing variants of 3R-hydroxyacyl-CoA dehydrogenase fragment of the human MFE-2 (multifunctional enzyme type 2) protein. Complementation analysis in vivo in yeast and in vitro enzyme kinetic and stability determinants as well as in silico stability and structural fluctuation calculations were correlated with clinical data of known patients. Despite variations not affecting the catalytic residues, enzyme kinetic performance (K(m), V(max) and k(cat)) of the recombinant protein variants were compromised to a varying extent and this can be judged as the direct molecular cause for D-BP deficiency. Protein stability plays an additional role in producing non-functionality of MFE-2 in case structural variations affect cofactor or substrate binding sites. Structure-function considerations of the variant proteins matched well with the available data of the patients.

Oligoarginine vectors for intracellular delivery: role of arginine side-chain orientation in chain length-dependent destabilization of lipid membranes

Arginine-rich peptides receive increased attention due to their capacity to cross different types of membranes and to transport cargo molecules inside cells. Even though peptide-induced destabilization has been investigated extensively, little is known about the peptide side-chain and backbone orientation with respect to the bilayer that may contribute to a molecular understanding of the peptide-induced membrane perturbations. The main objective of this work is to provide a detailed description of the orientation of arginine peptides in the lipid bilayer of PC and negatively charged PG liposomes using ATR-IR spectroscopy and molecular modeling, and to relate these orientational preferences to lipid bilayer destabilization. Molecular modeling showed that above the transition temperature arginine side-chains are preferentially solvent-directed at the PC/water interface whereas several arginine side-chains are pointing towards the PG hydrophobic core. IR dichroic spectra confirmed the orientation of the arginine side chains perpendicular to the lipid-water interface. IR spectra shows an randomly distributed backbone that seems essential to optimize interactions with the lipid membrane. The observed increase of permeation to a fluorescent dye is related to the peptide induced-formation of gauche bonds in the acyl chains. In the absence of hydrophobic residues, insertion of side-chains that favors phosphate/guanidium interaction is another mechanism of membrane permeabilization that has not been further analyzed so far.

Docking and scoring protein interactions: CAPRI 2009

Protein docking algorithms are assessed by evaluating blind predictions performed during 2007-2009 in Rounds 13-19 of the community-wide experiment on critical assessment of predicted interactions (CAPRI). We evaluated the ability of these algorithms to sample docking poses and to single out specific association modes in 14 targets, representing 11 distinct protein complexes. These complexes play important biological roles in RNA maturation, G-protein signal processing, and enzyme inhibition and function. One target involved protein-RNA interactions not previously considered in CAPRI, several others were hetero-oligomers, or featured multiple interfaces between the same protein pair. For most targets, predictions started from the experimentally determined structures of the free (unbound) components, or from models built from known structures of related or similar proteins. To succeed they therefore needed to account for conformational changes and model inaccuracies. In total, 64 groups and 12 web-servers submitted docking predictions of which 4420 were evaluated. Overall our assessment reveals that 67% of the groups, more than ever before, produced acceptable models or better for at least one target, with many groups submitting multiple high- and medium-accuracy models for two to six targets. Forty-one groups including four web-servers participated in the scoring experiment with 1296 evaluated models. Scoring predictions also show signs of progress evidenced from the large proportion of correct models submitted. But singling out the best models remains a challenge, which also adversely affects the ability to correctly rank docking models. With the increased interest in translating abstract protein interaction networks into realistic models of protein assemblies, the growing CAPRI community is actively developing more efficient and reliable docking and scoring methods for everyone to use.

Identification of specific lipid-binding sites in integral membrane proteins

Protein-lipid interactions are increasingly recognized as central to the structure and function of membrane proteins. However, with the exception of simplified models, specific protein-lipid interactions are particularly difficult to highlight experimentally. Here, we used molecular dynamics simulations to identify a specific protein-lipid interaction in lactose permease, a prototypical model for transmembrane proteins. The interactions can be correlated with the functional dependence of the protein to specific lipid species. The technique is simple and widely applicable to other membrane proteins, and a variety of lipid matrices can be used.