A hidden markov model derived structural alphabet for proteins

Design of inhibitor peptide sequences based on the interfacial knowledge of the protein G-IgG crystallographic complex and their binding studies with IgG

Protein-protein interactions (PPI) have emerged as valuable targets in medicinal chemistry due to their key roles in important biological processes. The modulation of PPI by small peptides offers an excellent opportunity to develop drugs against human diseases. Here, we exploited the knowledge of the binding interface of the IgG-protein G complex (PDB:1FCC) for designing peptides that can inhibit these complexes. Herein, we have designed several closely related peptides, and the comparison of results from experiments and computational studies indicated that all the peptides bind close to the expected binding site on IgG and the complexes are stable. A minimal sequence consisting of 11 amino acids (P5) with binding constants in the range of 100 nM was identified. We propose that the main affinity differences across the series of peptides arose from the presence of polar amino acid residues. Further, the molecular dynamic studies helped to understand the dynamic properties of complexes in terms of flexibility of residues and structural stability at the interface. The ability of P5 to compete with the protein G in recognizing IgG can help in the detection and purification of antibodies. Further, it can serve as a versatile tool for a better understanding of protein-protein interactions.

Machine learning-based prediction of proteins' architecture using sequences of amino acids and structural alphabets

In addition to the growth of protein structures generated through wet laboratory experiments and deposited in the PDB repository, AlphaFold predictions have significantly contributed to the creation of a much larger database of protein structures. Annotating such a vast number of structures has become an increasingly challenging task. CATH is widely recognized as one the most common platforms for addressing this challenge, as it classifies proteins based on their structural and evolutionary relationships, offering the scientific community an invaluable resource for uncovering various properties, including functional annotations. While CATH annotation involves - to some extent - human intervention, keeping up with the classification of the rapidly expanding repositories of protein structures has become exceedingly difficult. Therefore, there is a pressing need for a fully automated approach. On the other hand, the abundance of protein sequences stemming from next generation sequencing technologies, lacking structural annotations, presents an additional challenge to the scientific community. Consequently, 'pre-annotating' protein sequences with structural features, ensuring a high level of precision, could prove highly advantageous. In this paper, after a thorough investigation, we introduce a novel machine-learning model capable of classifying any protein domain, whether it has a known structure or not, into one of the 40 main CATH Architectures. We achieve an F1 Score of 0.92 using only the amino acid sequence and a score of 0.94 using both the sequence of amino acids and the sequence of structural alphabets.Communicated by Ramaswamy H. Sarma.

Quantifying Disorder in a Protein by Mapping its Locally Correlated Structure and Kinetics

Proteins under physiological conditions are inherently mobile and sample a vast array of structures. Consequently, the need arises, on the one hand, at a local level to determine the independent moving parts and their associated conformations and kinetics, and on the other hand, at a global level, to quantify the disorder in the full protein molecule. We present an approach that provides these quantities in the form of local kinetic network models, which are constructed by analyzing the molecular dynamics (MD) trajectories of the protein molecule. Entropies of independent parts of the molecule are quantified. The method outlined here, using the Trp-cage miniprotein prototype, offers a new tool to understand the dynamic structural changes that ultimately govern the functioning of a protein. The method is particularly suited to problems where there are subtle changes in the structure or dynamics at local levels, for example, due to ligand binding.

ORF3c is expressed in SARS-CoV-2-infected cells and inhibits innate sensing by targeting MAVS

Most SARS-CoV-2 proteins are translated from subgenomic RNAs (sgRNAs). While the majority of these sgRNAs are monocistronic, some viral mRNAs encode more than one protein. One example is the ORF3a sgRNA that also encodes ORF3c, an enigmatic 41-amino-acid peptide. Here, we show that ORF3c is expressed in SARS-CoV-2-infected cells and suppresses RIG-I- and MDA5-mediated IFN-β induction. ORF3c interacts with the signaling adaptor MAVS, induces its C-terminal cleavage, and inhibits the interaction of RIG-I with MAVS. The immunosuppressive activity of ORF3c is conserved among members of the subgenus sarbecovirus, including SARS-CoV and coronaviruses isolated from bats. Notably, however, the SARS-CoV-2 delta and kappa variants harbor premature stop codons in ORF3c, demonstrating that this reading frame is not essential for efficient viral replication in vivo and is likely compensated by other viral proteins. In agreement with this, disruption of ORF3c does not significantly affect SARS-CoV-2 replication in CaCo-2, CaLu-3, or Rhinolophus alcyone cells. In summary, we here identify ORF3c as an immune evasion factor of SARS-CoV-2 that suppresses innate sensing in infected cells.

Functional mimicry of sea urchin biomineralization proteins with CaCO3-binding peptides selected by phage display

The intricate process of biomineralization, e.g. in sea urchins, involves the precise interplay of highly regulated mineralization proteins and the spatiotemporal coordination achieved through compartmentalization. However, the investigation of biomineralization effector molecules, e.g. proteins, is challenging, due to their very low abundance. Therefore, we investigate the functional mimicry in the bioinspired precipitation of calcium carbonate (CaCO3) with artificial peptides selected from a peptide library by phage display based on peptide-binding to calcite and aragonite, respectively. The structure-directing effects of the identified peptides were compared to those of natural protein mixes isolated from skeletal (test) structures of two sea urchin species (Arbacia lixula and Paracentrotus lividus). The calcium carbonate samples deposited in the absence or presence of peptides were analyzed with a set of complementary techniques with regard to morphology, polymorph, and nanostructural motifs. Remarkably, some of the CaCO3-binding peptides induced morphological features in calcite that appeared similar to those obtained in the presence of the natural protein mixes. Many of the peptides identified as most effective in exerting a structure-directing effect on calcium carbonate crystallization were rich in basic amino acid residues. Hence, our in vitro mineralization study further highlights the important, but often neglected, role of positively charged soluble organic matrices associated with biological and bioinspired CaCO3 deposition.

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.

A Synthetically Accessible Small-Molecule Inhibitor of USP5-Cav3.2 Calcium Channel Interactions with Analgesic Properties

Cav3.2 calcium channels are important mediators of nociceptive signaling in the primary afferent pain pathway, and their expression is increased in various rodent models of chronic pain. Previous work from our laboratory has shown that this is in part mediated by an aberrant expression of deubiquitinase USP5, which associates with these channels and increases their stability. Here, we report on a novel bioactive rhodanine compound (II-1), which was identified in compound library screens. II-1 inhibits biochemical interactions between USP5 and the Cav3.2 domain III-IV linker in a dose-dependent manner, without affecting the enzymatic activity of USP5. Molecular docking analysis reveals two potential binding pockets at the USP5-Cav3.2 interface that are distinct from the binding site of the deubiquitinase inhibitor WP1130 (a.k.a. degrasyn). With an understanding of the ability of some rhodanines to produce false positives in high-throughput screening, we have conducted several orthogonal assays to confirm the validity of this hit, including in vivo experiments. Intrathecal delivery of II-1 inhibited both phases of formalin-induced nocifensive behaviors in mice, as well as abolished thermal hyperalgesia induced by the delivery of complete Freund's adjuvant (CFA) to the hind paw. The latter effects were abolished in Cav3.2 null mice, thus confirming that Cav3.2 is required for the action of II-1. II-1 also mediated a robust inhibition of mechanical allodynia induced by injury to the sciatic nerve. Altogether, our data uncover a novel class of analgesics─well suited to rapid structure-activity relationship studies─that target the Cav3.2/USP5 interface.

In-silico study of peptide-protein interaction of antimicrobial peptides potentially targeting SARS and SARS-CoV-2 nucleocapsid protein

This study is an attempt to find a suitable therapy using antimicrobial peptides (AMPs) by identifying peptide-protein interaction of AMPs and nucleocapsid protein of SARS and SARS-CoV- 2. The AMPs were shortlisted from the APD3 database (Antimicrobial peptide database) based on various physicochemical parameters. The binding efficacy of AMPs was measured using the lowest energy score of the docked complexes with 10 selected AMPs. For SARS-CoV, AP00180 showed the best pose with a binding affinity value of - 6.4 kcal/mol. Prominent hydrogen bonding interactions were observed between Lys85 (nucleocapsid receptor) and Arg13 (antimicrobial peptide ligand) having the least intermolecular distance of 1.759 Å. For SARS-CoV-2, AP00549 was docked with a binding affinity value of - 3.4 kcal/mol and Arg119 and Glu14 of receptor nucleocapsid protein and ligand AMP having the least intermolecular distance of 2.104 The dynamic simulation was performed at 50 ns to check the stability of the final docked complexes, one with each protein. The two best AMPs were AP00180 (Human Defensin-5) for SARS and AP00549 (Plectasin) for SARS-CoV-2. From positive results of dynamic simulation and previously known knowledge that some AMPs interact with the nucleocapsid of coronaviruses, these AMPs might be used as a potential therapeutic agent for the treatment regime of SARS-CoV-2 and SARS infection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-021-00103-z.

Identification of naturally processed Zika virus peptides by mass spectrometry and validation of memory T cell recall responses in Zika convalescent subjects

Once an obscure pathogen, Zika virus (ZIKV) has emerged as a significant global public health concern. Several studies have linked ZIKV infection in pregnant women with the development of microcephaly and other neurological abnormalities, emphasizing the need for a safe and effective vaccine to combat the spread of this disease. Preclinical studies and vaccine development efforts have largely focused on the role of humoral immunity in disease protection. Consequently, relatively little is known in regard to cellular immunity against ZIKV, although an effective vaccine will likely need to engage both the humoral and cellular arms of the immune system. To that end, we utilized two-dimensional liquid chromatography coupled with tandem mass spectrometry to identify 90 ZIKV peptides that were naturally processed and presented on HLA class I and II molecules (HLA-A*02:01/HLA-DRB1*04:01) of an immortalized B cell line infected with ZIKV (strain PRVABC59). Sequence identity clustering was used to filter the number of candidate peptides prior to evaluating memory T cell recall responses in ZIKV convalescent subjects. Peptides that individually elicited broad (4 of 7 subjects) and narrow (1 of 7 subjects) T cell responses were further analyzed using a suite of predictive algorithms and in silico modeling to evaluate HLA binding and peptide structural properties. A subset of nine broadly reactive peptides was predicted to provide robust global population coverage (97.47% class I; 70.74% class II) and to possess stable structural properties amenable for vaccine formulation, highlighting the potential clinical benefit for including ZIKV T cell epitopes in experimental vaccine formulations.

Immunoinformatics prediction of potential B-cell and T-cell epitopes as effective vaccine candidates for eliciting immunogenic responses against Epstein-Barr virus

BACKGROUND

The ongoing search for viable treatment options to curtail Epstein Barr Virus (EBV) pathogenicity has necessitated a paradigmatic shift towards the design of peptide-based vaccines. Potential B-cell and T-cell epitopes were predicted for nine antigenic EBV proteins that mediate epithelial cell-attachment and spread, capsid self-assembly, DNA replication and processivity.

METHODS

Predictive algorithms incorporated in the Immune Epitope Database (IEDB) resources were used to determine potential B-cell epitopes based on their physicochemical attributes. These were combined with a string-kernel method and an antigenicity predictive AlgPred tool to enhance accuracy in the end-point selection of highly potential antigenic EBV B-cell epitopes. NetCTL 1.2 algorithms enabled the prediction of probable T-cell epitopes which were structurally modeled and subjected to blind peptide-protein docking with HLA-A*02:01. All-atom molecular dynamics (MD) simulation and Molecular Mechanics Generalized-Born Surface Area methods were used to investigate interaction dynamics and affinities of predicted T-cell peptide-protein complexes.

RESULTS

Computational predictions and sequence overlapping analysis yielded 18 linear (continuous) and discontinuous (conformational) subunit epitopes from the antigenic proteins with characteristic surface accessibility, flexibility and antigenicity, and predictive scores above the threshold value (1) set. A novel site was identified on HLA-A*02:01 with preferential affinity binding for modeled BMRF2, BXLF1 and BGLF4 T-cell epitopes. Interaction dynamics and energies were also computed in addition to crucial residues that mediated complex formation and stability.

CONCLUSION

This study implemented an integrative meta-analytical approach to model highly probable B-cell and T-cell epitopes as potential peptide-vaccine candidates for the treatment of EBV-related diseases.

Designing of Potential Polyvalent Vaccine Model for Respiratory Syncytial Virus by System Level Immunoinformatics Approaches

BACKGROUND

Respiratory syncytial virus (RSV) infection is a public health epidemic, leading to around 3 million hospitalization and about 66,000 deaths each year. It is a life-threatening condition exclusive to children with no effective treatment.

METHODS

In this study, we used system-level and vaccinomics approaches to design a polyvalent vaccine for RSV, which could stimulate the immune components of the host to manage this infection. Our framework involves data accession, antigenicity and subcellular localization analysis, T cell epitope prediction, proteasomal and conservancy evaluation, host-pathogen-protein interactions, pathway studies, and in silico binding affinity analysis.

RESULTS

We found glycoprotein (G), fusion protein (F), and small hydrophobic protein (SH) of RSV as potential vaccine candidates. Of these proteins (G, F, and SH), we found 9 epitopes for multiple alleles of MHC classes I and II bear significant binding affinity. These potential epitopes were linked to form a polyvalent construct using AAY, GPGPG linkers, and cholera toxin B adjuvant at N-terminal with a 23.9 kDa molecular weight of 224 amino acid residues. The final construct was a stable, immunogenic, and nonallergenic protein containing cleavage sites, TAP transport efficiency, posttranslation shifts, and CTL epitopes. The molecular docking indicated the optimum binding affinity of RSV polyvalent construct with MHC molecules (-12.49 and -10.48 kcal/mol for MHC classes I and II, respectively). This interaction showed that a polyvalent construct could manage and control this disease.

CONCLUSION

Our vaccinomics and system-level investigation could be appropriate to trigger the host immune system to prevent RSV infection.

Protein nanofibril design via manipulation of hydrogen bonds

The process of amyloid nanofibril formation has broad implications including the generation of the strongest natural materials, namely silk fibers, and their major contribution to the progression of many degenerative diseases. The key question that remains unanswered is whether the amyloidogenic nature, which includes the characteristic H-bonded β-sheet structure and physical characteristics of protein assemblies, can be modified via controlled intervention of the molecular interactions. Here we show that tailored changes in molecular interactions, specifically in the H-bonded network, do not affect the nature of amyloidogenic fibrillation, and even have minimal effect on the initial nucleation events of self-assembly. However, they do trigger changes in networks at a higher hierarchical level, namely enhanced 2D packaging which is rationalized by the 3D hierarchy of β-sheet assembly, leading to variations in fibril morphology, structural composition and, remarkably, nanomechanical properties. These results pave the way to a better understanding of the role of molecular interactions in sculpting the structural and physical properties of protein supramolecular constructs.

CD9 inhibition reveals a functional connection of extracellular vesicle secretion with mitophagy in melanoma cells

Tetraspanins are often used as Extracellular Vesicle (EV) detection markers because of their abundance on these secreted vesicles. However, data on their function on EV biogenesis are controversial and compensatory mechanisms often occur upon gene deletion. To overcome this handicap, we have compared the effects of tetraspanin CD9 gene deletion with those elicited by cytopermeable peptides with blocking properties against tetraspanin CD9. Both CD9 peptide or gene deletion reduced the number of early endosomes. CD9 peptide induced an increase in lysosome numbers, while CD9 deletion augmented the number of MVB and EV secretion, probably because of compensatory CD63 expression upregulation. In vivo, CD9 peptide delayed primary tumour cell growth and reduced metastasis size. These effects on cell proliferation were shown to be concomitant with an impairment in mitochondrial quality control. CD9 KO cells were able to compensate the mitochondrial malfunction by increasing total mitochondrial mass reducing mitophagy. Our data thus provide the first evidence for a functional connection of tetraspanin CD9 with mitophagy in melanoma cells.

Universal Architectural Concepts Underlying Protein Folding Patterns

What is the architectural “basis set” of the observed universe of protein structures? Using information-theoretic inference, we answer this question with a dictionary of 1,493 substructures—called concepts—typically at a subdomain level, based on an unbiased subset of known protein structures. Each concept represents a topologically conserved assembly of helices and strands that make contact. Any protein structure can be dissected into instances of concepts from this dictionary. We dissected the Protein Data Bank and completely inventoried all the concept instances. This yields many insights, including correlations between concepts and catalytic activities or binding sites, useful for rational drug design; local amino-acid sequence–structure correlations, useful for ab initio structure prediction methods; and information supporting the recognition and exploration of evolutionary relationships, useful for structural studies. An interactive site, Proçodic, at http://lcb.infotech.monash.edu.au/prosodic (click), provides access to and navigation of the entire dictionary of concepts and their usages, and all associated information. This report is part of a continuing programme with the goal of elucidating fundamental principles of protein architecture, in the spirit of the work of Cyrus Chothia.

Topology-independent and global protein structure alignment through an FFT-based algorithm

MOTIVATION

Protein structure alignment is one of the fundamental problems in computational structure biology. A variety of algorithms have been developed to address this important issue in the past decade. However, due to their heuristic nature, current structure alignment methods may suffer from suboptimal alignment and/or over-fragmentation and thus lead to a biologically wrong alignment in some cases. To overcome these limitations, we have developed an accurate topology-independent and global structure alignment method through an FFT-based exhaustive search algorithm, which is referred to as FTAlign.

RESULTS

Our FTAlign algorithm was extensively tested on six commonly used datasets and compared with seven state-of-the-art structure alignment approaches, TMalign, DeepAlign, Kpax, 3DCOMB, MICAN, SPalignNS and CLICK. It was shown that FTAlign outperformed the other methods in reproducing manually curated alignments and obtained a high success rate of 96.7 and 90.0% on two gold-standard benchmarks, MALIDUP and MALISAM, respectively. Moreover, FTAlign also achieved the overall best performance in terms of biologically meaningful structure overlap (SO) and TMscore on both the sequential alignment test sets including MALIDUP, MALISAM and 64 difficult cases from HOMSTRAD, and the non-sequential sets including MALIDUP-NS, MALISAM-NS, 199 topology-different cases, where FTAlign especially showed more advantage for non-sequential alignment. Despite its global search feature, FTAlign is also computationally efficient and can normally complete a pairwise alignment within one second.

AVAILABILITY AND IMPLEMENTATION

http://huanglab.phys.hust.edu.cn/ftalign/.

Polyvalent therapeutic vaccine for type 2 diabetes mellitus: Immunoinformatics approach to study co-stimulation of cytokines and GLUT1 receptors

Background

Type 2 diabetes mellitus (T2DM) is a worldwide disease that have an impact on individuals of all ages causing micro and macro vascular impairments due to hyperglycemic internal environment. For ultimate treatment to cure T2DM, association of diabetes with immune components provides a strong basis for immunotherapies and vaccines developments that could stimulate the immune cells to minimize the insulin resistance and initiate gluconeogenesis through an insulin independent route.

Methodology

Immunoinformatics based approach was used to design a polyvalent vaccine for T2DM that involved data accession, antigenicity analysis, T-cell epitopes prediction, conservation and proteasomal evaluation, functional annotation, interactomic and in silico binding affinity analysis.

Results

We found the binding affinity of antigenic peptides with major histocompatibility complex (MHC) Class-I molecules for immune activation to control T2DM. We found 13-epitopes of 9 amino acid residues for multiple alleles of MHC class-I bears significant binding affinity. The downstream signaling resulted by T-cell activation is directly regulated by the molecular weight, amino acid properties and affinity of these epitopes. Each epitope has important percentile rank with significant ANN IC₅₀ values. These high score potential epitopes were linked using AAY, EAAAK linkers and HBHA adjuvant to generate T-cell polyvalent vaccine with a molecular weight of 35.6 kDa containing 322 amino acids residues. In silico analysis of polyvalent construct showed the significant binding affinity (− 15.34 Kcal/mol) with MHC Class-I. This interaction would help to understand our hypothesis, potential activation of T-cells and stimulatory factor of cytokines and GLUT1 receptors.

Conclusion

Our system-level immunoinformatics approach is suitable for designing potential polyvalent therapeutic vaccine candidates for T2DM by reducing hyperglycemia and enhancing metabolic activities through the immune system.

Impacts of drug resistance mutations on the structural asymmetry of the HIV-2 protease

Background

Drug resistance is a severe problem in HIV treatment. HIV protease is a common target for the design of new drugs for treating HIV infection. Previous studies have shown that the crystallographic structures of the HIV-2 protease (PR2) in bound and unbound forms exhibit structural asymmetry that is important for ligand recognition and binding. Here, we investigated the effects of resistance mutations on the structural asymmetry of PR2. Due to the lack of structural data on PR2 mutants, the 3D structures of 30 PR2 mutants of interest have been modeled using an in silico protocol. Structural asymmetry analysis was carried out with an in-house structural-alphabet-based approach.

Results

The systematic comparison of the asymmetry of the wild-type structure and a large number of mutants highlighted crucial residues for PR2 structure and function. In addition, our results revealed structural changes induced by PR2 flexibility or resistance mutations. The analysis of the highlighted structural changes showed that some mutations alter protein stability or inhibitor binding.

Conclusions

This work consists of a structural analysis of the impact of a large number of PR2 resistant mutants based on modeled structures. It suggests three possible resistance mechanisms of PR2, in which structural changes induced by resistance mutations lead to modifications in the dimerization interface, ligand recognition or inhibitor binding.

The search of sequence variants using a constrained protein evolution simulation approach

Protein engineering or candidate therapeutic peptide optimization are processes in which the identification of relevant sequence variants is critical. Starting from one amino-acid sequence, the choice of the substitutions must meet the objective of not disrupting the structure of the protein, not impacting the main functional properties of the starting entity, while also meeting the condition to enhance some expected property such as thermal stability, resistance to degradation, … Here, we introduce a new approach of sequence evolution that focuses on the objective of not disrupting the structure of the initial protein by embedding a point to point control on the preservation of the local structure at each position in the sequence. For 6 mini-proteins, we find that, starting from a single sequence, our simple approach intrinsically contains information about site-specific rate heterogeneity of substitution, and that it is able to reproduce sequence diversity as can be observed in the sequences available in the Uniref repository. We show that our approach is able to provide information about positions not to substitute and about substitutions not to perform at a given position to maintain structure integrity. Overall, our results demonstrate that point to point preservation of the local structure along a sequence is an important determinant of sequence evolution.

Computational reconstruction of atomistic protein structures from coarse-grained models

Three-dimensional protein structures, whether determined experimentally or theoretically, are often too low resolution. In this mini-review, we outline the computational methods for protein structure reconstruction from incomplete coarse-grained to all atomistic models. Typical reconstruction schemes can be divided into four major steps. Usually, the first step is reconstruction of the protein backbone chain starting from the C-alpha trace. This is followed by side-chains rebuilding based on protein backbone geometry. Subsequently, hydrogen atoms can be reconstructed. Finally, the resulting all-atom models may require structure optimization. Many methods are available to perform each of these tasks. We discuss the available tools and their potential applications in integrative modeling pipelines that can transfer coarse-grained information from computational predictions, or experiment, to all atomistic structures.

A Synthetic Derivative of Antimicrobial Peptide Holothuroidin 2 from Mediterranean Sea Cucumber (Holothuria tubulosa) in the Control of Listeria monocytogenes

Due to the limited number of available antibiotics, antimicrobial peptides (AMPs) are considered antimicrobial candidates to fight difficult-to-treat infections such as those associated with biofilms. Marine environments are precious sources of AMPs, as shown by the recent discovery of antibiofilm properties of Holothuroidin 2 (H2), an AMP produced by the Mediterranean sea cucumber Holothuria tubulosa. In this study, we considered the properties of a new H2 derivative, named H2d, and we tested it against seven strains of the dangerous foodborne pathogen Listeria monocytogenes. This peptide was more active than H2 in inhibiting the growth of planktonic L. monocytogenes and was able to interfere with biofilm formation at sub-minimum inhibitory concentrations (MICs). Atomic-level molecular dynamics (MD) simulations revealed insights related to the enhanced inhibitory activity of H2d, showing that the peptide is characterized by a more defined tertiary structure with respect to its ancestor. This allows the peptide to better exhibit an amphipathic character, which is an essential requirement for the interaction with cell membranes, similarly to other AMPs. Altogether, these results support the potential use of our synthetic peptide, H2d, as a template for the development of novel AMP-based drugs able to fight foodborne that are resistant to conventional antibiotics.

Characterizing the structural variability of HIV-2 protease upon the binding of diverse ligands using a structural alphabet approach

The HIV-2 protease (PR2) is an important target for designing new drugs against the HIV-2 infection. In this study, we explored the structural backbone variability of all available PR2 structures complexed with various inhibitors using a structural alphabet approach. 77% of PR2 positions are structurally variable, meaning they exhibit different local conformations in PR2 structures. This variability was observed all along the structure, particularly in the elbow and flap regions. A part of these backbone changes observed between the 18 PR2 is induced by intrinsic flexibility, and ligand binding putatively induces others occurring in the binding pocket. These latter changes could be important for PR2 adaptation to diverse ligands and are accompanied by changes outside the binding pocket. In addition, the study of the link between structural variability of the pocket and PR2-ligand interactions allowed us to localize pocket regions important for ligand binding and catalytic function, regions important for ligand recognition that adjust their backbone in response to ligand binding and regions important for the pocket opening and closing that have large intrinsic flexibility. Finally, we suggested that differences in ligand effectiveness for PR2 could be partially explained by different backbone deformations induced by these ligands. To conclude, this study is the first characterization of the PR2 structural variability considering ligand diversity. It provides information about the recognition of PR2 to various ligands and its mechanisms to adapt its local conformation to bound ligands that could help understand the resistance of PR2 to its inhibitors, a major antiretroviral class. Communicated by Ramaswamy H. Sarma.

Characterization of HIV-2 Protease Structure by Studying Its Asymmetry at the Different Levels of Protein Description

HIV-2 protease (PR2) is a homodimer, which is an important target in the treatment of the HIV-2 infection. In this study, we developed an in silico protocol to analyze and characterize the asymmetry of the unbound PR2 structure using three levels of protein description by comparing the conformation, accessibility, and flexibility of each residue in the two PR2 chains. Our results showed that 65% of PR2 residues have at least one of the three studied asymmetries (structural, accessibility, or flexibility) with 10 positions presenting the three asymmetries in the same time. In addition, we noted that structural and flexibility asymmetries are linked indicating that the structural asymmetry of some positions result from their large flexibility. By comparing the structural asymmetry of the crystallographic and energetically minimized structures of the unbound PR2, we confirmed that the structural asymmetry of unbound PR2 is an intrinsic property of this protein with an important role for the PR2 deformation upon ligand binding. This analysis also allowed locating asymmetries corresponding to crystallization artefacts. This study provides insight that will help to better understand the structural deformations of PR2 and to identify key positions for ligand binding.

Leptodactylus latrans Amphibian Skin Secretions as a Novel Source for the Isolation of Antibacterial Peptides

Amphibians´ skin produces a diverse array of antimicrobial peptides that play a crucial role as the first line of defense against microbial invasion. Despite the immense richness of wild amphibians in Argentina, current knowledge about the presence of peptides with antimicrobial properties is limited to a only few species. Here we used LC-MS-MS to identify antimicrobial peptides with masses ranging from 1000 to 4000 Da from samples of skin secretions of Leptodactylus latrans (Anura: Leptodactylidae). Three novel amino acid sequences were selected for chemical synthesis and further studies. The three synthetic peptides, named P1-Ll-1577, P2-Ll-1298, and P3-Ll-2085, inhibited the growth of two ATCC strains, namely Escherichia coli and Staphylococcus aureus. P3-Ll-2085 was the most active peptide. In the presence of trifluoroethanol (TFE) and anionic liposomes, it adopted an amphipathic α-helical structure. P2-Ll-1298 showed slightly lower activity than P3-Ll-2085. Comparison of the MIC values of these two peptides revealed that the addition of seven amino acid residues (GLLDFLK) on the N-terminal of P2-Ll-1298 significantly improved activity against both strains. P1-Ll-1577, which remarkably is an anionic peptide, showed interesting antimicrobial activity against E. coli and S. aureus strain, showing marked membrane selectivity and non-hemolysis. Due to this, P1-L1-1577 emerges as a potential candidate for the development of new antibacterial drugs.

dentification and molecular docking of novel ACE inhibitory peptides from protein hydrolysates of shrimp waste

The effect of enzymatic hydrolysis by Savinase on the interfacial properties and antihypertensive activity of shrimp waste proteins was evaluated. The physicochemical characterization, interfacial tension, and surface characteristics of shrimp waste protein hydrolysates (SWPH) using different enzyme/substrate (E/S) (SWPH₅ (SWPH using E/S = 5), SWPH₁₅ (SWPH using E/S = 15), and SWPH₄₀ (SWPH using E/S = 40)) were also studied. SWPH₅, SWPH₁₅, and SWPH₄₀ had an isoelectric pH around 2.07, 2.17, and 2.54 respectively. SWPH₅ exhibited the lowest interfacial tension (68.96 mN/m) followed by SWPH₁₅ (69.36 mN/m) and SWPH₄₀ (70.29 mN/m). The in vitro ACE inhibitory activity of shrimp waste protein hydrolysates showed that the most active hydrolysate was obtained using an enzyme/substrate of 15 U/mg (SWPH₁₅). SWPH₁₅ had a lower IC₅₀ value (2.17 mg/mL) than that of SWPH₅ and SWPH₄₀ (3.65 and 5.7 mg/mL, respectively). This hydrolysate was then purified and characterized. Fraction F1 separated by Sephadex G25 column which presents the best ACE inhibition activity was then separated by reversed-phase high performance liquid chromatography. Four ACE inhibitory peptides were identified and their molecular masses and amino acid sequences were determined using ESI-MS and ESI-MS/MS, respectively. The structures of the most potent peptides were SSSKAKKMP, HGEGGRSTHE, WLGHGGRPDHE, and WRMDIDGDIMISEQEAHQR. The structural modeling of anti-ACE peptides from shrimp waste through docking simulations results showed that these peptides bound to ACE with high affinity.

SAFlex: A structural alphabet extension to integrate protein structural flexibility and missing data information

In this paper, we describe SAFlex (Structural Alphabet Flexibility), an extension of an existing structural alphabet (HMM-SA), to better explore increasing protein three dimensional structure information by encoding conformations of proteins in case of missing residues or uncertainties. An SA aims to reduce three dimensional conformations of proteins as well as their analysis and comparison complexity by simplifying any conformation in a series of structural letters. Our methodology presents several novelties. Firstly, it can account for the encoding uncertainty by providing a wide range of encoding options: the maximum a posteriori, the marginal posterior distribution, and the effective number of letters at each given position. Secondly, our new algorithm deals with the missing data in the protein structure files (concerning more than 75% of the proteins from the Protein Data Bank) in a rigorous probabilistic framework. Thirdly, SAFlex is able to encode and to build a consensus encoding from different replicates of a single protein such as several homomer chains. This allows localizing structural differences between different chains and detecting structural variability, which is essential for protein flexibility identification. These improvements are illustrated on different proteins, such as the crystal structure of an eukaryotic small heat shock protein. They are promising to explore increasing protein redundancy data and obtain useful quantification of their flexibility.

Analysis of the HIV-2 protease's adaptation to various ligands: characterization of backbone asymmetry using a structural alphabet

The HIV-2 protease (PR2) is a homodimer of 99 residues with asymmetric assembly and binding various ligands. We propose an exhaustive study of the local structural asymmetry between the two monomers of all available PR2 structures complexed with various inhibitors using a structural alphabet approach. On average, PR2 exhibits asymmetry in 31% of its positions-i.e., exhibiting different backbone local conformations in the two monomers. This asymmetry was observed all along its structure, particularly in the elbow and flap regions. We first differentiated structural asymmetry conserved in most PR2 structures from the one specific to some PR2. Then, we explored the origin of the detected asymmetry in PR2. We localized asymmetry that could be induced by PR2's flexibility, allowing transition from the semi-open to closed conformations and the asymmetry potentially induced by ligand binding. This latter could be important for the PR2's adaptation to diverse ligands. Our results highlighted some differences between asymmetry of PR2 bound to darunavir and amprenavir that could explain their differences of affinity. This knowledge is critical for a better description of PR2's recognition and adaptation to various ligands and for a better understanding of the resistance of PR2 to most PR2 inhibitors, a major antiretroviral class.

Oxygen binding isotope effects of triazole-based HIV-1 reverse transcriptase inhibitors indicate the actual binding site

Binding isotope effects (BIEs) associated with binding of four triazole-based ligands to HIV-1 reverse transcriptase have been calculated at the QM/MM MD level of theory. Two main binding sites: allosteric cavity and RNase H active site, as well as three other sites reported in the literature (the Knuckles, the NNRTI Adjacent, and Incoming Nucleotide Binding) have been considered. The interactions between inhibitors and these protein sites have been quantified by binding free energies obtained from free energy perturbation (FEP) calculations, supported by interaction energy analysis. It has been shown that binding in the allosteric cavity can be distinguished from binding to other sites based on BIEs as it is associated with normal ¹⁸O-BIEs of the carbonyl oxygen atom while binding to RNase H active site is characterized by inverse binding isotope effect (¹⁸O-BIE < 1). For other sites ¹⁸O-BIEs close to unity are predicted. This information points to oxygen binding isotope effects of carbonyl group as indicative of the actual binding site of studied inhibitors.

Exploring the potential of a structural alphabet-based tool for mining multiple target conformations and target flexibility insight

Protein flexibility is often implied in binding with different partners and is essential for protein function. The growing number of macromolecular structures in the Protein Data Bank entries and their redundancy has become a major source of structural knowledge of the protein universe. The analysis of structural variability through available redundant structures of a target, called multiple target conformations (MTC), obtained using experimental or modeling methods and under different biological conditions or different sources is one way to explore protein flexibility. This analysis is essential to improve the understanding of various mechanisms associated with protein target function and flexibility. In this study, we explored structural variability of three biological targets by analyzing different MTC sets associated with these targets. To facilitate the study of these MTC sets, we have developed an efficient tool, SA-conf, dedicated to capturing and linking the amino acid and local structure variability and analyzing the target structural variability space. The advantage of SA-conf is that it could be applied to divers sets composed of MTCs available in the PDB obtained using NMR and crystallography or homology models. This tool could also be applied to analyze MTC sets obtained by dynamics approaches. Our results showed that SA-conf tool is effective to quantify the structural variability of a MTC set and to localize the structural variable positions and regions of the target. By selecting adapted MTC subsets and comparing their variability detected by SA-conf, we highlighted different sources of target flexibility such as induced by binding partner, by mutation and intrinsic flexibility. Our results support the interest to mine available structures associated with a target using to offer valuable insight into target flexibility and interaction mechanisms. The SA-conf executable script, with a set of pre-compiled binaries are available at http://www.mti.univ-paris-diderot.fr/recherche/plateformes/logiciels.

Trictide, a tricellulin-derived peptide to overcome cellular barriers

The majority of tight junction (TJ) proteins restrict the paracellular permeation of solutes via their extracellular loops (ECLs). Tricellulin tightens tricellular TJs (tTJs) and regulates bicellular TJ (bTJ) proteins. We demonstrate that the addition of recombinantly produced extracellular loop 2 (ECL2) of tricellulin opens cellular barriers. The peptidomimetic trictide, a synthetic peptide derived from tricellulin ECL2, increases the passage of ions, as well as of small and larger molecules up to 10 kDa, between 16 and 30 h after application to human epithelial colorectal adenocarcinoma cell line 2. Tricellulin and lipolysis-stimulated lipoprotein receptor relocate from tTJs toward bTJs, while the TJ proteins claudin-1 and occludin redistribute from bTJs to the cytosol. Analyzing the opening of the tricellular sealing tube by the peptidomimetic using super-resolution stimulated-emission depletion microscopy revealed a tricellulin-free area at the tricellular region. Cis-interactions (as measured by fluorescence resonance energy transfer) of tricellulin-tricellulin (tTJs), tricellulin-claudin-1, tricellulin-marvelD3, and occludin-occludin (bTJs) were strongly affected by trictide treatment. Circular dichroism spectroscopy and molecular modeling suggest that trictide adopts a β-sheet structure, resulting in a peculiar interaction surface for its binding to tricellulin. In conclusion, trictide is a novel and promising tool for overcoming cellular barriers at bTJs and tTJs with the potential to transiently improve drug delivery.

Identification and Molecular Characterization of the Chloroplast Targeting Domain of Turnip yellow mosaic virus Replication Proteins

Turnip yellow mosaic virus (TYMV) is a positive-strand RNA virus infecting plants. The TYMV 140K replication protein is a key organizer of viral replication complex (VRC) assembly, being responsible for recruitment of the viral polymerase and for targeting the VRCs to the chloroplast envelope where viral replication takes place. However, the structural requirements determining the subcellular localization and membrane association of this essential viral protein have not yet been defined. In this study, we investigated determinants for the in vivo chloroplast targeting of the TYMV 140K replication protein. Subcellular localization studies of deletion mutants identified a 41-residue internal sequence as the chloroplast targeting domain (CTD) of TYMV 140K; this sequence is sufficient to target GFP to the chloroplast envelope. The CTD appears to be located in the C-terminal extension of the methyltransferase domain-a region shared by 140K and its mature cleavage product 98K, which behaves as an integral membrane protein during infection. We predicted the CTD to fold into two amphipathic α-helices-a folding that was confirmed in vitro by circular dichroism spectroscopy analyses of a synthetic peptide. The importance for subcellular localization of the integrity of these amphipathic helices, and the function of 140K/98K, was demonstrated by performing amino acid substitutions that affected chloroplast targeting, membrane association and viral replication. These results establish a short internal α-helical peptide as an unusual signal for targeting proteins to the chloroplast envelope membrane, and provide new insights into membrane targeting of viral replication proteins-a universal feature of positive-strand RNA viruses.

Dynamic and Electrostatic Effects on the Reaction Catalyzed by HIV-1 Protease

HIV-1 Protease (HIV-1 PR) is one of the three enzymes essential for the replication process of HIV-1 virus, which explains why it has been the main target for design of drugs against acquired immunodeficiency syndrome (AIDS). This work is focused on exploring the proteolysis reaction catalyzed by HIV-1 PR, with special attention to the dynamic and electrostatic effects governing its catalytic power. Free energy surfaces for all possible mechanisms have been computed in terms of potentials of mean force (PMFs) within hybrid QM/MM potentials, with the QM subset of atoms described at semiempirical (AM1) and DFT (M06-2X) level. The results suggest that the most favorable reaction mechanism involves formation of a gem-diol intermediate, whose decomposition into the product complex would correspond to the rate-limiting step. The agreement between the activation free energy of this step with experimental data, as well as kinetic isotope effects (KIEs), supports this prediction. The role of the protein dynamic was studied by protein isotope labeling in the framework of the Variational Transition State Theory. The predicted enzyme KIEs, also very close to the values measured experimentally, reveal a measurable but small dynamic effect. Our calculations show how the contribution of dynamic effects to the effective activation free energy appears to be below 1 kcal·mol^-1. On the contrary, the electric field created by the protein in the active site of the enzyme emerges as being critical for the electronic reorganization required during the reaction. These electrostatic properties of the active site could be used as a mold for future drug design.

Characterization and Prediction of Protein Flexibility Based on Structural Alphabets

Motivation. To assist efforts in determining and exploring the functional properties of proteins, it is desirable to characterize and predict protein flexibilities. Results. In this study, the conformational entropy is used as an indicator of the protein flexibility. We first explore whether the conformational change can capture the protein flexibility. The well-defined decoy structures are converted into one-dimensional series of letters from a structural alphabet. Four different structure alphabets, including the secondary structure in 3-class and 8-class, the PB structure alphabet (16-letter), and the DW structure alphabet (28-letter), are investigated. The conformational entropy is then calculated from the structure alphabet letters. Some of the proteins show high correlation between the conformation entropy and the protein flexibility. We then predict the protein flexibility from basic amino acid sequence. The local structures are predicted by the dual-layer model and the conformational entropy of the predicted class distribution is then calculated. The results show that the conformational entropy is a good indicator of the protein flexibility, but false positives remain a problem. The DW structure alphabet performs the best, which means that more subtle local structures can be captured by large number of structure alphabet letters. Overall this study provides a simple and efficient method for the characterization and prediction of the protein flexibility.

A critical assessment of hidden markov model sub-optimal sampling strategies applied to the generation of peptide 3D models

Hidden Markov Model derived structural alphabets are a probabilistic framework in which the complete conformational space of a peptidic chain is described in terms of probability distributions that can be sampled to identify conformations of largest probabilities. Here, we assess how three strategies to sample sub-optimal conformations-Viterbi k-best, forward backtrack and a taboo sampling approach-can lead to the efficient generation of peptide conformations. We show that the diversity of sampling is essential to compensate biases introduced in the estimates of the probabilities, and we find that only the forward backtrack and a taboo sampling strategies can efficiently generate native or near-native models. Finally, we also find such approaches are as efficient as former protocols, while being one order of magnitude faster, opening the door to the large scale de novo modeling of peptides and mini-proteins. © 2016 Wiley Periodicals, Inc.

PEP-FOLD3: faster de novo structure prediction for linear peptides in solution and in complex

Structure determination of linear peptides of 5–50 amino acids in aqueous solution and interacting with proteins is a key aspect in structural biology. PEP-FOLD3 is a novel computational framework, that allows both (i) de novo free or biased prediction for linear peptides between 5 and 50 amino acids, and (ii) the generation of native-like conformations of peptides interacting with a protein when the interaction site is known in advance. PEP-FOLD3 is fast, and usually returns solutions in a few minutes. Testing PEP-FOLD3 on 56 peptides in aqueous solution led to experimental-like conformations for 80% of the targets. Using a benchmark of 61 peptide–protein targets starting from the unbound form of the protein receptor, PEP-FOLD3 was able to generate peptide poses deviating on average by 3.3Å from the experimental conformation and return a native-like pose in the first 10 clusters for 52% of the targets. PEP-FOLD3 is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD3.

Using Local States To Drive the Sampling of Global Conformations in Proteins

Conformational changes associated with protein function often occur beyond the time scale currently accessible to unbiased molecular dynamics (MD) simulations, so that different approaches have been developed to accelerate their sampling. Here we investigate how the knowledge of backbone conformations preferentially adopted by protein fragments, as contained in precalculated libraries known as structural alphabets (SA), can be used to explore the landscape of protein conformations in MD simulations. We find that (a) enhancing the sampling of native local states in both metadynamics and steered MD simulations allows the recovery of global folded states in small proteins; (b) folded states can still be recovered when the amount of information on the native local states is reduced by using a low-resolution version of the SA, where states are clustered into macrostates; and (c) sequences of SA states derived from collections of structural motifs can be used to sample alternative conformations of preselected protein regions. The present findings have potential impact on several applications, ranging from protein model refinement to protein folding and design.

Redox Regulation of Cell Contacts by Tricellulin and Occludin: Redox-Sensitive Cysteine Sites in Tricellulin Regulate Both Tri- and Bicellular Junctions in Tissue Barriers as Shown in Hypoxia and Ischemia

Tight junctions (TJs) seal paracellular clefts in epithelia/endothelia and form tissue barriers for proper organ function. TJ-associated marvel proteins (TAMPs; tricellulin, occludin, marvelD3) are thought to be relevant to regulation. Under normal conditions, tricellulin tightens tricellular junctions against macromolecules. Traces of tricellulin occur in bicellular junctions.

AIMS

As pathological disturbances have not been analyzed, the structure and function of human tricellulin, including potentially redox-sensitive Cys sites, were investigated under reducing/oxidizing conditions at 3- and 2-cell contacts.

RESULTS

Ischemia, hypoxia, and reductants redistributed tricellulin from 3- to 2-cell contacts. The extracellular loop 2 (ECL2; conserved Cys321, Cys335) trans-oligomerized between three opposing cells. Substitutions of these residues caused bicellular localization. Cys362 in transmembrane domain 4 contributed to bicellular heterophilic cis-interactions along the cell membrane with claudin-1 and marvelD3, while Cys395 in the cytosolic C-terminal tail promoted homophilic tricellullar cis-interactions. The Cys sites included in homo-/heterophilic bi-/tricellular cis-/trans-interactions contributed to cell barrier tightness for small/large molecules.

INNOVATION

Tricellulin forms TJs via trans- and cis-association in 3-cell contacts, as demonstrated electron and quantified fluorescence microscopically; it tightens 3- and 2-cell contacts. Tricellulin's ECL2 specifically seals 3-cell contacts redox dependently; a structural model is proposed.

CONCLUSIONS

TAMP ECL2 and claudins' ECL1 share functionally and structurally similar features involved in homo-/heterophilic tightening of cell-cell contacts. Tricellulin is a specific redox sensor and sealing element at 3-cell contacts and may compensate as a redox mediator for occludin loss at 2-cell contacts in vivo and in vitro. Molecular interaction mechanisms were proposed that contribute to tricellulin's function. In conclusion, tricellulin is a junctional redox regulator for ischemia-related alterations.

Amplitude spectrum distance: measuring the global shape divergence of protein fragments

Background

In structural bioinformatics, there is an increasing interest in identifying and understanding the evolution of local protein structures regarded as key structural or functional protein building blocks. A central need is then to compare these, possibly short, fragments by measuring efficiently and accurately their (dis)similarity. Progress towards this goal has given rise to scores enabling to assess the strong similarity of fragments. Yet, there is still a lack of more progressive scores, with meaningful intermediate values, for the comparison, retrieval or clustering of distantly related fragments.

Results

We introduce here the Amplitude Spectrum Distance (ASD), a novel way of comparing protein fragments based on the discrete Fourier transform of their C_α distance matrix. Defined as the distance between their amplitude spectra, ASD can be computed efficiently and provides a parameter-free measure of the global shape dissimilarity of two fragments. ASD inherits from nice theoretical properties, making it tolerant to shifts, insertions, deletions, circular permutations or sequence reversals while satisfying the triangle inequality. The practical interest of ASD with respect to RMSD, RMSD_d, BC and TM scores is illustrated through zinc finger retrieval experiments and concrete structure examples. The benefits of ASD are also illustrated by two additional clustering experiments: domain linkers fragments and complementarity-determining regions of antibodies.

Conclusions

Taking advantage of the Fourier transform to compare fragments at a global shape level, ASD is an objective and progressive measure taking into account the whole fragments. Its practical computation time and its properties make ASD particularly relevant for applications requiring meaningful measures on distantly related protein fragments, such as similar fragments retrieval asking for high recalls as shown in the experiments, or for any application taking also advantage of triangle inequality, such as fragments clustering.

ASD program and source code are freely available at: http://www.irisa.fr/dyliss/public/ASD/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0693-y) contains supplementary material, which is available to authorized users.

Protein flexibility in the light of structural alphabets

Protein structures are valuable tools to understand protein function. Nonetheless, proteins are often considered as rigid macromolecules while their structures exhibit specific flexibility, which is essential to complete their functions. Analyses of protein structures and dynamics are often performed with a simplified three-state description, i.e., the classical secondary structures. More precise and complete description of protein backbone conformation can be obtained using libraries of small protein fragments that are able to approximate every part of protein structures. These libraries, called structural alphabets (SAs), have been widely used in structure analysis field, from definition of ligand binding sites to superimposition of protein structures. SAs are also well suited to analyze the dynamics of protein structures. Here, we review innovative approaches that investigate protein flexibility based on SAs description. Coupled to various sources of experimental data (e.g., B-factor) and computational methodology (e.g., Molecular Dynamic simulation), SAs turn out to be powerful tools to analyze protein dynamics, e.g., to examine allosteric mechanisms in large set of structures in complexes, to identify order/disorder transition. SAs were also shown to be quite efficient to predict protein flexibility from amino-acid sequence. Finally, in this review, we exemplify the interest of SAs for studying flexibility with different cases of proteins implicated in pathologies and diseases.

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 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.

Antimicrobial peptides from skin secretions of Hypsiboas pulchellus (Anura: Hylidae)

The skin of many amphibians produces a large repertoire of antimicrobial peptides that are crucial in the first line of defense against microbial invasion. Despite the immense richness of wild amphibians in Argentina, knowledge about peptides with antimicrobial properties is limited to a few species. Here we used LC-MS-MS to analyze samples of Hypsiboas pulchellus skin with the aim to identify antimicrobial peptides in the mass range of 1000 to 2000 Da. Twenty-three novel sequences were identified by MS, three of which were selected for chemical synthesis and further studies. The three synthetic peptides, named P1-Hp-1971, P2-Hp-1935, and P3-Hp-1891, inhibited the growth of two ATCC strains: Escherichia coli (MIC: 16, 33, and 17 μM, respectively) and Staphylococcus aureus (MIC: 8, 66, and 17 μM, respectively). P1-Hp-1971 and P3-Hp-1891 were the most active peptides. P1-Hp-1971, which showed the highest therapeutic indices (40 for E. coli and 80 for S. aureus), is a proline-glycine-rich peptide with a highly unordered structure, while P3-Hp-1891 adopts an amphipathic α-helical structure in the presence of 2,2,2-trifluoroethanol and anionic liposomes. This is the first peptidomic study of Hypsiboas pulchellus skin secretions to allow the identification of antimicrobial peptides.