Prelude and Fugue, predicting local protein structure, early folding regions and structural weaknesses

Prelude&Fugue are bioinformatics tools aiming at predicting the local 3D structure of a protein from its amino acid sequence in terms of seven backbone torsion angle domains, using database-derived potentials. Prelude(&Fugue) computes all lowest free energy conformations of a protein or protein region, ranked by increasing energy, and possibly satisfying some interresidue distance constraints specified by the user. (Prelude&)Fugue detects sequence regions whose predicted structure is significantly preferred relative to other conformations in the absence of tertiary interactions. These programs can be used for predicting secondary structure, tertiary structure of short peptides, flickering early folding sequences and peptides that adopt a preferred conformation in solution. They can also be used for detecting structural weaknesses, i.e. sequence regions that are not optimal with respect to the tertiary fold. AVAILABILITY: http://babylone.ulb.ac.be/Prelude_and_Fugue.     

Defining parameters for homology-tolerant database searching.

De novo interpretation of tandem mass spectrometry (MS/MS) spectra provides sequences for searching protein databases when limited sequence information is present in the database. Our objective was to define a strategy for this type of homology-tolerant database search. Homology searches, using MS-Homology software, were conducted with 20, 10, or 5 of the most abundant peptides from 9 proteins, based either on precursor trigger intensity or on total ion current, and allowing for 50%, 30%, or 10% mismatch in the search. Protein scores were corrected by subtracting a threshold score that was calculated from random peptides. The highest (p < .01) corrected protein scores (i.e., above the threshold) were obtained by submitting 20 peptides and allowing 30% mismatch. Using these criteria, protein identification based on ion mass searching using MS/MS data (i.e., Mascot) was compared with that obtained using homology search. The highest-ranking protein was the same using Mascot, homology search using the 20 most intense peptides, or homology search using all peptides, for 63.4% of 112 spots from two-dimensional polyacrylamide gel electrophoresis gels. For these proteins, the percent coverage was greatest using Mascot compared with the use of all or just the 20 most intense peptides in a homology search (25.1%, 18.3%, and 10.6%, respectively). Finally, 35% of de novo sequences completely matched the corresponding known amino acid sequence of the matching peptide. This percentage increased when the search was limited to the 20 most intense peptides (44.0%). After identifying the protein using MS-Homology, a peptide mass search may increase the percent coverage of the protein identified.     

Geno3D: automatic comparative molecular modelling of protein

Geno3D (http://geno3d-pbil.ibcp.fr) is an automatic web server for protein molecular modelling. Starting with a query protein sequence, the server performs the homology modelling in six successive steps: (i) identify homologous proteins with known 3D structures by using PSI-BLAST; (ii) provide the user all potential templates through a very convenient user interface for target selection; (iii) perform the alignment of both query and subject sequences; (iv) extract geometrical restraints (dihedral angles and distances) for corresponding atoms between the query and the template; (v) perform the 3D construction of the protein by using a distance geometry approach and (vi) finally send the results by e-mail to the user.     

Assessing model accuracy using the homology modeling automatically software

Homology modeling is a powerful technique that greatly increases the value of experimental structure determination by using the structural information of one protein to predict the structures of homologous proteins. We have previously described a method of homology modeling by satisfaction of spatial restraints (Li et al., Protein Sci 1997;6:956-970). The Homology Modeling Automatically (HOMA) web site, , is a new tool, using this method to predict 3D structure of a target protein based on the sequence alignment of the target protein to a template protein and the structure coordinates of the template. The user is presented with the resulting models, together with an extensive structure validation report providing critical assessments of the quality of the resulting homology models. The homology modeling method employed by HOMA was assessed and validated using twenty-four groups of homologous proteins. Using HOMA, homology models were generated for 510 proteins, including 264 proteins modeled with correct folds and 246 modeled with incorrect folds. Accuracies of these models were assessed by superimposition on the corresponding experimentally determined structures. A subset of these results was compared with parallel studies of modeling accuracy using several other automated homology modeling approaches. Overall, HOMA provides prediction accuracies similar to other state-of-the-art homology modeling methods. We also provide an evaluation of several structure quality validation tools in assessing the accuracy of homology models generated with HOMA. This study demonstrates that Verify3D (Luthy et al., Nature 1992;356:83-85) and ProsaII (Sippl, Proteins 1993;17:355-362) are most sensitive in distinguishing between homology models with correct or incorrect folds. For homology models that have the correct fold, the steric conformational energy (including primarily the Van der Waals energy), MolProbity clashscore (Word et al., Protein Sci 2000;9:2251-2259), and the PROCHECK G-factors (Laskowski et al., J Biomol NMR 1996;8:477-486) provide sensitive and consistent methods for assessing accuracy and can distinguish between homology models of higher and lower accuracy. As demonstrated in the accompanying paper (Bhattacharya et al., accompanying paper), combinations of these scores for models generated with HOMA provide a basis for distinguishing low from high accuracy models.     

The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling

MOTIVATION: Homology models of proteins are of great interest for planning and analysing biological experiments when no experimental three-dimensional structures are available. Building homology models requires specialized programs and up-to-date sequence and structural databases. Integrating all required tools, programs and databases into a single web-based workspace facilitates access to homology modelling from a computer with web connection without the need of downloading and installing large program packages and databases. RESULTS: SWISS-MODEL workspace is a web-based integrated service dedicated to protein structure homology modelling. It assists and guides the user in building protein homology models at different levels of complexity. A personal working environment is provided for each user where several modelling projects can be carried out in parallel. Protein sequence and structure databases necessary for modelling are accessible from the workspace and are updated in regular intervals. Tools for template selection, model building and structure quality evaluation can be invoked from within the workspace. Workflow and usage of the workspace are illustrated by modelling human Cyclin A1 and human Transmembrane Protease 3. AVAILABILITY: The SWISS-MODEL workspace can be accessed freely at http://swissmodel.expasy.org/workspace/     

MollDE: a homology modeling framework you can click with

SUMMARY: Molecular Integrated Development Environment (MolIDE) is an integrated application designed to provide homology modeling tools and protocols under a uniform, user-friendly graphical interface. Its main purpose is to combine the most frequent modeling steps in a semi-automatic, interactive way, guiding the user from the target protein sequence to the final three-dimensional protein structure. The typical basic homology modeling process is composed of building sequence profiles of the target sequence family, secondary structure prediction, sequence alignment with PDB structures, assisted alignment editing, side-chain prediction and loop building. All of these steps are available through a graphical user interface. MolIDE's user-friendly and streamlined interactive modeling protocol allows the user to focus on the important modeling questions, hiding from the user the raw data generation and conversion steps. MolIDE was designed from the ground up as an open-source, cross-platform, extensible framework. This allows developers to integrate additional third-party programs to MolIDE. AVAILABILITY: http://dunbrack.fccc.edu/molide/molide.php CONTACT: rl_dunbrack@fccc.edu.     

Concordance analysis of microbial genomes.

The set of proteins which are conserved across families of microbes contain important targets of new anti-microbial agents. We have developed a simple and efficient computational tool which determines concordances of putative gene products that show sets of proteins conserved across one set of user specified genomes and not present in another set of user specified genomes. The thresholds and the homology scoring criterion are selectable to allow the user to decide the stringency of the homologies. The system uses a relational database to store protein coding regions from different genomes, and to store the results of a complete comparison of all sequences against all sequences using the FASTA program. Using Web technology, the display of all the related proteins for a given sequence and calculation of multiple sequence alignments (using CLUSTALW) can be performed with the click of a button. The current database holds 97 365 sequences from 19 complete or partial genomes and 8798905 FASTA comparison results. A example concordance is presented which demonstrates that the target of the quinolone antibiotics could have been identified using this tool.     

De novo identification of binding sequences for antibody replacement molecules

A new in silico method has been developed that automatically identifies peptide sequences that can bind to targets of known three‐dimensional structure. The method is potentially faster and more economical than traditional methods of raising antibodies by means of hybridomas or biopanning technology. The current algorithm creates an initial peptide library that is either completely random or that is constrained by the user. This library represents only a small fraction of possible sequence space and the peptides are created with a specified torsional geometry. The library is used as input to any number of available molecular docking programs and the library is docked and scored. The final rank ordering is then used to create a new library by constraining that library to the sequence conservation pattern deduced from the top N‐scoring peptides in the first round. Successive rounds of screening, scoring, and new library creation ultimately results in the system converging to a final solution set of peptides. To test the method, a family of novel peptides that can bind to, and inhibit the enzyme Deoxyribonuclease I has been discovered. The peptides inhibit the enzyme either alone or when placed into a protein backbone structure as has been confirmed experimentally. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

ATLAS: A database linking binding affinities with structures for wild‐type and mutant TCR‐pMHC complexes

The ATLAS (Altered TCR Ligand Affinities and Structures) database ( https://zlab.umassmed.edu/atlas/web /) is a manually curated repository containing the binding affinities for wild‐type and mutant T cell receptors (TCRs) and their antigens, peptides presented by the major histocompatibility complex (pMHC). The database links experimentally measured binding affinities with the corresponding three dimensional (3D) structures for TCR‐pMHC complexes. The user can browse and search affinities, structures, and experimental details for TCRs, peptides, and MHCs of interest. We expect this database to facilitate the development of next‐generation protein design algorithms targeting TCR‐pMHC interactions. ATLAS can be easily parsed using modeling software that builds protein structures for training and testing. As an example, we provide structural models for all mutant TCRs in ATLAS, built using the Rosetta program. Utilizing these structures, we report a correlation of 0.63 between experimentally measured changes in binding energies and our predicted changes. Proteins 2017; 85:908–916. © 2016 Wiley Periodicals, Inc.     

Rule of antibody structure. Primary structure of a human monoclonal IgAl-immunoglobulin (myeloma protein Tro). VI. Amino acid sequence of the L-chain, lambda-type, subgroup II]

The primary structure of the L-chain of an IgA1-immunoglobulin (Myeloma protein Tro) has been determined by means of cleavage with trypsin and, if necessary, with alpha-chymotrypsin. The tryptic peptides of the variable part were characterized by amino acid analysis, Dansyl-Edman degradation and cleavage with carboxypeptidase; the peptides of the constant part were identified by amino acid analyses and determination of its N- and C-terminal residues. The sequence of the remaining amino acids and the arrangement of the peptides were established in homology to known structures. The protein comprises 216 amino acids. The homology of the variable part clearly characterizes it as belonging to subgroup II of lambda-chains. In positions 27a, b and c, there are the subgroup-specific additional residues and in position 96 is the characteristic deletion. The constant part of the chain is Kern- and Oz- which indicates that it has serine in position 154 and arginine in position 191.     

The ProDom database of protein domain families.

The ProDom database contains protein domain families generated from the SWISS-PROT database by automated sequence comparisons. It can be searched on the World Wide Web (http://protein.toulouse.inra. fr/prodom.html ) or by E-mail (prodom@toulouse.inra.fr) to study domain arrangements within known families or new proteins. Strong emphasis has been put on the graphical user interface which allows for interactive analysis of protein homology relationships. Recent improvements to the server include: ProDom search by keyword; links to PROSITE and PDB entries; more sensitive ProDom similarity search with BLAST or WU-BLAST; alignments of query sequences with homologous ProDom domain families; and links to the SWISS-MODEL server (http: //www.expasy.ch/swissmod/SWISS-MODEL.html ) for homology based 3-D domain modelling where possible.     

Structures of designed armadillo repeat proteins binding to peptides fused to globular domains

Designed armadillo repeat proteins (dArmRP) are α‐helical solenoid repeat proteins with an extended peptide binding groove that were engineered to develop a generic modular technology for peptide recognition. In this context, the term “peptide” not only denotes a short unstructured chain of amino acids, but also an unstructured region of a protein, as they occur in termini, loops, or linkers between folded domains. Here we report two crystal structures of dArmRPs, in complex with peptides fused either to the N‐terminus of Green Fluorescent Protein or to the C‐terminus of a phage lambda protein D. These structures demonstrate that dArmRPs bind unfolded peptides in the intended conformation also when they constitute unstructured parts of folded proteins, which greatly expands possible applications of the dArmRP technology. Nonetheless, the structures do not fully reflect the binding behavior in solution, that is, some binding sites remain unoccupied in the crystal and even unexpected peptide residues appear to be bound. We show how these differences can be explained by restrictions of the crystal lattice or the composition of the crystallization solution. This illustrates that crystal structures have to be interpreted with caution when protein–peptide interactions are characterized, and should always be correlated with measurements in solution.     

Two protein 4.1 domains essential for mitotic spindle and aster microtubule dynamics and organization in vitro

Multifunctional structural proteins belonging to the 4.1 family are components of nuclei, spindles, and centrosomes in vertebrate cells. Here we report that 4.1 is critical for spindle assembly and the formation of centrosome-nucleated and motor-dependent self-organized microtubule asters in metaphase-arrested Xenopus egg extracts. Immunodepletion of 4.1 disrupted microtubule arrays and mislocalized the spindle pole protein NuMA. Remarkably, assembly was completely rescued by supplementation with a recombinant 4.1R isoform. We identified two 4.1 domains critical for its function in microtubule polymerization and organization utilizing dominant negative peptides. The 4.1 spectrin-actin binding domain or NuMA binding C-terminal domain peptides caused morphologically disorganized structures. Control peptides with low homology or variant spectrin-actin binding domain peptides that were incapable of binding actin had no deleterious effects. Unexpectedly, the addition of C-terminal domain peptides with reduced NuMA binding caused severe microtubule destabilization in extracts, dramatically inhibiting aster and spindle assembly and also depolymerizing preformed structures. However, the mutant C-terminal peptides did not directly inhibit or destabilize microtubule polymerization from pure tubulin in a microtubule pelleting assay. Our data showing that 4.1 is a crucial factor for assembly and maintenance of mitotic spindles and self-organized and centrosome-nucleated microtubule asters indicates that 4.1 is involved in regulating both microtubule dynamics and organization. These investigations underscore an important functional context for protein 4.1 in microtubule morphogenesis and highlight a previously unappreciated role for 4.1 in cell division.     

Antheprot: An interactive graphics software for analyzing protein structures from sequences

ANTHEPROT is a fully interactive program devoted to the analysis of protein structures using a graphics workstation. It presents four options: The first option can predict secondary structures using five methods, and hydrophobicity, solvent accessibility, flexibility and antigenicity profiles using eighteen scales. The user may introduce his own scales. The results displayed on the screen can be easily analyzed. The second option is for representing results concerning up to eight proteins by one method. To compare these proteins, it is possible to align the profiles or the predicted secondary structure according to various motifs. The secondary structure deduced from crystallographic data may also be introduced. The third option is designed to compare the primary structure of two proteins and to visualize on the screen regions that exhibit similarity. Six different comparison matrices may be used, but the user can also introduce his own matrices. The last option is for studying the proteolytic peptides resulting from a chemical or enzymatic digestion of a given protein. It is possible to analyze the protein cleavage using eleven chemical reagents or enzymes. The results are displayed on the screen as RP-HPLC chromatogram.     

The backrub motion: how protein backbone shrugs when a sidechain dances

Surprisingly, the frozen structures from ultra-high-resolution protein crystallography reveal a prevalent, but subtle, mode of local backbone motion coupled to much larger, two-state changes of sidechain conformation. This "backrub" motion provides an influential and common type of local plasticity in protein backbone. Concerted reorientation of two adjacent peptides swings the central sidechain perpendicular to the chain direction, changing accessible sidechain conformations while leaving flanking structure undisturbed. Alternate conformations in sub-1 angstroms crystal structures show backrub motions for two-thirds of the significant Cbeta shifts and 3% of the total residues in these proteins (126/3882), accompanied by two-state changes in sidechain rotamer. The Backrub modeling tool is effective in crystallographic rebuilding. For homology modeling or protein redesign, backrubs can provide realistic, small perturbations to rigid backbones. For large sidechain changes in protein dynamics or for single mutations, backrubs allow backbone accommodation while maintaining H bonds and ideal geometry.     

The peptaibol database: a sequence and structure resource.

The peptaibols are a large family of membrane-active peptides with considerable sequence homology, but with different biological properties and three-dimensional structures. They constitute a rich resource of naturally occurring 'mutants' which are potentially valuable for structure/function studies of ion channels. A searchable on-line database of sequences and structures of the peptaibols has been created at http://www.cryst.bbk.ac.uk/peptaibol, as a resource for the biological and structural community. In this paper, the contents and organization of the website are discussed as well as procedures for submission of new entries to the database. At present, more than 300 peptaibol sequences are stored in the database. Each sequence entry contains its full literature reference and information about its biological source. Tools are provided for searching for specific peptaibol sequences or groupings of sequences, and for locating peptaibols containing specified sequence motifs. In addition the website acts as a database for structural information. The coordinates of all currently available peptaibol x-ray and NMR structures are included and complemented, where appropriate. with molecular graphics illustrations. These include figures of model channel structures and comparisons between different peptaibol structures. The peptaibol database thus provides a tool for ready access to information and a means of investigating the sequences and structures of this class of polypeptides.     

Viral Coat Protein Peptides with Limited Sequence Homology Bind Similar Domains of Alfalfa Mosaic Virus and Tobacco Streak Virus RNAs

An unusual and distinguishing feature of alfalfa mosaic virus (AMV) and ilarviruses such as tobacco streak virus (TSV) is that the viral coat protein is required to activate the early stages of viral RNA replication, a phenomenon known as genome activation. AMV-TSV coat protein homology is limited; however, they are functionally interchangeable in activating virus replication. For example, TSV coat protein will activate AMV RNA replication and vice versa. Although AMV and TSV coat proteins have little obvious amino acid homology, we recently reported that they share an N-terminal RNA binding consensus sequence (Ansel-McKinney et al., EMBO J. 15:5077–5084, 1996). Here, we biochemically compare the binding of chemically synthesized peptides that include the consensus RNA binding sequence and lysine-rich (AMV) or arginine-rich (TSV) environment to 3′-terminal TSV and AMV RNA fragments. The arginine-rich TSV coat protein peptide binds viral RNA with lower affinity than the lysine-rich AMV coat protein peptides; however, the ribose moieties protected from hydroxyl radical attack by the two different peptides are localized in the same area of the predicted RNA structures. When included in an infectious inoculum, both AMV and TSV 3′-terminal RNA fragments inhibited AMV RNA replication, while variant RNAs unable to bind coat protein did not affect replication significantly. The data suggest that RNA binding and genome activation functions may reside in the consensus RNA binding sequence that is apparently unique to AMV and ilarvirus coat proteins.     

Proteome-Wide Inference of Src Homology 3 Domain-Binding Peptides

Src homology 3 (SH3) domain is a versatile protein structure module that participates in mediating various protein?Cprotein binding events by specifically recognizing proline-rich region of diverse plasmatic proteins. Reliable and fast inference of SH3-binding partners over the human proteome are fundamentally important for our understanding of the molecular functions and biological implications underlying SH3-mediated signaling network. Herein, we employ an atom-realistic protocol to perform proteome-wide inference of SH3-binding peptides using the information gained from both the primary sequence of affinity-known peptides and the interaction properties deriving from SH3?Cpeptide complex structures. It is revealed that the binding affinity and specificity of peptides to SH3 domain are co-contributed from electrostatic, steric and hydrophobic effects, and the hydrophobicity and electrostatic property at P₂, P₀ and/or P_?3 play an essential role in determining the binding. In addition, SH3 domain exhibits a broad specificity of recognizing its ligands and thus a large number of protein candidates that might be the potential interacting partners of SH3 domain are extracted from the human proteome, from which several samples are suggested to be the highly promising SH3 binders.     

Use of synthetic signal sequences to explore the protein export machinery

The information for correct localization of newly synthesized proteins in both prokaryotes and eukaryotes resides in self-contained, often transportable targeting sequences. Of these, signal sequences specify that a protein should be secreted from a cell or incorporated into the cytoplasmic membrane. A central puzzle is presented by the lack of primary structural homology among signal sequences, although they share common features in their sequences. Synthetic signal peptides have enabled a wide range of studies of how these "zipcodes" for protein secretion are decoded and used to target proteins to the protein machinery that facilitates their translocation across and integration into membranes. We review research on how the information in signal sequences enables their passenger proteins to be correctly and efficiently localized. Synthetic signal peptides have made possible binding and crosslinking studies to explore how selectivity is achieved in recognition by the signal sequence-binding receptors, signal recognition particle, or SRP, which functions in all organisms, and SecA, which functions in prokaryotes and some organelles of prokaryotic origins. While progress has been made, the absence of atomic resolution structures for complexes of signal peptides and their receptors has definitely left many questions to be answered in the future.