EPI-peptide designer: a tool for designing peptide ligand libraries based on epitope-paratope interactions.

MOTIVATION: Antibodies are an important class of biological drugs, but with limitations, such as inadequate pharmacokinetics, adverse immunogenicity and high production costs. Synthetic peptides for the desired target represent an important alternative to antibodies. However, no computational tool exists to guide the design of these peptides. RESULTS: To identify the interacting residues in a given antibody-antigen (Ab-Ag) interface we used Interface Interacting Residue (I2R), a selection method based on computed molecular interactions. The aggregation of all the molecular interactions between epitope and paratope residues allowed us to transform the 3D Ab-Ag complex structures into interface graphs. Based on these data and the probability of molecular interaction we developed EPI-Peptide Designer tool that uses predicted paratope residues for an epitope of interest to generate targeted peptide ligand libraries. EPI-Peptide Designer successfully predicted 301 peptides able to bind to LiD1 target protein (65% of the experimentally tested peptides), an enrichment of 22% compared to randomly generated peptides. This tool should enable the development of a new generation of synthetic interacting peptides that could be very useful in the biosensor, diagnostic and therapeutic fields. AVAILABILITY AND IMPLEMENTATION: All software developed in this work are available at http://www.biocomp.icb.ufmg.br/biocomp/ CONTACT: liza@icb.ufmg.br SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Proteinase inhibition using small Bowman-Birk-type structures.

Bowman-Birk inhibitors (BBIs) are cysteine-rich and highly cross-linked small proteins that function as specific pseudosubstrates for digestive proteinases. They typically display a "double-headed" structure containing an independent proteinase-binding loop that can bind and inhibit trypsin, chymotrypsin and elastase. In the present study, we used computational biology to study the structural characteristics and dynamics of the inhibition mechanism of the small BBI loop expressing a 35-amino acid polypeptide (ChyTB2 inhibitor) which has coding region for the mutated chymotrypsin-inhibitory site of the soybean BBI. We found that in the BBI-trypsin inhibition complex, the most important interactions are salt bridges and hydrogen bonds, whereas in the BBI-chymotrypsin inhibition complex, the most important interactions are hydrophobic. At the same time, ChyTB2 mutant structure maintained the individual functional domain structure and excellent binding/inhibiting capacities for trypsin and chymotrypsin at the same time. These results were confirmed by enzyme-linked immunosorbend assay experiments. The results showed that modeling combined with molecular dynamics is an efficient method to describe, predict and then obtain new proteinase inhibitors. For such study, however, it is necessary to start from the sequence and structure of the mutant interacting relatively strongly with both trypsin and chymotrypsin for designing the small BBI-type inhibitor against proteinases.

Sting_RDB: a relational database of structural parameters for protein analysis with support for data warehousing and data mining.

An effective strategy for managing protein databases is to provide mechanisms to transform raw data into consistent, accurate and reliable information. Such mechanisms will greatly reduce operational inefficiencies and improve one's ability to better handle scientific objectives and interpret the research results. To achieve this challenging goal for the STING project, we introduce Sting_RDB, a relational database of structural parameters for protein analysis with support for data warehousing and data mining. In this article, we highlight the main features of Sting_RDB and show how a user can explore it for efficient and biologically relevant queries. Considering its importance for molecular biologists, effort has been made to advance Sting_RDB toward data quality assessment. To the best of our knowledge, Sting_RDB is one of the most comprehensive data repositories for protein analysis, now also capable of providing its users with a data quality indicator. This paper differs from our previous study in many aspects. First, we introduce Sting_RDB, a relational database with mechanisms for efficient and relevant queries using SQL. Sting_rdb evolved from the earlier, text (flat file)-based database, in which data consistency and integrity was not guaranteed. Second, we provide support for data warehousing and mining. Third, the data quality indicator was introduced. Finally and probably most importantly, complex queries that could not be posed on a text-based database, are now easily implemented. Further details are accessible at the Sting_RDB demo web page: http://www.cbi.cnptia.embrapa.br/StingRDB.

Electrostatic potential calculation for biomolecules--creating a database of pre-calculated values reported on a per residue basis for all PDB protein structures.

STING and Java Protein Dossier provide a collection of physical-chemical parameters, describing protein structure, stability, function, and interaction, considered one of the most comprehensive among the available protein databases of similar type. Particular attention in STING is paid to the electrostatic potential. It makes use of DelPhi, a well-known tool that calculates this physical-chemical quantity for biomolecules by solving the Poisson Boltzmann equation. In this paper, we describe a modification to the DelPhi program aimed at integrating it within the STING environment. We also outline how the "amino acid electrostatic potential" and the "surface amino acid electrostatic potential" are calculated (over all Protein Data Bank (PDB) content) and how the corresponding values are made searchable in STING_DB. In addition, we show that the STING and Java Protein Dossier are also capable of providing these particular parameter values for the analysis of protein structures modeled in computers or being experimentally solved, but not yet deposited in the PDB. Furthermore, we compare the calculated electrostatic potential values obtained by using the earlier version of DelPhi and those by STING, for the biologically relevant case of lysozyme-antibody interaction. Finally, we describe the STING capacity to make queries (at both residue and atomic levels) across the whole PDB, by looking at a specific case where the electrostatic potential parameter plays a crucial role in terms of a particular protein function, such as ligand binding. BlueStar STING is available at http://www.cbi.cnptia.embrapa.br.

Finding protein-protein interaction patterns by contact map matching.

We propose a novel method for defining patterns of contacts present in protein-protein complexes. A new use of the traditional contact maps (more frequently used for representation of the intra-chain contacts) is presented for analysis of inter-chain contacts. Using an algorithm based on image processing techniques, we can compare protein-protein interaction maps and also obtain a dissimilarity score between them. The same algorithm used to compare the maps can align the contacts of all the complexes and be helpful in the determination of a pattern of conserved interactions at the interfaces. We present an example for the application of this method by analyzing the pattern of interaction of bovine pancreatic trypsin inhibitors and trypsins, chymotrypsins, a thrombin, a matriptase, and a kallikrein - all classified as serine proteases. We found 20 contacts conserved in trypsins and chymotrypsins and 3 specific ones are present in all the serine protease complexes studied. The method was able to identify important contacts for the protein family studied and the results are in agreement with the literature.

Finding protein-protein interaction patterns by contact map matching

We propose a novel method for defining patterns of contacts present in protein-protein complexes. A new use of the traditional contact maps (more frequently used for representation of the intra-chain contacts) is presented for analysis of inter-chain contacts. Using an algorithm based on image processing techniques, we can compare protein-protein interaction maps and also obtain a dissimilarity score between them. The same algorithm used to compare the maps can align the contacts of all the complexes and be helpful in the determination of a pattern of conserved interactions at the interfaces. We present an example for the application of this method by analyzing the pattern of interaction of bovine pancreatic trypsin inhibitors and trypsins, chymotrypsins, a thrombin, a matriptase, and a kallikrein - all classified as serine proteases. We found 20 contacts conserved in trypsins and chymotrypsins and 3 specific ones are present in all the serine protease complexes studied. The method was able to identify important contacts for the protein family studied and the results are in agreement with the literature.

Electrostatic potential calculation for biomolecules - creating a database of pre-calculated values reported on a per residue basis for all PDB protein structures

STING and JavaProtein Dossier provide a collection of physical-chemical parameters, describing protein structure, stability, function, and interaction, considered one of the most comprehensive among the available protein databases of similar type. Particular attention in STING is paid to the electrostatic potential. It makes use of DelPhi, a well-known tool that calculates this physical-chemical quantity for biomolecules by solving the Poisson Boltzmann equation. In this paper, we describe a modification to the DelPhi program aimed at integrating it within the STING environment. We also outline how the "amino acid electrostatic potential" and the "surface amino acid electrostatic potential" are calculated (over all Protein Data Bank (PDB) content) and how the corresponding values are made searchable in STING_DB. In addition, we show that the STING and JavaProtein Dossier are also capable of providing these particular parameter values for the analysis of protein structures modeled in computers or being experimentally solved, but not yet deposited in the PDB. Furthermore, we compare the calculated electrostatic potential values obtained by using the earlier version of DelPhi and those by STING, for the biologically relevant case of lysozyme-antibody interaction. Finally, we describe the STING capacity to make queries (at both residue and atomic levels) across the whole PDB, by looking at a specific case where the electrostatic potential parameter plays a crucial role in terms of a particular protein function, such as ligand binding. BlueStar STING is available at http://www.cbi.cnptia.embrapa.br.

Sting_RDB: a relational database of structural parameters for protein analysis with support for data warehousing and data mining

An effective strategy for managing protein databases is to provide mechanisms to transform raw data into consistent, accurate and reliable information. Such mechanisms will greatly reduce operational inefficiencies and improve one’s ability to better handle scientific objectives and interpret the research results. To achieve this challenging goal for the STING project, we introduce Sting_RDB, a relational database of structural parameters for protein analysis with support for data warehousing and data mining. In this article, we highlight the main features of Sting_RDB and show how a user can explore it for efficient and biologically relevant queries. Considering its importance for molecular biologists, effort has been made to advance Sting_RDB toward data quality assessment. To the best of our knowledge, Sting_RDB is one of the most comprehensive data repositories for protein analysis, now also capable of providing its users with a data quality indicator. This paper differs from our previous study in many aspects. First, we introduce Sting_RDB, a relational database with mechanisms for efficient and relevant queries using SQL. Sting_rdb evolved from the earlier, text (flat file)-based database, in which data consistency and integrity was not guaranteed. Second, we provide support for data warehousing and mining. Third, the data quality indicator was introduced. Finally and probably most importantly, complex queries that could not be posed on a text-based database, are now easily implemented. Further details are accessible at the Sting_RDB demo web page: http://www.cbi.cnptia.embrapa.br/StingRDB.

Proteinase inhibition using small Bowman-Birk-type structures

Bowman-Birk inhibitors (BBIs) are cysteine-rich and highly cross-linked small proteins that function as specific pseudosubstrates for digestive proteinases. They typically display a "double-headed" structure containing an independent proteinase-binding loop that can bind and inhibit trypsin, chymotrypsin and elastase. In the present study, we used computational biology to study the structural characteristics and dynamics of the inhibition mechanism of the small BBI loop expressing a 35-amino acid polypeptide (ChyTB2 inhibitor) which has coding region for the mutated chymotrypsin-inhibitory site of the soybean BBI. We found that in the BBI-trypsin inhibition complex, the most important interactions are salt bridges and hydrogen bonds, whereas in the BBI-chymotrypsin inhibition complex, the most important interactions are hydrophobic. At the same time, ChyTB2 mutant structure maintained the individual functional domain structure and excellent binding/inhibiting capacities for trypsin and chymotrypsin at the same time. These results were confirmed by enzyme-linked immunosorbend assay experiments. The results showed that modeling combined with molecular dynamics is an efficient method to describe, predict and then obtain new proteinase inhibitors. For such study, however, it is necessary to start from the sequence and structure of the mutant interacting relatively strongly with both trypsin and chymotrypsin for designing the small BBI-type inhibitor against proteinases.

The Star STING server: a multiplatform environment for protein structure analysis.

Star STING is the latest version of the STING suite of programs and corresponding database. We report on five important aspects of this package that have acquired some new characteristics, designed to add key advantages to the whole suite: 1) availability for most popular platforms and browsers, 2) introduction of the STING_DB quality assessment, 3) improvement in algorithms for calculation of three STING parameters, 4) introduction of five new STING modules, and 5) expansion of the existing modules. Star STING is freely accessible at: http://sms.cbi.cnptia.embrapa.br/SMS/, http://trantor.bioc.columbia.edu/SMS, http://www.es.embnet.org/SMS/, http://gibk26.bse.kyutech.ac.jp/SMS/ and http://www.ar.embnet.org/SMS.

Predicting enzyme class from protein structure using Bayesian classification

Predicting enzyme class from protein structure parameters is a challenging problem in protein analysis. We developed a method to predict enzyme class that combines the strengths of statistical and data-mining methods. This method has a strong mathematical foundation and is simple to implement, achieving an accuracy of 45%. A comparison with the methods found in the literature designed to predict enzyme class showed that our method outperforms the existing methods.

Building multiple sequence alignments with a flavor of HSSP alignments

Homology-derived secondary structure of proteins (HSSP) is a well-known database of multiple sequence alignments (MSAs) which merges information of protein sequences and their three-dimensional structures. It is available for all proteins whose structure is deposited in the PDB. It is also used by STING and (Java)Protein Dossier to calculate and present relative entropy as a measure of the degree of conservation for each residue of proteins whose structure has been solved and deposited in the PDB. However, if the STING and (Java)Protein Dossier are to provide support for analysis of protein structures modeled in computers or being experimentally solved but not yet deposited in the PDB, then we need a new method for building alignments having a flavor of HSSP alignments (myMSAr). The present study describes a new method and its corresponding databank (SH2QS--database of sequences homologue to the query [structure-having] sequence). Our main interest in making myMSAr was to measure the degree of residue conservation for a given query sequence, regardless of whether it has a corresponding structure deposited in the PDB. In this study, we compare the measurement of residue conservation provided by corresponding alignments produced by HSSP and SH2QS. As a case study, we also present two biologically relevant examples, the first one highlighting the equivalence of analysis of the degree of residue conservation by using HSSP or SH2QS alignments, and the second one presenting the degree of residue conservation for a structure modeled in a computer, which , as a consequence, does not have an alignment reported by HSSP.

PDB-Metrics: a web tool for exploring the PDB contents

PDB-Metrics (http://sms.cbi.cnptia.embrapa.br/SMS/pdb_metrics/index.html) is a component of the Diamond STING suite of programs for the analysis of protein sequence, structure and function. It summarizes the characteristics of the collection of protein structure descriptions deposited in the Protein Data Bank (PDB) and provides a Web interface to search and browse the PDB, using a variety of alternative criteria. PDB-Metrics is a powerful tool for bioinformaticians to examine the data span in the PDB from several perspectives. Although other Web sites offer some similar resources to explore the PDB contents, PDB-Metrics is among those with the most complete set of such facilities, integrated into a single Web site. This program has been developed using SQLite, a C library that provides all the query facilities of a database management system

The Star STING server: a multiplatform environment for protein structure analysis

Star STING is the latest version of the STING suite of programs and corresponding database. We report on five important aspects of this package that have acquired some new characteristics, designed to add key advantages to the whole suite: 1) availability for most popular platforms and browsers, 2) introduction of the STING_DB quality assessment, 3) improvement in algorithms for calculation of three STING parameters, 4) introduction of five new STING modules, and 5) expansion of the existing modules. Star STING is freely accessible at: http://sms.cbi.cnptia.embrapa.br/SMS/, http://trantor.bioc.columbia.edu/SMS, http://www.es.embnet.org/SMS/, http://gibk26.bse.kyutech.ac.jp/SMS/ and http://www.ar.embnet.org/SMS.

STING Contacts: a web-based application for identification and analysis of amino acid contacts within protein structure and across protein interfaces.

UNLABELLED: Amino acid contacts in terms of atomic interactions are essential factors to be considered in the analysis of the structure of a protein and its complexes. Consequently, molecular biologists do require specific tools for the identification and visualization of all such contacts. Graphical contacts (GC) and interface forming residue graphical contacts (IFRgc) presented here, calculate atomic contacts among amino acids based on a table of predefined pairs of the atom types and their distances, and then display them using number of different forms. The inventory of currently listed contact types by GC and IFRgc include hydrogen bonds (in nine different flavors), hydrophobic interactions, charge-charge interactions, aromatic stacking and disulfide bonds. Such extensive catalog of the interactions, representing the forces that govern protein folding, stability and binding, is the key feature of these two applications. GC and IFRgc are part of STING Millennium Suite. AVAILABILITY: http://sms.cbi.cnptia.embrapa.br/SMS, http://trantor.bioc.columbia.edu/SMS, http://mirrors.rcsb.org//SMS, http://www.es.embnet.org/SMS and http://www.ar.embnet.org/SMS (Options: Graphical Contacts and IFR Graphical Contacts).

Defining 3D residue environment in protein structures using SCORPION and FORMIGA.

SUMMARY: Two web-based applications to analyze amino acids three-dimensional (3D) local environment within protein structures-SCORPION and FORMIGA-are presented. SCORPION and FORMIGA produce a graphical presentation for simple statistical data showing the frequency of residue occurrence within a given sphere (defined here as the 3D contacts). The center of that sphere is placed at the Calpha and at the last heavy atom in the side chain of the selected amino acid. Further depth of detail is given in terms of a secondary structure to which the profiled amino acid belongs. Results obtained with those two applications are relevant for estimating the importance of the amino acid 3D local environment for protein folding and stability. Effectively, SCORPION and FORMIGA construct knowledge-based force fields. The difference between SCORPION and FORMIGA is in that the latter operates on protein interfaces, while the former only functions for a single protein chain. Both applications are implemented as stand-alone components of STING Millennium Suite. AVAILABILITY: http://sms.cbi.cnptia.embrapa.br/SMS, http://trantor.bioc.columbia.edu/SMS, http://mirrors.rcsb.org/SMS, http://www.es.embnet.org/SMS and http://www.ar.embnet.org/SMS. [options: Scorpion, Formiga]

ConSSeq: a web-based application for analysis of amino acid conservation based on HSSP database and within context of structure.

SUMMARY: A web-based application to analyze protein amino acids conservation-Consensus Sequence (ConSSeq) is presented. ConSSeq graphically represents information about amino acid conservation based on sequence alignments reported in homology-derived structures of proteins. Beyond the relative entropy for each position in the alignment, ConSSeq also presents the consensus sequence and information about the amino acids, which are predominant at each position of the alignment. ConSSeq is part of the STING Millennium Suite and is implemented as a Java Applet. AVAILABILITY: http://sms.cbi.cnptia.embrapa.br/SMS/STINGm/consseq/, http://trantor.bioc.columbia.edu/SMS/STINGm/consseq/, http://mirrors.rcsb.org//SMS/STINGm/consseq/, http://www.es.embnet.org/SMS/STINGm/consseq/ and http://www.ar.embnet.org/SMS/STINGm/consseq/

Analysis of structural and physico-chemical parameters involved in the specificity of binding between alpha-amylases and their inhibitors.

Enzyme-inhibitor specificity was studied for alpha-amylases and their inhibitors. We purified and cloned the cDNAs of two different alpha-amylase inhibitors from the common bean (Phaseolus vulgaris) and have recently cloned the cDNA of an alpha-amylase of the Mexican bean weevil (Zabrotes subfasciatus), which is inhibited by alpha-amylase inhibitor 2 but not by alpha-amylase inhibitor 1. The crystal structure of AI-1 complexed with pancreatic porcine alpha-amylase allowed us to model the structure of AI-2. The structure of Zabrotes subfasciatus alpha-amylase was modeled based on the crystal structure of Tenebrio molitor alpha-amylase. Pairwise AI-1 and AI-2 with PPA and ZSA complexes were modeled. For these complexes we first identified the interface forming residues. In addition, we identified the hydrogen bonds, ionic interactions and loss of hydrophobic surface area resulting from complex formation. The parameters we studied provide insight into the general scheme of binding, but fall short of explaining the specificity of the inhibition. We also introduce three new tools-software packages STING, HORNET and STINGPaint-which efficiently determine the interface forming residues and the ionic interaction data, the hydrogen bond net as well as aid in interpretation of multiple sequence alignment, respectively.