FTSite: high accuracy detection of ligand binding sites on unbound protein structures

MOTIVATION: Binding site identification is a classical problem that is important for a range of applications, including the structure-based prediction of function, the elucidation of functional relationships among proteins, protein engineering and drug design. We describe an accurate method of binding site identification, namely FTSite. This method is based on experimental evidence that ligand binding sites also bind small organic molecules of various shapes and polarity. The FTSite algorithm does not rely on any evolutionary or statistical information, but achieves near experimental accuracy: it is capable of identifying the binding sites in over 94% of apo proteins from established test sets that have been used to evaluate many other binding site prediction methods. AVAILABILITY: FTSite is freely available as a web-based server at http://ftsite.bu.edu.     

The FSSP database of structurally aligned protein fold families.

FSSP (families of structurally similar proteins) is a database of structural alignments of proteins in the Protein Data Bank (PDB). The database currently contains an extended structural family for each of 330 representative protein chains. Each data set contains structural alignments of one search structure with all other structurally significantly similar proteins in the representative set (remote homologs, < 30% sequence identity), as well as all structures in the Protein Data Bank with 70-30% sequence identity relative to the search structure (medium homologs). Very close homologs (above 70% sequence identity) are excluded as they rarely have marked structural differences. The alignments of remote homologs are the result of pairwise all-against-all structural comparisons in the set of 330 representative protein chains. All such comparisons are based purely on the 3D co-ordinates of the proteins and are derived by automatic (objective) structure comparison programs. The significance of structural similarity is estimated based on statistical criteria. The FSSP database is available electronically from the EMBL file server and by anonymous ftp (file transfer protocol).     

GTOP: a database of protein structures predicted from genome sequences

Large-scale genome projects generate an unprecedented number of protein sequences, most of them are experimentally uncharacterized. Predicting the 3D structures of sequences provides important clues as to their functions. We constructed the Genomes TO Protein structures and functions (GTOP) database, containing protein fold predictions of a huge number of sequences. Predictions are mainly carried out with the homology search program PSI-BLAST, currently the most popular among high-sensitivity profile search methods. GTOP also includes the results of other analyses, e.g. homology and motif search, detection of transmembrane helices and repetitive sequences. We have completed analyzing the sequences of 41 organisms, with the number of proteins exceeding 120 000 in total. GTOP uses a graphical viewer to present the analytical results of each ORF in one page in a ‘color-bar’ format. The assigned 3D structures are presented by Chime plug-in or RasMol. The binding sites of ligands are also included, providing functional information. The GTOP server is available at http://spock.genes.nig.ac.jp/~genome/gtop.html.     

ProtBuD: a database of biological unit structures of protein families and superfamilies

MOTIVATION: Modeling of protein interactions is often possible from known structures of related complexes. It is often time-consuming to find the most appropriate template. Hypothesized biological units (BUs) often differ from the asymmetric units and it is usually preferable to model from the BUs. RESULTS: ProtBuD is a database of BUs for all structures in the Protein Data Bank (PDB). We use both the PDBs BUs and those from the Protein Quaternary Server. ProtBuD is searchable by PDB entry, the Structural Classification of Proteins (SCOP) designation or pairs of SCOP designations. The database provides the asymmetric and BU contents of related proteins in the PDB as identified in SCOP and Position-Specific Iterated BLAST (PSI-BLAST). The asymmetric unit is different from PDB and/or Protein Quaternary Server (PQS) BUs for 52% of X-ray structures, and the PDB and PQS BUs disagree on 18% of entries. AVAILABILITY: The database is provided as a standalone program and a web server from http://dunbrack.fccc.edu/ProtBuD.php.     

Integrated displays of aligned amino acid sequences and protein structures

Programs for the Sun-4 workstation permit the combined displayof a table of aligned amino acid sequences of a family of proteins,and a corresponding three-dimensional fold. Interactive facilitiesinclude the ability, to scroll through the sequences, to rotatethe structure and to connect the examination of the sequencesand the structure by selecting a portion of the sequences andautomatically highlighting the corresponding region in the structureand vice versa. These programs are well suited to support applications suchas the investigation of the structural or functional significanceof conserved patterns of amino acids in the sequences of a familyof proteins. Received on July 3, 1990; accepted on January 25, 1991     

ProtBuD: a database of biological unit structures of protein families and superfamilies

Bioinformatics (2006)      

Beyond structural genomics: computational approaches for the identification of ligand binding sites in protein structures

Structural genomics projects have revealed structures for a large number of proteins of unknown function. Understanding the interactions between these proteins and their ligands would provide an initial step in their functional characterization. Binding site identification methods are a fast and cost-effective way to facilitate the characterization of functionally important protein regions. In this review we describe our recently developed methods for binding site identification in the context of existing methods. The advantage of energy-based approaches is emphasized, since they provide flexibility in the identification and characterization of different types of binding sites.     

Phosphate binding sites identification in protein structures

Nearly half of known protein structures interact with phosphate-containing ligands, such as nucleotides and other cofactors. Many methods have been developed for the identification of metal ions-binding sites and some for bigger ligands such as carbohydrates, but none is yet available for the prediction of phosphate-binding sites. Here we describe Pfinder, a method that predicts binding sites for phosphate groups, both in the form of ions or as parts of other non-peptide ligands, in proteins of known structure. Pfinder uses the Query3D local structural comparison algorithm to scan a protein structure for the presence of a number of structural motifs identified for their ability to bind the phosphate chemical group. Pfinder has been tested on a data set of 52 proteins for which both the apo and holo forms were available. We obtained at least one correct prediction in 63% of the holo structures and in 62% of the apo. The ability of Pfinder to recognize a phosphate-binding site in unbound protein structures makes it an ideal tool for functional annotation and for complementing docking and drug design methods. The Pfinder program is available at http://pdbfun.uniroma2.it/pfinder.     

NCIR: a database of non-canonical interactions in known RNA structures

The secondary and tertiary structure of an RNA molecule typically includes a number of non-canonical base–base interactions. The known occurrences of these interactions are tabulated in the NCIR database, which can be accessed from http://prion.bchs.uh.edu/bp_type/. The number of examples is now over 1400, which is an increase of >700% since the database was first published. This dramatic increase reflects the addition of data from the recently published crystal structures of the 50S (2.4 Å) and 30S (3.0 Å) ribosomal subunits. In addition, non-canonical interactions observed in published crystal and NMR structures of tRNAs, group I introns, ribozymes, RNA aptamers and synthetic oligonucleotides are included. Properties associated with these interactions, such as sequence context, sugar pucker conformation, glycosidic angle conformation, melting temperature, chemical shift and free energy, are also reported when available. Out of the 29 anticipated pairs with at least two hydrogen bonds, 28 have been observed to date. In addition, several novel examples, not generally predicted, have also been encountered, bringing the total of such pairs to 36. Added to this list are a variety of single, bifurcated, triple and quadruple interactions. The most common non-canonical pairs are the sheared GA, GA imino, AU reverse Hoogsteen, and the GU and AC wobble pairs. The most frequent triple interaction connects N3 of an A with the amino of a G that is also involved in a standard Watson–Crick pair.     

Ranking and compacting binding segments of protein families using aligned pattern clusters

Background

Discovering sequence patterns with variation can unveil functions of a protein family that are important for drug discovery. Exploring protein families using existing methods such as multiple sequence alignment is computationally expensive, thus pattern search, called motif finding in Bioinformatics, is used. However, at present, combinatorial algorithms result in large sets of solutions, and probabilistic models require a richer representation of the amino acid associations. To overcome these shortcomings, we present a method for ranking and compacting these solutions in a new representation referred to as Aligned Pattern Clusters (APCs). To tackle the problem of a large solution set, our method reveals a reduced set of candidate solutions without losing any information. To address the problem of representation, our method captures the amino acid associations and conservations of the aligned patterns. Our algorithm renders a set of APCs in which a set of patterns is discovered, pruned, aligned, and synthesized from the input sequences of a protein family.

Results

Our algorithm identifies the binding or other functional segments and their embedded residues which are important drug targets from the cytochrome c and the ubiquitin protein families taken from Unitprot. The results are independently confirmed by pFam's multiple sequence alignment. For cytochrome c protein the number of resulting patterns with variations are reduced by 76.62% from the number of original patterns without variations. Furthermore, all of the top four candidate APCs correspond to the binding segments with one of each of their conserved amino acid as the binding residue. The discovered proximal APCs agree with pFam and PROSITE results. Surprisingly, the distal binding site discovered by our algorithm is not discovered by pFam nor PROSITE, but confirmed by the three-dimensional cytochrome c structure. When applied to the ubiquitin protein family, our results agree with pFam and reveals six of the seven Lysine binding residues as conserved aligned columns with entropy redundancy measure of 1.0.

Conclusion

The discovery, ranking, reduction, and representation of a set of patterns is important to avert time-consuming and expensive simulations and experimentations during proteomic study and drug discovery.

     

Construction of protein binding sites in scaffold structures

We have developed a strategy for grafting a protein-protein interface based on the known crystal structure of a native ligand and receptor proteins in a complex. The key interaction residues at the ligand protein binding interface are transferred onto a scaffold protein so that the mutated scaffold protein will bind the receptor protein in the same manner as the ligand protein. First, our method identifies key residues and atoms in the ligand protein, which strongly interact with the receptor protein. Second, this method searches the scaffold protein for combinations of candidate residues, among which the distance between any two candidate residues is similar to that between relevant key interaction residues in the ligand protein. These candidate residues are mutated to key interaction residues in the ligand protein respectively. The scaffold protein is superposed onto the ligand protein based upon the coordinates of corresponding atoms, which are assumed to strongly interact with the receptor protein. Complementarity between scaffold and receptor proteins is evaluated. Scaffold proteins with a low superposing rms difference and high complementary score are accepted for further analysis. Then, the relative position of the scaffold protein is adjusted so that the interfaces between the scaffold and receptor proteins have a reasonable packing density. Other mutations are also considered to reduce the desolvation energy or bad steric contacts. Finally, the scaffold protein is cominimized with the receptor protein and evaluated. To test the method, the binding interface of barstar, the inhibitor of barnase, was grafted onto small proteins. Four scaffold proteins with high complementary scores are accepted.     

Multi-domain protein families and domain pairs: comparison with known structures and a random model of domain recombination

There is a limited repertoire of domain families in nature that are duplicated and combined in different ways to form the set of proteins in a genome. Most proteins in both prokaryote and eukaryote genomes consist of two or more domains, and we show that the family size distribution of multi-domain protein families follows a power law like that of individual families. Most domain pairs occur in four to six different domain architectures: in isolation and in combinations with different partners. We showed previously that within the set of all pairwise domain combinations, most small and medium-sized families are observed in combination with one or two other families, while a few large families are very versatile and combine with many different partners. Though this may appear to be a stochastic pattern, in which large families have more combination partners by virtue of their size, we establish here that all the domain families with more than three members in genomes are duplicated more frequently than would be expected by chance considering their number of neighbouring domains. This duplication of domain pairs is statistically significant for between one and three quarters of all families with seven or more members. For the majority of pairwise domain combinations, there is no known three-dimensional structure of the two domains together, and we term these novel combinations. Novel domain combinations are interesting and important targets for structural elucidation, as the geometry and interaction between the domains will help understand the function and evolution of multi-domain proteins. Of particular interest are those combinations that occur in the largest number of multi-domain proteins, and several of these frequent novel combinations contain DNA-binding domains.Abbreviations:SCOP: Structural Classification of Proteins database, PDB: Protein DataBank, HMM: hidden Markov model     

The PSSH database of alignments between protein sequences and tertiary structures

We introduce the PSSH ('Protein Sequence-to-Structure Homologies') database derived from HSSP2, an improved version of the HSSP ('Homology-derived Secondary Structure of Proteins') database [Dodge et al. (1998) Nucleic Acids Res., 26, 313-315]. Whereas each HSSP entry lists all protein sequences related to a given 3D structure, PSSH is the 'inverse', with each entry listing all structures related to a given sequence. In addition, we introduce two other derived databases: HSSPchain, in which each entry lists all sequences related to a given PDB chain, and HSSPalign, in which each entry gives details of one sequence aligned onto one PDB chain. This re-organization makes it easier to navigate from sequence to structure, and to map sequence features onto 3D structures. Currently (September 2002), PSSH provides structural information for over 400 000 protein sequences, covering 48% of SWALL and 61% of SWISS-PROT sequences; HSSPchain provides sequence information for over 25 000 PDB chains, and HSSPalign gives over 14 million sequence-to-structure alignments. The databases can be accessed via SRS 3D, an extension to the SRS system, at http://srs3d.ebi.ac.uk/.     

Analysis of zinc binding sites in protein crystal structures

The geometrical properties of zinc binding sites in a dataset of high quality protein crystal structures deposited in the Protein Data Bank have been examined to identify important differences between zinc sites that are directly involved in catalysis and those that play a structural role. Coordination angles in the zinc primary coordination sphere are compared with ideal values for each coordination geometry, and zinc coordination distances are compared with those in small zinc complexes from the Cambridge Structural Database as a guide of expected trends. We find that distances and angles in the primary coordination sphere are in general close to the expected (or ideal) values. Deviations occur primarily for oxygen coordinating atoms and are found to be mainly due to H-bonding of the oxygen coordinating ligand to protein residues, bidentate binding arrangements, and multi-zinc sites. We find that H-bonding of oxygen containing residues (or water) to zinc bound histidines is almost universal in our dataset and defines the elec-His-Zn motif. Analysis of the stereochemistry shows that carboxyl elec-His-Zn motifs are geometrically rigid, while water elec-His-Zn motifs show the most geometrical variation. As catalytic motifs have a higher proportion of carboxyl elec atoms than structural motifs, they provide a more rigid framework for zinc binding. This is understood biologically, as a small distortion in the zinc position in an enzyme can have serious consequences on the enzymatic reaction. We also analyze the sequence pattern of the zinc ligands and residues that provide elecs, and identify conserved hydrophobic residues in the endopeptidases that also appear to contribute to stabilizing the catalytic zinc site. A zinc binding template in protein crystal structures is derived from these observations.     

ProML--the protein markup language for specification of protein sequences,structures and families

We propose a specification language ProML for protein sequences, structures, and families based on the open XML standard. The language allows for portable, system-independent, machine-parsable and human-readable representation of essential features of proteins. The language is of immediate use for several bioinformatics applications: we discuss clustering of proteins into families and the representation of the specific shared features of the respective clusters. Moreover, we use ProML for specification of data used in fold recognition bench-marks exploiting experimentally derived distance constraints.     

MIPS: a database for genomes and protein sequences

The Munich Information Center for Protein Sequences (MIPS-GSF), Martinsried, near Munich, Germany, continues its longstanding tradition to develop and maintain high quality curated genome databases. In addition, efforts have been intensified to cover the wealth of complete genome sequences in a systematic, comprehensive form. Bioinformatics, supporting national as well as European sequencing and functional analysis projects, has resulted in several up-to-date genome-oriented databases. This report describes growing databases reflecting the progress of sequencing the Arabidopsis thaliana (MATDB) and Neurospora crassa genomes (MNCDB), the yeast genome database (MYGD) extended by functional analysis data, the database of annotated human EST-clusters (HIB) and the database of the complete cDNA sequences from the DHGP (German Human Genome Project). It also contains information on the up-to-date database of complete genomes (PEDANT), the classification of protein sequences (ProtFam) and the collection of protein sequence data within the framework of the PIR-International Protein Sequence Database. These databases can be accessed through the MIPS WWW server (http://www. mips.biochem.mpg.de).