MOTIVATION: Different resources exist for experimentally determined and computed three-dimensional (3D)-structures of low molecular weight structures but for approved drugs, no free, publicly accessible source of 3D-structures and conformers is available. Furthermore, for selection purposes or for correlation of structural similarity with medical application, the assignment of the Anatomical Therapeutic Chemical (ATC) classification codes to each structure according to the WHO-scheme would be desirable. RESULTS: The database contains approximately 2500 3D-structures of active ingredients of essential marketed drugs. To account for structural flexibility they are represented by 10(5) structural conformers. Here we present a web-query system enabling searches for drug name, synonyms, trade name, trivial name, formula, CAS-number, ATC-code etc. 2D-similarity screening (Tanimoto coefficients) and an automatic 3D-superposition procedure based on conformational representation are implemented. Drug structures above a similarity threshold as well as superimposed conformers can be retrieved in the mol- file format via a graphical interface. AVAILABILITY: For academic use the system is accessible at http://bioinf.charite.de/superdrug. The retrieval system requires the free browser-plugin 'chime' from MDL for visualization.

BACKGROUND: Structural and functional research often requires the computation of sets of protein structures based on certain properties of the proteins, such as sequence features, fold classification, or functional annotation. Compiling such sets using current web resources is tedious because the necessary data are spread over many different databases. To facilitate this task, we have created COLUMBA, an integrated database of annotations of protein structures. DESCRIPTION: COLUMBA currently integrates twelve different databases, including PDB, KEGG, Swiss-Prot, CATH, SCOP, the Gene Ontology, and ENZYME. The database can be searched using either keyword search or data source-specific web forms. Users can thus quickly select and download PDB entries that, for instance, participate in a particular pathway, are classified as containing a certain CATH architecture, are annotated as having a certain molecular function in the Gene Ontology, and whose structures have a resolution under a defined threshold. The results of queries are provided in both machine-readable extensible markup language and human-readable format. The structures themselves can be viewed interactively on the web. CONCLUSION: The COLUMBA database facilitates the creation of protein structure data sets for many structure-based studies. It allows to combine queries on a number of structure-related databases not covered by other projects at present. Thus, information on both many and few protein structures can be used efficiently. The web interface for COLUMBA is available at http://www.columba-db.de.

MOTIVATION: The Dictionary of Interfaces in Proteins (DIP) is a database collecting the 3D structure of interacting parts of proteins that are called patches. It serves as a repository, in which patches similar to given query patches can be found. The computation of the similarity of two patches is time consuming and traversing the entire DIP requires some hours. In this work we address the question of how the patches similar to a given query can be identified by scanning only a small part of DIP. The answer to this question requires the investigation of the distribution of the similarity of patches. RESULTS: The score values describing the similarity of two patches can roughly be divided into three ranges that correspond to different levels of spatial similarity. Interestingly, the two iso-score lines separating the three classes can be determined by two different approaches. Applying a concept of the theory of random graphs reveals significant structural properties of the data in DIP. These can be used to accelerate scanning the DIP for patches similar to a given query. Searches for very similar patches could be accelerated by a factor of more than 25. Patches with a medium similarity could be found 10 times faster than by brute-force search.

SUMMARY: The Structural Alignment Program STRAP is a comfortable comprehensive editor and analyzing tool for protein alignments. A wide range of functions related to protein sequences and protein structures are accessible with an intuitive graphical interface. Recent features include mapping of mutations and polymorphisms onto structures and production of high quality figures for publication. Here we address the general problem of multi-purpose program packages to keep up with the rapid development of bioinformatical methods and the demand for specific program functions. STRAP was remade implementing a novel design which aims at Keeping Interfaces in STRAP Simple (KISS). KISS renders STRAP extendable to bio-scientists as well as to bio-informaticians. Scientists with basic computer skills are capable of implementing statistical methods or embedding existing bioinformatical tools in STRAP themselves. For bio-informaticians STRAP may serve as an environment for rapid prototyping and testing of complex algorithms such as automatic alignment algorithms or phylogenetic methods. Further, STRAP can be applied as an interactive web applet to present data related to a particular protein family and as a teaching tool. REQUIREMENTS: JAVA-1.4 or higher. AVAILABILITY: http://www.charite.de/bioinf/strap/

MOTIVATION: There is no consensus in the literature about how the deepest portions of protein structures are packed. Using an improved Voronoi procedure, we calculate reference packing densities for different regions in the protein interior. Furthermore, we want to clarify where cavities are located. RESULTS: Sets of reference packing densities are provided for regions in proteins that differ in their distance to the surface and to internal cavities, supplementing previous data. Packing in the protein interior is tight but generally inhomogeneous. There are about 4.4 cavities per 100 amino acids in protein structures, they occur in all regions, most frequently in a depth of 2.5-3.6 A underneath the Connolly surface. However, the deepest protein regions have a lower mean packing density than circumjacent regions, because more contacts to cavities occur in the core. AVAILABILITY/SUPPLEMENTARY INFORMATION: Calculation software and detailed packing data are available on request.

BACKGROUND: For many applications one wishes to decide whether a certain set of numbers originates from an equiprobability distribution or whether they are unequally distributed. Distributions of relative frequencies may deviate significantly from the corresponding probability distributions due to finite sample effects. Hence, it is not trivial to discriminate between an equiprobability distribution and non-equally distributed probabilities when knowing only frequencies. RESULTS: Based on analytical results we provide a software tool which allows to decide whether data correspond to an equiprobability distribution. The tool is available at http://bioinf.charite.de/equifreq/. CONCLUSIONS: Its application is demonstrated for the distribution of point mutations in coding genes.

Abstract Motivation: Molecular Surface Patches (MSPs) of proteins are responsible for selective interactions between internal parts of one protein molecule or between protein and other molecules. The prediction of the neighbours of a distinct Secondary Structural Element (SSE) would be an important step for protein structure prediction. Results: Based on a computational analysis of complementary molecular patches of SSEs, feed-forward Neural Networks (NNs) are trained on a large set of helices for predicting the neighbours of given MSPs. Accuracy of prediction is 96% if only two types of neighbours: solvent or ‘protein’ are considered, yet drops to 81% for three types of neighbours: (1) solvent, (2) helix/strand or (3) coil. Implications of the method for the prediction of protein structure and subunit interaction are discussed. As a special test case, the structurally equivalent helices of monomeric myoglobin and the homologous subunits of tetrameric haemoglobin are compared. Availability: Programs are available on request from the authors. Contact: [email protected]; [email protected] * To whom correspondence should be addressed. 2 Present address: EMBL Qutstation EBI, Hinxton, Cambridge CB10 ISD, UK.

Abstract Summary: STRAP is a comfortable and extensible tool for the generation and refinement of multiple alignments of protein sequences. Various sequence ordered input file formats are supported. These are the SwissProt-,GenBank-, EMBL-, DSSP- PDB-, MSF-, and plain ASCII text format. The special feature of STRAP is the simple visualization of spatial distances of \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(C_{{\alpha}}\) \end{document}-atoms within the alignment. Thus structural information can easily be incorporated into the sequence alignment and can guide the alignment process in cases of low sequence similarities. Further STRAP is able to manage huge alignments comprising a lot of sequences. The protein viewers and modeling programs INSIGHT, RASMOL and WEBMOL are embedded into STRAP. STRAP is written in Java. The well-documented source code can be adapted easily to special requirements. STRAP may become the basis for complex alignment tools in the future. Availability: The tool is available to academic institutions at http://www.charite.de/bioinf. The source code can be requested via e-mail. Contact: [email protected] * To whom correspondence should be addressed.

MOTIVATION: Should reports on molecular mimicry in particular cases, e.g. responsible for cross-reactivity, be considered as accidental or as a general principle in protein evolution? To answer this question, two types of similarity have to be considered: those in homologues (synonyms) and resemblance between patches from unrelated proteins (homonyms). RESULTS: All interfaces from known protein structures were collected in a comprehensive data bank [Dictionary of Interfaces in Proteins (DIP)]. A fast, sequence-independent, three-dimensional superposition procedure was developed to search automatically for geometrically similar surface areas. Surprisingly, we found a large number of structurally similar interfaces on the surface of unrelated proteins. Even patches from different types of secondary structure were found resembling each other. The putative functional meaning of homonyms is demonstrated with striking examples.