ProteinsPlus: a comprehensive collection of web-based molecular modeling tools.

Upon the ever-increasing number of publicly available experimentally determined and predicted protein and nucleic acid structures, the demand for easy-to-use tools to investigate these structural models is higher than ever before. The ProteinsPlus web server (https://proteins.plus) comprises a growing collection of molecular modeling tools focusing on protein-ligand interactions. It enables quick access to structural investigations ranging from structure analytics and search methods to molecular docking. It is by now well-established in the community and constantly extended. The server gives easy access not only to experts but also to students and occasional users from the field of life sciences. Here, we describe its recently added new features and tools, beyond them a novel method for on-the-fly molecular docking and a search method for single-residue substitutions in local regions of a protein structure throughout the whole Protein Data Bank. Finally, we provide a glimpse into new avenues for the annotation of AlphaFold structures which are directly accessible via a RESTful service on the ProteinsPlus web server.

GeoMine: interactive pattern mining of protein-ligand interfaces in the Protein Data Bank.

SUMMARY: The searching of user-defined 3D queries in molecular interfaces is a computationally challenging problem that is not satisfactorily solved so far. Most of the few existing tools focused on that purpose are desktop based and not openly available. Besides that, they show a lack of query versatility, search efficiency and user-friendliness. We address this issue with GeoMine, a publicly available web application that provides textual, numerical and geometrical search functionality for protein-ligand binding sites derived from structural data contained in the Protein Data Bank (PDB). The query generation is supported by a 3D representation of a start structure that provides interactively selectable elements like atoms, bonds and interactions. GeoMine gives full control over geometric variability in the query while performing a deterministic, precise search. Reasonably selective queries are processed on the entire set of protein-ligand complexes in the PDB within a few minutes. GeoMine offers an interactive and iterative search process of successive result analyses and query adaptations. From the numerous potential applications, we picked two from the field of side-effect analyze showcasing the usefulness of GeoMine. AVAILABILITY AND IMPLEMENTATION: GeoMine is part of the ProteinsPlus web application suite and freely available at https://proteins.plus. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

ProteinsPlus: interactive analysis of protein-ligand binding interfaces.

Due to the increasing amount of publicly available protein structures searching, enriching and investigating these data still poses a challenging task. The ProteinsPlus web service (https://proteins.plus) offers a broad range of tools addressing these challenges. The web interface to the tool collection focusing on protein-ligand interactions has been geared towards easy and intuitive access to a large variety of functionality for life scientists. Since our last publication, the ProteinsPlus web service has been extended by additional services as well as it has undergone substantial infrastructural improvements. A keyword search functionality was added on the start page of ProteinsPlus enabling users to work on structures without knowing their PDB code. The tool collection has been augmented by three tools: StructureProfiler validates ligands and active sites using selection criteria of well-established protein-ligand benchmark data sets, WarPP places water molecules in the ligand binding sites of a protein, and METALizer calculates, predicts and scores coordination geometries of metal ions based on surrounding complex atoms. Additionally, all tools provided by ProteinsPlus are available through a REST service enabling the automated integration in structure processing and modeling pipelines.

From structure diagrams to visual chemical patterns.

The intuitive way of chemists to communicate molecules is via two-dimensional structure diagrams. The straightforward visual representations are mostly preferred to the often complicated systematic chemical names. For chemical patterns, however, no comparable visualization standards have evolved so far. Chemical patterns denoting descriptions of chemical features are needed whenever a set of molecules is filtered for certain properties. The currently available representations are constrained to linear molecular pattern languages which are hardly human readable and therefore keep chemists without computational background from systematically formulating patterns. Therefore, we introduce a new visualization concept for chemical patterns. The common standard concept of structure diagrams is extended to account for property descriptions and logic combinations of chemical features in patterns. As a first application of the new concept, we developed the SMARTSviewer, a tool that converts chemical patterns encoded in SMARTS strings to a visual representation. The graphic pattern depiction provides an overview of the specified chemical features, variations, and similarities without needing to decode the often cryptic linear expressions. Taking recent chemical publications from various fields, we demonstrate the wide application range of a graphical chemical pattern language.

Mitochondrial Genome of Fagus sylvatica L. as a Source for Taxonomic Marker Development in the Fagales.

European beech, Fagus sylvatica L., is one of the most important and widespread deciduous tree species in Central Europe and is widely managed for its hard wood. The complete DNA sequence of the mitochondrial genome of Fagus sylvatica L. was assembled and annotated based on Illumina MiSeq reads and validated using long reads from nanopore MinION sequencing. The genome assembled into a single DNA sequence of 504,715 bp in length containing 58 genes with predicted function, including 35 protein-coding, 20 tRNA and three rRNA genes. Additionally, 23 putative protein-coding genes were predicted supported by RNA-Seq data. Aiming at the development of taxon-specific mitochondrial genetic markers, the tool SNPtax was developed and applied to select genic SNPs potentially specific for different taxa within the Fagales. Further validation of a small SNP set resulted in the development of four CAPS markers specific for Fagus, Fagaceae, or Fagales, respectively, when considering over 100 individuals from a total of 69 species of deciduous trees and conifers from up to 15 families included in the marker validation. The CAPS marker set is suitable to identify the genus Fagus in DNA samples from tree tissues or wood products, including wood composite products.

The complete chloroplast genome sequence of Pinus cembra L. (Pinaceae).

The Swiss pine (Pinus cembra) is a montane tree in Central Europe and, therefore, known for its hardiness against severe winter colds. The seeds are harvested and eaten as pine nuts. We assembled and characterized the complete chloroplast genome of P. cembra to serve as a valuable resource in future genetic studies. The complete plastome sequence is 116,609 bp in length and contains 113 genes including 79 protein-coding genes, 30 tRNA genes, and 4 rRNA genes. A phylogenetic analysis of 34 Pinus plastome sequences shows that Pinus sibirica is the nearest relative to P. cembra and that there is a distinct clustering together with the other members of the section Quinquefoliae.

Molecular complexes at a glance: automated generation of two-dimensional complex diagrams.

MOTIVATION: In this paper a new algorithmic approach is presented, which automatically generates structure diagrams of molecular complexes. A complex diagram contains the ligand, the amino acids of the protein interacting with the ligand and the hydrophilic interactions schematized as dashed lines between the corresponding atoms. The algorithm is based on a combinatorial optimization strategy which solves parts of the layout problem non-heuristically. The depicted molecules are represented as structure diagrams according to the chemical nomenclature. Due to the frequent usage of complex diagrams in the scientific literature as well as in text books dealing with structural biology, biochemistry and medicinal chemistry, the new algorithm is a key element for computer applications in these areas. RESULTS: The method was implemented in the new software tool PoseView. It was tested on a representative dataset containing 305 protein-ligand complexes in total from the Brookhaven Protein Data Bank. PoseView was able to find collision-free layouts for more than three quarters of all complexes. In the following the layout generation algorithm is presented and, additional to the statistical results, representative test cases demonstrating the challenges of the layout generation will be discussed. AVAILABILITY: The method is available as a webservice at http://www.zbh.uni-hamburg.de/poseview.

A nearest neighbour approach by genetic distance to the assignment of individual trees to geographic origin.

During the past decade, the use of DNA for forensic applications has been extensively implemented for plant and animal species, as well as in humans. Tracing back the geographical origin of an individual usually requires genetic assignment analysis. These approaches are based on reference samples that are grouped into populations or other aggregates and intend to identify the most likely group of origin. Often this grouping does not have a biological but rather a historical or political justification, such as "country of origin". In this paper, we present a new nearest neighbour approach to individual assignment or classification within a given but potentially imperfect grouping of reference samples. This method, which is based on the genetic distance between individuals, functions better in many cases than commonly used methods. We demonstrate the operation of our assignment method using two data sets. One set is simulated for a large number of trees distributed in a 120km by 120km landscape with individual genotypes at 150 SNPs, and the other set comprises experimental data of 1221 individuals of the African tropical tree species Entandrophragma cylindricum (Sapelli) genotyped at 61 SNPs. Judging by the level of correct self-assignment, our approach outperformed the commonly used frequency and Bayesian approaches by 15% for the simulated data set and by 5-7% for the Sapelli data set. Our new approach is less sensitive to overlapping sources of genetic differentiation, such as genetic differences among closely-related species, phylogeographic lineages and isolation by distance, and thus operates better even for suboptimal grouping of individuals.

Consistent two-dimensional visualization of protein-ligand complex series.

BACKGROUND: The comparative two-dimensional graphical representation of protein-ligand complex series featuring different ligands bound to the same active site offers a quick insight in their binding mode differences. In comparison to arbitrary orientations of the residue molecules in the individual complex depictions a consistent placement improves the legibility and comparability within the series. The automatic generation of such consistent layouts offers the possibility to apply it to large data sets originating from computer-aided drug design methods. RESULTS: We developed a new approach, which automatically generates a consistent layout of interacting residues for a given series of complexes. Based on the structural three-dimensional input information, a global two-dimensional layout for all residues of the complex ensemble is computed. The algorithm incorporates the three-dimensional adjacencies of the active site residues in order to find an universally valid circular arrangement of the residues around the ligand. Subsequent to a two-dimensional ligand superimposition step, a global placement for each residue is derived from the set of already placed ligands. The method generates high-quality layouts, showing mostly overlap-free solutions with molecules which are displayed as structure diagrams providing interaction information in atomic detail. Application examples document an improved legibility compared to series of diagrams whose layouts are calculated independently from each other. CONCLUSIONS: The presented method extends the field of complex series visualizations. A series of molecules binding to the same protein active site is drawn in a graphically consistent way. Compared to existing approaches these drawings substantially simplify the visual analysis of large compound series.

Flat and Easy: 2D Depiction of Protein-Ligand Complexes.

Visualization of molecular complexes is commonly used to support the investigation of interaction patterns formed between the members of a molecular complex ensemble. Similar to the representation of single small molecules as structure diagrams, a schematic two-dimensional design of molecular complexes features several advantages. This visualization mode enables the peer to scan large numbers of complexes in short time, originating for example from a virtual screening or de novo design campaign, and to get an impression of their quality. In addition, the diagrams can be printed on hardcopies without information loss and are therefore well suited for publications and talks. We will give an overview of the existing algorithms for the automatic generation of two-dimensional complex diagrams. The reduction of dimensions from three to two is a quite difficult task since the resulting layout has to be more or less free of overlaps and has to follow esthetical guidelines. All programs proceed on input being composed of the three-dimensional ligand and receptor coordinates. Due to the lack of guiding principles, the algorithms and resulting diagrams of the different available tools substantially differ in graphical styles, level of detail, and information content.

Drawing the PDB: Protein-Ligand Complexes in Two Dimensions.

The two-dimensional representation of molecules is a popular communication medium in chemistry and the associated scientific fields. Computational methods for drawing small molecules with and without manual investigation are well-established and widely spread in terms of numerous software tools. Concerning the planar depiction of molecular complexes, there is considerably less choice. We developed the software PoseView, which automatically generates two-dimensional diagrams of macromolecular complexes, showing the ligand, the interactions, and the interacting residues. All depicted molecules are drawn on an atomic level as structure diagrams; thus, the output plots are clearly structured and easily readable for the scientist. We tested the performance of PoseView in a large-scale application on nearly all druglike complexes of the PDB (approximately 200000 complexes); for more than 92% of the complexes considered for drawing, a layout could be computed. In the following, we will present the results of this application study.

From modeling to medicinal chemistry: automatic generation of two-dimensional complex diagrams.

As a result of the increasing application of structure-based drug design, the visualization of protein-ligand complexes has become an important feature in medicinal chemistry. The large number of experimentally resolved complex structures and the further development of computer-aided methods like docking or de novo design establishes new possibilities in this field. During lead finding and optimization, a manual investigation of many complexes and their interaction patterns is typically performed. We present an algorithm that automatically generates 2D-protein-ligand diagrams as a possible solution for a transparent visualization of the contact partners in a complex and as a support for scientists in the evaluation of structure-based design results. Running the software on representative test data sets, it generates collision free layouts for approximately 76% of the cases in the range of tenths of a second per complex. The success rate for complexes with ligands which have a molecular weight <500 Da is 87%.