High-quality and universal empirical atomic charges for chemoinformatics applications.

BackgroundPartial atomic charges describe the distribution of electron density in a molecule and therefore provide clues to the chemical behaviour of molecules. Recently, these charges have become popular in chemoinformatics, as they are informative descriptors that can be utilised in pharmacophore design, virtual screening, similarity searches etc. Especially conformationally-dependent charges perform very successfully. In particular, their fast and accurate calculation via the Electronegativity Equalization Method (EEM) seems very promising for chemoinformatics applications. Unfortunately, published EEM parameter sets include only parameters for basic atom types and they often miss parameters for halogens, phosphorus, sulphur, triple bonded carbon etc. Therefore their applicability for drug-like molecules is limited.ResultsWe have prepared six EEM parameter sets which enable the user to calculate EEM charges in a quality comparable to quantum mechanics (QM) charges based on the most common charge calculation schemes (i.e., MPA, NPA and AIM) and a robust QM approach (HF/6-311G, B3LYP/6-311G). The calculated EEM parameters exhibited very good quality on a training set ([Formula: see text]) and also on a test set ([Formula: see text]). They are applicable for at least 95 % of molecules in key drug databases (DrugBank, ChEMBL, Pubchem and ZINC) compared to less than 60 % of the molecules from these databases for which currently used EEM parameters are applicable.ConclusionsWe developed EEM parameters enabling the fast calculation of high-quality partial atomic charges for almost all drug-like molecules. In parallel, we provide a software solution for their easy computation (http://ncbr.muni.cz/eem_parameters). It enables the direct application of EEM in chemoinformatics

Long-Residency Hydration, Cation Binding, and Dynamics of Loop E/Helix IV rRNA-L25 Protein Complex

Molecular dynamics simulations of RNA-protein complex between Escherichia coli loop E/helix IV (LE/HeIV) rRNA and L25 protein reveal a qualitative agreement between the experimental and simulated structures. The major groove of LE is a prominent rRNA cation-binding site. Divalent cations rigidify the LE major groove geometry whereas in the absence of divalent cations LE extensively interacts with monovalent cations via inner-shell binding. The HeIV region shows bistability of its major groove explaining the observed differences between x-ray and NMR structures. In agreement with the experiments, the simulations suggest that helix-alpha1 of L25 is the least stable part of the protein. Inclusion of Mg2+ cations into the simulations causes perturbation of basepairing at the LE/HeIV junction, which does not, however, affect the protein binding. The rRNA-protein complex is mediated by a number of highly specific hydration sites with long-residing water molecules and two of them are bound throughout the entire 24-ns simulation. Long-residing water molecules are seen also outside the RNA-protein contact areas with water-binding times substantially enhanced compared to simulations of free RNA. Long-residency hydration sites thus represent important elements of the three-dimensional structure of rRNA

ChannelsDB: database of biomacromolecular tunnels and pores

ChannelsDB (http://ncbr.muni.cz/ChannelsDB) is a database providing information about the positions, geometry and physicochemical properties of channels (pores and tunnels) found within biomacromolecular structures deposited in the Protein Data Bank. Channels were deposited from two sources; from literature using manual deposition and from a software tool automatically detecting tunnels leading to the enzymatic active sites and selected cofactors, and transmembrane pores. The database stores information about geometrical features (e.g. length and radius profile along a channel) and physicochemical properties involving polarity, hydrophobicity, hydropathy, charge and mutability. The stored data are interlinked with available UniProt annotation data mapping known mutation effects to channel-lining residues. All structures with channels are displayed in a clear interactive manner, further facilitating data manipulation and interpretation. As such, ChannelsDB provides an invaluable resource for research related to deciphering the biological function of biomacromolecular channels

SiteBinder: an improved approach for comparing multiple protein structural motifs.

There is a paramount need to develop new techniques and tools that will extract as much information as possible from the ever growing repository of protein 3D structures. We report here on the development of a software tool for the multiple superimposition of large sets of protein structural motifs. Our superimposition methodology performs a systematic search for the atom pairing that provides the best fit. During this search, the RMSD values for all chemically relevant pairings are calculated by quaternion algebra. The number of evaluated pairings is markedly decreased by using PDB annotations for atoms. This approach guarantees that the best fit will be found and can be applied even when sequence similarity is low or does not exist at all. We have implemented this methodology in the Web application SiteBinder, which is able to process up to thousands of protein structural motifs in a very short time, and which provides an intuitive and user-friendly interface. Our benchmarking analysis has shown the robustness, efficiency, and versatility of our methodology and its implementation by the successful superimposition of 1000 experimentally determined structures for each of 32 eukaryotic linear motifs. We also demonstrate the applicability of SiteBinder using three case studies. We first compared the structures of 61 PA-IIL sugar binding sites containing nine different sugars, and we found that the sugar binding sites of PA-IIL and its mutants have a conserved structure despite their binding different sugars. We then superimposed over 300 zinc finger central motifs and revealed that the molecular structure in the vicinity of the Zn atom is highly conserved. Finally, we superimposed 12 BH3 domains from pro-apoptotic proteins. Our findings come to support the hypothesis that there is a structural basis for the functional segregation of BH3-only proteins into activators and enablers

ValTrendsDB: bringing Protein Data Bank validation information closer to the user

Structures in PDB tend to contain errors. This is a very serious issue for authors that rely on such potentially problematic data. The community of structural biologists develops validation methods as countermeasures, which are also included in the PDB deposition system. But how are these validation efforts influencing the structure quality of subsequently published data? Which quality aspects are improving, and which remain problematic? We developed ValTrendsDB, a database that provides the results of an extensive exploratory analysis of relationships between quality criteria, size and metadata of biomacromolecules. Key input data are sourced from PDB. The discovered trends are presented via precomputed information-rich plots. ValTrendsDB also supports the visualization of a set of user-defined structures on top of general quality trends. Therefore, ValTrendsDB enables users to see the quality of structures published by selected author, laboratory or journal, discover quality outliers, etc. ValTrendsDB is updated weekly. ValTrendsDB is freely accessible at http://ncbr.muni.cz/ValTrendsDB. The web interface was implemented in JavaScript. The database was implemented in C++

Evaluation of Selected Classical Force Fields for Alchemical Binding Free Energy Calculations of Protein-Carbohydrate Complexes

Protein–carbohydrate recognition is crucial in many vital biological processes including host–pathogen recognition, cell-signaling, and catalysis. Accordingly, computational prediction of protein–carbohydrate binding free energies is of enormous interest for drug design. However, the accuracy of current force fields (FFs) for predicting binding free energies of protein–carbohydrate complexes is not well understood owing to technical challenges such as the highly polar nature of the complexes, anomerization, and conformational flexibility of carbohydrates. The present study evaluated the performance of alchemical predictions of binding free energies with the GAFF1.7/AM1-BCC and GLYCAM06j force fields for modeling protein–carbohydrate complexes. Mean unsigned errors of 1.1 ± 0.06 (GLYCAM06j) and 2.6 ± 0.08 (GAFF1.7/AM1-BCC) kcal·mol^–1 are achieved for a large data set of monosaccharide ligands for <i>Ralstonia solanacearum</i> lectin (RSL). The level of accuracy provided by GLYCAM06j is sufficient to discriminate potent, moderate, and weak binders, a goal that has been difficult to achieve through other scoring approaches. Accordingly, the protocols presented here could find useful applications in carbohydrate-based drug and vaccine developments

TRITON: a graphical tool for ligand-binding protein engineering

Summary: The new version of the TRITON program provides user-friendly graphical tools for modeling protein mutants using the external program MODELLER and for docking ligands into the mutants using the external program AutoDock. TRITON can now be used to design ligand-binding proteins, to study protein–ligand binding mechanisms or simply to dock any ligand to a protein