David Sehnal

MOLE 2.0: advanced approach for analysis of biomacromolecular channels

BackgroundChannels and pores in biomacromolecules (proteins, nucleic acids and their complexes) play significant biological roles, e.g., in molecular recognition and enzyme substrate specificity.ResultsWe present an advanced software tool entitled MOLE 2.0, which has been designed to analyze molecular channels and pores. Benchmark tests against other available software tools showed that MOLE 2.0 is by comparison quicker, more robust and more versatile. As a new feature, MOLE 2.0 estimates physicochemical properties of the identified channels, i.e., hydropathy, hydrophobicity, polarity, charge, and mutability. We also assessed the variability in physicochemical properties of eighty X-ray structures of two members of the cytochrome P450 superfamily.ConclusionEstimated physicochemical properties of the identified channels in the selected biomacromolecules corresponded well with the known functions of the respective channels. Thus, the predicted physicochemical properties may provide useful information about the potential functions of identified channels. The MOLE 2.0 software is available at http://mole.chemi.muni.cz.

MOLEonline 2.0: interactive web-based analysis of biomacromolecular channels

Biomolecular channels play important roles in many biological systems, e.g. enzymes, ribosomes and ion channels. This article introduces a web-based interactive MOLEonline 2.0 application for the analysis of access/egress paths to interior molecular voids. MOLEonline 2.0 enables platform-independent, easy-to-use and interactive analyses of (bio)macromolecular channels, tunnels and pores. Results are presented in a clear manner, making their interpretation easy. For each channel, MOLEonline displays a 3D graphical representation of the channel, its profile accompanied by a list of lining residues and also its basic physicochemical properties. The users can tune advanced parameters when performing a channel search to direct the search according to their needs. The MOLEonline 2.0 application is freely available via the Internet at http://ncbr.muni.cz/mole or http://mole.upol.cz.

Predicting pK(a) values of substituted phenols from atomic charges: comparison of different quantum mechanical methods and charge distribution schemes.

The acid dissociation (ionization) constant pK(a) is one of the fundamental properties of organic molecules. We have evaluated different computational strategies and models to predict the pK(a) values of substituted phenols using partial atomic charges. Partial atomic charges for 124 phenol molecules were calculated using 83 approaches containing seven theory levels (MP2, HF, B3LYP, BLYP, BP86, AM1, and PM3), three basis sets (6-31G*, 6-311G, STO-3G), and five population analyses (MPA, NPA, Hirshfeld, MK, and Löwdin). The correlations between pK(a) and various atomic charge descriptors were examined, and the best descriptors were selected for preparing the quantitative structure-property relationship (QSPR) models. One QSPR model was created for each of the 83 approaches to charge calculation, and then the accuracy of all these models was analyzed and compared. The pK(a)s predicted by most of the models correlate strongly with experimental pK(a) values. For example, more than 25% of the models have correlation coefficients (R²) greater than 0.95 and root-mean-square errors smaller than 0.49. All seven examined theory levels are applicable for pK(a) prediction from charges. The best results were obtained for the MP2 and HF level of theory. The most suitable basis set was found to be 6-31G*. The 6-311G basis set provided slightly weaker correlations, and unexpectedly also, the STO-3G basis set is applicable for the QSPR modeling of pK(a). The Mulliken, natural, and Löwdin population analyses provide accurate models for all tested theory levels and basis sets. The results provided by the Hirshfeld population analysis were also acceptable, but the QSPR models based on MK charges show only weak correlations.

Anatomy of Enzyme Channels

BackgroundEnzyme active sites can be connected to the exterior environment by one or more channels passing through the protein. Despite our current knowledge of enzyme structure and function, surprisingly little is known about how often channels are present or about any structural features such channels may have in common.ResultsHere, we analyze the long channels (i.e. >15 Å) leading to the active sites of 4,306 enzyme structures. We find that over 64% of enzymes contain two or more long channels, their typical length being 28 Å. We show that amino acid compositions of the channel significantly differ both to the composition of the active site, surface and interior of the protein.ConclusionsThe majority of enzymes have buried active sites accessible via a network of access channels. This indicates that enzymes tend to have buried active sites, with channels controlling access to, and egress from, them, and that suggests channels may play a key role in helping determine enzyme substrate.

LiteMol suite: interactive web-based visualization of large-scale macromolecular structure data

We present the LiteMol suite, a tool for visualizing large macromolecular structure data sets that is freely available at https://www.litemol.org.

PatternQuery: web application for fast detection of biomacromolecular structural patterns in the entire Protein Data Bank

Well defined biomacromolecular patterns such as binding sites, catalytic sites, specific protein or nucleic acid sequences, etc. precisely modulate many important biological phenomena. We introduce PatternQuery, a web-based application designed for detection and fast extraction of such patterns. The application uses a unique query language with Python-like syntax to define the patterns that will be extracted from datasets provided by the user, or from the entire Protein Data Bank (PDB). Moreover, the database-wide search can be restricted using a variety of criteria, such as PDB ID, resolution, and organism of origin, to provide only relevant data. The extraction generally takes a few seconds for several hundreds of entries, up to approximately one hour for the whole PDB. The detected patterns are made available for download to enable further processing, as well as presented in a clear tabular and graphical form directly in the browser. The unique design of the language and the provided service could pave the way towards novel PDB-wide analyses, which were either difficult or unfeasible in the past. The application is available free of charge at http://ncbr.muni.cz/PatternQuery.

ValidatorDB: database of up-to-date validation results for ligands and non-standard residues from the Protein Data Bank

Following the discovery of serious errors in the structure of biomacromolecules, structure validation has become a key topic of research, especially for ligands and non-standard residues. ValidatorDB (freely available at http://ncbr.muni.cz/ValidatorDB) offers a new step in this direction, in the form of a database of validation results for all ligands and non-standard residues from the Protein Data Bank (all molecules with seven or more heavy atoms). Model molecules from the wwPDB Chemical Component Dictionary are used as reference during validation. ValidatorDB covers the main aspects of validation of annotation, and additionally introduces several useful validation analyses. The most significant is the classification of chirality errors, allowing the user to distinguish between serious issues and minor inconsistencies. Other such analyses are able to report, for example, completely erroneous ligands, alternate conformations or complete identity with the model molecules. All results are systematically classified into categories, and statistical evaluations are performed. In addition to detailed validation reports for each molecule, ValidatorDB provides summaries of the validation results for the entire PDB, for sets of molecules sharing the same annotation (three-letter code) or the same PDB entry, and for user-defined selections of annotations or PDB entries.

Predicting p K a values from EEM atomic charges

AbstractThe acid dissociation constant p Kais a very important molecular property, and there is a strong interest in the development of reliable and fast methods for p Kaprediction. We have evaluated the p Kaprediction capabilities of QSPR models based on empirical atomic charges calculated by the Electronegativity Equalization Method (EEM). Specifically, we collected 18 EEM parameter sets created for 8 different quantum mechanical (QM) charge calculation schemes. Afterwards, we prepared a training set of 74 substituted phenols. Additionally, for each molecule we generated its dissociated form by removing the phenolic hydrogen. For all the molecules in the training set, we then calculated EEM charges using the 18 parameter sets, and the QM charges using the 8 above mentioned charge calculation schemes. For each type of QM and EEM charges, we created one QSPR model employing charges from the non-dissociated molecules (three descriptor QSPR models), and one QSPR model based on charges from both dissociated and non-dissociated molecules (QSPR models with five descriptors). Afterwards, we calculated the quality criteria and evaluated all the QSPR models obtained. We found that QSPR models employing the EEM charges proved as a good approach for the prediction of p Ka(63% of these models had R2 > 0.9, while the best had R2 = 0.924). As expected, QM QSPR models provided more accurate p Kapredictions than the EEM QSPR models but the differences were not significant. Furthermore, a big advantage of the EEM QSPR models is that their descriptors (i.e., EEM atomic charges) can be calculated markedly faster than the QM charge descriptors. Moreover, we found that the EEM QSPR models are not so strongly influenced by the selection of the charge calculation approach as the QM QSPR models. The robustness of the EEM QSPR models was subsequently confirmed by cross-validation. The applicability of EEM QSPR models for other chemical classes was illustrated by a case study focused on carboxylic acids. In summary, EEM QSPR models constitute a fast and accurate p Kaprediction approach that can be used in virtual screening.

AtomicChargeCalculator: interactive web-based calculation of atomic charges in large biomolecular complexes and drug-like molecules

AbstractBackgroundPartial atomic charges are a well-established concept, useful in understanding and modeling the chemical behavior of molecules, from simple compounds, to large biomolecular complexes with many reactive sites.Results This paper introduces AtomicChargeCalculator (ACC), a web-based application for the calculation and analysis of atomic charges which respond to changes in molecular conformation and chemical environment. ACC relies on an empirical method to rapidly compute atomic charges with accuracy comparable to quantum mechanical approaches. Due to its efficient implementation, ACC can handle any type of molecular system, regardless of size and chemical complexity, from drug-like molecules to biomacromolecular complexes with hundreds of thousands of atoms. ACC writes out atomic charges into common molecular structure files, and offers interactive facilities for statistical analysis and comparison of the results, in both tabular and graphical form.ConclusionsDue to high customizability and speed, easy streamlining and the unified platform for calculation and analysis, ACC caters to all fields of life sciences, from drug design to nanocarriers. ACC is freely available via the Internet at http://ncbr.muni.cz/ACC.

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.