- MeSH
- Molecular Diagnostic Techniques methods utilization MeSH
- Genetics standards statistics & numerical data trends MeSH
- Genomics methods standards statistics & numerical data MeSH
- Humans MeSH
- Molecular Biology methods statistics & numerical data trends MeSH
- Quality Control MeSH
- Check Tag
- Humans MeSH
- Publication type
- Practice Guideline MeSH
Structure validation has become a major issue in the structural biology community, and an essential step is checking the ligand structure. This paper introduces MotiveValidator, a web-based application for the validation of ligands and residues in PDB or PDBx/mmCIF format files provided by the user. Specifically, MotiveValidator is able to evaluate in a straightforward manner whether the ligand or residue being studied has a correct annotation (3-letter code), i.e. if it has the same topology and stereochemistry as the model ligand or residue with this annotation. If not, MotiveValidator explicitly describes the differences. MotiveValidator offers a user-friendly, interactive and platform-independent environment for validating structures obtained by any type of experiment. The results of the validation are presented in both tabular and graphical form, facilitating their interpretation. MotiveValidator can process thousands of ligands or residues in a single validation run that takes no more than a few minutes. MotiveValidator can be used for testing single structures, or the analysis of large sets of ligands or fragments prepared for binding site analysis, docking or virtual screening. MotiveValidator is freely available via the Internet at http://ncbr.muni.cz/MotiveValidator.
- MeSH
- Acetylglucosamine chemistry MeSH
- Ephrin-B3 chemistry MeSH
- Glycoproteins chemistry MeSH
- Internet MeSH
- Cholic Acid chemistry MeSH
- Ligands MeSH
- Macromolecular Substances chemistry MeSH
- Proteins chemistry MeSH
- Software * MeSH
- Binding Sites MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Práce se zabývá možností srovnání dvou přístupů – výsledků struktury osobnosti podle dotazníku temperamentu a charakteru C. R. Cloningera (TCI) a narativní metody Životního příběhu v případové studii. Pacientka Psychiatrického centra Praha byla požádána o sdělení svého životního příběhu, její vyprávění bylo doslovně přepsáno a porovnáno s dotazníkem TCI. Paralely mezi výsledky struktury osobnosti podle dotazníkové metody a vyprávěním Životního příběhu jsou demonstrovány pomocí citací vybraných z rozhovoru s pacientkou. Při hledání podobností a rozdílů mezi výsledkem TCI a Životního příběhu se autoři domnívají, že jde sice o náročnou, ale originální a potřebnou variantu z možných metod validizace dotazníkové metody.
This paper compares two approaches – psychometric structure of personality measured with Temperament and Character Inventory (TCI) and narrative Life story in a case study. A female patient from Prague Psychiatric center was asked to share her life story and the material was recorded and rewritten. The comparison between Life story and TCI was done and paralleles between them were pointed out. Examples from Life story are presented to confirm or refuse the results of TCI. On the way of finding the paralleles between Life story and TCI this approach is described as demanding but fruitful and original method of questionnaire validization.
- MeSH
- Research Support as Topic MeSH
- Histrionic Personality Disorder psychology MeSH
- Humans MeSH
- Personality Inventory MeSH
- Narration MeSH
- Check Tag
- Humans MeSH
- Female MeSH
- Publication type
- Case Reports MeSH
- Comparative Study MeSH
A way to legalization results of Quantitative Structure – Activity Relationships (QSAR) models is described. A basic impulse has come from OECD followed by the other countries of the world. Final tool, QSAR Application Tool Box, has been developed and as an open system will be developed in the future, too.
- MeSH
- Factor Analysis, Statistical MeSH
- Humans MeSH
- Adolescent MeSH
- Personality Tests statistics & numerical data MeSH
- Psychometrics methods statistics & numerical data MeSH
- Students psychology statistics & numerical data MeSH
- Check Tag
- Humans MeSH
- Adolescent MeSH
- Male MeSH
- Female MeSH
- Publication type
- Comparative Study MeSH
- MeSH
- Molecular Diagnostic Techniques methods utilization MeSH
- Genetics standards statistics & numerical data trends MeSH
- Genomics standards statistics & numerical data trends MeSH
- Humans MeSH
- Molecular Biology methods statistics & numerical data trends MeSH
- Quality Control MeSH
- Check Tag
- Humans MeSH
- Publication type
- Practice Guideline MeSH
In this paper, we present a novel algorithm for measuring protein similarity based on their 3-D structure (protein tertiary structure). The algorithm used a suffix tree for discovering common parts of main chains of all proteins appearing in the current research collaboratory for structural bioinformatics protein data bank (PDB). By identifying these common parts, we build a vector model and use some classical information retrieval (IR) algorithms based on the vector model to measure the similarity between proteins--all to all protein similarity. For the calculation of protein similarity, we use term frequency × inverse document frequency ( tf × idf ) term weighing schema and cosine similarity measure. The goal of this paper is to introduce new protein similarity metric based on suffix trees and IR methods. Whole current PDB database was used to demonstrate very good time complexity of the algorithm as well as high precision. We have chosen the structural classification of proteins (SCOP) database for verification of the precision of our algorithm because it is maintained primarily by humans. The next success of this paper would be the ability to determine SCOP categories of proteins not included in the latest version of the SCOP database (v. 1.75) with nearly 100% precision.
- MeSH
- Algorithms MeSH
- Data Mining methods MeSH
- Databases, Protein MeSH
- Humans MeSH
- Proteins chemistry MeSH
- Reproducibility of Results MeSH
- Structural Homology, Protein MeSH
- Protein Structure, Tertiary MeSH
- Artificial Intelligence MeSH
- Computational Biology methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
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.
- MeSH
- Amino Acids chemistry MeSH
- Molecular Sequence Annotation MeSH
- Databases, Protein * MeSH
- Internet MeSH
- Protein Conformation MeSH
- Ligands MeSH
- Models, Molecular MeSH
- Proteins chemistry MeSH
- Reproducibility of Results MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
A quantitative structure-activity relationship (QSAR) model dependent on log P(n - octanol/water), or log P(OW), was developed with acute toxicity index EC50, the median effective concentration measured as inhibition of movement of the oligochaeta Tubifex tubifex with 3 min exposure, EC50(Tt) (mol/L): log EC50(Tt) = -0.809 (+/-0.035) log P(OW) - 0.495 (+/-0.060), n=82, r=0.931, r2=0.867, residual standard deviation of the estimate 0.315. A learning series for the QSAR model with the oligochaete contained alkanols, alkenols, and alkynols; saturated and unsaturated aldehydes; aniline and chlorinated anilines; phenol and chlorinated phenols; and esters. Three cross-validation procedures proved the robustness and stability of QSAR models with respect to the chemical structure of compounds tested within a series of compounds used in the learning series. Predictive ability was described by q2 .801 (cross-validated r2; predicted variation estimated with cross-validation) in LSO (leave-a structurally series-out) cross-validation.
