Biomedical subjects

A Golbraikh

Publications and source records attributed to A Golbraikh.

5 recordsLinked to original sources

PubMed2000

Validation of protein-based alignment in 3D quantitative structure-activity relationships with CoMFA models.

The predictive capabilities of protein-based alignment (PBA) and structure-based alignment (SBA) comparative molecular field analysis (CoMFA) models have been compared. 3D quantitative structure-activity relationship (3D QSAR) models have been derived for a series of N-benzylpiperidine derivatives which are potent acetylcholinesterase (AChE) inhibitors interesting for Alzheimer's disease. To establish a comparison with the classical SBA procedure, different assay models were derived by superposing ligand conformers that are docked to the AChE active site and by using the most active compound as the reference one. A Kohonen self organizing map (SOM) was applied to analyse the molecular diversity of the test set relative to that of the training set, in order to explain the influence of molecular diversity on the predictive power of the considered models. SBA 3D QSAR models have to be used to predict the inhibitory activity only for compounds belonging to subgroups included in the training set. The PBA 3D QSAR models appeared to have a higher predictability, even for compounds with a molecular diversity greater than that of the training set. This results from the fact that the protein helps to automatically select the active conformation which is fitting the 3D QSAR model.

Acetylcholinesterase↗

PubMed2000

Molecular dataset diversity indices and their applications to comparison of chemical databases and QSAR analysis

A new mutual molecular dataset diversity index (MMDDI), individual molecular dataset diversity index (IMDDI), and volume ratio (VR) are proposed to assess molecular dataset diversity. MMDDI and IMDDI can serve as valuable instruments for selecting monomer pools for combinatorial synthesis and in decision making about acquiring new databases. MMDDI can also be used as one of the criteria to estimate the quality of quantitative structure-activity relationship (QSAR) models aimed at the prediction of biological activities. The indices can be calculated directly from molecular descriptor values. The procedures applied for MMDDI and IMDDI calculations allow one to automatically compile lists of compounds, which can simplify molecular diversity analyses and database searching. The information can also be used for forming training and test sets in QSAR analysis.

Journal Article↗

PubMed1999

A molecular mechanism for the cleavage of a disulfide bond as the primary function of agonist binding to G-protein-coupled receptors based on theoretical calculations supported by experiments.

A model of the binding site of delta-opioids in the extracellular region of the G-protein-coupled opioid receptor based on modelling studies is presented. The distance between Asp288 and the disulfide bridge (Cys121-Cys198) formed between the first and second extracellular loops was found to be short. This model is consistent with site-directed mutagenesis studies. The arrangement of the ligands found in the receptor led to the development of a reaction mechanism for the cleavage of the disulfide bond catalysed by the ligands. Semi-empirical quantum chemical PM3 and AM1 calculations as well as ab initio studies showed that the interaction between the carboxylic acid side chain of aspartic acid and the disulfide bond leads to the polarization of, and withdrawal of a proton from, the protonated nitrogen of the ligand to one of the sulfur atoms. A mixed sulfenic acid and carboxylic acid anhydrate is formed as an intermediate as well as a thiol. The accompanying cleavage of the disulfide bond may produce a conformational change in the extracellular loops such that the pore formed by the seven-helix bundle opens allowing entrance of the ligand, water and ions into the cell. Cleavage of the disulfide bond after opioid administration was demonstrated experimentally by flow-cytometric measurements employing CMTMR and monobromobimane-based analyses of membrane-located thiols. The suggested mechanism may explain, in a consistent way, the action of agonists and antagonists and is assumed to be common for many G-protein coupled receptors.

Animals↗

PubMedDate not supplied

Novel chirality descriptors derived from molecular topology.

Several series of novel chirality descriptors of chemical organic molecules have been introduced. The descriptors have been developed on the basis of conventional topological descriptors of molecular graphs. They include modified molecular connectivity indices, Zagreb group indices, extended connectivity, overall connectivity, and topological charge indices. These modified descriptors make use of an additional term called chirality correction, which is added to the vertex degrees of asymmetric atoms in a molecular graph. Chirality descriptors can be real or complex numbers. Advantages and drawbacks of different series of chirality descriptors are discussed. These descriptors circumvent the inability of conventional topological indices to distinguish chiral or enantiomeric isomers, which so far has been the major drawback of 2D descriptors as compared to true 3D descriptors (e.g., shape, molecular fields) of molecular structure. These novel chirality descriptors have been implemented in a quantitative structure-activity releationship (QSAR) study of a set of ecdysteroids with a high content of chiral and enantiomeric compounds using the k nearest neighbor QSAR method (kNN) recently developed in this laboratory. We show that the results of this study compare favorably with those obtained with the comparative molecular field analysis (CoMFA) applied to the same dataset. The novel chirality descriptors of molecular structure should find their applications in QSAR studies and related investigations of molecular sdatasets.

Models, Chemical↗

PubMedDate not supplied

QSAR modeling of datasets with enantioselective compounds using chirality sensitive molecular descriptors.

Shape descriptors used in 3D QSAR studies naturally take into account chirality; however, for flexible and structurally diverse molecules such studies require extensive conformational searching and alignment. QSAR modeling studies of two datasets of fragrance compounds with complex stereochemistry using simple alignment-free chirality sensitive descriptors developed in our laboratories are presented. In the first investigation, 44 alpha-campholenic derivatives with sandalwood odor were represented as derivatives of several common structural templates with substituents numbered according to their relative spatial positions in the molecules. Both molecular and substituent descriptors were used as independent variables in MLR calculations, and the best model was characterized by the training set q2 of 0.79 and external test set r2 of 0.95. In the second study, several types of chirality descriptors were employed in combinatorial QSAR modeling of 98 ambergris fragrance compounds. Among 28 possible combinations of seven types of descriptors and four statistical modeling techniques, k nearest neighbor classification with CoMFA descriptors was initially found to generate the best models with the internal and external accuracies of 76 and 89%, respectively. The same dataset was then studied using novel atom pair chirality descriptors (cAP). The cAP are based on a modified definition of the atomic chirality, in which the seniority of the substituents is defined by their relative partial charge values: higher values correspond to higher seniorities. The resulting models were found to have higher predictive power than those developed with CoMFA descriptors; the best model was characterized by the internal and external accuracies of 82 and 94%, respectively. The success of modeling studies using simple alignment free chirality descriptors discussed in this paper suggests that they should be applied broadly to QSAR studies of many datasets when compound stereochemistry plays an important role in defining their activity.

Ambergris↗