Structural, Physicochemical and Stereochemical Interpretation of QSAR Models Based on Simplex Representation of Molecular Structure

2017 ◽  
pp. 107-147 ◽  
Author(s):  
P. Polishchuk ◽  
E. Mokshyna ◽  
A. Kosinskaya ◽  
A. Muats ◽  
M. Kulinsky ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Qsar Models

QSAR models for ACE-inhibitor activity of tri-peptides based on representation of the molecular structure by graph of atomic orbitals and SMILES

2012 ◽  
Vol 23 (6) ◽  
pp. 1873-1878 ◽  
Author(s):  
A. P. Toropova ◽  
A. A. Toropov ◽  
B. F. Rasulev ◽  
E. Benfenati ◽  
G. Gini ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Ace Inhibitor ◽  
Inhibitor Activity ◽  
Atomic Orbitals ◽  
Qsar Models

scholarly journals Rodent Carcinogenicity Dataset

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Natalja Fjodorova ◽  
Marjana Novič
Keyword(s):  
Molecular Structure ◽  
Quantitative Structure Activity Relationship ◽  
Future Research ◽  
Qsar Modeling ◽  
Carcinogenic Potency ◽  
Dragon Descriptors ◽  
Qsar Models ◽  
Funded Project ◽  
Rodent Carcinogenicity

The rodent carcinogenicity dataset was compiled from the Carcinogenic Potency Database (CPDBAS) and was applied for the classification of quantitative structure-activity relationship (QSAR) models for the prediction of carcinogenicity based on the counter-propagation artificial neural network (CP ANN) algorithm. The models were developed within EU-funded project CAESAR for regulatory use. The dataset contains the following information: common information about chemicals (ID, chemical name, and their CASRN), molecular structure information (SDF files and SMILES), and carcinogenic (toxicological) properties information: carcinogenic potency (TD50_Rat_mg; carcinogen/noncarcinogen) and structural alert (SA) for carcinogenicity based on mechanistic data. Molecular structure information was used to get chemometrics information to calculate molecular descriptors (254 MDL and 784 Dragon descriptors), which were further used in predictive QSAR modeling. The dataset presented in the paper can be used in future research in oncology, ecology, or chemicals' risk assessment.

scholarly journals The analysis of structure-anticancer and antiviral activity relationships for macrocyclic pyridinophanes and their analogues on the basis of 4D QSAR models (simplex representation of molecular structure).

2002 ◽  
Vol 49 (1) ◽  
pp. 157-168 ◽  
Author(s):  
Victor E Kuz'min ◽  
Anatoly G Artemenko ◽  
Victor P Lozitsky ◽  
Eugene N Muratov ◽  
Alla S Fedtchouk ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Biological Activity ◽  
Antiviral Activity ◽  
Direct Synthesis ◽  
Antiviral Agents ◽  
Structural Models ◽  
Fourth Dimension ◽  
Molecular Fragments ◽  
Qsar Models ◽  
Fixed Structure

A new 4D-QSAR approach has been considered. For all investigated molecules the 3D structural models have been created and the set of conformers (fourth dimension) have been used. Each conformer is represented as a system of different simplexes (tetratomic fragments of fixed structure, chirality and symmetry). The investigation of influence of molecular structure of macrocyclic pyridinophanes, their analogues and certain other compounds on anticancer and antiviral (anti-influenza, antiherpes and antiadenovirus) activity has been carried out by means of the 4D-QSAR. Statistic characteristics for QSAR of PLS (partial least squares) models are satisfactory (R = 0.92-0.97; CVR = 0.63-0.83). Molecular fragments increasing and decreasing biological activity were defined. This information may be useful for design, and direct synthesis of novel anticancer and antiviral agents.

QSAR Study of Artemisinin Analogues as Antimalarial Drugs by Neural Network and Replacement Method

Drug Research ◽  
2017 ◽  
Vol 67 (08) ◽  
pp. 476-484 ◽  
Author(s):  
Fatemeh Abbasitabar ◽  
Vahid Zare-Shahabadi
Keyword(s):  
Neural Network ◽  
Molecular Structure ◽  
Antimalarial Activity ◽  
General Regression Neural Network ◽  
Relative Standard Error ◽  
Qsar Study ◽  
Test Set ◽  
Replacement Method ◽  
Relative Standard ◽  
Qsar Models

AbstractQuantitative structure–activity relationship (QSAR) models were derived for 179 analogues of artemisinin, a potent antimalarial agent. Molecular descriptors derived solely from molecular structure were used to represent molecular structure. Utilizing replacement method, a subset of 11 descriptors was selected. General regression neural network (GRNN) was used to construct the nonlinear QSAR models in all stages of study. The relative standard error percent in antimalarial activity predictions for the training set by the application of cross-validation (RMSE-CV) was 0.43, and for test set (RMSEtest) was 0.51. GRNN analysis yielded predicted activities in the excellent agreement with the experimentally obtained values (R2training = 0.967 and R2test = 0.918). The mean absolute error for the test set was computed as 0.4115.

Hierarchic system of QSAR models (1D–4D) on the base of simplex representation of molecular structure

2005 ◽  
Vol 11 (6) ◽  
pp. 457-467 ◽  
Author(s):  
Victor E. Kuz’min ◽  
Anatoly G. Artemenko ◽  
Pavel G. Polischuk ◽  
Eugene N. Muratov ◽  
Alexander I. Hromov ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Qsar Models ◽  
Hierarchic System

Comparative Analysis of QSAR Models for Predicting pKa of Organic Oxygen Acids and Nitrogen Bases from Molecular Structure

2010 ◽  
Vol 50 (11) ◽  
pp. 1949-1960 ◽  
Author(s):  
Haiying Yu ◽  
Ralph Kühne ◽  
Ralf-Uwe Ebert ◽  
Gerrit Schüürmann
Keyword(s):  
Molecular Structure ◽  
Comparative Analysis ◽  
Nitrogen Bases ◽  
Qsar Models

scholarly journals QSAR Models for Predicting Five Levels of Cellular Accumulation of Lysosomotropic Macrocycles

2019 ◽  
Vol 20 (23) ◽  
pp. 5938 ◽  
Author(s):  
Ulf Norinder ◽  
Vesna Munic Kos
Keyword(s):  
Molecular Structure ◽  
High Volume ◽  
Pharmacokinetic Profile ◽  
Quantitative Structure Activity Relationship ◽  
Volume Of Distribution ◽  
Cellular Accumulation ◽  
Large Size ◽  
Qsar Models ◽  
First Time ◽  
Very High

Drugs that accumulate in lysosomes reach very high tissue concentrations, which is evident in the high volume of distribution and often lower clearance of these compounds. Such a pharmacokinetic profile is beneficial for indications where high tissue penetration and a less frequent dosing regime is required. Here, we show how the level of lysosomotropic accumulation in cells can be predicted solely from molecular structure. To develop quantitative structure–activity relationship (QSAR) models, we used cellular accumulation data for 69 lysosomotropic macrocycles, the pharmaceutical class for which this type of prediction model is extremely valuable due to the importance of cellular accumulation for their anti-infective and anti-inflammatory applications as well as due to the fact that they are extremely difficult to model by computational methods because of their large size (Mw > 500). For the first time, we show that five levels of intracellular lysosomotropic accumulation (as measured by liquid chromatography coupled to tandem mass spectrometry—LC-MS/MS), from low/no to extremely high, can be predicted with 60% balanced accuracy solely from the compound’s structure. Although largely built on macrocycles, the eight non-macrocyclic compounds that were added to the set were found to be well incorporated by the models, indicating their possible broader application. By uncovering the link between the molecular structure and cellular accumulation as the key process in tissue distribution of lysosomotropic compounds, these models are applicable for directing the drug discovery process and prioritizing the compounds for synthesis with fine-tuned accumulation properties, according to the desired pharmacokinetic profile.

Molecular Structure of the Outermost Cell Wall Component of Spirillum Serpens

1977 ◽  
Vol 35 ◽  
pp. 342-343
Author(s):  
Wah Chiu ◽  
David Grano
Keyword(s):  
Molecular Structure ◽  
Cell Wall ◽  
Outer Membrane ◽  
Gel Electrophoresis ◽  
Electron Microscopic Examination ◽  
Electron Microscopic ◽  
Cell Wall Component ◽  
Protein Components ◽  
Exposure Technique ◽  
Structural Aspects

The periodic structure external to the outer membrane of Spirillum serpens VHA has been isolated by similar procedures to those used by Buckmire and Murray (1). From SDS gel electrophoresis, we have found that the isolated fragments contain several protein components, and that the crystalline structure is composed of a glycoprotein component with a molecular weight of ∽ 140,000 daltons (2). Under an electron microscopic examination, we have visualized the hexagonally-packed glycoprotein subunits, as well as the bilayer profile of the outer membrane. In this paper, we will discuss some structural aspects of the crystalline glycoproteins, based on computer-reconstructed images of the external cell wall fragments.The specimens were prepared for electron microscopy in two ways: negatively stained with 1% PTA, and maintained in a frozen-hydrated state (3). The micrographs were taken with a JEM-100B electron microscope with a field emission gun. The minimum exposure technique was essential for imaging the frozen- hydrated specimens.

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