ChemModLab, written by the ECCR @ NCSU consortium under NIH support, is a toolbox for fitting and assessing quantitative structure-activity relationships (QSARs). Its elements are: a cheminformatic front end used to supply molecular descriptors for use in modeling; a set of methods for fitting models; and methods for validating the resulting model. Compounds may be input as structures from whic...

recently several 1,3,4-oxadiazole derivatives were identified as potentially active antimycobacterial agents. various 5-aryl-2-thio-1,3,4-oxadiazoles have been reported having good antimycobacterial activity against mycobacterium tuberculosis h37rv (atcc 27294). in this paper we report 3d qsar studies for the 41 molecules of 1,3,4-oxadiazoles by using k-nearest neighbor molecular field analysis...

Insubria QSPR PaDEL-Descriptor model for Vapor Pressure prediction of Polybrominated Diphenyl Ethers. 1.2.Other related models: E. Papa, S. Kovarich, P. Gramatica, 2009, Validation and Inspection of the Applicability Domain of QSPR Models for Physicochemical Properties of Polybrominated Diphenyl Ethers, QSAR & Comb.Sci. 28, 790-796. [9] 1.3.Software coding the model: [1]PaDEL-Descriptor 2.18 A ...

Multivariate image analysis quantitative structure-activity relationship (MIA-QSAR) study aims to obtain information from a descriptor set, which are pixels of two-dimensional molecule structures. In the QSAR protein P38 mitogen-activated (MAP) kinase compounds, genetic algorithm application for pixel selection and processing is investigated. There between structure pIC50 based on obtained. (Th...

A quantitative structure activity relationship study was performed on different groups of anti-tuberculosis drug compound for establishing quantitative relationship between biological activity and their physicochemical /structural properties. In recent years, a large number of herbal drugs are promoted in treatment of tuberculosis especially due to the emergence of MDR (multi drug resistance) a...

In modern drug discovery, the combination of chemoinformatics and quantitative structure–activity relationship (QSAR) modeling has emerged as a formidable alliance, enabling researchers to harness vast potential machine learning (ML) techniques for predictive molecular design analysis. This review delves into fundamental aspects chemoinformatics, elucidating intricate nature chemical data cruci...

The Peroxisome proliferators-activated receptors (PPARs) constitute a highly conserved set of ligand activated transcription factors in the nuclear hormone receptor subfamily. Selective modulation of PPAR could provide significant anti-diabetic activity with the reduction or elimination of side effects. These have increasingly become attractive targets for developing novel anti-type 2 diabetic ...

There are many of pathogen parasite species with different susceptibility profile to antiparasitic drugs. Unfortunately, almost QSAR models predict the biological activity of drugs against only one parasite species. Consequently, predicting the probability with which a drug is active against different species with a single unify model is a goal of the major importance. In so doing, we use Marko...

QSARs establish a quantitative relationship between chemical structures and their properties [1]. In theory, QSAR models can be used to predict the properties of chemical structures, provided their structural information is available. In the recent years, there had been a growing awareness about QSARs and their applications. This is quite evident from their use for regulatory purposes. A new Eu...

A common step in drug design is the formation of a quantitative structure-activity relationship (QSAR) to model an exploratory series of compounds. A QSAR generalizes how the structure of a compound relates to its biological activity. There is growing interest in the application of machine learning techniques in QSAR modeling research. However, no single technique can claim to be uniformly supe...