in the current study, both ligand-based molecular docking and receptor-based quantitative structure activity relationships (qsar) modeling were performed on 35 diaryl urea derivative inhibitors of v600e b-raf. in this qsar study, a linear (multiple linear regressions) and a nonlinear (partial least squares least squares support vector machine (pls-ls-svm)) were used and compared. the predictive...

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...

QSAR (quantitative structure-activity relationship) modeling is one of the well developed areas in drug development through computational chemistry. Similar molecules with just a slight variation in their structure can have quit different biological activity. This kind of relationship between molecular structure and change in biological activity is center of focus for QSAR Modeling. Predictions...

Fullerene (C60) is enhanced with pyrrolidine group to produce fulleropyrrolidine which is considered as one of the most important derivatives of fullerene. Fulleropyrrolidine is further modified in order to enhance its solubility which in turn could enhance its biological applications. Accordingly this work is dedicated to modify fulleropyrrolidine carbodithioic acid as NO2 group introduced at ...

In the present work, we have applied group quantitative structure–activity relationships (G-QSAR) for exploring the relationship between the structures of a new emerging family of 2-{[2-(1Himidazol-1-yl)ethyl]sulfanyl}-1H-benzimidazole derivatives and their antiprotozoal activities. We have developed descriptive models, in order to aid in further optimization and development of newer antiprotoz...

Machine learning represents a milestone in data-driven research, including material informatics, robotics, and computer-aided drug discovery. With the continuously growing virtual synthetically available chemical space, efficient robust quantitative structure–activity relationship (QSAR) methods are required to uncover molecules with desired properties. Herein, we propose variable-length-array ...