The QSAR Toolbox is a free software supporting chemical hazard assessment, co-developed by ECHA and OECD. It helps to minimise testing on animals. Its results are based on existing experimental data and knowledge on the mechanisms of toxicity.
vlife qsar software free 21
The curated chemical structures were used to calculate molecular descriptors using the free and open-source software PaDEL [96]. PaDel was used to calculate only 1D and 2D descriptors; 3D descriptors were avoided even though they could potentially add useful chemical information about the molecules [27, 97]. We decided to use only 2D descriptors to keep the models as simple as possible, to speed up predictions, and to avoid repeatability problems associated with 3D descriptor values. These can arise due to differences between conformers, especially with very flexible molecules requiring geometry optimization. These differences can affect the predictability of the resulting chemical properties [98, 99]. To avoid inconsistencies due to explicit hydrogen atoms and interpretation of aromatic rings by the software during descriptor calculations, the aromaticity option was set to auto-detection as suggested by the PaDEL developers to fix known issues [100]. The need for the auto-detection setting was verified by performing tests that confirmed that PaDEL can interpret aromaticity in different ways for the same chemical, depending on whether it is provided in MOL, SMILES, or SDF format, and can provide different values for certain descriptors, such as number of aromatic rings.
A successful 3D-QSAR study was performed to establish the relationship between the spatial 3D pharmacophoric features and MAGL activity of a class of benzotriazol-1-yl carboxamide derivatives synthesized by Morera et al . [sup][19] The present 3D-QSAR study was performed with the dataset of 37 benzotriazol-1-yl carboxamide derivatives with well-defined MAGL inhibitory activity given as IC [sub]50 values in nanomolar concentration. For the correlation purpose, IC [sub]50 values were then converted to their molar values, and subseq uently, free energy-related terms were calculated, i.e. −log (1/IC [sub]50 ). The compounds with their inhibition data are summarized in [Table 1]. This dataset was then chosen for generating common pharmacophore hypotheses and then performing QSAR analysis. PHASE 3.5 module of Maestro-9.4 molecular modeling software was used to generate 3D pharmacophore models for selected series of MAGL inhibitors (PHASE 3.5, Schrö dinger, LLC, 2013). A pharmacophore conveys the characteristics of the three-dimensional arrangement of the pharmacophoric elements that are supposed to be critical for binding. A given hypothesis may be combined with known activity data to create a 3D-QSAR model that identifies the overall aspects of molecular structure which direct activity. The structures were sketched using maestro builder toolbar and were imported to develop pharmacophore model panel of the PHASE with their respective activity values. The ligands were assigned as actives with a threshold of pIC [sub]50 > 7.90 and inactives with a threshold of pIC [sub]50 2ff7e9595c
Comments