QSAR studies on imidazopyridazine derivatives as PfPK7 inhibitors

Identification of 3-Nitro-2,4,6-trihydroxybenzamide Derivatives as Photosynthetic Electron Transport Inhibitors by QSAR and Pharmacophore Studies

In the present investigation, quantitative structure-activity relationship (QSAR) analysis was performed on a data set consisting of structurally diverse compounds in order to investigate the role of their structural features on their photosynthetic electron transport Inhibitors. The best 2D-QSAR model was selected, having correlation coefficient r (2) = 0.8544 and cross-validated squared correlation coefficient q (2) = 0.7139 with external predictive ability of pred_r (2) = 0.7753. The results obtained in this study indicate that the presence of hydroxy and nitro groups, expressed by the SsOHcount and SddsN (nitro) count, is the most relevant molecular property determining efficiency of photosynthetic inhibitory. Molecular field analysis was used to construct the best k-nearest neighbor (kNN-MFA)-based 3D-QSAR model using SA-PLS method, showing good correlative and predictive capabilities in terms of [Formula: see text] and [Formula: see text]. The pharmacophore model includes three features viz. hydrogen bond donor, hydrogen bond acceptor, and one aromatic feature. The developed model was found to be predictive and can be used to design potent photosynthetic electron transport activities prior to their synthesis for further lead modification.

The effect of various atomic partial charge schemes to elucidate consensus activity-correlating molecular regions: a test case of diverse QSAR models

The estimation of atomic partial charges of the small molecules to calculate molecular interaction fields (MIFs) is an important process in field-based quantitative structure-activity relationship (QSAR). Several studies showed the influence of partial charge schemes that drastically affects the prediction accuracy of the QSAR model and focused on the selection of appropriate charge models that provide highest cross-validated correlation coefficient ([Formula: see text] or q(2)) to explain the variation in chemical structures against biological endpoints. This study shift this focus in a direction to understand the molecular regions deemed to explain SAR in various charge models and recognize a consensus picture of activity-correlating molecular regions. We selected eleven diverse dataset and developed MIF-based QSAR models using various charge schemes including Gasteiger-Marsili, Del Re, Merck Molecular Force Field, Hückel, Gasteiger-Hückel, and Pullman. The generalized resultant QSAR models were then compared with Open3DQSAR model to interpret the MIF descriptors decisively. We suggest the regions of activity contribution or optimization can be effectively determined by studying various charge-based models to understand SAR precisely.

Identification of 3-nitro-2, 4, 6-trihydroxybenzamide derivatives as photosynthetic electron transport inhibitors by QSAR and pharmacophore studies

In the present investigation, QSAR analysis was performed on a data set consist of structurally diverse compounds in order to investigate the role of its structural features on their Photosynthetic Electron Transport Inhibitors. The herbicidal activity co-related with certain topological and hydrophobicity based descriptors, 3D descriptors dependent steric, electrostatic and hydrophobic. The best 2D QSAR model was selected, having correlation coefficient r2 = 0.8544 and cross validated squared correlation coefficient q2 = 0.7139 with external predictive ability of pred_r2 = 0.7753 was developed. The results obtained in this study indicate that hydroxy and nitro groups, as expressed by the SsOHcount, SddsN (nitro) count, is the most relevant molecular property determining efficiency of photosynthetic inhibitory. Molecular field analysis was used to construct the best k-nearest neighbor (kNN-MFA)-based 3DQSAR model using SA-PLS method, showing good correlative and predictive capabilities in terms of q2 = 0.7694 and pred_r2 = 0.7381. The influences of steric, electrostatic and hydrophobic field effects generated by the contribution plots are discussed. The pharmacophore model includes three features viz. hydrogen bond donor, hydrogen bond acceptor, and one aromatic feature was developed. The developed model was found to be predictive and can be used to design potent Photosynthetic Electron Transport activities prior to their synthesis for further lead modification. The results obtained suggest that the 3-nitro-2, 4, 6-trihydroxybenzamide analogues represent promising candidates for the development of new active principles targeting photosynthesis to be used as herbicides.