Docking alignment-3D-QSAR of a new class of potent and non-chiral indole-3-carboxamide-based renin inhibitors

Abstract

Using generated conformations from docking analysis by CDOCKER algorithm, some 3D-QSAR models; CoMFA region focusing (CoMFA-RF) and CoMSIA have been created on a series of a new class of potent and non-chiral renin inhibitors. The satisfactory predictions were obtained by CoMFA-RF and CoMSIA based on docking alignment in comparison to CoMFA. Robustness and predictability of the models were further verified by using the test set, cross validation (leave one out and leave ten out), bootstrapping, and progressive scrambling. All-orientation search (AOS) strategy was used to acquire the best orientation and minimize the effect of the initial orientation of aligned compounds. The results of 3D-QSAR models are in agreement with docking results. Moreover, the resulting 3D CoMFA-RF/ CoMSIA contour maps and corresponding models were applied to design new and more active inhibitors.Hypertension is a main risk feature of high occurrence worldwide for cardiovascular diseases 1 . Different signals, for instance a drop in blood pressure, a decrease in the plasma sodium, or a reduction in the circulating volume, stimulate the release of renin from kidney 2 . Renin is an aspartic acid protease in the beginning of renin angiotensin system (RAS) cascade, one of the key regulators of blood pressure. The only known natural substrate for renin is angiotensinogen, and renin cleaves it to form a decapeptide, angiotensin I. Then angiotensin converting enzyme (ACE) catalyses conversion of angiotensin I to an octapeptide vasoconstrictor angiotensin II, which has a direct action on proximal tubule, to increase reabsorbing sodium and moreover motivate adrenal cortex to sprinkle aldostrone, that in turn acts upon the distal nephron to retain sodium leading to fluid retention 3 . ACE inhibitors, increase the level of angiotensin I, and do not block manufacture of angiotensin II, that are independent from ACE. Also ACE is

Docking and pharmacophore‐based alignment comparative molecular field analysis three‐dimensional quantitative structure–activity relationship analysis of dihydrofolate reductase inhibitors by linear and nonlinear calibration methods

“…The 3D structural alignment is a key component in 3D‐QSAR modeling and affects the results of the CoMFA statistical analysis . Alignment was conducted by constructing a qualitative pharmacophore model obtained using 10 compounds including 5, 35, and 36 as active compounds; 26 as inactive; and 12, 16, 17, 21, 22, and 32 as modestly active ones, which was further applied in the development of CoMFA models.…”

“…Energy minimizations were then performed using the Tripos force field with a distance-dependent dielectric and the Powell conjugate gradient algorithm (convergence criterion of 0.01 kcal/mol/Å) [39]. The 3D structural alignment is a key component in 3D-QSAR modeling and affects the results of the CoMFA statistical analysis [40][41][42]. Alignment was conducted by constructing a qualitative pharmacophore model obtained using 10 compounds including 5, 35, and 36 as active compounds; 26 as inactive; and 12, 16, 17, 21, 22, and 32 as modestly active ones, which was further applied in the development of CoMFA models.…”