Development of non-peptide ACE inhibitors as novel and potent cardiovascular therapeutics: An in silico modelling approach

Angiotensin-converting enzyme (ACE) inhibitors have been acknowledged as first-line agents for the treatment of hypertension and a variety of cardiovascular disorders. In this context, quantitative structure–activity relationship (QSAR) models for a series of non-peptide compounds as ACE inhibitors are developed based on Simplified Molecular Input-Line Entry System (SMILES) notation and local graph invariants. Three random splits into the training and test sets are used. The Monte Carlo method is applied for model development. Molecular docking studies are used for the final assessment of the developed QSAR model and the design of novel inhibitors. The statistical quality of the developed model is good. Molecular fragments responsible for the increase/decrease of the studied activity are calculated. The computer-aided design of new compounds, as potential ACE inhibitors, is presented. The predictive potential of the applied approach is tested, and the robustness of the model is proven using different methods. The results obtained from molecular docking studies are in excellent correlation with the results from QSAR studies. The presented study may be useful in the search for novel cardiovascular therapeutics based on ACE inhibition.     

Monte Carlo-based QSAR modeling of dimeric pyridinium compounds and drug design of new potent acetylcholine esterase inhibitors for potential therapy of <Emphasis Type="Italic">myasthenia gravis</Emphasis>

The Monte Carlo method was used for QSAR modeling of dimeric pyridinium compounds as acetylcholine esterase inhibitors. QSAR model was developed for a series of 39 dimeric pyridinium compounds. QSAR models were calculated with the representation of the molecular structure by the simplified molecular-input line-entry system. One split into the training and test set have been examined. The statistical quality of the developed model is very good. The calculated model for dimeric pyridinium derivatives had following statistical parameters: r ² = 0.9477 for the training set and r ² = 0.9332 the test set. Structural indicators considered as molecular fragments responsible for the increase and decrease in the inhibition activity have been defined. The computer-aided design of new dimeric pyridinium compounds potential acetylcholine esterase inhibitors with the application of defined structural alerts has been presented.     

咪唑啉酮类除草剂的三维构效关系研究

从三维角度出发,采取不同的构象搜索方法得到了咪唑酮类化合物分子的活性构象。利用比较分子场分析方法进一步证实了模板分子构象的正确性。并从静电场、立体场及活性关系等方面进行了三维定量构效关系研究,得到了具有较强预测能力的QSAR模型。     

1－环丙基－5，7，8取代－6－氟－1，4－二氢－4－氧－3－喹啉羧酸定量构效关系的比较分子力场分析研究

利用３Ｄ－ＱＳＡＲ中的比较分子力场分析法（ＣｏＭＦＡ）研究了标题化合物的定量构效关系。通过不同探针与空间网格点间隙的对比研究，发现以　、空间网格点间隙２０ｎｍ结果为最优。从　值来看，ＣｏＭＦＡ计算得到的模型有很高的预测性。依据ＣｏＭＦＡ系数图设计一些新化合物并预测了它们的活性，结果表明：对抑制革兰氏阳性菌有数种化合物的活性比迄今合成的化合物要高。     

QSAR for the Organophosphate-Induced Inhibition and ‚Aging‚ of the Enzyme Neuropathy Target Esterase (NTE)

Abstract

QSAR was devised for the neuropathy potency of various organophosphate (OP) compounds. The neuropathy-target-esterase (NTE) inhibition data were either obtained from the literature for a number of OP compounds or were determined experimentally for methamidophos, acephate, coumaphos and EPN. Aging Index that determined whether or not an OP would age NTE, correlated with molecular depth (MD) and the index density dipole-moment (density? Ω) (Eq. (1)). The t_1/2 values that represented the time (min) during which 50% of the OP-inhibited brain NTE undergoes ?aging‘, correlated with the topological indices Dif₃ and 1/Dif₄ (Eq. (2)). Log₁₀I₅₀ for AChE that determined the OP concentration causing 50% inhibition in AChE activity, correlated with E_bond and Charge^?1 (Eq. 3)). Log₁₀I₅₀ for NTE correlated with 1 HS² and H-Bonding (Eq. (4)). The (Log₁₀I₅₀NTE)/(Log₁₀I₅₀AChE) ratio that determined an OPs neuropathy potential relative to its cholinergic toxicity potential, correlated with log P and Log₁₀Polarity (Eq. (6)). Equation (3) accurately predicted AChE inhibition by methamidophos, coumaphos and EPN, but not by acephate. Equations (1), (2), (4)–(6), accurately predicted their respective biological indices. Therefore, it is proposed that the QSAR models developed in this study may accurately predict the neuropathy potential of OP compounds. The only exception is Eq. (3) that did not accurately predict the acephate-induced inhibition of AChE, possibly because acephate and other OPs inhibit the enzyme by distinct mechanisms.     

Molecular design of N,N-disubstituted 2-aminothiazolines as selective carboxylesterase inhibitors

Selective carboxylesterase inhibitors are employed as modulators of hydrolytic metabolism of ester or amide-containing drugs. Using the Molecular Field Topology Analysis (MFTA), the models for the relationships between the structures and inhibitory activities of 5-halomethyl-2-aminothiazolines against acetylcholinesterase, butyrylcholinesterase, and carboxylesterase were built, the molecular design was performed, and a focused library of potentially active and selective carboxylesterase inhibitors was proposed.     

Three-dimensional quantitative structure activity relationship (QSAR) of cytotoxic active 3,5-diaryl-4,5-dihydropyrazole analogs: a comparative molecular field analysis (CoMFA) revisited study

ABSTRACT: In vitro antitumor evaluation of the synthesized 46 compounds of 3,5-diaryl-4,5-dihydropyrazoles against EAC cell lines and 3D QSAR study using pharmacophore and Comparative Molecular Field Analysis (CoMFA) methods were described. CoMFA derived QSAR model shows a good conventional squared correlation coefficient r2 and cross validated correlation coefficient r2 cv 0.896 and 0.568 respectively. In this analysis steric and electrostatic field contribute to the QSAR equation by 70% and 30% respectively, suggesting that variation in biological activity of the compounds is dominated by differences in steric (van der Waals) interactions. To visualize the CoMFA steric and electrostatic field from partial least squares (PLS) analysis, contour maps are plotted as percentage contribution to the QSAR equation and are associated with the differences in biological activity. BACKGROUND: Pyrazole derivatives exhibit a wide range of biological properties including promising antitumor activity. Furthermore, Aldol condensation assisted organic synthesis has delivered rapid routes to N-containing heterocycles, including pyrazoles. Combining these features, the use of chalconisation-assisted processes will provide rapid access to a targeted dihydropyrazoles library bearing a hydrazino 3D QSAR study using pharmacophore and Comparative Molecular Field Analysis (CoMFA) methods were described for evaluation of antioxidant properties. RESULTS: Chalcones promoted 1 of the 2 steps in a rapid, convergent synthesis of a small library of hydrazinyl pyrazole derivatives, all of which exhibited significant antitumor activity against Ehrlich Ascites Carcinoma (EAC) human tumor cell line comparable to that of the natural anticancer doxorubicin, as a reference standard during this study. In order to understand the observed pharmacological properties, quantitative structure-activity relationship (3D QSAR) study was initiated. CONCLUSIONS: Chalcones heating provides a rapid and expedient route to a series of pyrazoles to investigate their chracterization scavenging properties. Given their favorable properties, in comparison with known anticancer, these pyrazole derivatives are promising leads for further development and optimization.     

3D-QSAR and molecular modeling of HIV-1 integrase inhibitors

Three-dimensional quantitative structure-activity relationship (3D QSAR) methods were applied on a series of inhibitors of HIV-1 integrase with respect to their inhibition of 3-processing and 3-end joining steps in vitro.The training set consisted of 27 compounds belonging to the class of thiazolothiazepines. The predictive ability of each model was evaluated using test set I consisting of four thiazolothiazepines and test set II comprised of seven compounds belonging to an entirely different structural class of coumarins. Maximum Common Substructure (MCS) based method was used to align the molecules and this was compared with other known methods of alignment. Two methods of 3D QSAR: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were analyzed in terms of their predictive abilities. CoMSIA produced significantly better results for all correlations. The results indicate a strong correlation between the inhibitory activity of these compounds and the steric and electrostatic fields around them. CoMSIA models with considerable internal as well as external predictive ability were obtained. A poor correlation obtained with hydrophobic field indicates that the binding of thiazolothiazepines to HIV-1 integrase is mainly enthalpic in nature. Further the most active compound of the series was docked into the active site using the crystal structure of integrase. The binding site was formed by the amino acid residues 64-67, 116, 148, 151-152, 155-156, and 159. The comparison of coefficient contour maps with the steric and electrostatic properties of the receptor shows high level of compatibility.     

DFT‐based QSAR study and molecular design of AHMA derivatives as potent anticancer agents

A quantitative structure–activity relationship (QSAR) of 3‐(9‐acridinylamino)‐5‐hydroxymethylaniline (AHMA) derivatives and their alkylcarbamates as potent anticancer agents has been studied using density functional theory (DFT), molecular mechanics (MM+), and statistical methods. In the best established QSAR equation, the energy (E_NL) of the next lowest unoccupied molecular orbital (NLUMO) and the net charges (Q_FR) of the first atom of the substituent R, as well as the steric parameter (MR₂) of subsituent R₂ are the main independent factors contributing to the anticancer activity of the compounds. A new scheme determining outliers by “leave‐one‐out” (LOO) cross‐validation coefficient (q) was suggested and successfully used. The fitting correlation coefficient (R²) and the “LOO” cross‐validation coefficient (q²) values for the training set of 25 compounds are 0.881 and 0.829, respectively. The predicted activities of 5 compounds in the test set using this QSAR model are in good agreement with their experimental values, indicating that this model has excellent predictive ability. Based on the established QSAR equation, 10 new compounds with rather high anticancer activity much greater than that of 34 compounds have been designed and await experimental verification. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2007     

Pharmacophore mapping and electronic feature analysis for a series of nitroaromatic compounds with antitubercular activity

A five point pharmacophore was generated using PHASE for a series of nitroaromatic compounds and their congeners as antitubercular agents. The generated pharmacophore yielded significant 3D‐QSAR model with r² of 0.890 for a training set of 92 molecules. The model also showed excellent predictive power with correlation coefficient Q² of 0.857 for a test set of 31 compounds. The pharmacophore indicated that presence of a nitro group, a piperazine moiety, one aromatic ring feature and two acceptor features are necessary for potent antitubercular activity. The pharmacophore was supported by electronic property analysis using density functional theory (DFT) at B3LYP/3–21*G level. Molecular electrostatic profile of the compounds was consistent with the generated pharmacophore model, particularly appearance of localized negative potential regions near both the oxygen atoms of nitro group extending laterally to the isoxazole ring system/amide bond in the most active compounds. Calculated data further revealed that all active compounds have smaller LUMO energies located over the nitro group, furan ring, and isoxazole ring/amide bond attached to it. Higher negative values of LUMO energies concentrated over the nitro group are indicative of the electron acceptor capacity of the compounds, suggesting that these compounds are prodrugs and must be activated by TB‐nitroreductase. The results obtained from this study should aid in efficient design and development of nitroaromatic compounds as antitubercular agents. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Identification of SARS-CoV-2 Receptor Binding Inhibitors by In Vitro Screening of Drug Libraries

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the coronavirus disease 2019 (COVID-19) global pandemic. The first step of viral infection is cell attachment, which is mediated by the binding of the SARS-CoV-2 receptor binding domain (RBD), part of the virus spike protein, to human angiotensin-converting enzyme 2 (ACE2). Therefore, drug repurposing to discover RBD-ACE2 binding inhibitors may provide a rapid and safe approach for COVID-19 therapy. Here, we describe the development of an in vitro RBD-ACE2 binding assay and its application to identify inhibitors of the interaction of the SARS-CoV-2 RBD to ACE2 by the high-throughput screening of two compound libraries (LOPAC^®1280 and DiscoveryProbeTM). Three compounds, heparin sodium, aurintricarboxylic acid (ATA), and ellagic acid, were found to exert an effective binding inhibition, with IC50 values ranging from 0.6 to 5.5 µg/mL. A plaque reduction assay in Vero E6 cells infected with a SARS-CoV-2 surrogate virus confirmed the inhibition efficacy of heparin sodium and ATA. Molecular docking analysis located potential binding sites of these compounds in the RBD. In light of these findings, the screening system described herein can be applied to other drug libraries to discover potent SARS-CoV-2 inhibitors.