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Acetylcholinesterase is used as a key target in the treatment of Alzheimer's disease. Recently, a series of new spirooxindolepyrrolidine derivatives were synthesized and preliminarily shown to have antibacterial activity and potential acetylcholinesterase inhibitors. For this reason, the current investigation examine 35 compounds in this series as acetylcholinesterase inhibitors and compare them to clinical trials using different molecular modeling methods, including molecular docking/dynamics simulations, MEP analysis, bioisosteric replacement, and ADME-T prediction. Molecular docking studies describe the hierarchical structure of the interaction between spirooxindolepyrrolidine derivatives and the AChE receptor, showing that compounds L27 and L28 have a high affinity (Score energies: -5.858 and -5.961 kcal/mol, respectively) with the binding site of the studied target. These results were confirmed by slighter conformational changes during the MD simulation analysis of the AChE-L27 and AChE-L28 complexes compared to tacrine and donepezil. Furthermore, the bioisosteric substitution approach was successfully applied; proposing two new analogs of each compound showing low energy scores ​​ and an important number of hydrogen bonds. In addition, ADME-Tox prediction and the different physicochemical properties of the best compounds (L27 and L28) were also used to evaluate their relevance as drug candidates they're and validate their favorable oral bioavailability. Thus, an in silico study showed that compounds L27, L28, and their analogs exhibit strong binding affinity towards the active site residues of the AChE target, suggesting that they may be potent inhibitors of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

In this paper, a data set of [3H] diazepam derivatives was analyzed using various computational methods: molecular docking/dynamic simulations, and QSAR analysis. The main aims of these studies are to understand the binding mechanisms by which benzodiazepines allosterically modulate GABAA receptor α1β2γ2 subtypes, from inducing neuronal inhibition at lower doses to the anesthetic effect at higher doses, and also, to define the structural requirements that contribute to improving the response of GABAA/α1β2γ2 receptor to benzodiazepine drugs. The results of the molecular docking study allowed selecting Ro12-6377 and proflazepam as the best modulators for the four binding sites simultaneously. Subsequently, the stability of the selected complexes was investigated by performing molecular dynamics simulation. The latter confirmed the features of both modulators to exert direct effects on the chloride-channel lining residues. Pharmacokinetics and drug-likeness profile were assessed through in silico tool. Furthermore, a QSAR analysis was conducted using an improved vemolecular dynamics simulations proposed byrsion of PLS regression. The goodness of fit and the predictive power of the resulting PLS model were estimated according to internal and external validation parameters: R2 = 0.632, R2adj = 0.584, F = 12.806; p-value = 6.2050e − 07, Q2loo = 0.639, and Q2F3 = 0.813. Clearly, the obtained results ensure the predictive ability of the developed QSAR model for the design of new high-potency benzodiazepine drugs. [ABSTRACT FROM AUTHOR]

Monoamine oxidase B and Adenosine A2A receptors are used as key targets for Parkinson's disease. Recently, hMAO-B and hA2AR Dual-targets inhibitory potential of a novel series of Phenylxanthine derivatives has been established in experimental findings. Hence, the current study examines the interactions between 38 compounds of this series with hMAO-B and hA2AR targets using different molecular modeling techniques to investigate the binding mode and stability of the formed complexes. A molecular docking study revealed that the compounds L24 ((E)-3-(3-Chlorophenyl)-N-(4-(1,3-dimethyl-2,6-dioxo-2,3,6,7-tetrahydro-1H-purin-8-yl) phenyl) acrylamide and L32 ((E)-3-(3-Chlorophenyl)-N-(3-(1,3-dimethyl-2,6-dioxo-2,3,6,7-tetrahydro-1H-purin-8-yl)phenyl)acrylamide) had a high affinity (S-score: −10.160 and −7.344 kcal/mol) with the pocket of hMAO-B and hA2AR targets respectively, and the stability of the studied complexes was confirmed during MD simulations. Also, the MEP maps of compounds 24 and 32 were used to identify the nucleophilic and electrophilic attack regions. Moreover, the bioisosteric replacement approach was successfully applied to design two new analogs of each compound with similar biological activities and low energy scores. Furthermore, ADME-T and Drug-likeness results revealed the promising pharmacokinetic properties and oral bioavailability of these compounds. Thus, compounds L24, L32, and their analogs can undergo further analysis and optimization in order to design new lead compounds with higher efficacy toward Parkinson's disease. [ABSTRACT FROM AUTHOR]

In the present work, a combined approach based on conceptual-DFT formalism and molecular docking simulations were performed to investigate the chemical reactivity of six Benzodiazepine analogs. Chemical reactivity descriptors derived from the conceptual DFT were determined and discussed to explain the global and local reactivity of the six studied analogs. Also, long-range interactions were studied using the quantitative analyses of molecular electrostatic potential (MEP) on van der Waals surface to identify the nucleophilic and electrophilic sites. Moreover, a statistical analysis was performed to assess the robustness of atomic charges to the basis set. The results revealed that Hirshfeld population analysis (HPA) was the most efficient for this purpose. Molecular docking simulations were performed to predict the binding affinities of the issued molecules and estimate the binding poses into four binding sites, three of them were recently discovered, located in GABAA receptor. [ABSTRACT FROM AUTHOR]

To establish a quantitative structure-activity relationship, 54 indazole derivatives were analyzed by multiple linear regression MLR. The DFT-B3LYP method, with the basis set 6-311G, was performed to define the structure, chemical reactivity and properties of the compounds. This study was accompanied by molecular docking, global reactivity descriptors, absorption, distribution, metabolism and elimination (ADME) properties on a series of 21 compounds of selective estrogen receptor degraders (SERDs) that present the most active compounds from the dataset. The MLR regression equation displayed a good agreement between fitted and observed biological activities. A high average R2 Boots greater than 0.5 indicates that the obtained model has good predictive power and robustness. In addition, an average value of R2 pred (0.57) approximately equal to 0.6 may be taken as an indicator of good external predictability. The interactions between the most active compounds from the indazole series and ERα targets were explored through a molecular docking to elucidate the binding mode between the studied compounds and corresponding protein. Based on this study compounds 14 , 43 , 8 and 45 have no violated Lipinski's rule of five and Veber's rule, suggesting that these compounds would not have problems with oral bioavailability. Most of global reactivity results have an agreement with those obtained in this docking study. Image 1 • Effective QSAR model for estrogen receptor alpha (ER-α) positive antagonists have been developed. • Molecular docking was deployed to explore the binding features between estrogen receptor alpha and antagonists. • Analyzed the molecular reactivity for more understanding of the relationship between structure, stability, and reactivity. • Lipinski's rule of five and Veber's rule, suggesting evaluating the oral bioavailability. [ABSTRACT FROM AUTHOR]