Novel Eubacterium rectale inhibitor from Coriandrum sativum L. for possible prevention of colorectal cancer: a computational approach.

This research aims to screen out the effective bioactive compounds from Coriander (Coriandrum sativum L.), which may be novel potential inhibitors of Eubacterium rectale for the prevention of colorectal cancer (CRC). A series of 8 coriander-derived chemical compounds previously assessed for their anti-inflammatory, antioxidant, and antidiabetic activities were tested against Carbohydrate ABC transporter substrate-binding protein and compared to the standard inhibitor Acarbose, to support their use as novel Eubacterium rectale inhibitors. Herein, these derivatives were submitted to a thorough analysis of docking studies, in which detailed interactions of the selected phytocompounds with carbohydrate ABC transporter substrate-binding protein were revealed. Molecular docking analysis recommends Rutin, Gallocatechin, and Epigallocatechin as the most potential Eubacterium rectale inhibitors among the eight selected phytochemical compounds. Subsequently, the stability of the three selected phytochemical complexes was checked using molecular dynamics (MD) simulation at 100 ns and Molecular Mechanics combined with Poisson-Boltzmann Surface Area (MM-PBSA). The results show quite good stability for Rutin and Gallocatechin. In silico ADMET prediction was performed on the selected compounds, and the findings revealed a reasonably good ADMET profile for both Rutin and Gallocatechin. The current findings predict that Gallocatechin could be a better CRC preventive natural compound, and, further in vitro, in vivo and clinical studies may confirm its therapeutic potential.Communicated by Ramaswamy H. Sarma.

Molecular docking, molecular dynamics simulation, and ADMET analysis of levamisole derivatives against the SARS-CoV-2 main protease (MPro).

Introduction: The new species of coronaviruses (CoVs), SARS-CoV-2, was reported as responsible for an outbreak of respiratory disease. Scientists and researchers are endeavoring to develop new approaches for the effective treatment against of the COVID-19 disease. There are no finally targeted antiviral agents able to inhibit the SARS-CoV-2 at present. Therefore, it is of interest to investigate the potential uses of levamisole derivatives, which are reported to be antiviral agents targeting the influenza virus. Methods: In the present study, 12 selected levamisole derivatives containing imidazo[2,1-b]thiazole were subjected to molecular docking in order to explore the binding mechanisms between these derivatives and the SARS-CoV-2 Mpro (PDB: 7BQY). The levamisole derivatives were evaluated for in silico ADMET properties for wet-lab applicability. Further, the stability of the best-docked complex was checked using molecular dynamics (MD) simulation at 20 ns. Results: Levamisole derivatives and especially molecule N°6 showed more promising docking results, presenting favorable binding interactions as well as better docking energy compared to chloroquine and mefloquine. The results of ADMET prediction and MD simulation support the potential of the molecule N°6 to be further developed as a novel inhibitor able to stop the newly emerged SARS-CoV-2. Conclusion: This research provided an effective first line in the rapid discovery of drug leads against the novel CoV (SARS-CoV-2).

Identification of novel acetylcholinesterase inhibitors through 3D-QSAR, molecular docking, and molecular dynamics simulation targeting Alzheimer's disease.

Acetylcholinesterase (AChE) is a potential target for the development of small molecules as inhibitors for the therapy of Alzheimer's disease (AD). To design highly active acetylcholinesterase inhibitors, a three-dimensional quantitative structure-activity relationship (3D-QSAR) approach was performed on a series of N-benzylpyrrolidine derivatives previously evaluated for acetylcholinesterase inhibitory activity. The developed two models, CoMFA and CoMSIA, were statistically validated, and good predictability was achieved for both models. The information generated from 3D-QSAR contour maps may provide a better understanding of the structural features required for acetylcholinesterase inhibition and help to design new potential anti-acetylcholinesterase molecules. Consequently, six novel acetylcholinesterase inhibitors were designed, among which compound A1 with the highest predicted activity was subjected to detailed molecular docking and compared to the most active compound. Extra-precision molecular dynamics (MD) simulation of 50 ns and binding free energy calculations using MM-GBSA were performed for the selected compounds to validate the stability. These results may afford important structural insights needed to identify novel acetylcholinesterase inhibitors and other promising strategies in drug discovery.

Integrated 3D-QSAR, molecular docking, and molecular dynamics simulation studies on 1,2,3-triazole based derivatives for designing new acetylcholinesterase inhibitors.

Alzheimer's disease (AD) is a multifactorial and polygenic disease. It is the most prevalent reason for dementia in the aging population. A dataset of twenty-six 1,2,3-triazole-based derivatives previously synthetized and evaluated for acetylcholinesterase inhibitory activity were subjected to the three-dimensional quantitative structure-activity relationship (3D-QSAR) study. Good predictability was achieved for comparative molecular field analysis (CoMFA) (Q2 = 0.604, R2 = 0.863, rext 2 = 0.701) and comparative molecular similarity indices analysis (CoMSIA) (Q2 = 0.606, R2 = 0.854, rext 2 = 0.647). The molecular features characteristics provided by the 3D-QSAR contour plots were quite useful for designing and improving the activity of acetylcholinesterase of this class. Based on these findings, a new series of 1,2,3-triazole based derivatives were designed, among which compound A1 with the highest predictive activity was subjected to detailed molecular docking and compared to the most active compound. The selected compounds were further subjected to 20 ns molecular dynamics (MD) simulations to study the comparative conformation dynamics of the protein after ligand binding, revealing promising results for the designed molecule. Therefore, this study could provide worthy guidance for further experimental analysis of highly effective acetylcholinesterase inhibitors.

Prediction of potential inhibitors of SARS-CoV-2 using 3D-QSAR, molecular docking modeling and ADMET properties.

Coronavirus (COVID-19), an enveloped RNA virus, primarily affects human beings. It has been deemed by the World Health Organization (WHO) as a pandemic. For this reason, COVID-19 has become one of the most lethal viruses which the modern world has ever witnessed although some established pharmaceutical companies allege that they have come up with a remedy for COVID-19. To that end, a set of carboxamides sulfonamide derivatives has been under study using 3D-QSAR approach. CoMFA and CoMSIA are one of the most cardinal techniques used in molecular modeling to mold a worthwhile 3D-QSAR model. The expected predictability has been achieved using the CoMFA model (Q2 = 0.579; R2 = 0.989; R2test = 0.791) and the CoMSIA model (Q2 = 0.542; R2 = 0.975; R2test = 0.964). In a similar vein, the contour maps extracted from both CoMFA and CoMSIA models provide much useful information to determine the structural requirements impacting the activity; subsequently, these contour maps pave the way for proposing 8 compounds with important predicted activities. The molecular surflex-docking simulation has been adopted to scrutinize the interactions existing between potentially and used antimalarial molecule on a large scale, called Chloroquine (CQ) and the proposed carboxamides sulfonamide analogs with COVID-19 main protease (PDB: 6LU7). The outcomes of the molecular docking point out that the new molecule P1 has high stability in the active site of COVID-19 and an efficient binding affinity (total scoring) in relation with the Chloroquine. Last of all, the newly designed carboxamides sulfonamide molecules have been evaluated for their oral bioavailability and toxicity, the results point out that these scaffolds have cardinal ADMET properties and can be granted as reliable inhibitors against COVID-19.