In silico design of new pyrimidine-2,4-dione derivatives as promising inhibitors for HIV Reverse Transcriptase-associated RNase H using 2D-QSAR modeling and (ADME/Tox) properties

The main target of present QSAR modeling is to pave the way for the development of new pyrimidine-2,4-dione derivatives and predict their HIV reverse transcriptase-associated RNase H inhibitory activity. To accelerate this process, linear and non-linear models of thirty-nine pyrimidine-2,4-dione derivatives have been constructed by exploiting PCA, MLR, and MNLR statistical techniques available in the XLSTAT software, as well as the (DFT/ Beck3LYP/6-31G (d,p)) approach. Among the 16 quantum and physicochemical descriptors measured, only four optimal molecular descriptors have been employed to perform QSAR models, i.e., density, number of H-bond acceptors, octanol/water partition coefficient, and LUMO energy. The Loo/cross-validation procedure, the Y-scrambling test, Golbraikh-Tropsha’s criteria and the applicability area have all been utilized to evaluate the linear model's performance accuracy. Likewise, the nonlinear model's predictive power has been measured internally through the Loo/cross-validation procedure with coefficient R_(CV(LOO))^2  and externally through test set compounds with external prediction coefficient R_pred^2. Herein, both MLR and MNLR models which exhibited excellent performance and met OECD criteria were exploited to predict inhibitory activities. By analyzing the structural characteristics of the studied compounds encoded in the afore-mentioned descriptors along with their effects on pIC50 inhibitory activity, we have been able to design eleven new chemical inhibitors. All of these inhibitors with new substituents displayed significantly higher HIV RT-associated RNase H inhibitory activities than the existing ones, as well as satisfactory results in silico ADME/Toxicity assessments

in silico studies of 1,4-disubstituted 1,2,3-triazole with amide functionality antimicrobial evaluation against Escherichia coli using 3D-QSAR, molecular docking, and ADMET properties

E. coli are microbes responsible for the development of urinary tract cancer in women, therefore, the discovery of new antimicrobial agents by computer chemistry allows to improve and provide the new compounds with antimicrobial activity, it is necessary to carry out a 3D-QSAR (quantitative three-dimensional structure-activity) study of antimicrobial analogues to study the validity of this study by statistical parameters. We established the 3D-QSAR model from the comparative analysis of the molecular field (CoMFA)and the comparative analysis of molecular similarity indices (CoMSIA), The most tabular modulus of which is obtained by the CoMFA model (Q2=0,71; R2=0.98; R=0.97) and the best comparative model of acceptor and hydrophobic molecular similarity indices (CoMSIA /AH) (Q2=0.69; R2 = 0.96; R =0.94). To test the validity of the two models, we need to compute the SEE, t-F and their y-randomization for the training set, and the parameters of k. Roy de A. Golbraikh, A. Tropsha for the test set. The CoMFA model analysis shows that the activity of the antimicrobial molecules in our study is influenced by the steric effect and by the acceptor effect of hydrogen for the CoMSIA/AH model, in particular the molecular docking results we show that the interest of amino acids has a direct influence on antimicrobial activity, based on this result we have proposed 4 molecules with antimicrobial activity. These molecules are tested by analyzing their ADMET properties and their drug similarity

CoMFA Topomer, CoMFA, CoMSIA, HQSAR, docking molecular, dynamique study and ADMET study on phenyloxylpropyl isoxazole derivatives for coxsackie virus B3 virus inhibitors activity

Absent of drugs to treat entervirus infections, notably the coxsackievirus B3 virus (CVB3) which causes acute and chronic illnesses, the world remains in need of new antiviral drugs. The main objective of this work is the quantitative analysis of the structure-activity relationship (QSAR) of a series of phenyloxy propy isoxazoles derivatives against the CVB3 virus using two 2D approaches using the HQSAR method and 3D using the Topomer CoMFA and CoMFA and CoMSIA methods, followed by molecular docking analysis to validate established patterns and understand the mechanism of receptor-ligand interaction.  The results of the 2D / 3D QSAR models are quite satisfactory and give significant statistical results: R2 = 0.953, Q2 = 0.819, R2ext = 0.750 for the HQSAR, R2 = 0.980, Q2 = 0.83, R2 ext = 0.749 for the CoMFA topomer, R2 = 0.977, Q2 = 0.748, R2 ext = 0.843 for CoMFA, R2 = 0.962, Q2 = 0.804, R2 ext = 0.953 for CoMSIA.  It can be noted that these four models exceeded the external validation criteria used with success and respected the limits of the criteria of Tropsha and Glorbaikh. Based on the results obtained from the four models, we proposed a candidate for each model as an inhibitory agent against CVB3. Docking analyzes and molecular simulation were performed to understand the mechanism of interactions of these four designed compounds within the receptor active site. small-sized electron donor groups molecular docking shows that the proposed compounds performed greater interactions than the more active compound in the database. However, the groups added for the molecules A1, A2, A3, A4 help to create additional interactions between these ligands and the residues to stabilize the conformation of the ligands at the level of the binding pocket. The stability and binding modes of compounds A1, A2 and the most active compound in the data set were evaluated by molecular dynamics simulations during a simulation time of 100 ns. It is shown that the interactions of the selected compounds are stable and fluctuate weakly in the complex. Free energy calculations based on the MM-GBSA method confirmed that the two designed compounds A1 and A2 were able to form bonds in the protein cavity. In addition, the ADMET study and the five-parameter Lipinski's rule prediction were estimated to ensure that the proposed candidates are viable drugs with synthetic accessibility. These results can be used for the discovery of new drugs and can solve the problem of resistance of the CVB3 viru