On the Prediction of the Enantioselectivity of Candida rugosa Lipase by Comparative Molecular Field Analysis

Comparative molecular field analysis (CoMFA) was used to derive a quantitative substrate model for the enzymatic resolution of norbornanol esters by the lipase of Candida rugosa. Within these calculations, the steric and electrostatic interactions of both enantiomers and the differences in the corresponding two fields were used for the correlation of the substrate structure with the enantioselectivity of the hydrolysis. Different alignments of the molecules were used to improve the model.     

Structural insights of PA-824 derivatives: ligand-based 3D-QSAR study and design of novel PA824 derivatives as anti-tubercular agents

Abstract

With the purpose of designing novel chemical entities with improved inhibitory potencies against drug-resistant Mycobacterium tuberculosis, the 3D- quantitative structure–activity relationship (QSAR) studies were carried out on biphenyl analogs of the tuberculosis (TB) drug, PA-824. Anti-mycobacterial activity (MABA) was considered for the 3D-QSAR studies using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The best CoMFA and CoMSIA models were found statistically significant with cross-validated coefficients (q²) of 0.784 and 0.768, respectively, and conventional coefficients (r²) of 0.823 and 0.981, respectively. The cross-validated and the external validation results revealed that both the CoMFA and CoMSIA models possesses high accommodating capacities and they would be reliable for predicting the pMIC values of new PA-824 derivatives. Based on the models and structural insights, a series of new PA-824 derivatives were designed and the anti-mycobacterial activities of the designed compounds were predicted based on the best 3D-QSAR model. The predicted data results suggest the designed compounds are more potent than existed ones.     

Molecular modelling studies on d-annulated benzazepinones as VEGF-R2 kinase inhibitors using docking and 3D-QSAR

Chemotypes comprising the d-annulated 1,3-dihydro-2H-1-benzazepin-2-one scaffold derived from the paullone structure were found to be potent vascular endothelial growth factor receptor 2 (VEGF-R2) kinase inhibitors. Three-dimensional quantitative structure-activity relationship (3D-QSAR) and docking studies were performed on a series of d-annulated benzazepinones with VEGF-R2 kinase inhibition activities. The comparative molecular field analysis and comparative molecular similarity indices analysis models using 32 molecules in the training set gave r²_cv values of 0.811 and 0.769, r² values of 0.962 and 0.953, respectively. 3D contour maps generated from the two models revealed that the electron-withdrawing groups at R₁ and the bulky, electron-withdrawing as well as hydrogen bond donor groups at R₂ position are favourable; the bulky, hydrogen bond acceptor substituent at R₃ and the minor groups at R₄ position may benefit the potency. We have designed a series of novel VEGF-R2 inhibitors by utilizing the SAR results revealed in the present study, which were predicted with excellent potencies in the developed models. The results may aid in designing of potential VEGF-R2 inhibitors with better activities.     

Evaluation of structural features in fungal cytochromes P450 predicted to rule catalytic diversification

Fungi belong to the large kingdom of lower eukaryotic organisms encompassing yeasts along with filamentous and dimorphic members. Microbial P450 enzymes have contributed to exploration of and adaptation to diverse ecological niches such as conversion of lipophilic compounds to more hydrophilic derivatives or degradation of a vast array of environmental toxicants. To better understand diversification of the catalytic behavior of fungal P450s, detailed insight into the molecular machinery steering oxidative attack on the distinctly structured endogenous and xenobiotic substrates is of preeminent interest. Based on a general, CYP102A1-related template the bulk of predicted substrate/inhibitor-binding determinants were shown to cluster near the distal heme face within the six known substrate recognition sites (SRSs) made up by the α-helical B′/F/G/I tetrad, the B′–C interhelical loop and strands of the β6-sheet, population density being highest in the structurally flexible SRS-1 and SRS-4 domains, showing a low degree of conservation. Reactivity toward ligands favorably coincides with the lipophilicity/hydrophilicity profile and bulkiness of critical amino acids acting as selective filters. Some decisive elements may also serve in maintenance of catalytic competence via their action as gatekeepers directing substrate access/positioning or stabilizers of the heme environment enabling dioxygen activation. Non-SRS residues seem to control spin state equilibria and attract redox partners by electrostatic forces. Of note, the inhibitory potency of azole-type fungicides is likely to arise from perturbation of the complex interplay of the mechanistic principles addressed above. Knowledge-supported exploitation of the topological data will be helpful in the manufacture of commodity/specialty chemicals as well as therapeutic agents. Also, engineered fungal P450s may be used to improve pollutant-specific bioremediation of contaminated soils.     

QSAR studies on the human sirtuin 2 inhibition by non-covalent 7,5,2-anilinobenzamide derivatives

Abstract

Sirtuin 2 is a key enzyme in gene expression regulation that is often associated with tumor proliferation control and therefore is a relevant anticancer drug target. Anilinobenzamide derivatives have been discussed as selective sirtuin 2 inhibitors and can be developed further. In the present study, hologram and three-dimensional quantitative structure–activity relationship (HQSAR and 3D-QSAR) analyses were employed for determining structural contributions of a compound series containing human sirtuin-2-selective inhibitors that were then correlated with structural data from the literature. The final QSAR models were robust and predictive according to statistical validation (q² and r²_pred values higher than 0.85 and 0.75, respectively) and could be employed further to generate fragment contribution and contour maps. 3D-QSAR models together with information about the chemical properties of sirtuin 2 inhibitors can be useful for designing novel bioactive ligands.

Communicated by Ramaswamy H. Sarma     

Models of Monoamine Oxidase A and B Active Sites Obtained by using 3D QSAR with CoMFA Analysis

Abstract

The monoamine oxidase catalyses the oxidative deamination of neuroactive amines. This enzyme exists in two forms A and B, which differ by substrates preference and inhibitors specificity. Investigation of the structures of these enzymes and design new selective inhibitors are of greatly interesting since MAO A inhibitors are used in therapeutic practice as antidepressants and MAO B inhibitors – in the treatment Parkinson's diseases. The three dimension structures of monoamine oxidases are still unknown. Therefore, one of the most perspective approach to define significant features of structure active site is method based on analysis of structure-activity relationship (3D QSAR) with comparison of molecular fields analysis (CoMFA) allowing to get the spatial distribution of important properties affecting the activity.

In present study we investigate the structures of active sites MAO A and B using 16 pyrazinocarbazole derivatives in variant conformation. Majority of pyrazinocarbazole derivatives have a rigit conformation, but three of those is sufficiently flexible. The latters can be in two conformation types: long molecules (substitution accommodate along axis of main structure) and short molecules (substitution accommodate at acute angle about of main structure). Several 3D QSAR and CoMFA models of MAO A and B active sites were design for data sets containing various types of flexible molecules conformation. All obtained models are statistical reliable and have sufficient predictive power for tested compound tetrindole. The best MAO A model that include two flexible molecules in long conformations was obtained, and the longest one of those in short conformation. In contrast, for MAO B model containing all flexible molecules in the short conformations is more preferred.

On the basis of obtained data the schematic models of MAO A and B active sites structures are proposed. According to these models MAO A active site have the narrow long cavity that accommodate long molecules, while MAO B active site is broader and shorter.     

3D-QSAR studies of checkpoint kinase 1 inhibitors based on molecular docking and CoMFA

Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on a series of substituted 1,4-dihydroindeno[1,2-c]pyrazoles inhibitors, using molecular docking and comparative molecular field analysis (CoMFA). The docking results from GOLD 3.0.1 provide a reliable conformational alignment scheme for the 3D-QSAR model. Based on the docking conformations and alignments, highly predictive CoMFA model was built with cross-validated q ² value of 0.534 and non-cross-validated partial least-squares analysis with the optimum components of six showed a conventional r ² value of 0.911. The predictive ability of this model was validated by the testing set with a conventional r ² value of 0.812. Based on the docking and CoMFA, we have identified some key features of the 1,4-dihydroindeno[1,2-c]pyrazoles derivatives that are responsible for checkpoint kinase 1 inhibitory activity. The analyses may be used to design more potent 1,4-dihydroindeno[1,2-c]pyrazoles derivatives and predict their activity prior to synthesis.     

3D-QSAR,molecular docking and molecular dynamics studies of a series of RORγt inhibitors

The discovery of clinically relevant inhibitors of retinoic acid receptor-related orphan receptor-gamma-t (RORγt) for autoimmune diseases therapy has proven to be a challenging task. In the present work, to find out the structural features required for the inhibitory activity, we show for the first time a three-dimensional quantitative structure–activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations for a series of novel thiazole/thiophene ketone amides with inhibitory activity at the RORγt receptor. The optimum CoMFA and CoMSIA models, derived from ligand-based superimposition I, exhibit leave-one-out cross-validated correlation coefficient (R²_cv) of .859 and .805, respectively. Furthermore, the external predictive abilities of the models were evaluated by a test set, producing the predicted correlation coefficient (R²_pred) of .7317 and .7097, respectively. In addition, molecular docking analysis was applied to explore the binding modes between the inhibitors and the receptor. MD simulation and MM/PBSA method were also employed to study the stability and rationality of the derived conformations, and the binding free energies in detail. The QSAR models and the results of molecular docking, MD simulation, binding free energies corroborate well with each other and further provide insights regarding the development of novel RORγt inhibitors with better activity.     

3D-QSAR with CoMFA Model of Prolylendopeptidase Substrates

Abstract

The prolylendopeptidase (PEP) is the proteolytic enzyme, which plays an essential role in the regulation of some processes in central nervous system, such as memory, learning and behavior. It was shown that PEP activity changes at different diseases, like Parkinsons or Alzheimer's diseases, and some PEP inhibitors are used in therapy. At present time the discovery of new types of PEP inhibitors are the actual task.

In this study the structure of PEP active site was analyzed by 3D-QSAR with CoMFA methods using of 12 PEP substrates. The designed pharmacophore model assumes that substrates interact with PEP active site by pyrrolidol ring of proline residue and by hydrogen bonding.

The 3-D-QSAR + CoMFA model of PEP substrates propose that the hydrophobic bonds play the essential role in substrate interaction with enzyme. This model reveals the important steric and electrostatic areas around the molecules and the presence of substituents controls the PEP activity for substrates. Analysis of obtained data allows to assume, that substrate binding in PEP active site causes essential perturbations of substrate structure. This effect mainly depends on chemical nature of the amino acid side chain, located near to proline.