Current Computer - Aided Drug Design - Volume 15, Issue 4, 2019

Background: In past few decades, computational chemistry has seen significant advancements in design and development of novel therapeutics. Benzimidazole derivatives showed promising anti-inflammatory activity through the inhibition of COX-2 enzyme.

Objective: The structural features necessary for COX-2 inhibitory activity for a series of oxadiazole substituted benzimidazoles were explored through 3D-QSAR, combinatorial library generation (Combi Lab) and molecular docking.

Methods: 3D-QSAR (using kNN-MFA (SW-FB) and PLSR (GA) methods) and Combi Lab studies were performed by using VLife MDS Molecular Design Suite. The molecular docking study was performed by using AutoDockVina.

Results: Significant QSAR models generated by PLSR exhibited r2 = 0.79, q2 = 0.68 and pred_r2 = 0. 84 values whereas kNN showed q2 = 0.71 and pred_r2 = 0.84. External validation of developed models by various parameters assures their reliability and predictive efficacy. A library of 72 compounds was generated by combinatorial technique in which 11 compounds (A1-A5 and B1-B6) showed better predicted biological activity than the most active compound 27 (pIC50 = 7.22) from the dataset. These compounds showed proximal interaction with amino acid residues like TYR355 and/or ARG120 on COX-2(PDB ID: 4RS0).

Conclusion: The present work resulted in the design of more potent benzimidazoles as COX-2 inhibitors with good interaction as compared to reference ligand. The results of the study may be helpful in the development of novel COX-2 inhibitors for inflammatory disorders.

Background: Vortioxetine is a multimodal antidepressant drug with combined effects on SERT as an inhibitor, 5-HT1A as agonist and 5-HT3A as an antagonist. Series of vortioxetine analogs have been reported as multi antidepressant compounds and they block serotonin transport into the neuronal cells, activate the postsynaptic 5-HT1A receptors and eliminate the low activity of 5-HT3A receptors.

Objective: To explore the important properties of vortioxetine analogs involved in antidepressant activity by developing 2D QSAR models.

Methods: Selections of significant descriptors were performed by Least Absolute Shrinkage and Selection Operator (LASSO) method and, the Multiple Linear Regression (MLR) method and All Subsets and GA algorithm included in QSARINS software were used for generating QSAR models. Further, the virtual screening was performed based on bioactivity and structure similarity using the PubChem database.

Results: The four descriptor model of complementary information content (CIC2), solubility (bcutp3), mass (bcutm8) and partial charge in van der Waals surface area (PEOEVSA7) of the molecules is obtained for SERT inhibition with the significant statistics of R2= 0.69, RMSEtr= 0.44, R2 ext= 0.62 and CCCext= 0.78. For 5-HT1A agonist, the two descriptor model of molecular shape (Kappm3) and van der Waals volume of the atoms (bcutv11) with R2= 0.78, RMSEtr= 0.33, R2 ext = 0.83, and CCCext= 0.87 is established. The three descriptor model of information content (IC3), solubility (bcutp9) and electronegativity (GATSe5) of the molecules with R2= 0.61, RMSEtr= 0.34, R2 ext= 0.69 and CCCext= 0.72 is obtained for 5-HT3A antagonist. The antidepressant activities of 16 virtual screened compounds were predicted using the developed models.

Conclusion: The developed QSAR models may be useful to predict antidepressant activity for the newly synthesized vortioxetine analogs.

Background: Orthosiphon stamineus is a traditional medicinal plant in Southeast Asia countries with various well-known pharmacological activities such as antidiabetic, diuretics and antitumor activities. Transketolase is one of the proteins identified in the leaves of the plant and transketolase is believed able to lower blood sugar level in human through non-pancreatic mechanism. In order to understand the protein behavioral properties, 3D model of transketolase and analysis of protein structure are of obvious interest.

Methods: In the present study, 3D model of transketolase was constructed and its atomic characteristics revealed. Besides, molecular dynamic simulation of the protein at 310 K and 368 K deciphered transketolase may be a thermophilic protein as the structure does not distort even at elevated temperature. This study also used the protein at 310 K and 368 K resimulated back at 310 K environment.

Results: The results revealed that the protein is stable at all condition which suggest that it has high capacity to adapt at different environment not only at high temperature but also from high temperature condition to low temperature where the structure remains unchanged while retaining protein function.

Conclusion: The thermostability properties of transketolase is beneficial for pharmaceutical industries as most of the drug making processes are at high temperature condition.

Objective: To screen the phytochemicals for phosphodiesterase 5A (PDE5A) inhibitory potential and identify lead scaffolds of antihypertensive phytochemicals using in silico docking studies.

Methods: In this perspective, reported 269 antihypertensive phytochemicals were selected. Sildenafil, a PDE5A inhibitor was used as the standard. In silico docking study was carried out to screen and identify the inhibiting potential of the selected phytochemicals against PDE5A enzyme using vLife MDS 4.4 software.

Results: Based on docking score, π-stacking, H-bond and ionic interactions, 237 out of 269 molecules were selected which have shown one or more interactions. Protein residue Gln817A was involved in H-boding whereas Val782A, Phe820A and Leu804A were involved in π-stacking interaction with ligand. The selected 237 phytochemicals were structurally diverse, therefore 82 out of 237 molecules with one or more tricycles were filtered out for further analysis. Amongst tricyclic molecules, 14 molecules containing nitrogen heteroatom were selected for lead scaffold identification which finally resulted in three different basic chemical backbones like pyridoindole, tetrahydro-pyridonaphthyridine and dihydro-pyridoquinazoline as lead scaffolds.

Conclusion: In silico docking studies revealed that nitrogen-containing tetrahydro-pyridonaphthyridine and dihydro-pyridoquinazoline tricyclic lead scaffolds have emerged as novel PDE5A inhibitors for antihypertensive activity. The identified lead scaffolds may provide antihypertensive lead molecules after its optimization.

Background: The phosphodiesterase (PDE) is a superfamily represented by four genes: PDE4A, B,C, and D which cause the hydrolysis of phosphodiester bond of cAMP to yield inactive AMP. c-AMP catalyzing enzyme is predominant in inflammatory and immunomodulatory cells. Therapy to treat Chronic Obstructive Pulmonary Disease (COPD) with the use of PDE4 inhibitors is highly envisaged.

Objective: A molecular docking experiment with large dataset of diverse scaffolds has been performed on PDE4 inhibitors to analyze the role of amino acid responsible for binding and activation of the secondary transmitters. Apart from the general docking experiment, the main focus was to discover the role of water molecules present in the ligand-binding domain.

Methods: All the compounds were docked in the PDE4B and PDE4D active cavity to produce the free binding energy scores and spatial disposition/orientation of chemical groups of inhibitors around the cavity. Under uniform condition, the experiments were carried out with and without water molecules in the LBD. The exhaustive study was carried out on the Autodock 4.2 software and explored the role of water molecules present in the binding domain.

Results: In presence of water molecule, Roflumilast has more binding affinity (-8.48 Kcal/mol with PDE4B enzyme and -8.91 Kcal/mol with PDE4D enzyme) and forms two hydrogen bonds with Gln443 and Glu369 and amino acid with PDE4B and PDE4D enzymes respectively. While in absence of water molecule its binding affinity has decreased (-7.3 Kcal/mol with PDE4B enzyme and -5.17 Kcal/mol with PDE4D enzyme) as well as no H-bond interactions were observed. Similar observation was made with clinically tested molecules.

Conclusion: In protein-ligand binding interactions, appropriate selection of water molecules facilitated the ligand binding, which eventually enhances the efficiency as well as the efficacy of ligand binding.