In Silico Exploration of Novel Tubulin Inhibitors: A Combination of Docking and Molecular Dynamics Simulations, Pharmacophore Modeling, and Virtual Screening

Microtubules play a critical role in mitosis and cell division and are regarded as an excellent target for anticancer therapy. Although microtubule-targeting agents have been widely used in the clinical treatment of different human cancers, their clinical application in cancer therapy is limited by both intrinsic and acquired drug resistance and adverse toxicities. In a previous work, we synthesized compound 9IV-c, ((E)-2-(3,4-dimethoxystyryl)-6,7,8-trimethoxy-N-(3,4,5-trimethoxyphenyl)quinoline-4-amine) that showed potent activity against multiple human tumor cell lines, by targeting spindle formation and/or the microtubule network. Accordingly, in this study, to identify potent tubulin inhibitors, at first, molecular docking and molecular dynamics studies of compound 9IV-c were performed into the colchicine binding site of tubulin; then, a pharmacophore model of the 9IV-c-tubulin complex was generated. The pharmacophore model was then validated by Güner–Henry (GH) scoring methods and receiver operating characteristic (ROC) analysis. The IBScreen database was searched by using this pharmacophore model as a screening query. Finally, five retrieved compounds were selected for molecular docking studies. These efforts identified two compounds (b and c) as potent tubulin inhibitors. Investigation of pharmacokinetic properties of these compounds (b and c) and compound 9IV-c displayed that ligand b has better drug characteristics compared to the other two ligands.

In Silico Discovery of Potential Azole-Containing mPGES-1 Inhibitors By Virtual Screening, Pharmacophore Modeling and Molecular Dynamics Simulations

Inhibition of microsomal prostaglandin E2 synthase-1 (mPGES-1) is promising for designing novel nonsteroidal anti-inflammatory drugs, as they lack side-effects associated with inhibition of cyclooxygenase enzymes. Azole compounds are nitrogen-containing heterocycles and have a wide use in medicine and are considered as promising compounds in medicinal chemistry. Various computer-aided drug design strategies are incorporated in this study. Structure-based virtual screening was performed employing various docking programs. Receiver Operator Characteristic (ROC) curves were used to evaluate the selectivity of each program. Furthermore, scoring power of Autodock4 and Autodock Vina was assessed by Pearson’s correlation coefficients. Pharmacophore models were generated and Güner-Henry score of the best model was calculated as 0.89. Binding modes of the final 10 azole compounds were analyzed and further investigation of the best binding (-8.38 kcal/mol) compound was performed using molecular dynamics simulation, revealing that furazan1224 (ZINC001142847306) occupied the binding site of the substrate, prostaglandin H2 (PGH2) and remained stable for 100 ns. Continuous hydrogen bonds with amino acids in the active site supported the stability of furazan1224 throughout the trajectory. Pharmacokinetic profile showed that furazan1224 lacks the risks of inhibiting cytochrome P450 3A4 enzyme and central nervous system-related side-effects.

Pharmacophore Modeling, Docking, and Molecular Dynamics Simulation of Flavonoids as Inhibitors of Urokinase-type Plasminogen Activator

The urokinase-type plasminogen activator (uPA) system plays a significant role in the invasion and metastasis of cancer cells. The present study was conducted to investigate natural product compounds as inhibitors and hit molecules of uPA using in-silico analysis. A pharmacophore model was built to screen the Indonesian Herbal Database (HerbalDB) to obtain inhibitors of different scaffolds. Based on the molecular docking score, four ligands were selected as potential uPA inhibitors. Subsequently, the stability of the ligand-uPA complex was analyzed using molecular dynamics (MD) simulation. An RMSD graph of the backbone protein and the RMSF values of the amino acid residues were also determined. In addition, the MM-PBSA method was applied to calculate the free binding energy. According to the results, Model_3, characterized by aromatic rings 23 (F1 and F2), cationic H-bond donor (F3), and metal ligator (F4) features, had an adequate goodness-of-hit score (GH). The four top-ranked ligands, isorhamnetin, rhamnetin, quercetin, and kaempferol, showed higher docking scores compared to the others. This study confirmed that isorhamnetin, rhamnetin, and kaempferol build stable complexes with uPA with lower binding energy than quercetin.

An overview of in silico methods used in the design of VEGFR-2 inhibitors as anticancer agents

VEGFR-2 enzyme known for physiological functioning of the cell also involves in pathological angiogenesis and tumor progression. Recently VEGFR-2 has gained the interest of researchers all around the world as a promising target for the drug design and discovery of new anticancer agents. VEGFR2 inhibitors are a major class of anticancer agents used for clinical purposes. In silico methods like virtual screening, molecular docking, molecular dynamics, pharmacophore modeling, and other computational approaches help extensively in identifying the main molecular interactions necessary for the binding of the small molecules with the respective protein target to obtain the expected pharmacological potency. In this chapter, we discussed some representative case studies of in silico techniques used to determine molecular interactions and rational drug design of VEGFR-2 inhibitors as anticancer agents.

Discovery of Small Molecules as Membrane-Bound Catechol-O-methyltransferase Inhibitors with Interest in Parkinson’s Disease: Pharmacophore Modeling, Molecular Docking and In Vitro Experimental Validation Studies

A pharmacophore-based virtual screening methodology was used to discover new catechol-O-methyltransferase (COMT) inhibitors with interest in Parkinson’s disease therapy. To do so, pharmacophore models were constructed using the structure of known inhibitors and then they were used in a screening in the ZINCPharmer database to discover hit molecules with the desired structural moieties and drug-likeness properties. Following this, the 50 best ranked molecules were submitted to molecular docking to better understand their atomic interactions and binding poses with the COMT (PDB#6I3C) active site. Additionally, the hits’ ADMET properties were also studied to improve the obtained results and to select the most promising compounds to advance for in-vitro studies. Then, the 10 compounds selected were purchased and studied regarding their in-vitro inhibitory potency on human recombinant membrane-bound COMT (MBCOMT), as well as their cytotoxicity in rat dopaminergic cells (N27) and human dermal fibroblasts (NHDF). Of these, the compound ZIN27985035 displayed the best results: For MBCOMT inhibition an IC50 of 17.6 nM was determined, and low cytotoxicity was observed in both cell lines (61.26 and 40.32 μM, respectively). Therefore, the promising results obtained, combined with the structure similarity with commercial COMT inhibitors, can allow for the future development of a potential new Parkinson’s disease drug candidate with improved properties.

Computational Study Reveals PARP1 and P2Y1 Receptors as Prospective Targets of Withaferin-A for Cardiovascular Diseases

Background: Cardiovascular Diseases (CVDs) remain the leading cause of death worldwide, which urges for effective strategies of prevention and treatment. Withaferin-A (WFA), the key metabolite identified in Withania somnifera, has been known for its cardioprotective properties. Although it has been traditionally employed to treat cardiovascular ailments for several decades, its exact mechanism of action still remains unexplained Objective: The current study modelled and scored the interactions of WFA with nine prospective protein-targets associated with cardiovascular diseases through molecular docking and DSX-scoring. Methods: Molecular docking was carried out using Autodock and DSX-scoring was carried out using DSX standalone software. WFA was observed to favorably interact with six targets before DSX-based rescoring, but only with Poly (ADP-Ribose) Polymerase-1 and P2Y Purinoceptor-1 after DSX-based rescoring. The spatial orientation, physicochemical properties and structural features of Withaferin-A were compared with that of these approved drugs by pharmacophore modeling and hierarchical clustering Results: The results of molecular docking, DSX-based rescoring and complete pharmacophore modeling together revealed that PARP1 and P2Y1 receptor could be prospective targets of WFA for the treatment of CVD. Conclusion: Simulation using GROMACS has revealed that WFA forms a more stable complex with PARP1 and will be useful in developing the broad-spectrum drugs against cardiovascular diseases. Further computational studies through machine learning and network pharmacology methods can be carried out to improve Withaferin-A compound features by incorporating additional functional groups necessary for molecular recognition of the target genes in network responsible for cardiovascular diseases.