Identification of potent virtual leads and ADME prediction of isoxazolidine podophyllotoxin derivatives as topoisomerase II and tubulin inhibitors

Design and Synthesis of 4-O-Podophyllotoxin Sulfamate Derivatives as Potential Cytotoxic Agents

4-O-Podophyllotoxin sulfamate derivatives were prepared using the natural lignan podophyllotoxin. The prepared compounds were afforded by reacting O-sulfonyl chloride podophyllotoxin with ammonia or aminoaryl/heteroaryl motif. Biological evaluation was performed in human breast cancer (MCF7), ovarian cancer (A2780), colon adenocarcinoma (HT29), and normal lung fibroblast (MRC5) cell lines. Compound 3 exhibited potent inhibitory activity and good selectivity margin. Compounds 2, 3, and 7 exerted apoptotic effect in MCF7 cells in a dose-dependent manner. The cytotoxicity of the verified compounds was inferior to that of podophyllotoxin.

Characterization of the Trypanosoma brucei Pteridine Reductase Active- Site using Computational Docking and Virtual Screening Techniques

Background:

Human African trypanosomiasis is a fatal disease prevalent in approximately 36 sub-Saharan countries. Emerging reports of drug resistance in Trypanosoma brucei are a serious cause of concern as only limited drugs are available for the treatment of the disease. Pteridine reductase is an enzyme of Trypanosoma brucei.

Methods:

It plays a critical role in the pterin metabolic pathway that is absolutely essential for its survival in the human host. The success of finding a potent inhibitor in structure-based drug design lies within the ability of computational tools to efficiently and accurately dock a ligand into the binding cavity of the target protein. Here we report the computational characterization of Trypanosoma brucei pteridine reductase (Tb-PR) active-site using twenty-four high-resolution co-crystal structures with various drugs. Structurally, the Tb-PR active site can be grouped in two clusters; one with high Root Mean Square Deviation (RMSD) of atomic positions and another with low RMSD of atomic positions. These clusters provide fresh insight for rational drug design against Tb-PR. Henceforth, the effect of several factors on docking accuracy, including ligand and protein flexibility were analyzed using Fred.

Results:

The online server was used to analyze the side chain flexibility and four proteins were selected on the basis of results. The proteins were subjected to small-scale virtual screening using 85 compounds, and statistics were calculated using Bedroc and roc curves. The enrichment factor was also calculated for the proteins and scoring functions. The best scoring function was used to understand the ligand protein interactions with top common compounds of four proteins. In addition, we made a 3D structural comparison between the active site of Tb-PR and Leishmania major pteridine reductase (Lm- PR). We described key structural differences between Tb-PR and Lm-PR that can be exploited for rational drug design against these two human parasites.

Conclusion:

The results indicated that relying just on re-docking and cross-docking experiments for virtual screening of libraries isn’t enough and results might be misleading. Hence it has been suggested that small scale virtual screening should be performed prior to large scale screening.

Repurposing of Benzimidazole Scaffolds for HER2 Positive Breast Cancer Therapy: An In-Silico Approach

BACKGROUND

A newer trend has been seen recently to reuse the conventional drugs with distinct indications for the newer applications to speed up the drug discovery and development based on earlier records and safety data. Most of the non-cancerous agents could afford a little or tolerable side effects in individuals. However, the repositioning of these non-cancerous agents for successful anticancer therapy is an outstanding strategy for future anti-cancer drug development. Since more diverse and selective cancer drug targets are being discovered and developed, the approved drug collections are particularly useful to quickly identify clinically advanced anticancer drugs against those targets.

OBJECTIVE

Antihelminthic drugs such as Mebendazole and Albendazole (Benzimidazole class) have been reported to exhibit cytotoxicity (or anticancer activities) against several types of cancer. Therefore, this study aims to repurpose the benzimidazole scaffold for breast cancer treatment.

METHODS

In the present study, three hydrazone analogs having a benzimidazole motif in their structural frame were synthesized. Their in-silico binding studies against HER2 receptor (PDB ID: 4LQM) and ADMET studies were carried out using Accelrys drug discovery studio 4.1. Cytotoxicity of the synthesized compounds against HER2 overexpressed MCF-7 cell lines was determined by MTT assay.

RESULTS

One of the compounds 2-[2-(2,4-dinitrophenyl)hydrazinylidene]-2,3-dihydro-1H-benzimidazole (U1) has shown good cytotoxicity when compared to the standard Lapatinib, which is a well known HER2 inhibitor.

CONCLUSIONS

Thus, the designed benzimidazole scaffold might serve as the best leads for treating breast cancer, which is additionally confirmed by performing their docking study via Accelrys discovery studio.

Advancement in the development of heterocyclic nucleosides for the treatment of cancer - A review

Cancer diseases are widely recognised as an important medical problem and killing millions of people in a year. Chemotherapeutic drugs are successful against cancer in many cases and different compounds, including the analogues of natural substances, may be used for anticancer agents. Nucleoside analogues also have become a necessity for the treatment of cancer diseases. Nucleoside, nucleotide and base analogues have been utilised for decades for the treatment of viral pathogens, neoplasms and in anticancer chemotherapy. This review focuses on the different types of nucleosides and their potential role as anticancer agents. It also discusses the nucleoside analogues approved by FDA and in process of approval. The effect of the substitution on the nucleoside analogues and their pharmacological role is also discussed in the review. Owing to the advances in computational chemistry, it concludes with the future advancement and possible outcome of the nucleoside analogues. Also, it depicts the development of heterocyclic nucleoside analogues, explores the QSAR of the synthesised compounds and discusses the 3 D QSAR pharmacophore modelling in order to examine their potential anti-cancer activities.

QSAR and Docking Studies on Piperidyl-cyclohexylurea Derivatives for Prediction of Selective and Potent Inhibitor of Matriptase

Methods:

Docking and alignment methodologies were used to develop models in 3D QSAR. The best models among all were selected on the basis of regression statistics as r2, predictive r2 and Friedman Lack of fit measure. Hydrogen donors and rotatable bonds were found to be positively correlated properties for this target. The models were validated and used for the prediction of new compounds. Based on the predictions of 3D-QSAR model, 17 new compounds were prepared and their activities were predicted and compared with the active compound. Prediction of activities was performed for these 18 compounds using consensus results of all models. ADMET was also performed for the best-chosen compound and compared with the known active.

Results and Conclusion:

The developed model was able to validate the obtained results and can be successfully used to predict new potential and active compounds.

Pharmacoinformatics analysis of merbarone binding site in human topoisomerase IIα

Merbarone is a derivative of thiobarbituric acid, possessing catalytic inhibitory potential against human topoisomerase IIα (hTopoIIα). Merbarone was reported to inhibit DNA cleavage by hTopoIIα. It is important to understand the molecular mechanism of hTopoIIα inhibition by merbarone, as these details guide the rational design of new ligands. In this work, a systematic pharmacoinformatics analysis has been reported to analyze the merbarone-hTopoIIα interactions and to identify merbarone analogs as potential hTopoIIα inhibitors. The reported crystal structure of hTopoIIα-DNA complex (PDB ID: 4FM9) is not suitable for analyzing the merbarone-binding domain, because it is a biological assembly of hTopoIIα in C-gate open conformation. Therefore, 3D structure of hTopoIIα-DNA complex suitable for molecular modeling analysis at merbarone binding site was first generated. Using this generated complex, molecular docking analysis and molecular dynamics simulations were performed to explore the effect of merbarone on hTopoIIα-DNA complex. The binding energy for the enol form of merbarone with hTopoIIα-DNA was estimated to be -51.28 kcal/mol. The explored binding site and identified molecular recognition interactions were in accordance with the previously reported interference in the DNA-cleavage by merbarone. Virtual screening was performed using drug likeness filters, toxicity filters and ADMET descriptor based filters followed by molecular docking (ZINC database). Sixteen compounds were identified as merbarone-functional analogs suitable for hTopoIIα inhibition. These identified molecules can be considered for further evaluation of their anti-hTopoIIα activity.

Computational Cell Cycle Profiling of Cancer Cells for Prioritizing FDA-Approved Drugs with Repurposing Potential

Discovery of first-in-class medicines for treating cancer is limited by concerns with their toxicity and safety profiles, while repurposing known drugs for new anticancer indications has become a viable alternative. Here, we have developed a new approach that utilizes cell cycle arresting patterns as unique molecular signatures for prioritizing FDA-approved drugs with repurposing potential. As proof-of-principle, we conducted large-scale cell cycle profiling of 884 FDA-approved drugs. Using cell cycle indexes that measure changes in cell cycle profile patterns upon chemical perturbation, we identified 36 compounds that inhibited cancer cell viability including 6 compounds that were previously undescribed. Further cell cycle fingerprint analysis and 3D chemical structural similarity clustering identified unexpected FDA-approved drugs that induced DNA damage, including clinically relevant microtubule destabilizers, which was confirmed experimentally via cell-based assays. Our study shows that computational cell cycle profiling can be used as an approach for prioritizing FDA-approved drugs with repurposing potential, which could aid the development of cancer therapeutics.