Computational Studies in Drug Design Against Cancer

Abstract

The application of in silico tools in the development of anti cancer drugs. </p> <p> Objective: The summing of different computer aided drug design approaches that have been applied in the development of anti cancer drugs. </p> <p> Method: Structure based, ligand based, hybrid protein-ligand pharmacophore methods, Homology modeling, molecular docking aids in different steps of drug discovery pipeline with considerable saving in time and expenditure. In silico tools also finds applications in the domain of cancer drug development. </p> <p> Results: Structure-based pharmacophore modeling aided in the identification of PUMA inhibitors, structure based approach with high throughput screening for the development of Bcl-2 inhibitors, to derive the most relevant protein-protein interactions, anti mitotic agents; I-Kappa-B Kinase β (IKK- β) inhibitor, screening of new class of aromatase inhibitors that can be important targets in cancer therapy. </p> <p> Conclusion: Application of computational methods in the design of anti cancer drugs was found to be effective.

The Synthesis, Characterization, Molecular Docking and In Vitro Antitumor Activity of Benzothiazole Aniline (BTA) Conjugated Metal-Salen Complexes as Non-Platinum Chemotherapeutic Agents

“…Moreover, in terms of docking binding energies, the compound L outperformed the corresponding metal complex MnL and parent BTA for the DNA topologies tested. Intercalation, or major/minor groove binding with DNA, is the most prevalent interaction for small molecular anticancer agents [55]. The ligand in the groove binding mode is usually flexible, has rotatable bonds, and can position itself along the major or minor groove of the DNA, limiting normal DNA function.…”

Rationale design and synthesis of new apoptotic thiadiazole derivatives targeting VEGFR-2: computational andin vitrostudies

“…19 Furthermore, this approach shows promise in minimizing side effects associated with traditional chemotherapy through the precise targeting of cancer-specic pathways. 20,21 This selectivity could revolutionize cancer treatment, providing therapies that are not only more potent against the disease but also safer for patients. 22,23 Computational chemistry encompasses several approaches, such as design, 24 docking, 25 and prediction of ADMET (absorption, distribution, metabolism, excretion, and toxicity), 26 as well as DFT (density functional theory).…”

“… 19 Furthermore, this approach shows promise in minimizing side effects associated with traditional chemotherapy through the precise targeting of cancer-specific pathways. 20,21 This selectivity could revolutionize cancer treatment, providing therapies that are not only more potent against the disease but also safer for patients. 22,23 …”

A computational peptide model induces cancer cells’ apoptosis by docking Kringle 5 to GRP78

“…Utilizing computational analysis methods, specifically molecular dynamic simulation, is one method for addressing the problem of therapeutic cancer treatment [ 4 – 7 ]. The computational approach enables researchers to investigate the atomic-level behavior of molecules and gain insight into the molecular mechanisms that drive cancer progression and treatment response.…”