Integrating biocomputational techniques for Breast cancer drug discovery via the HER-2, BCRA, VEGF and ER protein targets

Computational modelling remains an indispensable technique in drug discovery. With myriad of high computing resources, and improved modelling algorithms, there has been a high-speed in the drug development cycle with promising success rate compared to the traditional route. For example, lapatinib; a well-known anticancer drug with clinical applications was discovered with computational drug design techniques. Similarly, molecular modelling has been applied to various disease areas ranging from cancer to neurodegenerative diseases. The techniques ranges from high-throughput virtual screening, molecular mechanics with generalized Born and surface area solvation (MM/GBSA) to molecular dynamics simulation. This review focuses on the application of computational modelling tools in the identification of drug candidates for Breast cancer. First, we begin with a succinct overview of molecular modelling in the drug discovery process. Next, we take note of special efforts on the developments and applications of combining these techniques with particular emphasis on possible breast cancer therapeutic targets such as estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2), vascular endothelial growth factor (VEGF), breast cancer gene 1 (BRCA1), and breast cancer gene 2 (BRCA2). Finally, we discussed the search for covalent inhibitors against these receptors using computational techniques, advances, pitfalls, possible solutions, and future perspectives.

Protein-protein interaction and interference of carcinogenesis by supramolecular modifications

Protein-protein interactions (PPIs) are essential in normal biological processes, but they can become disrupted or imbalanced in cancer. Various technological advancements have led to an increase in the number of PPI inhibitors, which target hubs in cancer cell's protein networks. However, it remains difficult to develop PPI inhibitors with desired potency and specificity. Supramolecular chemistry has only lately become recognized as a promising method to modify protein activities. In this review, we highlight recent advances in the use of supramolecular modification approaches in cancer therapy. We make special note of efforts to apply supramolecular modifications, such as molecular tweezers, to targeting the nuclear export signal (NES), which can be used to attenuate signaling processes in carcinogenesis. Finally, we discuss the strengths and weaknesses of using supramolecular approaches to targeting PPIs.

Identification of HER2 inhibitors from curcumin derivatives using combination of in silico screening and molecular dynamics simulation

Breast cancer remains a major world health challenge in women. Some Breast cancers are human epidermal growth factor receptor 2 (HER2) positive. Since this protein promotes the growth of cancer cells, it remains a therapeutic target for novel drugs. This study uses in silico model to predict HER2 inhibitors from curcumin derivatives via QSAR, e-pharmacophore, ADMET as well as structure-based virtual screening using Schrodinger suite. The molecular dynamics simulation of lead compounds, reference ligand and co-crystalized ligand was performed using GROMACS. At the end, eight active curcumin derivatives were predicted as inhibitors of HER2 with high binding affinity and better interaction compared with the reference drug (Neratinib) but lower binding affinity compared with the co-crystalized ligand (TAK-285). After prediction of the bioactivity of the molecules using AutoQSAR, the hit compounds showed appreciable inhibitory pIC50 compared with the reference and co-crystalized ligands against HER2. The pharmacokinetics profile predicted the eight hit compounds as drug-like and drug candidates. The MD simulation predicted the stability of the two top-scored compounds (10763284 and 78321412) in complex with HER2 for the final 80 ns of the trajectory period after initial equilibration with higher H-bond interactions in the protein-reference drug complex compared to the hit compounds-HER2 complexes. This study revealed that curcumin derivatives especially (1E,6E)-1,8-bis(4-hydroxy-3-methoxyphenyl)octa-1,6-diene-3,5-dione and (1E,6E)-4-ethyl-1,7-bis(4-hydroxy-3-methoxyphenyl)hepta-1,6-diene-3,5-dione were identified to demonstrate inhibitory activity against HER2 which is comparable to neratinib. Conclusively, the lead compounds require further in vitro and in vivo experimental validation for the discovery of new HER2 antagonists for breast cancer management.Communicated by Ramaswamy H. Sarma.