Discovery of new human epidermal growth factor receptor-2 (HER2) inhibitors for potential use as anticancer agents via ligand-based pharmacophore modeling

In silico approaches for drug repurposing in oncology: a scoping review

Introduction: Cancer refers to a group of diseases characterized by the uncontrolled growth and spread of abnormal cells in the body. Due to its complexity, it has been hard to find an ideal medicine to treat all cancer types, although there is an urgent need for it. However, the cost of developing a new drug is high and time-consuming. In this sense, drug repurposing (DR) can hasten drug discovery by giving existing drugs new disease indications. Many computational methods have been applied to achieve DR, but just a few have succeeded. Therefore, this review aims to show in silico DR approaches and the gap between these strategies and their ultimate application in oncology. Methods: The scoping review was conducted according to the Arksey and O'Malley framework and the Joanna Briggs Institute recommendations. Relevant studies were identified through electronic searching of PubMed/MEDLINE, Embase, Scopus, and Web of Science databases, as well as the grey literature. We included peer-reviewed research articles involving in silico strategies applied to drug repurposing in oncology, published between 1 January 2003, and 31 December 2021. Results: We identified 238 studies for inclusion in the review. Most studies revealed that the United States, India, China, South Korea, and Italy are top publishers. Regarding cancer types, breast cancer, lymphomas and leukemias, lung, colorectal, and prostate cancer are the top investigated. Additionally, most studies solely used computational methods, and just a few assessed more complex scientific models. Lastly, molecular modeling, which includes molecular docking and molecular dynamics simulations, was the most frequently used method, followed by signature-, Machine Learning-, and network-based strategies. Discussion: DR is a trending opportunity but still demands extensive testing to ensure its safety and efficacy for the new indications. Finally, implementing DR can be challenging due to various factors, including lack of quality data, patient populations, cost, intellectual property issues, market considerations, and regulatory requirements. Despite all the hurdles, DR remains an exciting strategy for identifying new treatments for numerous diseases, including cancer types, and giving patients faster access to new medications.

Comparative anti-proliferative effects of potential HER2 inhibitors on a panel of breast cancer cell lines

BACKGROUND

Breast cancer is one of the most lethal types of cancer in women worldwide. The human epidermal growth factor receptor 2 (HER2) is considered as a validated target in breast cancer therapy. Previously, we have used quantitative structure activity relationship QSAR equations and their associated pharmacophore models to screen for new promising HER2 structurally diverse inhibitory leads which were tested against HER2-overexpressing SKOV3 ovarian cancer cell line.

OBJECTIVE

In this study, we sought to explore the effect of most active ligands against different normal and breast cancer cell lines that represent different breast cancer subtypes with distinguished expression levels in HER2 and HER1.

METHODS

We have tested the promising compounds against SKBR3, MDA-MB-231, MCF7, human fibroblast, and MCF10 cell lines. To understand the inhibitory effects of the active ligands against HER2 over expressed breast cancer cell lines, all inhibitors and the control compound, lapatinib, were docked into the active site of HER2 enzyme performed using Ligand Fit docking engine and PMF scoring function.

RESULTS

Five ligands exhibited promising results with relatively low IC₅₀ values on cells that amplify HER2 and high IC₅₀ on those that do not express such a receptor. The most potent compound (compound 13) showed an IC₅₀ of 0.046 µM. To test their toxicity against normal cells, the active compounds were tested against both normal fibroblast and normal breast cancer cell MCF-10 and relatively high IC₅₀ values were scored. The IC₅₀ values on HER2 over-expressed breast cancer and normal fibroblast cells provided a promising safety index. Docking results showed the highest similarity in the binding site between the most active ligand and the lapatinib.

CONCLUSION

Our pharmacophore model resulted in a high potent ligand that shows high potency against HER2 positive breast cancer and relatively low toxicity towards the normal human cells.

Ligand efficiency metrics in drug discovery: the pros and cons from a practical perspective

INTRODUCTION

Ligand efficiency metrics are almost universally accepted as a valuable indicator of compound quality and an aid to reduce attrition. Areas covered: In this review, the authors describe ligand efficiency metrics giving a balanced overview on their merits and points of weakness in order to enable the readers to gain an informed opinion. Relevant theoretical breakthroughs and drug-like properties are also illustrated. Several recent exemplary case studies are discussed in order to illustrate the main fields of application of ligand efficiency metrics. Expert opinion: As a medicinal chemist guide, ligand efficiency metrics perform in a context- and chemotype-dependent manner; thus, they should not be used as a magic box. Since the 'big bang' of efficiency metrics occurred more or less ten years ago and the average time to develop a new drug is over the same period, the next few years will give a clearer outlook on the increased rate of success, if any, gained by means of these new intriguing tools.