Project Abstract

Molecular Docking and Virtual Screening for the Identification of Novel Anti-Cancer Drug Candidates Cancer remains one of the most pressing global health challenges, with millions of lives lost each year. Despite significant advancements in cancer treatment, the need for more effective and targeted therapies persists. This project aims to leverage the power of computational drug discovery techniques, specifically molecular docking and virtual screening, to identify novel small-molecule compounds with the potential to serve as anti-cancer drug candidates. The project's cornerstone is the exploration of the vast chemical space of drug-like molecules, searching for compounds that can selectively bind to and modulate the activity of key cancer-related protein targets. By employing sophisticated in silico methods, the research team will systematically screen and evaluate millions of compounds, examining their structural and physicochemical properties, as well as their predicted interactions with target proteins. The first phase of the project will involve the careful selection and curation of a comprehensive dataset of cancer-related protein targets. These targets will be chosen based on their established roles in cancer pathogenesis, their druggability, and the availability of high-quality structural information. The team will then utilize cutting-edge molecular docking algorithms to efficiently dock the large compound library against the selected target proteins, predicting the binding affinities and identifying promising lead compounds. The virtual screening process will be further refined and enhanced through the incorporation of machine learning techniques. By training predictive models on the docking results and known active/inactive compounds, the team will develop intelligent scoring functions that can more accurately distinguish between potential drug candidates and non-binders. This approach will help to narrow down the pool of compounds, focusing the subsequent experimental validation efforts on the most promising hits. Once the in silico screening process has identified a set of high-priority lead compounds, the project will move into the experimental validation phase. The selected compounds will be subjected to a series of in vitro assays, including target-specific binding and activity assays, as well as more comprehensive cell-based functional screens in relevant cancer cell lines. This experimental validation will provide crucial insights into the compounds' mechanism of action, potency, and selectivity, ultimately paving the way for further optimization and preclinical development. The successful completion of this project will contribute to the development of a robust computational drug discovery pipeline, leveraging the power of molecular docking and virtual screening to identify novel anti-cancer drug candidates. The identification of promising lead compounds, coupled with a deeper understanding of their interactions with cancer-related targets, will have far-reaching implications for the future of cancer therapeutics. By accelerating the drug discovery process and providing a rich pool of potential drug candidates, this project has the potential to significantly impact the fight against this devastating disease.

Project Overview