Evaluating Quantum And Classical Computing Approaches In Modern Drug Discovery

Drug discovery is inherently complex and expensive with many requisites in terms of precision with respect to interactions\\\' molecular modelling, biological activity prediction and chemical compounds optimisation. Classical computing methods have contributed substantially to the progress of computational drug discovery via molecular simulations, machine learning models and high-throughput virtual screening. However, challenges emerge from the exponentiality of molecular configuration space and the low efficiency of classical algorithms. Quantum computing as a new computing paradigm that offers a novel approach to computation based on various phenomena such as superposition and entanglement and therefore offers a way to overcome the previous limitations. This work presents a comparison of classical and quantum computing approaches in drug discovery with emphasis on their strengths and weaknesses, current progress and future prospects in different aspects of pharmaceutical research.