Drug discovery using computational methods has gained momentum in recent years, offering novel approaches to address complex healthcare challenges. However, this field also faces various challenges, including data quality, model accuracy, and the complexity of biological systems. Additionally, computational cost and polypharmacology remain critical issues. Nonetheless, exciting future perspectives offer promising solutions. Integration of multi-omics data, artificial intelligence applications, and personalized medicine advancements provide opportunities to enhance drug discovery efficiency. Furthermore, incorporating quantum mechanics in drug design and leveraging cloud computing and high-performance resources hold transformative potential. These advancements pave the way for revolutionizing drug discovery and improving treatment efficacy, fostering better healthcare outcomes for patients worldwide.