Application of in-silico approaches in subunit vaccines: Overcoming the challenges of antigen and adjuvant...

Subunit vaccines are crucial in preventing modern diseases due to their safety, stability, and ability to elicit targeted immune responses. However, challenges in antigen and adjuvant design hinder their development. Recent advancements in in-silico approaches, including reverse vaccinology, structural vaccinology, and machine learning, have revolutionized vaccine development from empirical practices to rational design approaches. This review summarizes the transformative impact of in-silico approaches on subunit vaccine development. We address the challenges of antigen identification and designation, highlighting how advanced computational techniques are employed to accelerate antigen acquisition. We also examine the challenges in adjuvant discovery and illustrate how machine learning helps overcome these barriers. Finally, we explore potential future directions for subunit vaccines, highlighting the importance of combining computational methods with other technologies to tackle the challenges associated with subunit vaccine development.