Year: 2024
Type: article
Abstract: Antibodies are microscopic defenders in our body's immune system, protecting us against foreign pathogens.These specialized protein molecules, shaped like the letter Y are produced by plasma cells and possess the ability to precisely locate and bind to specific antigens, inactivating harmful substances like toxins and facilitating the destruction or neutralization of pathogens.The remarkable diversity of antibodies, generated by immune systems' adaptability often referred to as immune repertoire or a condition of genetic variations, allows the immune system to respond to a vast array of potential threats.Recent advancements in artificial intelligence have opened new doors in many fields including medicine.By harnessing machine learning algorithms, generative AI models can be trained to design ground-breaking antibody structures with selected traits from existing data and knowledge.This approach can significantly accelerate the antibody discovery process, leading to the ushering era of smart medicine.This paper aims to explore how generative AI is being utilized to design new antibodies.We explore how this technology could potentially streamline the traditionally lengthy process of developing new antibodies through physical enumeration.We aim to shed light on a promising frontier in drug discovery and synthesis.Our discussion encompasses both the potential benefits and the challenges of this emerging approach
Institution: Jawaharlal Nehru Technological University, Hyderabad
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4402372847