Chinese researchers claim to have created an AI model that can forecast the intricate structural alterations that protein molecules undergo.
Chinese researchers claim to have created an AI model that can forecast the intricate structural alterations that protein molecules undergo, potentially to speed up the development of new drugs.
Chinese researchers claim to have accomplished “the impossible”: creating an AI that can forecast changes in protein structure, a task so challenging that many biologists, including Yan Ning, China’s “goddess scientist,” believed it was beyond the scope of machine learning.
According to the researchers, who were under the direction of Professor Li Ziqing from the engineering school at Westlake University, the discovery could speed up the development of preclinical drugs. In October, the peer-reviewed journal Advanced Science published a portion of their work.
Proteins are long chains of amino acids that are essential for many biological functions in the body. The specific sequence of amino acids in a protein determines its three-dimensional structure, which can change in response to various stimuli.
These changes in conformation can have important effects on the protein’s function. For example, enzymes, which are proteins that catalyze chemical reactions, often have specific conformations that allow them to bind to their substrates and carry out their catalytic function.
Similarly, structural proteins, such as collagen and keratin, have specific conformations that give them their strength and elasticity. The ability of proteins to change conformation allows them to perform a wide variety of functions in the body.
Using artificial intelligence (AI) to predict protein structure and function can be a powerful tool for drug development. Protein structure is important because it determines how the protein functions in the body.
By understanding the structure and how it changes in response to different stimuli, researchers can design drugs that target specific proteins and alter their function. There are several approaches to using AI for protein structure prediction, including machine learning algorithms that can analyze large datasets of known protein structures to predict the structure of new proteins.
These methods can be used to rapidly screen large numbers of potential drug candidates and identify those with the greatest potential for success.