{"id":10429,"date":"2021-03-31T14:11:18","date_gmt":"2021-03-31T13:11:18","guid":{"rendered":"https:\/\/www.innovationnewsnetwork.com\/?p=10429"},"modified":"2021-08-06T13:34:49","modified_gmt":"2021-08-06T12:34:49","slug":"engineering-protein-based-drugs-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/www.innovationnewsnetwork.com\/engineering-protein-based-drugs-artificial-intelligence\/10429\/","title":{"rendered":"Engineering protein-based drugs using Artificial Intelligence"},"content":{"rendered":"
Proteins are large molecules that play significant roles in all living cells, building, modifying, and breaking down other molecules naturally inside our cells.<\/p>\n
Protein-based drugs are widely used, with insulin, the diabetes drug, being the most prescribed. Various cancer treatments as well as antibody formulas currently being used to treat COVID-19<\/a>, are also protein based.<\/p>\n Current methods used for engineering proteins are reliant on the introduction of random mutations to protein sequences. However, with each additional random mutation introduced, the protein activity declines.<\/p>\n The research team\u2019s new results, that have been published in the journal Nature Machine Intelligence<\/em>, represent a breakthrough in the field of synthetic proteins.<\/p>\n Aleksej Zelezniak, Associate Professor at the Department of Biology and Biological Engineering at Chalmers University of Technology<\/a>, commented: \u201cWhat we are now able to demonstrate offers fantastic potential for a number of future applications, such as faster and more cost-efficient development of protein-based drugs.<\/p>\n \u201cConsequently, one must perform multiple rounds of very expensive and time-consuming experiments, screening millions of variants, to engineer proteins and enzymes that end up being significantly different from those found in nature.. This engineering process is very slow, but now we have an AI-based method where we can go from computer design to working protein in just a few weeks.\u201d<\/p>\n Zelezniak\u2019s research group and collaborators have developed an AI-based approach called ProteinGAN, which uses a generative deep learning approach.<\/p>\n