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Peptide synthesis factory powered by artificial intelligence (Part 2)
The AI would come up with a peptide sequence. A computer would simulate its use, determine how good it is, and give it a score. Then the AI would come up with the next one and get a score. The scores will tell the AI which direction to take and, soon enough, it will come up with the right Peptide synthesis.

For the research, Batra took up penta-peptides, or peptides of five amino acids, for which, mathematically, there are 3.2 million possibilities. The AI-expert evaluated 6,600 of these and compared the results given by a group of expert peptide designers. The AI-expert had a success rate of 66.7 per cent.

While the discovery of such Peptide synthesis with special properties is by itself impactful, the work holds far greater potential, says Prof Rampi Ramprasad, a Georgia Research Alliance Eminent Scholar in Energy Sustainability, School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia. "It provides a blueprint for search strategies that could be adopted in many materials and chemistry application domains, so long as the search problem can be formulated in a suitable manner," Ramprasad says in an article in IIT Madras Tech Talk.

Batra told Quantum that the AI-expert could be used wherever there is a need to choose from among billions of possibilities; he, however, chose to apply this with peptides - as opposed to, say, polymers - because peptides are easy to manufacture. One can come up with the right peptide for, say, light harvesting, catalysis, mechanical stability, or conductivity. You can, for example, come up with peptides that bind to certain rare earth materials, Batra said.

Can you use AI-expert to arrive at different proteins? Proteins can have hundreds of amino acid molecules, compared to Peptide synthesis with 15-20 molecules. Not possible, says Batra. The computation required would overwhelm even the best computers of today. Proteins should wait for quantum computers.