Overcoming human bias in peptide discovery | Argonne National Laboratory

October 31, 2022

As reported in Nature Communications, researchers have developed s fully automated computational search engine for peptide discovery.

Of 3.2 million possible pentapeptides, the AI expert evaluated roughly 6,600. The 9 top-scoring AI sequences were screened for actual synthesis, 6 of which were found to self-assemble based on light scattering and atomic force microscopy measurements. In comparison, 6 of 11 pentapeptides suggested by human experts were found to self-assemble.

Scientific Achievement

Typically, peptide discovery research yields fewer than ten candidates per study and is subject to human bias. A fully autonomous computational search engine has been developed to reveal peptide sequences with high potential for self-assembly.

Significance and Impact

This AI expert has the potential to accelerate discovery of self-assembling peptides with applications ranging from tissue engineering and surface coating to catalysis and sensing.

Research Details

The AI expert developed in this work combines Monte Carlo tree search, molecular dynamics simulations, and a peptide-structure-based scoring function.
It was demonstrated to efficiently search spaces with 8,000 tripeptides and 6,600 pentapeptides.

Work was performed, in part, at the Center for Nanoscale Materials (CNM).

DOI: 10.1038/s41557-022-01055-3

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About Argonne’s Center for Nanoscale Materials
The Center for Nanoscale Materials is one of the five DOE Nanoscale Science Research Centers, premier national user facilities for interdisciplinary research at the nanoscale supported by the DOE Office of Science. Together the NSRCs comprise a suite of complementary facilities that provide researchers with state-of-the-art capabilities to fabricate, process, characterize and model nanoscale materials, and constitute the largest infrastructure investment of the National Nanotechnology Initiative. The NSRCs are located at DOE’s Argonne, Brookhaven, Lawrence Berkeley, Oak Ridge, Sandia and Los Alamos National Laboratories. For more information about the DOE NSRCs, please visit https://science.osti.gov/User-Facilities/User-Facilities-at-a-Glance.

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