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Protein design with a machine-learned potential about backbone designability

Trends Biochem Sci. 2022 Apr 21:S0968-0004(22)00089-5. doi: 10.1016/j.tibs.2022.04.004. Online ahead of print.

ABSTRACT

Proteins are fundamental molecules that mediate diverse biological processes, and protein design can shed light on the molecular mechanisms underlying their biological functions. Huang and colleagues have developed a sequence-independent statistical model for de novo protein design using neural networks (NNs) to learn the distribution of backbone structures with minimal side-chain information.

PMID:35466034 | DOI:10.1016/j.tibs.2022.04.004

By Nevin Manimala

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