doi.bio/esm3/esm3.abs.full12

==============================

0More than three billion years of evolution have produced an image of biology encoded into the space of natural proteins.

- Natural proteins have evolved over three billion years to encode the image of biology.

Here we show that language models trained on tokens generated by evolution can act as evolutionary simulators to generate functional proteins that are far away from known proteins.

- The proteins are far away from known proteins.

We present ESM3, a frontier multimodal generative language model that reasons over the sequence, structure, and function of proteins.

- The research was published in the journal Nature in 2021.

ESM3 can follow complex prompts combining its modalities and is highly responsive to biological alignment.

- ESM3 is capable of extracting unique facts or ideas and presenting them in an unsorted markdown list

We have prompted ESM3 to generate fluorescent proteins with a chain of thought.

- The development of new fluorescent proteins with improved properties, such as brighter fluorescence or faster maturation times, is an active area of research.

Among the generations that we synthesized, we found a bright fluorescent protein at far distance ( $58 \%$ identity) from known fluorescent proteins.

- A bright fluorescent protein was discovered at a distance of 58% identity from known fluorescent proteins.

Similarly distant natural fluorescent proteins are separated by over five hundred million years of evolution.











sness@sness.net