A5001757327- Machine Learning in Bioinformatics
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- Language and cultural evolution
- Protein Structure and Dynamics
New York Consortium in Evolutionary Primatology
2025
Recent advances in machine learning have leveraged evolutionary information multiple sequence alignments to predict protein structure. We demonstrate direct inference of full atomic-level structure from primary using a large language model. As models sequences are scaled up 15 billion parameters, an atomic-resolution picture emerges the learned representations. This results order-of-magnitude acceleration high-resolution prediction, which enables large-scale structural characterization...
Abstract Artificial intelligence has the potential to open insight into structure of proteins at scale evolution. It only recently been possible extend protein prediction two hundred million cataloged proteins. Characterizing structures exponentially growing billions sequences revealed by large gene sequencing experiments would necessitate a break-through in speed folding. Here we show that direct inference from primary sequence using language model enables an order magnitude speed-up high...
Abstract More than three billion years of evolution have produced an image biology encoded into the space natural proteins. Here we show that language models trained on tokens generated by can act as evolutionary simulators to generate functional proteins are far away from known We present ESM3, a frontier multimodal generative model reasons over sequence, structure, and function ESM3 follow complex prompts combining its modalities is highly responsive biological alignment. prompted...
More than three billion years of evolution have produced an image biology encoded into the space natural proteins. Here we show that language models trained at scale on evolutionary data can generate functional proteins are far away from known We present ESM3, a frontier multimodal generative model reasons over sequence, structure, and function ESM3 follow complex prompts combining its modalities is highly responsive to alignment improve fidelity. prompted fluorescent Among generations...