The scientific research to better understand the full potential and functions of proteins lies within the protein's structure. EMSFold is a great biological tool developed to predict protein structure based on the ESM-2 language model. The focus on this project is to build an algorithm to predict an end-end single sequence protein structure. This project is motivated by Osanseviero.
Visit streamlit app and make protein sequence prediction.
The evaluation metric used to monitor the performance of the model is predicted local distance difference test (pLDDT). The predicted structures contain atomic coordinates and per-residue confidence estimates on a scale from 0 to 100, with higher scores corresponding to higher confidence. This confidence measure corresponds to the model's predicted per-residue scores on the IDDT-Cα metric.
Thanks to Data Professor for the support.