{"id":"doi:10.3390/biom12070985","kind":"article","title":"Benchmarking the Accuracy of AlphaFold 2 in Loop Structure Prediction","authors":["Amy O. Stevens","Yi Jie He"],"author_count":2,"year":2022,"published":"2022-07-14","venue":"Biomolecules","cited_by":97,"doi":"10.3390/biom12070985","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.3390/biom12070985","archive_url":"https://space-kitty.com/papers/doi:10.3390/biom12070985","updated":null,"pmid":"35883541","pmcid":null,"openalex_id":"W4285594705","pdf_url":"https://www.mdpi.com/2218-273X/12/7/985/pdf?version=1658241523","abstract":"The inhibition of protein-protein interactions is a growing strategy in drug development. In addition to structured regions, many protein loop regions are involved in protein-protein interactions and thus have been identified as potential drug targets. To effectively target such regions, protein structure is critical. Loop structure prediction is a challenging subgroup in the field of protein structure prediction because of the reduced level of conservation in protein sequences compared to the secondary structure elements. AlphaFold 2 has been suggested to be one of the greatest achievements in the field of protein structure prediction. The AlphaFold 2 predicted protein structures near the X-ray resolution in the Critical Assessment of protein Structure Prediction (CASP 14) competition in 2020. The purpose of this work is to survey the performance of AlphaFold 2 in specifically predicting protein loop regions. We have constructed an independent dataset of 31,650 loop regions from 2613 proteins (deposited after the AlphaFold 2 was trained) with both experimentally determined structures and AlphaFold 2 predicted structures. With extensive evaluation using our dataset, the results indicate that AlphaFold 2 is a good predictor of the structure of loop regions, especially for short loop regions. Loops less than 10 residues in length have an average Root Mean Square Deviation (RMSD) of 0.33 Å and an average the Template Modeling score (TM-score) of 0.82. However, we see that as the number of residues in a given loop increases, the accuracy of AlphaFold 2's prediction decreases. Loops more than 20 residues in length have an average RMSD of 2.04 Å and an average TM-score of 0.55. Such a correlation between accuracy and length of the loop is directly linked to the increase in flexibility. Moreover, AlphaFold 2 does slightly over-predict α-helices and β-strands in proteins.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Protein Structure and Dynamics"],"details":null,"provenance":"openalex","attribution":"Abstract of \"Benchmarking the Accuracy of AlphaFold 2 in Loop Structure Prediction\" by Amy O. Stevens, Yi Jie He, https://doi.org/10.3390/biom12070985, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.","topics":[{"slug":"protein-design","name":"AI Protein Design & Structure Prediction","domain_slug":"biotech"}],"cited_in_dossiers":[]}