AlphaFold Blindness to Topological Barriers Affects Its Ability to Correctly Predict Proteins’ Topology
AlphaFold is a groundbreaking deep learning tool for protein structure prediction. It achieved remarkable accuracy in modeling many 3D structures while taking as the user input only the known amino acid sequence of proteins in question. Intriguingly though, in the early steps of each individual stru...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-11-01
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| Series: | Molecules |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1420-3049/28/22/7462 |
| _version_ | 1797458242433974272 |
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| author | Pawel Dabrowski-Tumanski Andrzej Stasiak |
| author_facet | Pawel Dabrowski-Tumanski Andrzej Stasiak |
| author_sort | Pawel Dabrowski-Tumanski |
| collection | DOAJ |
| description | AlphaFold is a groundbreaking deep learning tool for protein structure prediction. It achieved remarkable accuracy in modeling many 3D structures while taking as the user input only the known amino acid sequence of proteins in question. Intriguingly though, in the early steps of each individual structure prediction procedure, AlphaFold does not respect topological barriers that, in real proteins, result from the reciprocal impermeability of polypeptide chains. This study aims to investigate how this failure to respect topological barriers affects AlphaFold predictions with respect to the topology of protein chains. We focus on such classes of proteins that, during their natural folding, reproducibly form the same knot type on their linear polypeptide chain, as revealed by their crystallographic analysis. We use partially artificial test constructs in which the mutual non-permeability of polypeptide chains should not permit the formation of complex composite knots during natural protein folding. We find that despite the formal impossibility that the protein folding process could produce such knots, AlphaFold predicts these proteins to form complex composite knots. Our study underscores the necessity for cautious interpretation and further validation of topological features in protein structures predicted by AlphaFold. |
| first_indexed | 2024-03-09T16:34:17Z |
| format | Article |
| id | doaj.art-696e35bbf1f54cb3b27c506a443ea47c |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-09T16:34:17Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-696e35bbf1f54cb3b27c506a443ea47c2023-11-24T14:57:49ZengMDPI AGMolecules1420-30492023-11-012822746210.3390/molecules28227462AlphaFold Blindness to Topological Barriers Affects Its Ability to Correctly Predict Proteins’ TopologyPawel Dabrowski-Tumanski0Andrzej Stasiak1Faculty of Mathematics and Natural Sciences, School of Exact Sciences, Cardinal Wyszynski University in Warsaw, Wóycickiego 1/3, 01-938 Warsaw, PolandCenter for Integrative Genomics, University of Lausanne, 1015 Lausanne, SwitzerlandAlphaFold is a groundbreaking deep learning tool for protein structure prediction. It achieved remarkable accuracy in modeling many 3D structures while taking as the user input only the known amino acid sequence of proteins in question. Intriguingly though, in the early steps of each individual structure prediction procedure, AlphaFold does not respect topological barriers that, in real proteins, result from the reciprocal impermeability of polypeptide chains. This study aims to investigate how this failure to respect topological barriers affects AlphaFold predictions with respect to the topology of protein chains. We focus on such classes of proteins that, during their natural folding, reproducibly form the same knot type on their linear polypeptide chain, as revealed by their crystallographic analysis. We use partially artificial test constructs in which the mutual non-permeability of polypeptide chains should not permit the formation of complex composite knots during natural protein folding. We find that despite the formal impossibility that the protein folding process could produce such knots, AlphaFold predicts these proteins to form complex composite knots. Our study underscores the necessity for cautious interpretation and further validation of topological features in protein structures predicted by AlphaFold.https://www.mdpi.com/1420-3049/28/22/7462AlphaFoldprotein structure predictiontopological barriersknotted proteinstopology validationresidue gas model |
| spellingShingle | Pawel Dabrowski-Tumanski Andrzej Stasiak AlphaFold Blindness to Topological Barriers Affects Its Ability to Correctly Predict Proteins’ Topology Molecules AlphaFold protein structure prediction topological barriers knotted proteins topology validation residue gas model |
| title | AlphaFold Blindness to Topological Barriers Affects Its Ability to Correctly Predict Proteins’ Topology |
| title_full | AlphaFold Blindness to Topological Barriers Affects Its Ability to Correctly Predict Proteins’ Topology |
| title_fullStr | AlphaFold Blindness to Topological Barriers Affects Its Ability to Correctly Predict Proteins’ Topology |
| title_full_unstemmed | AlphaFold Blindness to Topological Barriers Affects Its Ability to Correctly Predict Proteins’ Topology |
| title_short | AlphaFold Blindness to Topological Barriers Affects Its Ability to Correctly Predict Proteins’ Topology |
| title_sort | alphafold blindness to topological barriers affects its ability to correctly predict proteins topology |
| topic | AlphaFold protein structure prediction topological barriers knotted proteins topology validation residue gas model |
| url | https://www.mdpi.com/1420-3049/28/22/7462 |
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