MARC details
| 000 -LEADER |
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| fixed length control field |
01908nam a2200277Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
MX-MdCICY |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20250625162440.0 |
| 040 ## - CATALOGING SOURCE |
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| Transcribing agency |
CICY |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
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| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
B-19973 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
250602s9999 xx |||||s2 |||| ||und|d |
| 245 10 - TITLE STATEMENT |
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| Title |
Evaluation of AlphaFold2 structures as docking targets |
| 490 0# - SERIES STATEMENT |
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| Volume/sequential designation |
Protein Science, 32(1), p.e4530, 2023 |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
AlphaFold2 is a promising new tool for researchers to predict protein structures and generate high?quality models, with low backbone and global root?mean?square deviation (RMSD)when compared with experimental structures. However, it is unclear if the structures predicted by AlphaFold2 will be valuable targets of docking. To address this question, we redocked ligands in the PDBbind datasets against the experimental co?crystallized receptor structures and against the AlphaFold2 structures using AutoDock?GPU. We find that the quality measure provided during structure prediction is not a good predictor of docking performance, despite accurately reflecting the quality of the alpha carbon alignment with experimental structures. Removing low?confidence regions of the predicted structure and making side chains flexible improves the docking outcomes. Overall, despite high?quality prediction of backbone conformation, fine structural details limit the naive application of AlphaFold2 models as docking targets. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
ALPHAFOLD2 |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
AUTODOCK PROTEIN STRUCTURE PREDICTION |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
COMPUTATIONAL DOCKING |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
COMPUTER?AIDED DRUG DESIGN |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
DRUG DESIGN AND DEVELOPMENT |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
VIRTUAL SCREENING |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Holcomb, M. |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Chang, Y. T. |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Goodsell, D. S. |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Forli, S. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
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| Uniform Resource Identifier |
<a href="https://drive.google.com/file/d/1v6LlzW5LQw1kUZWmyp590lA_D9fuGt9Q/view?usp=drivesdk">https://drive.google.com/file/d/1v6LlzW5LQw1kUZWmyp590lA_D9fuGt9Q/view?usp=drivesdk</a> |
| Public note |
Para ver el documento ingresa a Google con tu cuenta: @cicy.edu.mx |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Clasificación local |
| Koha item type |
Documentos solicitados |
