التفاصيل البيبلوغرافية
| العنوان: |
Addressing docking pose selection with structure-based deep learning: Recent advances, challenges and opportunities |
| المؤلفون: |
Serena Vittorio, Filippo Lunghini, Pietro Morerio, Davide Gadioli, Sergio Orlandini, Paulo Silva, Jan Martinovic, Alessandro Pedretti, Domenico Bonanni, Alessio Del Bue, Gianluca Palermo, Giulio Vistoli, Andrea R. Beccari |
| المصدر: |
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 2141-2151 (2024) |
| بيانات النشر: |
Elsevier, 2024. |
| سنة النشر: |
2024 |
| المجموعة: |
LCC:Biotechnology |
| مصطلحات موضوعية: |
Artificial intelligence, Deep learning, Molecular docking, Scoring functions, Pose selection, Biotechnology, TP248.13-248.65 |
| الوصف: |
Molecular docking is a widely used technique in drug discovery to predict the binding mode of a given ligand to its target. However, the identification of the near-native binding pose in docking experiments still represents a challenging task as the scoring functions currently employed by docking programs are parametrized to predict the binding affinity, and, therefore, they often fail to correctly identify the ligand native binding conformation. Selecting the correct binding mode is crucial to obtaining meaningful results and to conveniently optimizing new hit compounds. Deep learning (DL) algorithms have been an area of a growing interest in this sense for their capability to extract the relevant information directly from the protein-ligand structure. Our review aims to present the recent advances regarding the development of DL-based pose selection approaches, discussing limitations and possible future directions. Moreover, a comparison between the performances of some classical scoring functions and DL-based methods concerning their ability to select the correct binding mode is reported. In this regard, two novel DL-based pose selectors developed by us are presented. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2001-0370 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S2001037024001727; https://doaj.org/toc/2001-0370 |
| DOI: |
10.1016/j.csbj.2024.05.024 |
| URL الوصول: |
https://doaj.org/article/ccdbf80f896a465092452dc83d441d51 |
| رقم الانضمام: |
edsdoj.bf80f896a465092452dc83d441d51 |
| قاعدة البيانات: |
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