CAT-Site : predicting protein binding sites using a convolutional neural network

Hafner Petrovski, Žan (avtor), Hribar-Lee, Barbara (avtor), Bosnić, Zoran (avtor)

Identifying binding sites on the protein surface is an important part of computer-assisted drug design processes. Reliable prediction of binding sites not only assists with docking algorithms, but it can also explain the possible side-effects of a potential drug as well as its efficiency. In this work, we propose a novel workflow for predicting possible binding sites of a ligand on a protein surface. We use proteins from the PDBbind and sc-PDB databases, from which we combine available ligand information for similar proteins using all the possible ligands rather than only a special sub-selection to generalize the work of existing research. After performing protein clustering and merging of ligands of similar proteins, we use a three-dimensional convolutional neural network that takes into account the spatial structure of a protein. Lastly, we combine ligandability predictions for points on protein surfaces into joint binding sites. Analysis of our model’s performance shows that its achieved sensitivity is 0.829, specificity is 0.98, and F$_1$ score is 0.517, and that for 54% of larger and pharmacologically relevant binding sites, the distance between their real and predicted centers amounts to less than 4 Å.

• Jezik: Angleški jezik
• Ključne besede: protein binding site prediction, ligands, molecular docking, machine learning, convolutional neural network
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FRI - Fakulteta za računalništvo in informatiko; FKKT - Fakulteta za kemijo in kemijsko tehnologijo
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2022
• Št. strani: 21 str.
• Številčenje: Vol. 15, iss. 1, art. 119
• PID: 20.500.12556/RUL-154114
• UDK: 004.8:615
• ISSN pri članku: 1999-4923
• DOI: 10.3390/pharmaceutics15010119
• COBISS.SI-ID: 135845635
• Datum objave v RUL: 25.01.2024

Gradivo je del revije

• Naslov: Pharmaceutics
• Skrajšan naslov: Pharmaceutics
• Založnik: MDPI
• ISSN: 1999-4923
• COBISS.SI-ID: 517949977

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: napovedovanje veznih mest proteinov, ligandi, molekulsko sidranje, strojno učenje, konvolucijska nevronska mreža