Virtual Screening Meets Deep Learning

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BACKGROUND: Automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the number of new drugs that was expected. Computer- aided compounds search, known as Virtual Screening, has shown the benefits to this field as a complement or even alternative to the robotic drug discovery. There are different methods and approaches to address this problem and most of them are often included in one of the main screening strategies. Machine learning, however, has established itself as a virtual screening methodology in its own right and it may grow in popularity with the new trends on artificial intelligence.

OBJECTIVE: This paper will attempt to provide a comprehensive and structured review that collects the most important proposals made so far in this area of research. Particular attention is given to some recent developments carried out in the machine learning field: the deep learning approach, which is pointed out as a future key player in the virtual screening landscape.

Medienart:

E-Artikel

Erscheinungsjahr:

2019

Erschienen:

2019

Enthalten in:

Zur Gesamtaufnahme - volume:15

Enthalten in:

Current computer-aided drug design - 15(2019), 1 vom: 22., Seite 6-28

Sprache:

Englisch

Beteiligte Personen:

Pérez-Sianes, Javier [VerfasserIn]
Pérez-Sánchez, Horacio [VerfasserIn]
Díaz, Fernando [VerfasserIn]

Links:

Volltext

Themen:

Deep learning
Drug discovery
Journal Article
Ligand-based virtual screening
Machine learning
Review
Structure-based virtual screening
Virtual screening.

Anmerkungen:

Date Completed 08.04.2019

Date Revised 08.04.2019

published: Print

Citation Status MEDLINE

doi:

10.2174/1573409914666181018141602

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM289732492