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A Structure-Based Drug Discovery Paradigm
Batool, Maria ; Ahmad, Bilal ; Choi, Sangdun
International journal of molecular sciences, 2019-06, Vol.20 (11), p.2783
[Periódico revisado por pares]
Switzerland: MDPI AG
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Título:
A Structure-Based Drug Discovery Paradigm
Autor:
Batool, Maria
;
Ahmad, Bilal
;
Choi, Sangdun
Assuntos:
Algorithms
;
Artificial intelligence
;
Binding sites
;
Clinical trials
;
Combinatorial analysis
;
Combinatorial chemistry
;
Deep Learning
;
Drug development
;
Drug discovery
;
Drug Discovery - methods
;
Drugs
;
FDA approval
;
Identification
;
Learning algorithms
;
Ligands
;
Machine learning
;
Methods
;
Molecular Docking Simulation - methods
;
neural network
;
Organic chemistry
;
Pharmaceutical industry
;
Proteins
;
Proteomics
;
Quantitative Structure-Activity Relationship
;
Review
;
scoring function
;
Software
;
Statistical methods
;
structure-based drug discovery
;
virtual screening
É parte de:
International journal of molecular sciences, 2019-06, Vol.20 (11), p.2783
Notas:
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-3
content type line 23
ObjectType-Review-1
Descrição:
Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structural studies have provided hundreds of new targets and opportunities for future drug discovery. This situation poses a major problem: the necessity to handle the "big data" generated by combinatorial chemistry. Artificial intelligence (AI) and deep learning play a pivotal role in the analysis and systemization of larger data sets by statistical machine learning methods. Advanced AI-based sophisticated machine learning tools have a significant impact on the drug discovery process including medicinal chemistry. In this review, we focus on the currently available methods and algorithms for structure-based drug design including virtual screening and de novo drug design, with a special emphasis on AI- and deep-learning-based methods used for drug discovery.
Editor:
Switzerland: MDPI AG
Idioma:
Inglês
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