Artificial intelligence to deep learning: machine intelligence approach for drug discovery

Rohan Gupta; Devesh Srivastava; Mehar Sahu; Swati Tiwari; Rashmi K. Ambasta; Pravir Kumar

doi:10.1007/s11030-021-10217-3

Keywords

Artificial intelligenceComputer scienceDrug discoveryDeep learningMachine learningBig dataDrug developmentData scienceDrugData miningBioinformaticsMedicinePharmacology

Affiliated Institutions

Delhi Technological University IN

Related Publications

A Structure-Based Drug Discovery Paradigm

Maria Batool , Sheikh Bilal Ahmad , Sangdun Choi

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 structura...

2019 International Journal of Molecular Sc... 671 citations

Applications of machine learning in drug discovery and development

Jessica Vamathevan , Dominic A. Clark , Paul Czodrowski +8 more

Drug discovery and development pipelines are long, complex and depend on numerous factors. Machine learning (ML) approaches provide a set of tools that can improve discovery and...

2019 Nature Reviews Drug Discovery 2563 citations

Structure-based drug design with geometric deep learning

Clemens Isert , Kenneth Atz , Gisbert Schneider

Structure-based drug design uses three-dimensional geometric information of macromolecules, such as proteins or nucleic acids, to identify suitable ligands. Geometric deep learn...

2023 Current Opinion in Structural Biology 132 citations

The rise of deep learning in drug discovery

Hongming Chen , Ola Engkvist , Yinhai Wang +2 more

Over the past decade, deep learning has achieved remarkable success in various artificial intelligence research areas. Evolved from the previous research on artificial neural ne...

2018 Drug Discovery Today 1619 citations

DeepDTA: deep drug–target binding affinity prediction

Hakime Öztürk , Arzucan Özgür , Elif Özkırımlı

Abstract Motivation The identification of novel drug–target (DT) interactions is a substantial part of the drug discovery process. Most of the computational methods that have be...

2018 Bioinformatics 1417 citations

Publication Info

Year: 2021
Type: review
Volume: 25
Issue: 3
Pages: 1315-1360
Citations: 1233
Access: Closed

External Links

View on DOI.org

Social Impact

Altmetric

Artificial intelligence to deep learning: machine intelligence approach for drug discovery

PlumX Metrics

Social media, news, blog, policy document mentions

Citation Metrics

1233

OpenAlex

Cite This

APA Style

                            
                                
                                    Rohan Gupta, 
                                
                                    Devesh Srivastava, 
                                
                                    Mehar Sahu
                                
                                et al.
                            
                            (2021). 
                            Artificial intelligence to deep learning: machine intelligence approach for drug discovery. 
                            Molecular Diversity
                            , 25
                            (3)
                            , 1315-1360.
                            https://doi.org/10.1007/s11030-021-10217-3
                        

Identifiers

DOI: 10.1007/s11030-021-10217-3