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SimBoost: a read-across approach for predicting drug–target binding affinities using gradient boosting machines

Journal of cheminformatics, 2017-04, Vol.9 (1), p.24-24, Article 24

2017

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Rapid Identification of Potential Inhibitors of SARS‐CoV‐2 Main Protease by Deep Docking of 1.3 Billion Compounds

Molecular informatics, 2020-08, Vol.39 (8), p.e2000028-n/a

2020

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QSAR without borders

Chemical Society reviews, 2020-06, Vol.49 (11), p.3525-3564

2020

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Therapeutic Inhibition of Myc in Cancer. Structural Bases and Computer-Aided Drug Discovery Approaches

International journal of molecular sciences, 2018-12, Vol.20 (1), p.120

2018

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The value of antimicrobial peptides in the age of resistance

The Lancet infectious diseases, 2020-09, Vol.20 (9), p.e216-e230

2020

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The transformational role of GPU computing and deep learning in drug discovery

Nature machine intelligence, 2022-03, Vol.4 (3), p.211-221

2022

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Crystallographic structure of wild-type SARS-CoV-2 main protease acyl-enzyme intermediate with physiological C-terminal autoprocessing site

Nature communications, 2020-11, Vol.11 (1), p.5877-5877, Article 5877

2020

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Deep Docking: A Deep Learning Platform for Augmentation of Structure Based Drug Discovery

ACS central science, 2020-06, Vol.6 (6), p.939-949

2020

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X-ray crystallographic characterization of the SARS-CoV-2 main protease polyprotein cleavage sites essential for viral processing and maturation

Nature communications, 2022-09, Vol.13 (1), p.5196-5196, Article 5196

2022

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Computer-Aided Ligand Discovery for Estrogen Receptor Alpha

International journal of molecular sciences, 2020-06, Vol.21 (12), p.4193

2020

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Lin28 Regulates Cancer Cell Stemness for Tumour Progression

Cancers, 2022-09, Vol.14 (19), p.4640

2022

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Discovery of Small-Molecule Inhibitors Selectively Targeting the DNA-Binding Domain of the Human Androgen Receptor

Journal of medicinal chemistry, 2014-08, Vol.57 (15), p.6458-6467

2014

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The ‘Big Bang’ of the chemical universe

Nature chemical biology, 2023-06, Vol.19 (6), p.667-668

Cherkasov, Artem

2023

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Moving Towards Precision Urologic Oncology: Targeting Enzalutamide-resistant Prostate Cancer and Mutated Forms of the Androgen Receptor Using the Novel Inhibitor Darolutamide (ODM-201)

European urology, 2018-01, Vol.73 (1), p.4-8

2018

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Deep Learning Modeling of Androgen Receptor Responses to Prostate Cancer Therapies

International journal of molecular sciences, 2020-08, Vol.21 (16), p.5847

2020

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Role of Androgen Receptor Variants in Prostate Cancer: Report from the 2017 Mission Androgen Receptor Variants Meeting

European urology, 2018-05, Vol.73 (5), p.715-723

2018

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Deep Modeling of Regulating Effects of Small Molecules on Longevity-Associated Genes

Pharmaceuticals (Basel, Switzerland), 2021-09, Vol.14 (10), p.948

2021

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Ligand Binding Prediction Using Protein Structure Graphs and Residual Graph Attention Networks

Molecules (Basel, Switzerland), 2022-08, Vol.27 (16), p.5114

2022

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Ivermectin inhibits HSP27 and potentiates efficacy of oncogene targeting in tumor models

The Journal of clinical investigation, 2020-02, Vol.130 (2), p.699-714

2020

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Dual-Inhibitors of N-Myc and AURKA as Potential Therapy for Neuroendocrine Prostate Cancer

International journal of molecular sciences, 2020-11, Vol.21 (21), p.8277

2020

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Identification of Novel Antibacterial Peptides by Chemoinformatics and Machine Learning

Journal of medicinal chemistry, 2009-04, Vol.52 (7), p.2006-2015

2009

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Development of Novel Inhibitors Targeting the D-Box of the DNA Binding Domain of Androgen Receptor

International journal of molecular sciences, 2021-03, Vol.22 (5), p.2493

2021

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Targeting the Binding Function 3 (BF3) Site of the Human Androgen Receptor through Virtual Screening

Journal of medicinal chemistry, 2011-12, Vol.54 (24), p.8563-8573

2011

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Computer-aided drug discovery of Myc-Max inhibitors as potential therapeutics for prostate cancer

European journal of medicinal chemistry, 2018-12, Vol.160, p.108-119

2018

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Use of Artificial Intelligence in the Design of Small Peptide Antibiotics Effective against a Broad Spectrum of Highly Antibiotic-Resistant Superbugs

ACS chemical biology, 2009-01, Vol.4 (1), p.65-74

2009

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SimBoost: a read-across approach for predicting drug–target binding affinities using gradient boosting machines

Rapid Identification of Potential Inhibitors of SARS‐CoV‐2 Main Protease by Deep Docking of 1.3 Billion Compounds

QSAR without borders

Therapeutic Inhibition of Myc in Cancer. Structural Bases and Computer-Aided Drug Discovery Approaches

The value of antimicrobial peptides in the age of resistance

The transformational role of GPU computing and deep learning in drug discovery

Crystallographic structure of wild-type SARS-CoV-2 main protease acyl-enzyme intermediate with physiological C-terminal autoprocessing site

Deep Docking: A Deep Learning Platform for Augmentation of Structure Based Drug Discovery

X-ray crystallographic characterization of the SARS-CoV-2 main protease polyprotein cleavage sites essential for viral processing and maturation

Computer-Aided Ligand Discovery for Estrogen Receptor Alpha

Lin28 Regulates Cancer Cell Stemness for Tumour Progression

Discovery of Small-Molecule Inhibitors Selectively Targeting the DNA-Binding Domain of the Human Androgen Receptor

The ‘Big Bang’ of the chemical universe

Moving Towards Precision Urologic Oncology: Targeting Enzalutamide-resistant Prostate Cancer and Mutated Forms of the Androgen Receptor Using the Novel Inhibitor Darolutamide (ODM-201)

Deep Learning Modeling of Androgen Receptor Responses to Prostate Cancer Therapies

Role of Androgen Receptor Variants in Prostate Cancer: Report from the 2017 Mission Androgen Receptor Variants Meeting

Deep Modeling of Regulating Effects of Small Molecules on Longevity-Associated Genes

Ligand Binding Prediction Using Protein Structure Graphs and Residual Graph Attention Networks

Ivermectin inhibits HSP27 and potentiates efficacy of oncogene targeting in tumor models

Dual-Inhibitors of N-Myc and AURKA as Potential Therapy for Neuroendocrine Prostate Cancer

Identification of Novel Antibacterial Peptides by Chemoinformatics and Machine Learning

Development of Novel Inhibitors Targeting the D-Box of the DNA Binding Domain of Androgen Receptor

Targeting the Binding Function 3 (BF3) Site of the Human Androgen Receptor through Virtual Screening

Computer-aided drug discovery of Myc-Max inhibitors as potential therapeutics for prostate cancer

Use of Artificial Intelligence in the Design of Small Peptide Antibiotics Effective against a Broad Spectrum of Highly Antibiotic-Resistant Superbugs

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