Journal ArticleDOI
Recent progress on cheminformatics approaches to epigenetic drug discovery.
Zoe L Sessions,Norberto Sánchez-Cruz,Fernando D. Prieto-Martínez,Vinicius M. Alves,Hudson P. Santos,Eugene N. Muratov,Alexander Tropsha,José L. Medina-Franco +7 more
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TLDR
The advances in computational approaches to drug discovery of small molecules with epigenetic modulation profiles are reviewed, the current chemogenomics data available for epigenetics targets are summarized, and a perspective on the greater utility of biomedical knowledge mining as a means to advance the epigenetic drug discovery is provided.About:
This article is published in Drug Discovery Today.The article was published on 2020-09-30. It has received 22 citations till now. The article focuses on the topics: Chemogenomics & Cheminformatics.read more
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Artificial intelligence–enabled virtual screening of ultra-large chemical libraries with deep docking
Francesco Gentile,Jean Charle Yaacoub,James Gleave,Michael Fernandez,Anh-Tien Ton,Fuqiang Ban,Abraham C. Stern,Artem Cherkasov +7 more
TL;DR: The Deep Docking (DD) platform as discussed by the authors enables up to 100-fold acceleration of structure-based virtual screening by docking only a subset of a chemical library, iteratively synchronized with a ligand-based prediction of the remaining docking scores.
Journal ArticleDOI
Epigenetic Target Fishing with Accurate Machine Learning Models.
TL;DR: In this article, a large-scale study of 26 318 compounds with a quantitative measure of biological activity for 55 protein targets with epigenetic activity was conducted. And the results indicated that the models reported herein have considerable potential to identify small molecules with epigenetics activity.
Journal ArticleDOI
Epigenetic Target Profiler: A Web Server to Predict Epigenetic Targets of Small Molecules.
TL;DR: The Epigenetic Target Profiler (ETP) as discussed by the authors uses a consensus model based on two binary classification models for each target, relying on support vector machines and built on molecular fingerprints of different design.
Journal ArticleDOI
KDM4 Involvement in Breast Cancer and Possible Therapeutic Approaches.
TL;DR: The KDM4 gene family includes more than 30 members, grouped into six subfamilies and two classes based on their sequency homology and catalytic mechanisms, respectively as mentioned in this paper.
Journal ArticleDOI
Design, Synthesis, and Biological Evaluation of Lysine Demethylase 5 C Degraders.
Tetsuya Iida,Tetsuya Iida,Yukihiro Itoh,Yukihiro Itoh,Yukari Takahashi,Yasunobu Yamashita,Takashi Kurohara,Yuka Miyake,Makoto Oba,Takayoshi Suzuki,Takayoshi Suzuki +10 more
TL;DR: In this article, a protein-knockdown strategy was used to identify Lysine demethylase 5 C (KDM5C) degraders, which inhibited the growth of prostate cancer PC-3 cells more strongly than compound 1.
References
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Journal ArticleDOI
Computational Epigenetics: the new scientific paradigm.
TL;DR: Examination of existing computational strategies for the study of epigenetic factors offers new opportunities to further the understanding of transcriptional regulation, nuclear organization, development and disease.
Journal ArticleDOI
Toward Learned Chemical Perception of Force Field Typing Rules.
Camila Zanette,Caitlin C. Bannan,Christopher I. Bayly,Josh Fass,Michael K. Gilson,Michael R. Shirts,John D. Chodera,David L. Mobley +7 more
TL;DR: Novel methods that automate the discovery of appropriate chemical perception are described: SMARTY allows for the creation of atom types, while SMIRKY goes further by automating the created of fragment types, which are used within a Monte Carlo optimization approach.
Journal ArticleDOI
Development of a versatile DNMT and HDAC inhibitor C02S modulating multiple cancer hallmarks for breast cancer therapy.
Zigao Yuan,Shaopeng Chen,Chunmei Gao,Qiuzi Dai,Cunlong Zhang,Qinsheng Sun,Jin-Shun Lin,Chun Guo,Yu Zong Chen,Yuyang Jiang,Yuyang Jiang +10 more
TL;DR: The development of a novel dual DNMT and HDAC inhibitor C02S which showed potent enzymatic inhibitory activities against DNMT1, DNMT3A,DNMT3B andHDAC1 with IC50 values of 2.05, 0.93, 1.16 µM, respectively is reported.
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Development, Validation, and Use of Quantitative Structure−Activity Relationship Models of 5-Hydroxytryptamine (2B) Receptor Ligands to Identify Novel Receptor Binders and Putative Valvulopathic Compounds among Common Drugs
Rima Hajjo,Christopher M. Grulke,Alexander Golbraikh,Vincent Setola,Xi Ping Huang,Bryan L. Roth,Alexander Tropsha +6 more
TL;DR: It is suggested that the QSAR models developed in this study could be used as reliable predictors to flag drug candidates that are likely to cause valvulopathy.
Journal ArticleDOI
BET bromodomain inhibitors: fragment-based in silico design using multi-target QSAR models
TL;DR: Two different multi- target models based on quantitative structure–activity relationships (mt-QSAR) for the prediction and in silico design of multi-target bromodomain inhibitors against the proteins BRD2, BRD3, and BRD4 are described.