Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators

Nature Biotechnology, Journal Year: 2012, Volume and Issue: 30(9), P. 858 - 867

Published: Aug. 19, 2012

Language: Английский

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Protein kinase C, an elusive therapeutic target?

Nature Reviews Drug Discovery, Journal Year: 2012, Volume and Issue: 11(12), P. 937 - 957

Published: Nov. 30, 2012

Language: Английский

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DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences

PLoS Computational Biology, Journal Year: 2019, Volume and Issue: 15(6), P. e1007129 - e1007129

Published: June 14, 2019

Identification of drug-target interactions (DTIs) plays a key role in drug discovery. The high cost and labor-intensive nature vitro vivo experiments have highlighted the importance silico-based DTI prediction approaches. In several computational models, conventional protein descriptors been shown to not be sufficiently informative predict accurate DTIs. Thus, this study, we propose deep learning based model capturing local residue patterns proteins participating When employ convolutional neural network (CNN) on raw sequences, perform convolution various lengths amino acids subsequences capture generalized classes. We train our with large-scale information demonstrate performance proposed using an independent dataset that is seen during training phase. As result, performs better than previous descriptor-based models. Also, recently developed models for massive By examining pooled results, confirmed can detect binding sites conclusion, detecting target successfully enriches features sequence, yielding results Our code available at https://github.com/GIST-CSBL/DeepConv-DTI.

Language: Английский

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Molecular conformations, interactions, and properties associated with drug efficiency and clinical performance among VEGFR TK inhibitors

Proceedings of the National Academy of Sciences, Journal Year: 2012, Volume and Issue: 109(45), P. 18281 - 18289

Published: Sept. 5, 2012

Analyses of compounds in clinical development have shown that ligand efficient-molecules with privileged physical properties and low dose are less likely to fail the various stages testing, fewer postapproval withdrawals, receive black box safety warnings. However, detailed side-by-side examination molecular interactions within single drug classes lacking. As a class, VEGF receptor tyrosine kinase inhibitors (VEGFR TKIs) changed landscape how cancer is treated, particularly clear cell renal carcinoma, which molecularly linked signaling axis. Despite role target, member molecules this validated class exhibit distinct efficacy profiles comparable carcinoma studies. The first head-to-head randomized phase III comparative study between active VEGFR TKIs has confirmed significant differences performance [Rini BI, et al. (2011) Lancet 378:193–1939]. To elucidate fundamental potency–efficiency achieved impacts differentiation TKI we determined potencies, time dependence, selectivities, X-ray structures drug–kinase complexes using VEGFR2 TK construct inclusive important juxtamembrane domain. Collectively, studies unique dependent on domain conformations, resulting potency efficiency differences. identified structural trends consistent vitro measurements, translate well performance, underscoring principle may be broadly applicable prospective design for optimal vivo performance.

Language: Английский

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Differential PROTAC substrate specificity dictated by orientation of recruited E3 ligase

Nature Communications, Journal Year: 2019, Volume and Issue: 10(1)

Published: Jan. 4, 2019

Abstract PROteolysis-TArgeting Chimeras (PROTACs) are hetero-bifunctional molecules that recruit an E3 ubiquitin ligase to a given substrate protein resulting in its targeted degradation. Many potent PROTACs with specificity for dissimilar targets have been developed; however, the factors governing degradation selectivity within closely-related families remain elusive. Here, we generate isoform-selective p38 MAPK family using single warhead (foretinib) and recruited (von Hippel-Lindau). Based on their distinct linker attachments lengths, these two differentially VHL, of p38α or p38δ. We characterize role ternary complex formation driving selectivity, showing it is necessary, but insufficient, PROTAC-induced ubiquitination. Lastly, explore p38δ:PROTAC:VHL explain different profiles PROTACs. Our work attributes selective proteins same heretofore underappreciated aspects model.

Language: Английский

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