scholarly journals ZINC20—A Free Ultralarge-Scale Chemical Database for Ligand Discovery

2020 ◽  
Vol 60 (12) ◽  
pp. 6065-6073 ◽  
Author(s):  
John J. Irwin ◽  
Khanh G. Tang ◽  
Jennifer Young ◽  
Chinzorig Dandarchuluun ◽  
Benjamin R. Wong ◽  
...  
2014 ◽  
Vol 15 (12) ◽  
pp. 1089-1093 ◽  
Author(s):  
Amit Kumar ◽  
Nidhi Agarwal ◽  
Lalit Pant ◽  
Jay Singh ◽  
Indira Ghosh ◽  
...  

2021 ◽  
Vol 14 (677) ◽  
pp. eaav0320
Author(s):  
Tao Che ◽  
Hemlata Dwivedi-Agnihotri ◽  
Arun K. Shukla ◽  
Bryan L. Roth

The opioid crisis represents a major worldwide public health crisis that has accelerated the search for safer and more effective opioids. Over the past few years, the identification of biased opioid ligands capable of eliciting selective functional responses has provided an alternative avenue to develop novel therapeutics without the side effects of current opioid medications. However, whether biased agonism or other pharmacological properties, such as partial agonism (or low efficacy), account for the therapeutic benefits remains questionable. Here, we provide a summary of the current status of biased opioid ligands that target the μ- and κ-opioid receptors and highlight advances in preclinical and clinical trials of some of these ligands. We also discuss an example of structure-based biased ligand discovery at the μ-opioid receptor, an approach that could revolutionize drug discovery at opioid and other receptors. Last, we briefly discuss caveats and future directions for this important area of research.


2021 ◽  
Vol 17 (4) ◽  
pp. 501-501 ◽  
Author(s):  
Tony Ngo ◽  
Andrey V. Ilatovskiy ◽  
Alastair G. Stewart ◽  
James L. J. Coleman ◽  
Fiona M. McRobb ◽  
...  

2021 ◽  
Author(s):  
Wenchao Lu ◽  
Milka Kostic ◽  
Tinghu Zhang ◽  
Jianwei Che ◽  
Matthew P. Patricelli ◽  
...  
Keyword(s):  

Correction for ‘Fragment-based covalent ligand discovery’ by Wenchao Lu et al., RSC Chem. Biol., 2021, DOI: 10.1039/d0cb00222d.


2011 ◽  
Vol 415-417 ◽  
pp. 523-526
Author(s):  
Yan Dong ◽  
Mei Li

This paper put forward a geometry feature recognition method of part drawing based on graph matching. Describe the constraints structure of geometric feature in geometric elements and those constraint relationships. Match sub-graph in contour closure graphics and those combination. Using linear symbol notation of chemical compounds in chemical database for reference, encode to constraint structure of geometry graphics, establish recognition mechanism of geometric characteristics by structure codes. Taking the fine-tune screw and fork parts for example, this method has been proved to be effective.


Nature ◽  
2021 ◽  
Author(s):  
Arman A. Sadybekov ◽  
Anastasiia V. Sadybekov ◽  
Yongfeng Liu ◽  
Christos Iliopoulos-Tsoutsouvas ◽  
Xi-Ping Huang ◽  
...  

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