a-high-throughput-calcium-flux-assay-to-study-nmda-receptors-with

A High-throughput Calcium-flux Assay to Study NMDA-receptors with Sensitivity to Glycine/D-serine and Glutamate

N-methyl-D-aspartate (NMDA) receptors (NMDAR) are classified as ionotropic glutamate receptors and have critical roles in learning and memory. NMDAR ...

Novartis Institutes for BioMedical Research

Computational target prediction methods using chemical descriptors have been applied exhaustively in drug discovery to elucidate the mechanisms-of-action (MOAs) of small molecules. To predict truly novel and unexpected small molecule-target interactions, compounds must be compared by means other than their chemical structure alone. Here we investigated predictions made by a method, HTS fingerprints (HTSFPs), that matches patterns of activities in experimental screens. Over 1,400 drugs and 1,300 natural products (NPs) were screened in more than 200 diverse assays, creating encodable activity patterns. The comparison of these activity patterns to an MOA-annotated reference panel led to the prediction of 5,281 and 2,798 previously unknown targets for the NP and drug sets, respectively. Intriguingly, there was limited overlap among the targets predicted; the drugs were more biased toward membrane receptors and the NPs toward soluble enzymes, consistent with the idea that they represent unexplored pharmacologies. Importantly, HTSFPs inferred targets that were beyond the prediction capabilities of standard chemical descriptors, especially for NPs but also for the more explored drug set. Of 65 drug-target predictions that we tested in vitro, 48 (73.8%) were confirmed with AC50 values ranging from 38 nM to 29 μM. Among these interactions was the inhibition of cyclooxygenases 1 and 2 by the HIV protease inhibitor Tipranavir. These newly discovered targets that are phylogenetically and phylochemically distant to the primary target provide an explanation for spontaneous bleeding events observed for patients treated with this drug, a physiological effect that was previously difficult to reconcile with the drug's known MOA. 

A screening pattern recognition method finds new and divergent targets for drugs and natural products.

Metallo-β-lactamases (MBLs), such as New Delhi metallo-β-lactamase (NDM-1) have spread world-wide and present a serious threat. Expression of MBLs confers resistance in Gram-negative bacteria to all classes of β-lactam antibiotics, with the exception of monobactams, which are intrinsically stable to MBLs. However, existing first generation monobactam drugs like aztreonam have limited clinical utility against MBL-expressing strains because they are impacted by serine β-lactamases (SBLs), which are often co-expressed in clinical isolates. Here, we optimized novel monobactams for stability against SBLs, which led to the identification of LYS228 (compound 31). LYS228 is potent in the presence of all classes of β-lactamases and shows potent activity against carbapenem-resistant isolates of Enterobacteriaceae (CRE).

Article	Year
A screening pattern recognition method finds new and divergent targets for drugs and natural products. ACS chemical biology\| PubMed ID: 24802392	2014
Optimization of novel monobactams with activity against carbapenem-resistant Enterobacteriaceae - Identification of LYS228. Bioorganic & medicinal chemistry letters\| PubMed ID: 29336873	2018

Hongqiu Guo

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