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Paris, L.

Publications and source records attributed to Paris, L..

3 recordsLinked to original sources

Library docking for Cannabinoid-2 Receptor ligands

Cannabinoid receptors are therapeutically promising GPCRs that are also interesting test systems for structure-based methods, which have targeted them previously. Here we used the CB2 receptor as a template to explore several topical questions in library docking. Whereas an earlier campaign against the CB1 receptor led to potent but relatively non-selective ligands, here we found that targeting interactions with polar, orthosteric site residues led to subtype-selective ligands. Docking hit rate and especially hit affinity improved in moving from a 7 million to a 2.6 billion molecule library. Similar to earlier studies, docking against active and inactive states of the receptor did not reliably bias toward the discovery of agonists or inverse agonists. Cryo-EM structures of two of the new agonists, each in a different chemotype, superposed well on the docking predictions. Correspondingly, structure-based optimization led to 10- to 140-fold improvements within three different series, also consistent with well-behaved ligand families. Hit rates with a fully enumerated 2.6 billion molecule library resembled those of an implied 11 billion molecule library from a building-block method, consistent with the latters ability to explore this space, though higher affinities were discovered from the fully enumerated set. Overall, eight diverse families of ligands, with potencies <100 nM and mostly unrelated to previously known ligands were found. Implications for future studies are considered.

biochemistry↗

Drug-induced phospholipidosis as an artifact in antiviral drug repurposing

Drug repurposing in principle can speed antiviral drug discovery. Among the molecules most frequently advanced in such repurposing efforts are a group of structurally diverse cationic amphiphilic drugs (CADs). While CADs have shown micromolar to mid-nanomolar antiviral activity in cell-based assays, they can induce phospholipidosis, confounding in COVID-19 repurposing. A barrier to the identification of phospholipidosis inducers has been the involved nature of the microscopy assays used to characterize them. To ease the identification of these artifacts, we describe a rapid microplate-based assay to detect phospholipidosis. Leveraging this assay, we quantified the prevalence of phospholipidosis-inducers across several cell-based antiviral repurposing screens. We selected 40 drugs reported to have micromolar antiviral activities and found that 26 of them (65%) induced phospholipidosis within the same concentration range as their reported antiviral activities. Intriguingly, we identified four non-CADs that also induce phospholipidosis, revealing a new group of drugs that can lead to this toxic event and highlighting the importance of facile experimental assays to detect it. Understanding how phospholipidosis can confound antiviral drug discovery, and its rapid detection, will help prevent what is an apparently general artifact, active across viruses, from distracting investigators from potentially more useful candidates.

cell biology↗

Identifying Artifacts from Large Library Docking

While large library docking has discovered potent ligands for multiple targets, as the libraries have grown, the very top of the hit-lists can become populated with artifacts that cheat our scoring functions. Though these cheating molecules are rare, they become ever-more dominant with library growth. Here, we investigate rescoring top-ranked molecules from docking screens with orthogonal methods to identify these artifacts, exploring implicit solvent models and absolute binding free energy perturbation (AB-FEP) as cross-filters. In retrospective studies, this approach deprioritized high-ranking non-binders for nine targets while leaving true ligands relatively unaffected. We tested the method prospectively against results from large library docking AmpC {beta}-lactamase. From the very top of the docking hit lists, we prioritized 128 molecules for synthesis and experimental testing, a mixture of 39 molecules that rescoring flagged as likely cheaters and another 89 that were plausible true actives. None of the 39 predicted cheating compounds inhibited AmpC up to 200{micro}M in enzyme assays, while 57% of the 89 plausible true actives did do so, with 19 of them inhibiting the enzyme with apparent Ki values better than 50{micro}M. As our libraries continue to grow, a strategy of catching docking artifacts by rescoring with orthogonal methods may find wide use in the field. Graphical TOC Entry O_FIG O_LINKSMALLFIG WIDTH=166 HEIGHT=200 SRC="FIGDIR/small/603966v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@c2f1a5org.highwire.dtl.DTLVardef@86bc58org.highwire.dtl.DTLVardef@1b739c7org.highwire.dtl.DTLVardef@325b93_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗