Chemical space docking enables large-scale structure-based virtual screening to discover ROCK1 kinase inhibitors.

With the ever-increasing number of synthesis-on-demand compounds for drug lead discovery, there is a great need for efficient search technologies. We present the successful application of a virtual screening method that combines two advances: (1) it avoids full library enumeration (2) products are evaluated by molecular docking, leveraging protein structural information. Crucially, these advances enable a structure-based technique that can efficiently explore libraries with billions of molecules and beyond. We apply this method to identify inhibitors of ROCK1 from almost one billion commercially available compounds. Out of 69 purchased compounds, 27 (39%) have Ki values < 10 µM. X-ray structures of two leads confirm their docked poses. This approach to docking scales roughly with the number of reagents that span a chemical space and is therefore multiple orders of magnitude faster than traditional docking.

Zebrafish behavioural profiling identifies GABA and serotonin receptor ligands related to sedation and paradoxical excitation.

Anesthetics are generally associated with sedation, but some anesthetics can also increase brain and motor activity-a phenomenon known as paradoxical excitation. Previous studies have identified GABAA receptors as the primary targets of most anesthetic drugs, but how these compounds produce paradoxical excitation is poorly understood. To identify and understand such compounds, we applied a behavior-based drug profiling approach. Here, we show that a subset of central nervous system depressants cause paradoxical excitation in zebrafish. Using this behavior as a readout, we screened thousands of compounds and identified dozens of hits that caused paradoxical excitation. Many hit compounds modulated human GABAA receptors, while others appeared to modulate different neuronal targets, including the human serotonin-6 receptor. Ligands at these receptors generally decreased neuronal activity, but paradoxically increased activity in the caudal hindbrain. Together, these studies identify ligands, targets, and neurons affecting sedation and paradoxical excitation in vivo in zebrafish.

A Simple Representation of Three-Dimensional Molecular Structure.

Statistical and machine learning approaches predict drug-to-target relationships from 2D small-molecule topology patterns. One might expect 3D information to improve these calculations. Here we apply the logic of the extended connectivity fingerprint (ECFP) to develop a rapid, alignment-invariant 3D representation of molecular conformers, the extended three-dimensional fingerprint (E3FP). By integrating E3FP with the similarity ensemble approach (SEA), we achieve higher precision-recall performance relative to SEA with ECFP on ChEMBL20 and equivalent receiver operating characteristic performance. We identify classes of molecules for which E3FP is a better predictor of similarity in bioactivity than is ECFP. Finally, we report novel drug-to-target binding predictions inaccessible by 2D fingerprints and confirm three of them experimentally with ligand efficiencies from 0.442-0.637 kcal/mol/heavy atom.

Zebrafish behavioral profiling identifies multitarget antipsychotic-like compounds.

Many psychiatric drugs act on multiple targets and therefore require screening assays that encompass a wide target space. With sufficiently rich phenotyping and a large sampling of compounds, it should be possible to identify compounds with desired mechanisms of action on the basis of behavioral profiles alone. Although zebrafish (Danio rerio) behavior has been used to rapidly identify neuroactive compounds, it is not clear what types of behavioral assays would be necessary to identify multitarget compounds such as antipsychotics. Here we developed a battery of behavioral assays in larval zebrafish to determine whether behavioral profiles can provide sufficient phenotypic resolution to identify and classify psychiatric drugs. Using the antipsychotic drug haloperidol as a test case, we found that behavioral profiles of haloperidol-treated zebrafish could be used to identify previously uncharacterized compounds with desired antipsychotic-like activities and multitarget mechanisms of action.

Leveraging Large-scale Behavioral Profiling in Zebrafish to Explore Neuroactive Polypharmacology.

Many psychiatric drugs modulate the nervous system through multitarget mechanisms. However, systematic identification of multitarget compounds has been difficult using traditional in vitro screening assays. New approaches to phenotypic profiling in zebrafish can help researchers identify novel compounds with complex polypharmacology. For example, large-scale behavior-based chemical screens can rapidly identify large numbers of structurally diverse and phenotype-related compounds. Once these compounds have been identified, a systems-level analysis of their structures may help to identify statistically enriched target pathways. Together, systematic behavioral profiling and multitarget predictions may help researchers identify new behavior-modifying pathways and CNS therapeutics.