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In this work, we combined Deep Docking and free energy MD simulations for the in silico screening and experimental validation for potential inhibitors of leucine rich repeat kinase 2 (LRRK2) targeting the WD40 repeat (WDR) domain. 

The CACHE challenges are a series of prospective benchmarking exercises to evaluate progress in the field of computational hit-finding. Here we report the results of the inaugural CACHE challenge in which 23 computational teams each selected up to 100 commercially available compounds that they predicted would bind to the WDR domain of the Parkinson’s disease target LRRK2, a domain with no known ligand and only an apo structure in the PDB. The lack of known binding data and presumably low druggability of the target is a challenge to computational hit finding methods. Of the 1955 molecules predicted by participants in Round 1 of the challenge, 73 were found to bind to LRRK2 in an SPR assay with a KD lower than 150 μM. These 73 molecules were advanced to the Round 2 hit expansion phase, where computational teams each selected up to 50 analogs. Binding was observed in two orthogonal assays for seven chemically diverse series, with affinities ranging from 18 to 140 μM. The seven successful computational workflows varied in their screening strategies and techniques. Three used molecular dynamics to produce a conformational ensemble of the targeted site, three included a fragment docking step, three implemented a generative design strategy and five used one or more deep learning steps. CACHE #1 reflects a highly exploratory phase in computational drug design where participants adopted strikingly diverging screening strategies. Machine learning-accelerated methods achieved similar results to brute force (e.g., exhaustive) docking. First-in-class, experimentally confirmed compounds were rare and weakly potent, indicating that recent advances are not sufficient to effectively address challenging targets. 

Background and PurposeAMPA receptors, which shape excitatory postsynaptic currents and are directly involved in overactivation of synaptic function during seizures, represent a well‐accepted target for anti‐epileptic drugs. Trans‐4‐butylcyclohexane carboxylic acid (4‐BCCA) has emerged as a new promising anti‐epileptic drug in several in vitro and in vivo seizure models, but the mechanism of its action remained unknown. The purpose of this study is to characterize structure and dynamics of 4‐BCCA interaction with AMPA receptors. Experimental ApproachWe studied the molecular mechanism of AMPA receptor inhibition by 4‐BCCA using a combination of X‐ray crystallography, mutagenesis, electrophysiological assays, and molecular dynamics simulations. Key ResultsWe identified 4‐BCCA binding sites in the transmembrane domain (TMD) of AMPA receptor, at the lateral portals formed by transmembrane segments M1–M4. At this binding site, 4‐BCCA is very dynamic, assumes multiple poses, and can enter the ion channel pore. Conclusion and Implications4‐BCCA represents a low‐affinity inhibitor of AMPA receptors that acts at the TMD sites distinct from non‐competitive inhibitors, such as the anti‐epileptic drug perampanel and the ion channel blockers. Further studies might examine the possibsility of synergistic use of these inhibitors in treatment of epilepsy and a wide range of neurological disorders and gliomas. LINKED ARTICLESThis article is part of a themed issue on Structure Guided Pharmacology of Membrane Proteins (BJP 75th Anniversary). To view the other articles in this section visithttp://onlinelibrary.wiley.com/doi/10.1111/bph.v179.14/issuetoc