Pushing the Limits of Computational Structure-Based Drug Design with a Cryo-EM Structure: The Ca2+ Channel α2δ-1 Subunit as a Test Case.
Martin KotevRosalia PascualCarmen AlmansaVictor GuallarRobert SolivaPublished in: Journal of chemical information and modeling (2018)
Cryo-electron microscopy (cryo-EM) is emerging as a real alternative for structural elucidation. In spite of this, very few cryo-EM structures have been described so far as successful platforms for in silico drug design. Gabapentin and pregabalin are some of the most successful drugs in the treatment of epilepsy and neuropathic pain. Although both are in clinical use and are known to exert their effects by binding to the regulatory α2δ subunit of voltage gated calcium channels, their binding modes have never been characterized. We describe here the successful use of an exhaustive protein-ligand sampling algorithm on the α2δ-1 subunit of the recently published cryo-EM structure, with the goal of characterizing the ligand entry path and binding mode for gabapentin, pregabalin, and several other amino acidic α2δ-1 ligands. Our studies indicate that (i) all simulated drugs explore the same path for accessing the occluded binding site on the interior of the α2δ-1 subunit; (ii) they all roughly occupy the same pocket; (iii) the plasticity of the binding site allows the accommodation of a variety of amino acidic modulators, driven by the flexible "capping loop" delineated by residues Tyr426-Val435 and the floppy nature of Arg217; (iv) the predicted binding modes are in line with previously available mutagenesis data, confirming Arg217 as key for binding, with Asp428 and Asp467 highlighted as additional anchoring points for all amino acidic drugs. The study is one of the first proofs that latest-generation cryo-EM structures combined with exhaustive computational methods can be exploited in early drug discovery.
Keyphrases
- neuropathic pain
- spinal cord
- spinal cord injury
- electron microscopy
- drug discovery
- high resolution
- binding protein
- protein kinase
- dna binding
- ionic liquid
- transcription factor
- drug induced
- machine learning
- small molecule
- crispr cas
- deep learning
- electronic health record
- randomized controlled trial
- molecular docking
- systematic review
- adverse drug
- artificial intelligence
- big data