Exploring the interaction of SV2A with racetams using homology modelling, molecular dynamics and site-directed mutagenesis.

Journal article

The putative Major Facilitator Superfamily (MFS) transporter, SV2A, is the target for levetiracetam (LEV), which is a successful anti-epileptic drug. Furthermore, SV2A knock out mice display a severe seizure phenotype and die after a few weeks. Despite this, the mode of action of LEV is not known at the molecular level. It would be extremely desirable to understand this more fully in order to aid the design of improved anti-epileptic compounds. Since there is no structure for SV2A, homology modelling can provide insight into the ligand-binding site. However, it is not a trivial process to build such models, since SV2A has low sequence identity to those MFS transporters whose structures are known. A further level of complexity is added by the fact that it is not known which conformational state of the receptor LEV binds to, as multiple conformational states have been inferred by tomography and ligand binding assays or indeed, if binding is exclusive to a single state. Here, we explore models of both the inward and outward facing conformational states of SV2A (according to the alternating access mechanism for MFS transporters). We use a sequence conservation analysis to help guide the homology modelling process and generate the models, which we assess further with Molecular Dynamics (MD). By comparing the MD results in conjunction with docking and simulation of a LEV-analogue used in radioligand binding assays, we were able to suggest further residues that line the binding pocket. These were confirmed experimentally. In particular, mutation of D670 leads to a complete loss of binding. The results shed light on the way LEV analogues may interact with SV2A and may help with the on-going design of improved anti-epileptic compounds.

Authors: Lee, J; Daniels, V; Sands, Z; Lebon, F; Shi, J

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Public Library of Science
• Journal: PloS one
• Volume: 10
• Issue: 2
• Pages: e0116589
• Publication date: 2015-01-01
• DOI: 10.1371/journal.pone.0116589
• EISSN: 1932-6203
• ISSN: 1932-6203
• Language: English
• Keywords: drug interactions; binding analysis; BLAST algorithm; simulation and modeling; membrane proteins; biochemical simulations; multiple alignment calculation; sequence alignment