Jaramillo-Martinez, V. | Search bioRxiv

bioRxiv2024

Molecular phenotypes segregate missense mutations in SLC13A5 Epilepsy

The sodium-coupled citrate transporter (NaCT, SLC13A5) mediates citrate uptake across the plasma membrane via an inward Na+ gradient. Mutations in SLC13A5 cause early infantile epileptic encephalopathy type-25 (EIEE25, SLC13A5 Epilepsy) due to impaired citrate uptake in neurons. Despite clinical identification of disease-causing mutations, underlying mechanisms and cures remain elusive. We mechanistically classify the molecular phenotypes of six mutations. C50R, T142M, and T227M exhibit impaired citrate transport despite normal expression at the cell surface. G219R, S427L, and L488P are hampered by low protein expression, ER retention, and reduced transport. Mutants mRNA levels resemble wildtype, suggesting post-translational defects. Class II mutations display immature core-glycosylation and shortened half-lives, indicating protein folding defects. These experiments provide a comprehensive understanding of the mutations defects in SLC13A5 Epilepsy at the biochemical and molecular level and shed light into the trafficking pathway(s) of NaCT. The two classes of mutations will require fundamentally different treatment approaches to either restore transport function, or enable correction of protein folding defects. SummaryLoss-of-function mutations in the SLC13A5 causes SLC13A5-Epilepsy, a devastating disease characterized by neonatal epilepsy. Currently no cure is available. We clarify the molecular-level defects to guide future developments for phenotype-specific treatment of disease-causing mutations.

biochemistry↗

bioRxiv2021

Gaussian accelerated molecular dynamics reveals that a proline-rich signaling peptide frequently samples cis conformations when unbound

Disordered proline-rich motifs are common across the proteomes of many species and are often involved in protein-protein interactions. Proline is a unique amino acid due to the covalent bond between the backbone nitrogen and the proline side chain. The resulting five-membered ring allows proline to sample the cis state about its peptide bond, which other residues cannot do as readily. Because proline-rich disordered sequences exist as ensembles that likely include structures with the proline peptide bond in cis, a robust methodology to accurately account for these conformations in the overall ensemble is crucial. Observing the cis conformations of proline in a disordered sequence is challenging both experimentally and computationally. Nitrogen-hydrogen NMR spectroscopy cannot directly observe proline residues, which lack an amide bond, and computational methods struggle to overcome the large kinetic barrier between the cis and trans states, since isomerization usually occurs on the order of seconds. In the current work, Gaussian accelerated molecular dynamics was used to overcome this free energy barrier and simulate proline isomerization in a tetrapeptide (KPTP) and in the 12-residue proline-rich SH3 binding peptide, ArkA. We found that Gaussian accelerated molecular dynamics, when combined with a lowered peptide bond dihedral angle potential energy barrier (15 kcal/mol), allowed sufficient sampling of the proline cis and trans states on a microsecond timescale. All ArkA prolines spend a significant fraction of time in cis, leading to a more compact ensemble with less polyproline II helix structure than an ArkA ensemble with all peptide bonds in trans. The ensemble containing cis prolines also matches more closely to in vitro circular dichroism data than the all-trans ensemble. The ability of the ArkA prolines to isomerize likely affects the peptides ability to bind its partner SH3 domain, and should be studied further. This is the first molecular dynamics simulation study of proline isomerization in a biologically relevant proline-rich sequence that we know of, and a similar protocol could be applied to study multi-proline isomerization in other proline-containing proteins to improve conformational diversity and agreement with in vitro data.

biophysics↗