Mechanism of glucocerebrosidase activation and dysfunction in Gaucher disease unraveled by molecular dynamics and deep learning

Raquel Romero, Arvind Ramanathan, Tony Yuen, Debsindhu Bhowmik, Mehr Mathew, Lubna Bashir Munshi, Seher Javaid, Madison Bloch, Daria Lizneva, Alina Rahimova, Ayesha Khan, Charit Taneja, Se Min Kim, Li Sun, Maria I. New, Shozeb Haider, Mone Zaidi

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

The lysosomal enzyme glucocerebrosidase-1 (GCase) catalyzes the cleavage of a major glycolipid glucosylceramide into glucose and ceramide. The absence of fully functional GCase leads to the accumulation of its lipid substrates in lysosomes, causing Gaucher disease, an autosomal recessive disorder that displays profound genotype-phenotype nonconcordance. More than 250 diseasecausing mutations in GBA1, the gene encoding GCase, have been discovered, although only one of these, N370S, causes 70% of disease. Here, we have used a knowledge-based docking protocol that considers experimental data of protein-protein binding to generate a complex between GCase and its known facilitator protein saposin C (SAPC). Multiscale molecular-dynamics simulations were used to study lipid self-assembly, membrane insertion, and the dynamics of the interactions between different components of the complex. Deep learning was applied to propose a model that explains the mechanism of GCase activation, which requires SAPC. Notably, we find that conformational changes in the loops at the entrance of the substrate-binding site are stabilized by direct interactions with SAPC and that the loss of such interactions induced by N370S and another common mutation, L444P, result in destabilization of the complex and reduced GCase activation. Our findings provide an atomistic-level explanation for GCase activation and the precise mechanism through which N370S and L444P cause Gaucher disease.

Original languageEnglish
Pages (from-to)5086-5095
Number of pages10
JournalProceedings of the National Academy of Sciences of the United States of America
Volume116
Issue number11
DOIs
StatePublished - 2019

Keywords

  • Gene mutations
  • Lysosomal storage disease
  • Multiscale simulations
  • Rare disease

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