Design of a stable human acid‐β‐glucosidase: towards improved Gaucher disease therapy and mutation classification

Author:

Pokorna Sarka12ORCID,Khersonsky Olga1,Lipsh‐Sokolik Rosalie1,Goldenzweig Adi1,Nielsen Rebekka1,Ashani Yacov1,Peleg Yoav3,Unger Tamar3,Albeck Shira3,Dym Orly3,Tirosh Asa3,Tarayra Rana4,Hocquemiller Michaël5,Laufer Ralph5,Ben‐Dor Shifra3ORCID,Silman Israel6,Sussman Joel L.4ORCID,Fleishman Sarel J.1ORCID,Futerman Anthony H.1ORCID

Affiliation:

1. Department of Biomolecular Sciences Weizmann Institute of Science Rehovot Israel

2. J.Heyrovsky Institute of Physical Chemistry of the Czech Academy of Sciences Prague Czech Republic

3. Department of Life Sciences Core Facilities Weizmann Institute of Science Rehovot Israel

4. Department of Chemical and Structural Biology Weizmann Institute of Science Rehovot Israel

5. Lysogene Neuilly‐sur‐Seine France

6. Department of Brain Sciences Weizmann Institute of Science Rehovot Israel

Abstract

Acid‐β‐glucosidase (GCase, EC3.2.1.45), the lysosomal enzyme which hydrolyzes the simple glycosphingolipid, glucosylceramide (GlcCer), is encoded by the GBA1 gene. Biallelic mutations in GBA1 cause the human inherited metabolic disorder, Gaucher disease (GD), in which GlcCer accumulates, while heterozygous GBA1 mutations are the highest genetic risk factor for Parkinson's disease (PD). Recombinant GCase (e.g., Cerezyme®) is produced for use in enzyme replacement therapy for GD and is largely successful in relieving disease symptoms, except for the neurological symptoms observed in a subset of patients. As a first step toward developing an alternative to the recombinant human enzymes used to treat GD, we applied the PROSS stability‐design algorithm to generate GCase variants with enhanced stability. One of the designs, containing 55 mutations compared to wild‐type human GCase, exhibits improved secretion and thermal stability. Furthermore, the design has higher enzymatic activity than the clinically used human enzyme when incorporated into an AAV vector, resulting in a larger decrease in the accumulation of lipid substrates in cultured cells. Based on stability‐design calculations, we also developed a machine learning‐based approach to distinguish benign from deleterious (i.e., disease‐causing) GBA1 mutations. This approach gave remarkably accurate predictions of the enzymatic activity of single‐nucleotide polymorphisms in the GBA1 gene that are not currently associated with GD or PD. This latter approach could be applied to other diseases to determine risk factors in patients carrying rare mutations.

Funder

Israel Science Foundation

Akademie Věd České Republiky

Publisher

Wiley

Subject

Cell Biology,Molecular Biology,Biochemistry

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