Repurposing FIASMAs against Acid Sphingomyelinase for COVID-19: A Computational Molecular Docking and Dynamic Simulation Approach.

Over the past few years, COVID-19 has caused widespread suffering worldwide. There is great research potential in this domain and it is also necessary. The main objective of this study was to identify potential inhibitors against acid sphingomyelinase (ASM) in order to prevent coronavirus infection.

Targeted exome sequencing identified a novel frameshift variant in the PGAM2 gene causing glycogen storage disease type X.

Background: Phosphoglycerate mutase (PGAM) deficiency is associated with a rare glycogen storage disease (glycogenosis type X) in humans caused by pathogenic variants in the PGAM2 gene. Several genes causing autosomal forms of glycogen storage disease (GSD) have been identified, involved in various forms of neuromuscular anomalies.

Methods: Targeted whole exome sequencing (WES) was performed on the DNA of single affected individual (IV-1) followed by Sanger sequencing confirmation of the identified variant in all available members of the family.

Combining fragment docking with graph theory to improve ligand docking for homology model structures.

Computational protein-ligand docking is well-known to be prone to inaccuracies in input receptor structures, and it is challenging to obtain good docking results with computationally predicted receptor structures (e.g. through homology modeling).

Comparative modeling and virtual screening for the identification of novel inhibitors for myo-inositol-1-phosphate synthase.

Myo-inositol-1-phosphate (MIP) synthase is a key enzyme in the myo-inositol biosynthesis pathway. Disruption of the inositol signaling pathway is associated with bipolar disorders. Previous work suggested that MIP synthase could be an attractive target for the development of anti-bipolar drugs.