Molecular Modeling of ABHD5 Structure and Ligand Recognition

Artificial Intelligence Aided Lipase Production and Engineering for Enzymatic Performance Improvement

With the development of artificial intelligence (AI), tailoring methods for enzyme engineering have been widely expanded. Additional protocols based on optimized network models have been used to predict and optimize lipase production as well as properties, namely, catalytic activity, stability, and substrate specificity. Here, different network models and algorithms for the prediction and reforming of lipase, focusing on its modification methods and cases based on AI, are reviewed in terms of both their advantages and disadvantages. Different neural networks coupled with various algorithms are usually applied to predict the maximum yield of lipase by optimizing the external cultivations for lipase production, while one part is used to predict the molecule variations affecting the properties of lipase. However, few studies have directly utilized AI to engineer lipase by affecting the structure of the enzyme, and a set of research gaps needs to be explored. Additionally, future perspectives of AI application in enzymes, including lipase engineering, are deduced to help the redesign of enzymes and the reform of new functional biocatalysts. This review provides a new horizon for developing effective and innovative AI tools for lipase production and engineering and facilitating lipase applications in the food industry and biomass conversion.

Chanarin-Dorfman Syndrome (CDS): A Rare Lipid Metabolism Disorder

Chanarin-Dorfman syndrome (CDS) is a rare medical condition that is inherited in an autosomal recessive pattern. In CDS, a comparative gene identification-58 gene mutation causes the accumulation of triglycerides in neutrophils, which can be observed as vacuoles on a peripheral smear. CDS patients present with a characteristic dermatological finding, ichthyosis, which is a non-bullous white scaling of the skin. Here, we describe a case report of a one-year-old boy who presented to the pediatric outpatient department (OPD) with chief complaints of peeling of the skin and ballooning of the abdomen since birth. Our patient had achieved all the developmental milestones pertaining to his age. Genetic testing was positive for heterozygous alleles in both parents.

A FRET sensor for the real-time detection of long chain acyl-CoAs and synthetic ABHD5 ligands

Intracellular long-chain acyl-coenzyme As (LC-acyl-CoAs) are thought to be under tight spatial and temporal controls, yet the ability to image LC-acyl-CoAs in live cells is lacking. Here, we developed a fluorescence resonance energy transfer (FRET) sensor for LC-acyl-CoAs based on the allosterically regulated interaction between α/β hydrolase domain-containing 5 (ABHD5) and Perilipin 5. The genetically encoded sensor rapidly detects intracellular LC-acyl-CoAs generated from exogenous and endogenous fatty acids (FAs), as well as synthetic ABHD5 ligands. Stimulation of lipolysis in brown adipocytes elevated intracellular LC-acyl-CoAs in a cyclic fashion, which was eliminated by inhibiting PNPLA2 (ATGL), the major triglyceride lipase. Interestingly, inhibition of LC-acyl-CoA transport into mitochondria elevated intracellular LC-acyl-CoAs and dampened their cycling. Together, these observations reveal an intimate feedback control between LC-acyl-CoA generation from lipolysis and utilization in mitochondria. We anticipate that this sensor will be an important tool to dissect intracellular LC-acyl-CoA dynamics as well to discover novel synthetic ABHD5 ligands.

Electrostatics in Computational Biophysics and Its Implications for Disease Effects

This review outlines the role of electrostatics in computational molecular biophysics and its implication in altering wild-type characteristics of biological macromolecules, and thus the contribution of electrostatics to disease mechanisms. The work is not intended to review existing computational approaches or to propose further developments. Instead, it summarizes the outcomes of relevant studies and provides a generalized classification of major mechanisms that involve electrostatic effects in both wild-type and mutant biological macromolecules. It emphasizes the complex role of electrostatics in molecular biophysics, such that the long range of electrostatic interactions causes them to dominate all other forces at distances larger than several Angstroms, while at the same time, the alteration of short-range wild-type electrostatic pairwise interactions can have pronounced effects as well. Because of this dual nature of electrostatic interactions, being dominant at long-range and being very specific at short-range, their implications for wild-type structure and function are quite pronounced. Therefore, any disruption of the complex electrostatic network of interactions may abolish wild-type functionality and could be the dominant factor contributing to pathogenicity. However, we also outline that due to the plasticity of biological macromolecules, the effect of amino acid mutation may be reduced, and thus a charge deletion or insertion may not necessarily be deleterious.