An overview on glycation: molecular mechanisms, impact on proteins, pathogenesis, and inhibition

The formation of a heterogeneous set of advanced glycation end products (AGEs) is the final outcome of a non-enzymatic process that occurs in vivo on long-life biomolecules. This process, known as glycation, starts with the reaction between reducing sugars, or their autoxidation products, with the amino groups of proteins, DNA, or lipids, thus gaining relevance under hyperglycemic conditions. Once AGEs are formed, they might affect the biological function of the biomacromolecule and, therefore, induce the development of pathophysiological events. In fact, the accumulation of AGEs has been pointed as a triggering factor of obesity, diabetes-related diseases, coronary artery disease, neurological disorders, or chronic renal failure, among others. Given the deleterious consequences of glycation, evolution has designed endogenous mechanisms to undo glycation or to prevent it. In addition, many exogenous molecules have also emerged as powerful glycation inhibitors. This review aims to provide an overview on what glycation is. It starts by explaining the similarities and differences between glycation and glycosylation. Then, it describes in detail the molecular mechanism underlying glycation reactions, and the bio-molecular targets with higher propensity to be glycated. Next, it discusses the precise effects of glycation on protein structure, function, and aggregation, and how computational chemistry has provided insights on these aspects. Finally, it reports the most prevalent diseases induced by glycation, and the endogenous mechanisms and the current therapeutic interventions against it.

Tailoring FPOX enzymes for enhanced stability and expanded substrate recognition

Fructosyl peptide oxidases (FPOX) are deglycating enzymes that find application as key enzymatic components in diabetes monitoring devices. Indeed, their use with blood samples can provide a measurement of the concentration of glycated hemoglobin and glycated albumin, two well-known diabetes markers. However, the FPOX currently employed in enzymatic assays cannot directly detect whole glycated proteins, making it necessary to perform a preliminary proteolytic treatment of the target protein to generate small glycated peptides that can act as viable substrates for the enzyme. This is a costly and time consuming step. In this work, we used an in silico protein engineering approach to enhance the overall thermal stability of the enzyme and to improve its catalytic activity toward large substrates. The final design shows a marked improvement in thermal stability relative to the wild type enzyme, a distinct widening of its access tunnel and significant enzymatic activity towards a range of glycated substrates.

Characterization of feruloyl esterases from Pecoramyces sp. F1 and the synergistic effect in biomass degradation

Feruloyl esterase (FAE; EC 3.1.1.73) cleaves the ester bond between ferulic acid (FA) and sugar, to assist the release of FAs and degradation of plant cell walls. In this study, two FAEs (Fae13961 and Fae16537) from the anaerobic fungus Pecoramyces sp. F1 were heterologously expressed in Pichia pastoris (P. pastoris). Compared with Fae16537, Fae13961 had higher catalytic efficiency. The optimum temperature and pH of both the FAEs were 45 ℃ and 7.0, respectively. They showed good stability-Fae16537 retained up to 80% activity after incubation at 37 ℃ for 24 h. The FAEs activity was enhanced by Ca²⁺ and reduced by Zn²⁺, Mn²⁺, Fe²⁺ and Fe³⁺. Additionally, the effect of FAEs on the hydrolytic efficiency of xylanase and cellulase was also determined. The FAE Fae13961 had synergistic effect with xylanase and it promoted the degradation of xylan substrates by xylanase, but it did not affect the degradation of cellulose substrates by cellulase. When Fae13961 was added in a mixture of xylanase and cellulase to degrade complex agricultural biomass, it significantly enhanced the mixture's ability to disintegrate complex substrates. These FAEs could serve as superior auxiliary enzymes for other lignocellulosic enzymes in the process of degradation of agricultural residues for industrial applications.

In Silico Engineering of Enzyme Access Tunnels

Enzyme engineering is a tailoring process that allows the modification of naturally occurring enzymes to provide them with improved catalytic efficiency, stability, or specificity. By introducing partial modifications to their sequence and to their structural features, enzyme engineering can transform natural enzymes into more efficient, specific and resistant biocatalysts and render them suitable for virtually countless industrial processes. Current enzyme engineering methods mostly target the active site of the enzyme, where the catalytic reaction takes place. Nonetheless, the tunnel that often connects the surface of an enzyme with its buried active site plays a key role in the activity of the enzyme as it acts as a gatekeeper and regulates the access of the substrate to the catalytic pocket. Hence, there is an increasing interest in targeting the sequence and the structure of substrate entrance tunnels in order to fine-tune enzymatic activity, regulate substrate specificity, or control reaction promiscuity.In this chapter, we describe the use of a rational in silico design and screening method to engineer the access tunnel of a fructosyl peptide oxidase with the aim to facilitate access to its catalytic site and to expand its substrate range. Our goal is to engineer this class of enzymes in order to utilize them for the direct detection of glycated proteins in diabetes monitoring devices. The design strategy involves remodeling of the backbone structure of the enzyme , a feature that is not possible with conventional enzyme engineering techniques such as single-point mutagenesis and that is highly unlikely to occur using a directed evolution approach.The proposed strategy, which results in a significant reduction in cost and time for the experimental production and characterization of candidate enzyme variants, represents a promising approach to the expedited identification of novel and improved enzymes. Rational enzyme design aims to provide in silico strategies for the fast, accurate, and inexpensive development of biocatalysts that can meet the needs of multiple industrial sectors, thus ultimately promoting the use of green chemistry and improving the efficiency of chemical processes.

Dasatinib-SIK2 Binding Elucidated by Homology Modeling, Molecular Docking, and Dynamics Simulations

Salt-inducible kinases (SIKs) are calcium/calmodulin-dependent protein kinase (CAMK)-like (CAMKL) family members implicated in insulin signal transduction, metabolic regulation, inflammatory response, and other processes. Here, we focused on SIK2, which is a target of the Food and Drug Administration (FDA)-approved pan inhibitor N-(2-chloro-6-methylphenyl)-2-(6-(4-(2-hydroxyethyl)piperazin-1-yl)-2-methylpyrimidin-4-ylamino)thiazole-5-carboxamide (dasatinib), and constructed four representative SIK2 structures by homology modeling. We investigated the interactions between dasatinib and SIK2 via molecular docking, molecular dynamics simulation, and binding free energy calculation and found that dasatinib showed strong binding affinity for SIK2. Binding free energy calculations suggested that the modification of various dasatinib regions may provide useful information for drug design and to guide the discovery of novel dasatinib-based SIK2 inhibitors.

Molecular modeling, docking and simulation dynamics of β-glucosidase reveals high-efficiency, thermo-stable, glucose tolerant enzyme in Paenibacillus lautus BHU3 strain

The enzyme β-glucosidase mediates the rate limiting step of conversion of cellobiose to glucose and thus plays a vital role in the process of cellulose degradation. The present study deals with analysis of the effective novel strain of Paenibacillus lautus BHU3 for identifying high-efficiency thermostable, glucose tolerant β-glucosidases. Seven counterparts with elevated T_m values ranging from 64.6 to 75.8 °C with high thermo-stability, were revealed through this analysis. The blind molecular docking of the model enzymes structures with cellobiose and pNPG gave high negative interaction energies ranging from -11.33 to -13.29 and -6.43 to -9.054 (kcal mol^-1), respectively. The enzyme WP_096774744.1 effectively formed 5 hydrogen bonds with the highest interaction energy (-13.29 kcal mol^-1) with cellobiose at its catalytic site. Molecular dynamics simulation analysis performed for the WP_096774744.1-pNPG complex predicted Glu5, Arg7, Lue68, Gly69 and Phe325 as the major contributing residues for accomplishing hydrolysis of β-1-4-linkage. Further, the molecular docking of WP_096774744.1 enzyme with glucose revealed a distinct glucose-binding site distant from the substrate-binding site, thus confirming the deficient competitive inhibition by glucose. Hence, WP_096774744.1 β-glucosidase appears to be an efficient enzyme with enhanced activity to biodegrade the cellulosic materials and highly relevant for waste management and various industrial applications.

Recent advances in computational methods for biosensor design

Biosensors are analytical tools with a great application in healthcare, food quality control, and environmental monitoring. They are of considerable interest to be designed by using cost-effective and efficient approaches. Designing biosensors with improved functionality or application in new target detection has been converted to a fast-growing field of biomedicine and biotechnology branches. Experimental efforts have led to valuable successes in the field of biosensor design; however, some deficiencies restrict their utilization for this purpose. Computational design of biosensors is introduced as a promising key to eliminate the gap. A set of reliable structure prediction of the biosensor segments, their stability, and accurate descriptors of molecular interactions are required to computationally design biosensors. In this review, we provide a comprehensive insight into the progress of computational methods to guide the design and development of biosensors, including molecular dynamics simulation, quantum mechanics calculations, molecular docking, virtual screening, and a combination of them as the hybrid methodologies. By relying on the recent advances in the computational methods, an opportunity emerged for them to be complementary or an alternative to the experimental methods in the field of biosensor design.

Rational backbone redesign of a fructosyl peptide oxidase to widen its active site access tunnel

Fructosyl peptide oxidases (FPOXs) are enzymes currently used in enzymatic assays to measure the concentration of glycated hemoglobin and albumin in blood samples, which serve as biomarkers of diabetes. However, since FPOX are unable to work directly on glycated proteins, current enzymatic assays are based on a preliminary proteolytic digestion of the target proteins. Herein, to improve the speed and costs of the enzymatic assays for diabetes testing, we applied a rational design approach to engineer a novel enzyme with a wider access tunnel to the catalytic site, using a combination of Rosetta design and molecular dynamics simulations. Our final design, L3_35A, shows a significantly wider and shorter access tunnel, resulting from the deletion of five-amino acids lining the gate structures and from a total of 35 point mutations relative to the wild-type (WT) enzyme. Indeed, upon experimental testing, our engineered enzyme shows good structural stability and maintains significant activity relative to the WT.

The Anti-Amyloidogenic Action of Doxycycline: A Molecular Dynamics Study on the Interaction with Aβ42

The pathological aggregation of amyloidogenic proteins is a hallmark of many neurological diseases, including Alzheimer’s disease and prion diseases. We have shown both in vitro and in vivo that doxycycline can inhibit the aggregation of Aβ42 amyloid fibrils and disassemble mature amyloid fibrils. However, the molecular mechanisms of the drug’s anti-amyloidogenic property are not understood. In this study, a series of molecular dynamics simulations were performed to explain the molecular mechanism of the destabilization of Aβ42 fibrils by doxycycline and to compare the action of doxycycline with those of iododoxorubicin (a toxic structural homolog of tetracyclines), curcumin (known to have anti-amyloidogenic activity) and gentamicin (an antibiotic with no experimental evidence of anti-amyloidogenic properties). We found that doxycycline tightly binds the exposed hydrophobic amino acids of the Aβ42 amyloid fibrils, partly leading to destabilization of the fibrillar structure. Clarifying the molecular determinants of doxycycline binding to Aβ42 may help devise further strategies for structure-based drug design for Alzheimer’s disease.

Molecular dynamics investigation of halogenated amyloidogenic peptides

Besides their biomolecular relevance, amyloids, generated by the self-assembly of peptides and proteins, are highly organized structures useful for nanotechnology applications. The introduction of halogen atoms in these peptides, and thus the possible formation of halogen bonds, allows further possibilities to finely tune the amyloid nanostructure. In this work, we performed molecular dynamics simulations on different halogenated derivatives of the β-amyloid peptide core-sequence KLVFF, by using a modified AMBER force field in which the σ-hole located on the halogen atom is modeled with a positively charged extra particle. The analysis of equilibrated structures shows good agreement with crystallographic data and experimental results, in particular concerning the formation of halogen bonds and the stability of the supramolecular structures. The modified force field described here allows describing the atomistic details contributing to peptides aggregation, with particular focus on the role of halogen bonds. This framework can potentially help the design of novel halogenated peptides with desired aggregation propensity. Graphical abstract Molecular dynamics investigation of halogenated amyloidogenic peptides.

Thermal stabilization of the deglycating enzyme Amadoriase I by rational design

Amadoriases are a class of FAD-dependent enzymes that are found in fungi, yeast and bacteria and that are able to hydrolyze glycated amino acids, cleaving the sugar moiety from the amino acidic portion. So far, engineered Amadoriases have mostly found practical application in the measurement of the concentration of glycated albumin in blood samples. However, these engineered forms of Amadoriases show relatively low absolute activity and stability levels, which affect their conditions of use. Therefore, enzyme stabilization is desirable prior to function-altering molecular engineering. In this work, we describe a rational design strategy based on a computational screening method to evaluate a library of potentially stabilizing disulfide bonds. Our approach allowed the identification of two thermostable Amadoriase I mutants (SS03 and SS17) featuring a significantly higher T₅₀ (55.3 °C and 60.6 °C, respectively) compared to the wild-type enzyme (52.4 °C). Moreover, SS17 shows clear hyperstabilization, with residual activity up to 95 °C, whereas the wild-type enzyme is fully inactive at 55 °C. Our computational screening method can therefore be considered as a promising approach to expedite the design of thermostable enzymes.