An algebraic model to determine substrate kinetic parameters by global nonlinear fit of progress curves

Landscape of In Silico Tools for Modeling Covalent Modification of Proteins: A Review on Computational Covalent Drug Discovery

Covalent drug discovery has been a challenging research area given the struggle of finding a sweet balance between selectivity and reactivity for these drugs, the lack of which often leads to off-target activities and hence undesirable side effects. However, there has been a resurgence in covalent drug design following the success of several covalent drugs such as boceprevir (2011), ibrutinib (2013), neratinib (2017), dacomitinib (2018), zanubrutinib (2019), and many others. Design of covalent drugs includes many crucial factors, where "evaluation of the binding affinity" and "a detailed mechanistic understanding on covalent inhibition" are at the top of the list. Well-defined experimental techniques are available to elucidate these factors; however, often they are expensive and/or time-consuming and hence not suitable for high throughput screens. Recent developments in in silico methods provide promise in this direction. In this report, we review a set of recent publications that focused on developing and/or implementing novel in silico techniques in "Computational Covalent Drug Discovery (CCDD)". We also discuss the advantages and disadvantages of these approaches along with what improvements are required to make it a great tool in medicinal chemistry in the near future.

Substrate-dependent inactivation of recombinant paraoxonase 1 during catalytic dihydrocoumarin turnover and the protective properties of surfactants

Human paraoxonase-1 (PON1) is the most studied member of the paraoxonases (PONs) family and catalyzes the hydrolysis of various substrates (lactones, aryl esters, and paraoxon). Numerous studies link PON1 to oxidative stress-related diseases such as cardiovascular disease, diabetes, HIV infection, autism, Parkinson's, and Alzheimer's, where the kinetic behavior of an enzyme is characterized by initial rates or by modern methods that obtain enzyme kinetic parameters by fitting the computed curves over the entire time-courses of product formation (progress curves). In the analysis of progress curves, the behavior of PON1 during hydrolytically catalyzed turnover cycles is unknown. Hence, progress curves for enzyme-catalyzed hydrolysis of the lactone substrate dihydrocoumarin (DHC) by recombinant PON1 (rePON1) were analyzed to investigate the effect of catalytic DHC turnover on the stability of rePON1. Although rePON1 was significantly inactivated during the catalytic DHC turnover, its activity was not lost due to the product inhibition or spontaneous inactivation of rePON1 in the sample buffers. Examination of the progress curves of DHC hydrolysis by rePON1 led to the conclusion that rePON1 inactivates itself during catalytic DHC turnover hydrolysis. Moreover, human serum albumin or surfactants protected rePON1 from inactivation during this catalytic process, which is significant because the activity of PON1 in clinical samples is measured in the presence of albumin.

Reagent-Free Immobilization of Industrial Lipases to Develop Lipolytic Membranes with Self-Cleaning Surfaces

Biocatalytic membrane reactors combine the highly efficient biotransformation capability of enzymes with the selective filtration performance of membrane filters. Common strategies to immobilize enzymes on polymeric membranes are based on chemical coupling reactions. Still, they are associated with drawbacks such as long reaction times, high costs, and the use of potentially toxic or hazardous reagents. In this study, a reagent-free immobilization method based on electron beam irradiation was investigated, which allows much faster, cleaner, and cheaper fabrication of enzyme membrane reactors. Two industrial lipase enzymes were coupled onto a polyvinylidene fluoride (PVDF) flat sheet membrane to create self-cleaning surfaces. The response surface methodology (RSM) in the design-of-experiments approach was applied to investigate the effects of three numerical factors on enzyme activity, yielding a maximum activity of 823 ± 118 U m⁻² (enzyme concentration: 8.4 g L⁻¹, impregnation time: 5 min, irradiation dose: 80 kGy). The lipolytic membranes were used in fouling tests with olive oil (1 g L⁻¹ in 2 mM sodium dodecyl sulfate), resulting in 100% regeneration of filtration performance after 3 h of self-cleaning in an aqueous buffer (pH 8, 37 °C). Reusability with three consecutive cycles demonstrates regeneration of 95%. Comprehensive membrane characterization was performed by determining enzyme kinetic parameters, permeance monitoring, X-ray photoelectron spectroscopy, FTIR spectroscopy, scanning electron microscopy, and zeta potential, as well as water contact angle measurements.

Evaluation of the paraoxonase-1 kinetic parameters of the lactonase activity by nonlinear fit of progress curves

Although paraoxonase-1 (PON1) activity has been demonstrated to be a reliable biomarker of various diseases, clinical studies have been based only on relative comparison of specific enzyme activities, which capture differences mainly due to (usually unknown) PON1 concentration. Hence, the aim of this report is to present for the first time the simple evaluation method for determining autonomous kinetic parameter of PON1 that could be also associated with polymorphic forms and diseases; i.e. the Michaelis constant which is enzyme concentration independent quantity. This alternative approach significantly reduces the number of experiments needed, and it yields the results with great accuracy.