Enzyme Kinetics and Drugs as Enzyme Inhibitors
Peter Grunwald in Pharmaceutical Biocatalysis, 2019
Copeland (2011, 2016) described the conformational selection model as an ensemble of conformers in which the enzyme/receptor exists, of which in the absent of an inhibitor/ligand only some few are capable of binding which are in equilibrium with those being unable to bind. Conformers binding an inhibitor are removed from this equilibrium so that more and more ligands become bound. The rate-limiting step in this model is the interconversion between both conformers. Examples of this enzyme-ligand binding interaction are human glucokinase/glucose or α -chymotrypsin/proflavin. In the majority of drug-binding events the induced-fit model becomes effective. The enzyme/receptor is present in a single conformational state that binds the inhibitor or ligand rapidly. Binding is followed by an optimization of the complementarity between the inhibitor molecule and the receptor’s binding pocket via structural adjustments. This comparatively slow conformational transition is the rate-limiting step in this model. Examples are among others cyclooxygenase-1/indomethacin, xanthine oxidase/allopurinol, dihydrofolate reductase/methotrexate, or HIV-1 protease/Darunivir. To sum up, the drug-target residence time is an important aspect for drug optimization by chemists being active in this field.
Kinetic Thinking: Back to the Future
Clive R. Bagshaw in Biomolecular Kinetics, 2017
Initial analysis of the stopped-flow data was performed by fitting an exponential function to each reaction profile, although some measurements deviated from pseudo-first-order conditions (Figure 10.9b). The concentration dependence showed indications of an initial decrease in kobs with increasing ligand concentration, indicative of conformational selection. Note the decrease in kobs occurs in the region where [peptide] < [recoverin] but increases when [peptide] > [recoverin]. The latter behavior suggests k−3 < k+0 (Figure 2.15). An attempt to fit an induced-fit mechanism failed to account for the initial decrease in kobs at low [peptide]. Given the diagnostic behavior that occurs in the region where the profiles should deviate from a single exponential profile, the authors [66] also carried out a global fit to the models across the full concentration range with either the recoverin or the peptide in molar excess. This analysis likewise showed a better fit to the conformational-selection model than an induced-fit model. Isothermal titration calorimetry was used to determine the overall equilibrium constant and place limits on the fits of the kinetic data. The best-fit values for Equation 10.14 were determined as in Table 10.2.
In Vitro to In Vivo Extrapolation of Metabolic Rate Constants for Physiologically Based Pharmacokinetic Models
John C. Lipscomb, Edward V. Ohanian in Toxicokinetics and Risk Assessment, 2016
Some enzymes are membrane bound to cellular organelles, such as the endoplasmic reticulum or mitochondria, while others are present in the soluble portion of the cell known as the cytoplasm. However, the aqueous cytoplasm of the cell is highly organized via a group of polymeric proteins called the cytomatrix, and soluble enzymes appear to be associated with this dynamic network (3–5). This intracellular organization can influence the efficiency of enzyme catalysis and promote the coupling of metabolic processes. For example, a chemical that is hydroxylated by endoplasmic reticulum-bound cytochrome P450 (CYP) can be so efficiently conjugated with glucuronic acid by neighboring membrane-bound glucuronosyl transferase that the free alcohol product cannot be detected in the cell. The coupling of metabolic processes can lead to very efficient detoxication of toxicants, but it can also promote toxication processes that can ultimately lead to cellular damage and death.
In silico screening for identification of fatty acid synthase inhibitors and evaluation of their antiproliferative activity using human cancer cell lines
Published in Journal of Receptors and Signal Transduction, 2018
Amrutha Nisthul A., Archana P. Retnakumari, Shabna A., Ruby John Anto, C. Sadasivan
IFD was carried out for the ligands with favorable GScore after XP docking. The active site residues, as well as ligands, were assumed to be flexible in IFD. The protocol was initiated with the constrained refinement of the receptor with RMSD 0.18 Å. Initial Glide docking was performed with a softened van der Waals radii of 0.5 Å for both protein and ligand. Ten poses were selected for the second step, the Prime induced fit, in which the receptor residues within 5 Å of ligand were identified and minimized. The receptor now represents the induced fit model for each protein-ligand complex. In the final Glide redocking stage, the ligand was redocked with the minimized protein structure (within 30 kcal/mol) in XP mode. The binding energy was estimated as IFD score. IFD score was calculated from the protein–ligand interaction energy and the prime energy of the total system which is given by the equation:
Recent advances in the development of polyethylenimine-based gene vectors for safe and efficient gene delivery
Published in Expert Opinion on Drug Delivery, 2019
Cuiping Jiang, Jiatong Chen, Zhuoting Li, Zitong Wang, Wenli Zhang, Jianping Liu
As the substances that are inherently present in the human body, biological molecules draw growing interests as promising triggering motifs in the design of smart PEI-based gene vectors. Among different classes of biological components, ATP, enzyme, glucose, and antigen are the most attractive endogenous stimuli that enable biomolecule-responsive release. As we all know, enzymes are potent catalysts during almost all biological processes, and enzyme catalysis is highly selective towards specific substrates under mild conditions. Using tumor as an example again, several enzymes (i.e. proteases, lipase, hyaluronidase (HAase), etc.) have great potential to be specific stimuli in a controlled gene delivery system [117]. For instance, Yin et al. [118] reported an HA-conjugated PEI polymer for the active tumor targeting via interaction of HA with CD44 receptor. Once the nanocarrier reached the tumor extracellular matrix, the surface layer of HA would be deshielded under the catalysis of HAase, leading to the enhanced cellular uptake owing to the exposure of positive charges.
Production, purification and biochemical characterisation of a novel lipase from a newly identified lipolytic bacterium Staphylococcus caprae NCU S6
Published in Journal of Enzyme Inhibition and Medicinal Chemistry, 2021
Junxin Zhao, Maomao Ma, Zheling Zeng, Ping Yu, Deming Gong, Shuguang Deng
Temperature is one of the most important factors affecting the reaction rate of enzyme catalysis. As shown in Figure 5(A), the lipase was active in the wide range of temperatures from 10 to 60 °C. The maximum hydrolytic activity was found at 40 °C, with the relative activity and specific activity of 100% and 503 U/mg respectively. The optimal reaction temperature was lower than the lipase from Aureobasidium pullulans (55 °C)18. Activity analyses of the lipase at temperatures from 10 to 60 °C for 240 min showed that the remaining activity at 40 °C was at the highest level (Figure 5(B)). Only the extremely high temperatures, such as 50 or 60 °C, significantly inhibited the lipase activity, and prolonged incubation may rapidly inactivate the lipase. The highest remaining activity was at 40 °C for 80 min, and the lipase activity decreased with an increase of culture period. The decrease may be because the molecular structure of the enzyme was irreversibly changed, which may have altered the configuration of the active site, thereby decreasing interaction of the lipase with substrates19.
Related Knowledge Centers
- Active Site
- Biochemistry
- Biomolecule
- Catalysis
- Cofactor
- Enzyme
- Reaction Rate
- Process
- Protein Complex
- Adenosine Triphosphate