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Enzyme Kinetics and Drugs as Enzyme Inhibitors
Published in Peter Grunwald, Pharmaceutical Biocatalysis, 2019
The conversion of IC50 to Ki-values is influenced by the type of inhibition (see above and Brandt et al., 1987; Cer et al., 2009); an equation (Eq. 21.2) for competitive inhibition has been provided by Cheng and Prusoff (1973), and for tightly bound inhibitors (see below) by Copeland et al. (1995) (Eq. 21.3). In the case of weak interaction between enzyme and inhibitor, corresponding to µM or mM Ki-values, equilibrium is established rapidly and a discussion of enzyme-inhibitorinteraction via Eqs. 21.1 and 21.2 following Emil Fischer’s lock-and-key model (the enzyme’s active site has a structure complimentary to the substrate molecule) is possible. However, when drug-binding occurs with lower Ki-values association and in particular dissociation of the drug proceed more slowly meaning the residence time (t = 1/k–1), or the half-life of the drug target complex increases which has to be considered for a quantitative treatment. The interaction is accompanied by a variety of more or less subtle structural changes of the enzyme for which two pathway models exist, the conformational selection model and the induced-fit model of inhibitor binding.
Biochemistry
Published in Sarah Armstrong, Barry Clifton, Lionel Davis, Primary FRCA in a Box, 2019
Sarah Armstrong, Barry Clifton, Lionel Davis
‘Induced fit model’ (Koshland 1958) – the active site is continually remodelled by interactions with the substrate until the substrate is completely bound. May enhance the fidelity of molecular recognition in the presence of competition
Kinetic Thinking: Back to the Future
Published in Clive R. Bagshaw, 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 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:
Investigation of anomalous charge variant profile reveals discrete pH-dependent conformations and conformation-dependent charge states within the CDR3 loop of a therapeutic mAb
Published in mAbs, 2020
Wenkui Lan, Joseph J. Valente, Andrew Ilott, Naresh Chennamsetty, Zhihua Liu, Joseph M. Rizzo, Aaron P. Yamniuk, Difei Qiu, Holly M. Shackman, Mark S. Bolgar
Conformational flexibility within the native state in particular in CDRs was described mainly using two models, the induced fit18 and conformational selection19 models. In principle, the induced fit model contends that a ligand is required to actively induce the protein into its binding-competent conformation while the conformational selection model contends that the binding-competent conformation preexists within the native state ensemble and that a ligand merely shifts the equilibrium toward that conformation. There are numerous examples in the literature that provide support for both models,20,21 but one particularly notable and recent report from Fernandez-Quintero et al.22 highlighted the importance of describing HC-CDR3 loop structures as conformational ensembles and concluded that all of the antibodies in their study demonstrated behavior consistent with the conformational selection model. Of the numerous extrinsic factors other than substrates that are known to influence such conformational changes, pH is among the most commonly cited. As pH can alter the ionization behavior of charged amino acid groups, changes in pH may interfere with favorable intramolecular interactions required for maintenance of certain folded structures. Under certain circumstances, it may even be possible to observe a pH-dependent equilibrium between two distinctly different native-state conformations, such as in the case of Nitrophorin-4 (NP4). Crystallographic data from Kondrashov et al.23 revealed that NP4 switches from a predominantly “closed” conformation at pH 5.6 to a predominantly “open” conformation at pH 7.4. Subsequent investigations by Menyhard et al.24 showed that an aspartic acid (Asp) that is buried in the closed conformation has an anomalously high pKa value, enabling it to remain protonated (uncharged) within the relatively nonpolar interior of the protein. Di Russo et al.25 then demonstrated the interconnectivity of pH-dependent conformational changes in NP4 and distinct conformation-dependent pKa values of the Asp in question. Specifically, these authors showed that in the open conformation, where the Asp side-chain is fully exposed to the solvent, its pKa was calculated as 4.3, consistent with theoretical values. In the closed conformation, however, intramolecular interactions with neighboring amino acids raised its calculated pKa to 8.5. Such coupling of pH-dependent conformational changes and conformationally dependent pKa values exemplifies the complex interdependencies that can contribute to the overall structure-function relationship of a protein.