The steroid and xenobiotic-responsive human pregnane X receptor (PXR) binds a broad range of structurally diverse compounds. The structures of the apo and ligand-bound forms of PXR are very similar, in contrast to most promiscuous proteins that generally adapt their shape to different ligands. We investigated the structural origins of PXR's recognition promiscuity using computational solvent mapping, a technique developed for the identification and characterization of hot spots, i.e., regions of the protein surface that are major contributors to the binding free energy. Results reveal that the smooth and nearly spherical binding site of PXR has a well-defined hot spot structure, with four hot spots located on four different sides of the pocket and a fifth close to its center. Three of these hot spots are already present in the ligand-free protein. The most important hot spot is defined by three structurally and sequentially conserved residues, W299, F288, and Y306. This largely hydrophobic site is not very specific, and interacts with all known PXR ligands. Depending on their sizes and shapes, individual PXR ligands extend into 2, 3, or 4 more hot spot regions. The large number of potential arrangements within the binding site explains why PXR is able to accommodate a large variety of compounds. All five hot spots include at least one important residue, which is conserved in all mammalian PXRs, suggesting that the hot spot locations have remained largely invariant during mammalian evolution. The same side chains also show a high level of structural conservation across hPXR structures. However, each of the hPXR hot spots also includes residues with moveable side chains, further increasing the size variation in ligands that PXR can bind. Results also suggest a unique signal transduction mechanism between the PXR homodimerization interface and its coactivator binding site.The human pregnane X receptor, PXR, is a transcriptional regulator of a large number of genes involved in steroid and xenobiotic metabolism and excretion (1,2), including cytochrome P450 (CYP) 3A4 (3,4), CYP2B6 (5), aldehyde dehydrogenases, glutathione-S-transferase, sulfotransferases, and many others. Like other nuclear receptors, PXR contains both a DNAbinding domain and a ligand-binding domain. However, unlike the classical steroid, retinoid, and thyroid hormone receptors, which are highly selective for their cognate hormones, PXR has evolved to detect structurally diverse compounds. Human PXR activators include a wide range of prescription and herbal drugs such as paclitaxel, troglitazone, rifampicin, ritonavir, clotrimazole, and St. John's Wort, which can be involved in clinically relevant drug-drug interactions (6). PXR can also be activated by various environmental chemicals, including *To whom correspondence should be addressed. edu. † This investigation was supported by Superfund Research Program at Boston University, grant 5 P42 ES07381 from the National Institute of Environmental Health Sciences, and grant GM64700 from the Natio...
Molecular docking is a frequently used method in structure-based rational drug design. It is used for evaluating the complex formation of small ligands with large biomolecules, predicting the strength of the bonding forces and finding the best geometrical arrangements. The major goal of this advanced undergraduate biochemistry laboratory exercise is to illustrate the importance and application of this tool. Students carry out the computational modeling of the interaction of acetylcholinesterase and its inhibitor, tacrine, and learn about the concepts of protein structure, enzyme-inhibitor interactions, intermolecular forces, and role of molecular design in drug-development.Keywords: Molecular docking, AutoDock, structure-based drug design, acetylcholinesterase inhibitor.Computer-based methods are becoming increasingly important and complementary to wet laboratory experiments in studying the structure and function of biomolecules. Molecular docking is a frequently used tool in structure-based rational drug design. Although early efforts were hindered by limited possibilities in computational resources, due to recent advances in high performance computing virtual screening methods became more and more efficient. These methods contributed to the development of several drugs and drug candidates that advanced to clinical trials. Examples include lead compounds to prevent myocardial infarction, to treat HIV infection, Alzheimer's disease, rheumatoid arthritis, and many other diseases [1,2]. Docking programs simulate how a target macromolecule (receptor, enzyme, or nucleic acid) interacts with small molecule ligands, such as substrates, inhibitors, or other drug candidates. To model the binding between the ligand and the target molecule, their known threedimensional structures are superimposed and the fit between the key sites of the target molecule and the ligand is then analyzed. By using molecular mechanics, the programs usually determine the binding energy between the host's binding site and the ligand, a feature used to predict and describe the efficacy of the binding [3].
A broad group of compounds including substituted pyrazoles, pyrroles, indoles, and carbazoles were screened to identify potential inhibitor lead compounds of fructose-1,6-bisphosphatase (FBPase). Best inhibitors are (1H-indol-1-yl)(4-(trifluoromethyl)phenyl)methanone, ethyl 3-(3,5-dimethyl-1H-pyrrol-2-yl)-4,4,4-trifluoro-3-hydroxybutanoate, 3,5-diphenyl-1-(3-(trifluoromethyl) phenyl)-1H-pyrazole, and ethyl 3,3,3-trifluoro-2-hydroxy-2-(1-methyl-1H-indol-3-yl)propanoate. The IC50 values (3.1, 4.8, 6.1, and 11.9 microM) were comparable to that of AMP, the natural inhibitor of murine FBPase (IC50 of 4.0 microM). Docking programs were utilized to interpret the experiments.
Recent developments in the biophysical characterization of proteins have provided a means of directly measuring electrostatic fields by introducing a probe molecule to the system of interest and interpreting photon absorption in the context of the Stark effect. To fully account for this effect, the development of accurate atomistic models is of paramount importance. However, suitable computational protocols for evaluating Stark shifts in proteins are yet to be established. In this work, we present a comprehensive computational method to predict the change in absorption frequency of a probe functional group as a direct result of a perturbation in its surrounding electrostatic field created by a protein environment, i.e., the Stark shift. We apply the method to human aldose reductase, a key protein enzyme that catalyzes the reduction of monosaccharides. We develop a protocol based on a combination of molecular dynamics and moving-domain QM/MM methods, which achieves quantitative agreement with experiment. We outline the difficulties in predicting localized electrostatic field changes within a protein environment, and by extension the Stark shift, due to a protein site mutation. Furthermore, the combined use of Stark effect spectroscopy and computational modeling is used to predict the protonation state of ionizable residues in the vicinity of the electrostatic probe.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.