Search

Using the available structural information of the chemokine receptor CXCR4, we present hit finding and hit exploration studies that make use of virtual fragment screening, design, synthesis and structure activity relationship (SAR) studies. Fragment 2 was identified as virtual screening hit and used as a starting point for the exploration of 31 N-substituted piperidin-4-yl-methanamine derivatives to investigate and improve the interactions with the CXCR4 binding site. Additionally, subtle structural ligand changes lead to distinct interactions with CXCR4 resulting in a full to partial displacement of CXCL12 binding and competitive and/or non-competitive antagonism. Three-dimensional quantitative structure-activity relationship (3D-QSAR) and binding model studies were used to identify important hydrophobic interactions that determine binding affinity and indicate key ligand-receptor interactions. (C) 2018 Elsevier Masson SAS. All rights reserved.

SAR beyond protein-ligand interactions: By combining structure-affinity relationships, protein-ligand modeling studies, and quantum mechanical calculations, we show that ligand conformational energies and basicity play critical roles in ligand binding to the histamine H4 receptor, a GPCR that plays a key role in inflammation.

This review will focus on the construction, refinement, and validation of chemokine receptor models for the purpose of structure-based virtual screening and ligand design. The review will present a comparative analysis of ligand binding pockets in chemokine receptors, including a review of the recently released CXCR4 X-ray structures, and their implication on chemokine receptor (homology) modeling. The recommended protein-ligand modeling procedure as well as the use of experimental anchors to steer the modeling procedure is discussed and an overview of several successful structure-based ligand discovery and design studies is provided. This review shows that receptor models, despite structural inaccuracies, can be efficiently used to find novel ligands for chemokine receptors. Crown Copyright©2012 Published by Elsevier Ltd. All rights reserved.

The G protein-coupled chemokine receptor CXCR3 plays a role in numerous inflammatory events. The endogenous ligands for the chemokine receptors are peptides, but in this study we disclose small-molecule ligands that are able to activate CXCR3. A class of biaryl-type compounds that is assembled by convenient synthetic routes is described as a new class of CXCR3 agonists. Intriguingly, structure-activity relationship and structure-function relationship studies reveal that subtle chemical modifications on the outer aryl ring (e.g., either the size or position of a halogen atom) result in a full spectrum of agonist efficacies on CXCR3. Quantum mechanics calculations and nuclear Overhauser effect spectroscopy NMR studies suggest that the biaryl dihedral angle and the electronic nature of ortho-substituents play an important role in determining agonist efficacies. Compounds 38 (VUF11222) and 39 (VUF11418) are the first reported nonpeptidomimetic agonists on CXCR3, rendering them highly useful chemical tools for detailed assessment of CXCR3 activation as well as for studying downstream CXCR3 signaling. © 2012 American Chemical Society.

Recently the first community-wide assessments of the prediction of the structures of complexes between proteins and small molecule ligands have been reported in the so-called GPCR Dock 2008 and 2010 assessments. In the current review we discuss the different steps along the protein-ligand modeling workflow by critically analyzing the modeling strategies we used to predict the structures of protein-ligand complexes we submitted to the recent GPCR Dock 2010 challenge. These representative test cases, focusing on the pharmaceutically relevant G Protein-Coupled Receptors, are used to demonstrate the strengths and challenges of the different modeling methods. Our analysis indicates that the proper performance of the sequence alignment, introduction of structural adjustments guided by experimental data, and the usage of experimental data to identify protein-ligand interactions are critical steps in the protein-ligand modeling protocol.

Aldosterone is synthesised by aldosterone synthase (CYP11B2). CYP11B2 has a highly homologous isoform, steroid 11beta-hydroxylase (CYP11B1), which is responsible for the biosynthesis of aldosterone precursors and glucocorticoids. To investigate aldosterone biosynthesis and facilitate the search for selective CYP11B2 inhibitors, we constructed three-dimensional models for CYP11B1 and CYP11B2 for both human and rat. The models were constructed based on the crystal structure of Pseudomonas Putida CYP101 and Oryctolagus Cuniculus CYP2C5. Small steric active site differences between the isoforms were found to be the most important determinants for the regioselective steroid synthesis. A possible explanation for these steric differences for the selective synthesis of aldosterone by CYP11B2 is presented. The activities of the known CYP11B inhibitors metyrapone, R-etomidate, R-fadrazole and S-fadrazole were determined using assays of V79MZ cells that express human CYP11B1 and CYP11B2, respectively. By investigating the inhibitors in the human CYP11B models using molecular docking and molecular dynamics simulations we were able to predict a similar trend in potency for the inhibitors as found in the in vitro assays. Importantly, based on the docking and dynamics simulations it is possible to understand the enantioselectivity of the human enzymes for the inhibitor fadrazole, the R-enantiomer being selective for CYP11B2 and the S-enantiomer being selective for CYP11B1.

We have explored the possibilities and challenges of structure-based virtual screening (SBVS) against the human histamine H4 receptor (H4R), a key player in inflammatory responses. Several SBVS strategies, employing different H4R ligand conformations, were validated and optimized with respect to their ability to discriminate small fragment-like H4R ligands from true inactive fragments, and compared to ligand-based virtual screening (LBVS) approaches. SBVS studies with a molecular interaction fingerprint (IFP) scoring method enabled the identification of H4R ligands that were not identified in LBVS runs, demonstrating the scaffold hopping potential of combining molecular docking and IFP scoring. Retrospective VS evaluations against H4R homology models based on the histamine H1 receptor (H1R) crystal structure did not give higher enrichments of H4R ligands than H4R models based on the beta-2 adrenergic receptor (β2R). Complementary prospective SBVS studies against β2R-based and H1R-based H4R homology models led to the discovery of different new fragment-like H4R ligand chemotypes. Of the 37 tested compounds, 9 fragments (representing 5 different scaffolds) had affinities between 0.14 and 6.3 μM at the H4R.

Contains fulltext : 103510.pdf (Publisher’s version ) (Closed access) We present the systematic prospective evaluation of a protein-based and a ligand-based virtual screening platform against a set of three G-protein-coupled receptors (GPCRs): the beta-2 adrenoreceptor (ADRB2), the adenosine A(2A) receptor (AA2AR), and the sphingosine 1-phosphate receptor (S1PR1). Novel bioactive compounds were identified using a consensus scoring procedure combining ligand-based (frequent substructure ranking) and structure-based (Snooker) tools, and all 900 selected compounds were screened against all three receptors. A striking number of ligands showed affinity/activity for GPCRs other than the intended target, which could be partly attributed to the fuzziness and overlap of protein-based pharmacophore models. Surprisingly, the phosphodiesterase 5 (PDE5) inhibitor sildenafil was found to possess submicromolar affinity for AA2AR. Overall, this is one of the first published prospective chemogenomics studies that demonstrate the identification of novel cross-pharmacology between unrelated protein targets. The lessons learned from this study can be used to guide future virtual ligand design efforts.

The histamine H(4) receptor (H(4)R) is a G protein-coupled receptor (GPCR) that plays an important role in inflammation. Similar to the homologous histamine H(3) receptor (H(3)R), two acidic residues in the H(4)R binding pocket, D(3.32) and E(5.46), act as essential hydrogen bond acceptors of positively ionizable hydrogen bond donors in H(4)R ligands. Given the symmetric distribution of these complementary pharmacophore features in H(4)R and its ligands, different alternative ligand binding mode hypotheses have been proposed. The current study focuses on the elucidation of the molecular determinants of H(4)R-ligand binding modes by combining (3D) quantitative structure-activity relationship (QSAR), protein homology modeling, molecular dynamics simulations, and site-directed mutagenesis studies. We have designed and synthesized a series of clobenpropit (N-(4-chlorobenzyl)-S-[3-(4(5)-imidazolyl)propyl]isothiourea) derivatives to investigate H(4)R-ligand interactions and ligand binding orientations. Interestingly, our studies indicate that clobenpropit (2) itself can bind to H(4)R in two distinct binding modes, while the addition of a cyclohexyl group to the clobenpropit isothiourea moiety allows VUF5228 (5) to adopt only one specific binding mode in the H(4)R binding pocket. Our ligand-steered, experimentally supported protein modeling method gives new insights into ligand recognition by H(4)R and can be used as a general approach to elucidate the structure of protein-ligand complexes.

A pharmacophore describes the arrangement of molecular features a ligand must contain to efficaciously bind a receptor. Pharmacophore models are developed to improve molecular understanding of ligand-protein interactions, and can be used as a tool to identify novel compounds that fulfil the pharmacophore requirements and have a high probability of being biologically active. Protein structure-based pharmacophores (SBPs) derive these molecular features by conversion of protein properties to reciprocal ligand space. Unlike ligand-based pharmacophore models, which require templates of ligands in their bioactive conformation, SBPs do not depend on ligand information. The current review describes the different steps in the construction of SBPs: (i) protein structure preparation, (ii) binding site detection, (iii) pharmacophore feature definition, and (iv) pharmacophore feature selection. We show that the SBP modeling workflow poses different challenges than ligand-based pharmacophore modeling, including the definition of protein pharmacophore features essential for ligand binding. A comprehensive overview of different SBP modeling and screening methods and applications is provided to illustrate that SBPs can be efficiently used for virtual screening, ligand binding mode prediction, and binding site similarity detection. Our review demonstrates that SBPs are valuable tools for hit and lead optimization, compound library design and target hopping, especially in cases where ligand information is scarce. © The Royal Society of Chemistry.

Reducing aldosterone action is beneficial in various major diseases such as heart failure. Currently, this is achieved with mineralocorticoid receptor antagonists, however, aldosterone synthase (CYP11B2) inhibitors may offer a promising alternative. In this study, we used three-dimensional modeling of CYP11B2 to model the binding modes of the natural substrate 18-hydroxycorticosterone and the recently published CYP11B2 inhibitor R-fadrozole as a rational guide to design 44 structurally simple and achiral 1-benzyl-1H-imidazoles. Their syntheses, in vitro inhibitor potencies, and in silico docking are described. Some promising CYP11B2 inhibitors were identified, with our novel lead MOERAS115 (4-((5-phenyl-1H-imidazol-1-yl)methyl)benzonitrile) displaying an IC(50) for CYP11B2 of 1.7 nM, and a CYP11B2 (versus CYP11B1) selectivity of 16.5, comparable to R-fadrozole (IC(50) for CYP11B2 6.0 nM, selectivity 19.8). Molecular docking of the inhibitors in the models enabled us to generate posthoc hypotheses on their binding modes, providing a valuable basis for future studies and further design of CYP11B2 inhibitors.