How To Design Selective Ligands for Highly Conserved Binding Sites: A Case Study Using N-Myristoyltransferases as a Model System

Under embargo until: 2020-08-19A model system of two related enzymes with conserved binding sites, namely N-myristoyltransferase from two different organisms, was studied to decipher the driving forces that lead to selective inhibition in such cases. Using a combination of computational and experimental tools, two different selectivity-determining features were identified. For some ligands, a change in side-chain flexibility appears to be responsible for selective inhibition. Remarkably, this was observed for residues orienting their side chains away from the ligands. For other ligands, selectivity is caused by interfering with a water molecule that binds more strongly to the off-target than to the target. On the basis of this finding, a virtual screen for selective compounds was conducted, resulting in three hit compounds with the desired selectivity profile. This study delivers a guideline on how to assess selectivity-determining features in proteins with conserved binding sites and to translate this knowledge into the design of selective inhibitors.acceptedVersio

Bridging the Binding Sites : Dualsteric Ligands for the Cannabinoid 2 Receptor (CB2R)

Acknowledgements This project was financially supported by the German Research Foundation (Deutsche Forschungsgemeinschaft under DFG DE1546/10-1). Gratitude is expressed to the International Doctorate Program “Receptor Dynamics” of the Elite Network of Bavaria (ENB) for financial support of A.T. and S.A.M.S. (grant No. K-BM-2013-247). Y.A.R. was granted a scholarship by the German Academic Exchange Service (Deutscher Akademischer Austauschdienst, DAAD) program “Research stays for university academics and scientists.” D.A.R.-S. was awarded a Ph.D. scholarship by the DAAD. J.N.H. was financially supported by NHS Grampian. Furthermore, the authors thank Professor Dr. Kristina Lorenz (Institute of Pharmacology and Toxicology, University of Würzburg) for enabling them to conduct in vitro experiments in her laboratory. Open access funding enabled and organized by Projekt DEAL.Peer reviewedPublisher PD

From ligand to complexes: Part 2: Remarks on human immunodeficiency virus type 1 integrase inhibition by beta-diketo acid metal complexes

In a previous work we reported results about the coordination ability of the diketo acid pharmacophore, and discussed on the anti-HIV-1 IN activity of a series of synthesized β-diketo acid metal complexes. Herein, a further extension of this study is reported. In particular, a new set of complexes with different stoichiometry was synthesized, and a series of potentiometric measurements were conducted for two diketo acids as model ligands in the presence of other divalent metal ions in order to outline a speciation model. The first X-ray solved structure of a diketo acid metal complex is presented. Moreover, we tested the obtained complexes for anti-HIV 1 IN activity. Furthermore, detailed docking studies were conducted in order to investigate the mode of binding of the free ligands compared with their metal complexes on the active site

Glycolytic flux control by drugging phosphoglycolate phosphatase

Targeting the intrinsic metabolism of immune or tumor cells is a therapeutic strategy in autoimmunity, chronic inflammation or cancer. Metabolite repair enzymes may represent an alternative target class for selective metabolic inhibition, but pharmacological tools to test this concept are needed. Here, we demonstrate that phosphoglycolate phosphatase (PGP), a prototypical metabolite repair enzyme in glycolysis, is a pharmacologically actionable target. Using a combination of small molecule screening, protein crystallography, molecular dynamics simulations and NMR metabolomics, we discover and analyze a compound (CP1) that inhibits PGP with high selectivity and submicromolar potency. CP1 locks the phosphatase in a catalytically inactive conformation, dampens glycolytic flux, and phenocopies effects of cellular PGP-deficiency. This study provides key insights into effective and precise PGP targeting, at the same time validating an allosteric approach to control glycolysis that could advance discoveries of innovative therapeutic candidates

Slow-Onset Inhibition of Mycobacterium tuberculosis InhA: Revealing Molecular Determinants of Residence Time by MD Simulations

An important kinetic parameter for drug efficacy is the residence time of a compound at a drug target, which is related to the dissociation rate constant koff. For the essential antimycobacterial target InhA, this parameter is most likely governed by the ordering of the flexible substrate binding loop (SBL). Whereas the diphenyl ether inhibitors 6PP and triclosan (TCL) do not show loop ordering and thus, no slow-binding inhibition and high koff values, the slightly modified PT70 leads to an ordered loop and a residence time of 24 minutes. To assess the structural differences of the complexes from a dynamic point of view, molecular dynamics (MD) simulations with a total sampling time of 3.0 µs were performed for three ligand-bound and two ligand-free (perturbed) InhA systems. The individual simulations show comparable conformational features with respect to both the binding pocket and the SBL, allowing to define five recurring conformational families. Based on their different occurrence frequencies in the simulated systems, the conformational preferences could be linked to structural differences of the respective ligands to reveal important determinants of residence time. The most abundant conformation besides the stable EI* state is characterized by a shift of Ile202 and Val203 toward the hydrophobic pocket of InhA. The analyses revealed potential directions for avoiding this conformational change and, thus, hindering rapid dissociation: (1) an anchor group in 2'-position of the B-ring for scaffold stabilization, (2) proper occupation of the hydrophobic pocket, and (3) the introduction of a barricade substituent in 5'-position of the diphenyl ether B-ring

SFCscore^<i>RF</i>: A Random Forest-Based Scoring Function for Improved Affinity Prediction of Protein–Ligand Complexes

A major shortcoming of empirical scoring functions for protein–ligand complexes is the low degree of correlation between predicted and experimental binding affinities, as frequently observed not only for large and diverse data sets but also for SAR series of individual targets. Improvements can be envisaged by developing new descriptors, employing larger training sets of higher quality, and resorting to more sophisticated regression methods. Herein, we describe the use of SFCscore descriptors to develop an improved scoring function by means of a PDBbind training set of 1005 complexes in combination with random forest for regression. This provided SFCscore^<i>RF</i> as a new scoring function with significantly improved performance on the PDBbind and CSAR–NRC HiQ benchmarks in comparison to previously developed SFCscore functions. A leave-cluster-out cross-validation and performance in the CSAR 2012 scoring exercise point out remaining limitations but also directions for further improvements of SFCscore^<i>RF</i> and empirical scoring functions in general

Collective backbone RMSD values of the substrate binding loop in the InhA monomers.

<p>Each monomer of the simulated homotetrameric systems (150 ns) was fitted individually onto chain A of the 2X23 crystal structure as reference for the RMSD measurements and the data of the four monomers were combined to one box plot per system. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0127009#pone.0127009.g004" target="_blank">Fig 4</a> for further explanations.</p