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

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

2D density plot for the ether dihedral angles <i>α</i> and <i>β</i> of the unbound ligands PT70 (left) and 6PP (right) based on a 150 ns MD simulation in aqueous solution.

<p>The dihedral angles <i>α</i> (C_<i>OH</i>-C-O-C) and <i>β</i> (C-O-C-C_{<i>Me</i>/<i>H</i>}) are illustrated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0127009#pone.0127009.g002" target="_blank">Fig 2</a>.</p

Collective backbone RMSD values (C, N, and C_<i>α</i> atoms) of 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. Boxes indicate the interquartile range (first to third quartile), black lines in the boxes show the median of each distribution. The whiskers extend to values 1.5 times the interquartile range from the box. Significant differences in the medians are indicated by non-overlapping notches. Average values are marked by white triangles.</p

Open and closed conformations of InhA observed in the MD simulations.

<p>Figure (a) shows the closed state represented by the medoid of conformational Family 1, figure (b) illustrates the open state represented by the medoid of cluster 4 (belonging to conformational Family 3). The same view of the binding pocket as in Fig 3 of Li et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0127009#pone.0127009.ref017" target="_blank">17</a>] is used for better comparison. In this view, the portal-forming elements are located left (helix <i>α</i>6) and right (strand-4) of the binding site. The distances highlighted as yellow dashed lines were measured between Ala198/Ile202 on helix <i>α</i>6 and Phe97 on strand-4. For comparison, in the crystal structure of the <b>PT70</b> complex (PDB 2X23) respresenting the closed state, a distance of 4 Å is found between Ile202 and Phe97, whereas the open state is characterized by a distance of about 10 Å between Ala198 and Phe97 in chain B of the <b>PT155</b>-complex crystal structure (PDB 4OXN) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0127009#pone.0127009.ref017" target="_blank">17</a>].</p

Mechanisms of drug-target complex formation.

<p><b>(a)</b> Equilibria for rapid reversible inhibition via a one-step mechanism and slow-binding inhibition via a two-step induced-fit mechanism along with a schematic free-energy profile for this reaction. E denotes the enzyme, I the inhibitor, EI the initial enzyme-inhibitor complex, and EI* the final enzyme-inhibitor complex. In the case of InhA, the diphenyl ether inhibitors bind to the enzyme with bound oxidized cofactor NAD⁺, forming a ternary complex. The double-headed arrows in the energy profile highlight the importance of the barrier height for the kinetics of the reaction. <b>(b)</b> Schematic free-energy profiles for a slow-binding inhibitor (left) and a destabilized EI* state as a consequence of ligand removal or the presence of a rapid-reversible inhibitor (right). Each macrostate (EI, EI*) is obviously associated with many microstates.</p