Ligand binding mechanism in steroid receptors; from conserved plasticity to differential evolutionary constraints

Steroid receptor drugs have been available for more than half a century, but details 24 of the ligand binding mechanism has remained elusive. We solved X-ray structures of 25 the glucocorticoid and mineralocorticoid receptors to identify a conserved plasticity at 26 helix 6-7 region that extend the ligand binding pocket towards the receptor surface. 27 Since none of the endogenous ligands exploit this region, we hypothesized that it 28 constitutes an integral part of the binding event. Extensive all atom unbiased ligand 29 exit and entrance simulations corroborate a ligand binding pathway that gives the 30 observed structural plasticity a key functional role. Kinetic measurements reveal that 31 the receptor residence time correlate with structural rearrangements observed in both 32 structures and simulations. Ultimately, our findings reveal why nature has conserved 33 the capacity to open up this region and highlight how differences in the details of the 34 ligand entry process result in differential evolutionary constraints across the steroid 35 receptors.This study was supported by The European Research Council (2009-Adg25027-535 PELE) to V.G and by the SEV-2011-00067 grant of the Severo Ochoa Program. We 536 would like to acknowledge our AstraZeneca colleagues J. Hartleib, R.Unwin and 537 R.Knöll for helpful discussions. We also thank N. Blomberg (ELIXIR) and R. Neutze 538 (University of Gothenburg) for careful reading of the manuscript.Peer ReviewedPostprint (author's final draft

Unraveling the Allosteric Cross-Talk Between Coactivator Peptide and Ligand Binding Site in Glucocorticoid Receptor

Glucocorticoid receptor (GR) is a nuclear receptor that controls critical biological processes by regulating thetranscription of specific genes. There is a known allosteric cross-talk between the ligand and coregulator bindingsites within the GR ligand binding domain that is crucial for the control of the functional response. However, themolecular mechanisms underlying such an allosteric control remain elusive. Here, molecular dynamics (MD)simulations, bioinformatic analysis and biophysical measurements are integrated to capture the structural anddynamic features of the allosteric cross-talk within GR. We identified a network of evolutionarily conservedresidues that enables the allosteric signal transduction, in agreement with experimental data. MD simulationsclarify how such network is dynamically interconnected and offer a mechanistic explanation of how the differentpeptides affect the intensity of the allosteric signal. This study provides useful insights to elucidate the GRallosteric regulation, ultimately, posing the foundation for designing novel drugs.</div

Combining Monte Carlo and molecular dynamics simulations for enhanced binding free energy estimation through Markov State models

We present a multistep protocol, combining Monte Carlo and molecular dynamics simulations, for the estimation of absolute binding free energies, one of the most significant challenges in computer-aided drug design. The protocol is based on an initial short enhanced Monte Carlo simulation, followed by clustering of the ligand positions, which serve to identify the most relevant states of the unbinding process. From these states, extensive molecular dynamics simulations are run to estimate an equilibrium probability distribution obtained with Markov State Models, which is subsequently used to estimate the binding free energy. We tested the procedure on two different protein systems, the Plasminogen kringle domain 1 and Urokinase, each with multiple ligands, for an aggregated molecular dynamics length of 760 μs. Our results indicate that the initial sampling of the unbinding events largely facilitates the convergence of the subsequent molecular dynamics exploration. Moreover, the protocol is capable to properly rank the set of ligands examined, albeit with a significant computational cost for the, more realistic, Urokinase complexes. Overall, this work demonstrates the usefulness of combining enhanced sampling methods with regular simulation techniques as a way to obtain more reliable binding affinity estimates.This work has been funded by Spanish projects CTQ2016-79138-R and RTC-2017-6295-1.Peer ReviewedPostprint (author's final draft

Oxadiazoles in Medicinal Chemistry

Oxadiazoles are five-membered heteroaromatic rings containing two carbons, two nitrogens, and one oxygen atom, and they exist in different regioisomeric forms. Oxadiazoles are frequently occurring motifs in druglike molecules, and they are often used with the intention of being bioisosteric replacements for ester and amide functionalities. The current study presents a systematic comparison of 1,2,4- and 1,3,4-oxadiazole matched pairs in the AstraZeneca compound collection. In virtually all cases, the 1,3,4-oxadiazole isomer shows an order of magnitude lower lipophilicity (log <i>D</i>), as compared to its isomeric partner. Significant differences are also observed with respect to metabolic stability, hERG inhibition, and aqueous solubil ity, favoring the 1,3,4-oxadiazole isomers. The difference in profile between the 1,2,4 and 1,3,4 regioisomers can be rationalized by their intrinsically different charge distributions (e.g., dipole moments). To facilitate the use of these heteroaromatic rings, novel synthetic routes for ready access of a broad spectrum of 1,3,4-oxadiazoles, under mild conditions, are described

Oxadiazoles in Medicinal Chemistry

Oxadiazoles are five-membered heteroaromatic rings containing two carbons, two nitrogens, and one oxygen atom, and they exist in different regioisomeric forms. Oxadiazoles are frequently occurring motifs in druglike molecules, and they are often used with the intention of being bioisosteric replacements for ester and amide functionalities. The current study presents a systematic comparison of 1,2,4- and 1,3,4-oxadiazole matched pairs in the AstraZeneca compound collection. In virtually all cases, the 1,3,4-oxadiazole isomer shows an order of magnitude lower lipophilicity (log <i>D</i>), as compared to its isomeric partner. Significant differences are also observed with respect to metabolic stability, hERG inhibition, and aqueous solubil ity, favoring the 1,3,4-oxadiazole isomers. The difference in profile between the 1,2,4 and 1,3,4 regioisomers can be rationalized by their intrinsically different charge distributions (e.g., dipole moments). To facilitate the use of these heteroaromatic rings, novel synthetic routes for ready access of a broad spectrum of 1,3,4-oxadiazoles, under mild conditions, are described

Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design

Computer-aided drug design plays an important role in medicinal chemistry to obtain insights into molecular mechanisms and to prioritize design strategies. Although significant improvement has been made in structure based design, it still remains a key challenge to accurately model and predict induced fit mechanisms. Most of the current available techniques either do not provide sufficient protein conformational sampling or are too computationally demanding to fit an industrial setting. The current study presents a systematic and exhaustive investigation of predicting binding modes for a range of systems using PELE (Protein Energy Landscape Exploration), an efficient and fast protein–ligand sampling algorithm. The systems analyzed (cytochrome P, kinase, protease, and nuclear hormone receptor) exhibit different complexities of ligand induced fit mechanisms and protein dynamics. The results are compared with results from classical molecular dynamics simulations and (induced fit) docking. This study shows that ligand induced side chain rearrangements and smaller to medium backbone movements are captured well in PELE. Large secondary structure rearrangements, however, remain challenging for all employed techniques. Relevant binding modes (ligand heavy atom RMSD < 1.0 Å) can be obtained by the PELE method within a few hours of simulation, positioning PELE as a tool applicable for rapid drug design cycles

Exploring Binding Mechanisms in Nuclear Hormone Receptors by Monte Carlo and X-ray-derived Motions

In this study, we performed an extensive exploration of the ligand entry mechanism for members of the steroid nuclear hormone receptor family (androgen receptor, estrogen receptor α, glucocorticoid receptor, mineralocorticoid receptor, and progesterone receptor) and their endogenous ligands. The exploration revealed a shared entry path through the helix 3, 7, and 11 regions. Examination of the x-ray structures of the receptor-ligand complexes further showed two distinct folds of the helix 6–7 region, classified as “open” and “closed”, which could potentially affect ligand binding. To improve sampling of the helix 6–7 loop, we incorporated motion modes based on principal component analysis of existing crystal structures of the receptors and applied them to the protein-ligand sampling. A detailed comparison with the anisotropic network model (an elastic network model) highlights the importance of flexibility in the entrance region. While the binding (interaction) energy of individual simulations can be used to score different ligands, extensive sampling further allows us to predict absolute binding free energies and analyze reaction kinetics using Markov state models and Perron-cluster cluster analysis, respectively. The predicted relative binding free energies for three ligands binding to the progesterone receptor are in very good agreement with experimental results and the Perron-cluster cluster analysis highlighted the importance of a peripheral binding site. Our analysis revealed that the flexibility of the helix 3, 7, and 11 regions represents the most important factor for ligand binding. Furthermore, the hydrophobicity of the ligand influences the transition between the peripheral and the active binding site.This work has the support of the grant SEV-2011-00067 of Severo Ochoa Program, awarded by the Spanish Government.Peer Reviewe