3D-e-Chem-VM: Structural Cheminformatics Research Infrastructure in a Freely Available Virtual Machine.

3D-e-Chem-VM is an open source, freely available Virtual Machine ( http://3d-e-chem.github.io/3D-e-Chem-VM/ ) that integrates cheminformatics and bioinformatics tools for the analysis of protein-ligand interaction data.

Data-driven medicinal chemistry in the era of big data.

Science, and the way we undertake research, is changing. The increasing rate of data generation across all scientific disciplines is providing incredible opportunities for data-driven research, with the potential to transform our current practices. The exploitation of so-called 'big data' will enable us to undertake research projects never previously possible but should also stimulate a re-evaluation of all our data practices.

Org 214007-0: a novel non-steroidal selective glucocorticoid receptor modulator with full anti-inflammatory properties and improved therapeutic index.

Glucocorticoids (GCs) such as prednisolone are potent immunosuppressive drugs but suffer from severe adverse effects, including the induction of insulin resistance. Therefore, development of so-called Selective Glucocorticoid Receptor Modulators (SGRM) is highly desirable. Here we describe a non-steroidal Glucocorticoid Receptor (GR)-selective compound (Org 214007-0) with a binding affinity to GR similar to that of prednisolone.

X-ray structures of progesterone receptor ligand binding domain in its agonist state reveal differing mechanisms for mixed profiles of 11β-substituted steroids.

We present here the x-ray structures of the progesterone receptor (PR) in complex with two mixed profile PR modulators whose functional activity results from two differing molecular mechanisms. The structure of Asoprisnil bound to the agonist state of PR demonstrates the contribution of the ligand to increasing stability of the agonist conformation of helix-12 via a specific hydrogen-bond network including Glu(723). This interaction is absent when the full antagonist, RU486, binds to PR.

Structural basis for agonism and antagonism for a set of chemically related progesterone receptor modulators.

The progesterone receptor is able to bind to a large number and variety of ligands that elicit a broad range of transcriptional responses ranging from full agonism to full antagonism and numerous mixed profiles inbetween. We describe here two new progesterone receptor ligand binding domain x-ray structures bound to compounds from a structurally related but functionally divergent series, which show different binding modes corresponding to their agonistic or antagonistic nature. In addition, we present a third progesterone receptor ligand binding domain dimer bound to an agonist in monomer A and an antagonist in monomer B, which display binding modes in agreement with the earlier observation that agonists and antagonists from this series adopt different binding modes.

A molecular informatics view on best practice in multi-parameter compound optimization.

The difference between biologically active molecules and drugs is that the latter balance an array of related and unrelated properties required for administration to patients. Inevitability, during optimization, some of these multiple factors will conflict. Although informatics has a crucial role in addressing the challenges of modern compound optimization, it is arguably still undervalued and underutilized.

Discovery and optimisation of a selective non-steroidal glucocorticoid receptor antagonist.

High-throughput screening of 3.87 million compounds delivered a novel series of non-steroidal GR antagonists. Subsequent rounds of optimisation allowed progression from a non-selective ligand with a poor ADMET profile to an orally bioavailable, selective, stable, glucocorticoid receptor antagonist.

Systematic structure-function analysis of androgen receptor Leu701 mutants explains the properties of the prostate cancer mutant L701H.

One mechanism of prostate tumors for escape from androgen ablation therapies is mutation of the androgen receptor (AR). We investigated the unique properties of the AR L701H mutant, which is strongly stimulated by cortisol, by a systematic structure-function analysis. Most amino acid substitutions at position 701 did not affect AR activation by 5alpha-dihydrotestosterone.

Computational design, synthesis, and evaluation of miniproteins as androgen receptor coactivator mimics.

Insertion of 3 to 4 mutations, based on in silico modelling, in a diverse set of natural miniproteins generates potent androgen receptor (AR) binders and a clear insight into the structure-activity relationship of such coactivator mimics concerning helix length.

Non-steroidal steroid receptor modulators.

The discovery and launch of non-steroidal ligands for estrogen receptors (ERs) and for androgen receptors (ARs) demonstrated the potential of these ligands as therapeutic agents. Based on these successes, substantial attention in the past ten years has been focused on identifying non-steroidal ligands for all of the classic steroid receptors. Non-steroidal ligands are currently in the discovery phase or in early clinical development for glucocorticoid, mineralocorticoid and progesterone receptors, and therefore must still provide evidence of their beneficial features over their steroidal counterparts.