Analyzing Kinase Similarity in Small Molecule and Protein Structural Space to Explore the Limits of Multi-Target Screening.

While selective inhibition is one of the key assets for a small molecule drug, many diseases can only be tackled by simultaneous inhibition of several proteins. An example where achieving selectivity is especially challenging are ligands targeting human kinases. This difficulty arises from the high structural conservation of the kinase ATP binding sites, the area targeted by most inhibitors. We investigated the possibility to identify novel small molecule ligands with pre-defined binding profiles for a series of kinase targets and anti-targets by in silico docking. The candidate ligands originating from these calculations were assayed to determine their experimental binding profiles. Compared to previous studies, the acquired hit rates were low in this specific setup, which aimed at not only selecting multi-target kinase ligands, but also designing out binding to anti-targets. Specifically, only a single profiled substance could be verified as a sub-micromolar, dual-specific EGFR/ErbB2 ligand that indeed avoided its selected anti-target BRAF. We subsequently re-analyzed our target choice and in silico strategy based on these findings, with a particular emphasis on the hit rates that can be expected from a given target combination. To that end, we supplemented the structure-based docking calculations with bioinformatic considerations of binding pocket sequence and structure similarity as well as ligand-centric comparisons of kinases. Taken together, our results provide a multi-faceted picture of how pocket space can determine the success of docking in multi-target drug discovery efforts.

The European Research Network on Signal Transduction (ERNEST): Toward a Multidimensional Holistic Understanding of G Protein-Coupled Receptor Signaling.

G protein-coupled receptors (GPCRs) are intensively studied due to their therapeutic potential as drug targets. Members of this large family of transmembrane receptor proteins mediate signal transduction in diverse cell types and play key roles in human physiology and health. In 2013 the research consortium GLISTEN (COST Action CM1207) was founded with the goal of harnessing the substantial growth in knowledge of GPCR structure and dynamics to push forward the development of molecular modulators of GPCR function. The success of GLISTEN, coupled with new findings and paradigm shifts in the field, led in 2019 to the creation of a related consortium called ERNEST (COST Action CA18133). ERNEST broadens focus to entire signaling cascades, based on emerging ideas of how complexity and specificity in signal transduction are not determined by receptor-ligand interactions alone. A holistic approach that unites the diverse data and perspectives of the research community into a single multidimensional map holds great promise for improved drug design and therapeutic targeting.

Guava (Psidium guajava) Fruit Extract Prepared by Supercritical CO2 Extraction Inhibits Intestinal Glucose Resorption in a Double-Blind, Randomized Clinical Study.

Inhibition of intestinal glucose resorption can serve as an effective strategy for the prevention of an increase in blood glucose levels. We have recently shown that various extracts prepared from guava (Psidium guajava) inhibit sodium-dependent glucose cotransporter 1 (SGLT1)- and glucose transporter 2 (GLUT2)-mediated glucose transport in vitro (Caco-2 cells) and in vivo (C57BL/6N mice). However, the efficacy in humans remains to be confirmed. For this purpose, we conducted a parallelized, randomized clinical study with young healthy adults. Thirty-one volunteers performed an oral glucose tolerance test (OGTT) in which the control group received a glucose solution and the intervention group received a glucose solution containing a guava fruit extract prepared by supercritical CO2 extraction. The exact same extract was used for our previous in vitro and in vivo experiments. Blood samples were collected prior to and up to two hours after glucose consumption to quantitate blood glucose and insulin levels. Our results show that, in comparison to the control group, consumption of guava fruit extract resulted in a significantly reduced increase in postprandial glucose response over the basal fasting plasma glucose levels after 30 min (Δ control 2.60 ± 1.09 mmol/L versus Δ intervention 1.96 ± 0.96 mmol/L; p = 0.039) and 90 min (Δ control 0.44 ± 0.74 mmol/L versus Δ intervention -0.18 ± 0.88 mmol/L; p = 0.023). In addition, we observed a slightly reduced, but non-significant insulin secretion (Δ control 353.82 ± 183.31 pmol/L versus Δ intervention 288.43 ± 126.19 pmol/L, p = 0.302). Interestingly, storage time and repeated freeze-thawing operations appeared to negatively influence the efficacy of the applied extract. Several analytical methods (HPLC-MS, GC-MS, and NMR) were applied to identify putative bioactive compounds in the CO2 extract used. We could assign several substances at relevant concentrations including kojic acid (0.33 mg/mL) and 5-hydroxymethylfurfural (2.76 mg/mL). Taken together, this clinical trial and previous in vitro and in vivo experiments confirm the efficacy of our guava fruit extract in inhibiting intestinal glucose resorption, possibly in combination with reduced insulin secretion. Based on these findings, the development of food supplements or functional foods containing this extract appears promising for patients with diabetes and for the prevention of insulin resistance. Trial registration: 415-E/2319/15-2018 (Ethics Commissions of Salzburg).

Structure-Based Virtual Screening for Dopamine D2 Receptor Ligands as Potential Antipsychotics.

Structure-based virtual screening using a D2 receptor homology model was performed to identify dopamine D2 receptor ligands as potential antipsychotics. From screening a library of 6.5 million compounds, 21 were selected and were subjected to experimental validation. From these 21 compounds tested, ten D2 ligands were identified (47.6% success rate, among them D2 receptor antagonists, as expected) that have additional affinity for other receptors tested, in particular 5-HT2A receptors. The affinity (Ki values) of the compounds ranged from 58 nm to about 24 µM. Similarity and fragment analysis indicated a significant degree of structural novelty among the identified compounds. We found one D2 receptor antagonist that did not have a protonatable nitrogen atom, which is a key structural element of the classical D2 pharmacophore model necessary for interaction with the conserved Asp(3.32) residue. This compound exhibited greater than 20-fold binding selectivity for the D2 receptor over the D3 receptor. We provide additional evidence that the amide hydrogen atom of this compound forms a hydrogen bond with Asp(3.32), as determined by tests of its derivatives that cannot maintain this interaction.

Docking screens: right for the right reasons?

Whereas docking screens have emerged as the most practical way to use protein structure for ligand discovery, an inconsistent track record raises questions about how well docking actually works. In its favor, a growing number of publications report the successful discovery of new ligands, often supported by experimental affinity data and controls for artifacts. Few reports, however, actually test the underlying structural hypotheses that docking makes. To be successful and not just lucky, prospective docking must not only rank a true ligand among the top scoring compounds, it must also correctly orient the ligand so the score it receives is biophysically sound. If the correct binding pose is not predicted, a skeptic might well infer that the discovery was serendipitous. Surveying over 15 years of the docking literature, we were surprised to discover how rarely sufficient evidence is presented to establish whether docking actually worked for the right reasons. The paucity of experimental tests of theoretically predicted poses undermines confidence in a technique that has otherwise become widely accepted. Of course, solving a crystal structure is not always possible, and even when it is, it can be a lot of work, and is not readily accessible to all groups. Even when a structure can be determined, investigators may prefer to gloss over an erroneous structural prediction to better focus on their discovery. Still, the absence of a direct test of theory by experiment is a loss for method developers seeking to understand and improve docking methods. We hope this review will motivate investigators to solve structures and compare them with their predictions whenever possible, to advance the field.