Peter Kolb

Structure-based tailoring of compound libraries for high-throughput screening: Discovery of novel EphB4 kinase inhibitors

High‐throughput docking is a computational tool frequently used to discover small‐molecule inhibitors of enzymes or receptors of known three‐dimensional structure. Because of the large number of molecules in chemical libraries, automatic procedures to prune multimillion compound collections are useful for high‐throughput docking and necessary for in vitro screening. Here, we propose an anchor‐based library tailoring approach (termed ALTA) to focus a chemical library by docking and prioritizing molecular fragments according to their binding energy which includes continuum electrostatics solvation. In principle, ALTA does not require prior knowledge of known inhibitors, but receptor‐based pharmacophore information (hydrogen bonds with the hinge region) is additionally used here to identify molecules with optimal anchor fragments for the ATP‐binding site of the EphB4 receptor tyrosine kinase. The 21,418 molecules of the focused library (from an initial collection of about 730,000) are docked into EphB4 and ranked by force‐field‐based energy including electrostatic solvation. Among the 43 compounds tested in vitro, eight molecules originating from two different anchors show low‐micromolar activity in a fluorescence‐based enzymatic assay. Four of them are active in a cell‐based assay and are potential anti‐angiogenic compounds. Proteins 2008.

Automated docking of highly flexible ligands by genetic algorithms: A critical assessment

An improved version of the fragment‐based flexible ligand docking approach SEED–FFLD is tested on inhibitors of human immunodeficiency virus type 1 protease, human α‐thrombin and the estrogen receptor β. The docking results indicate that it is possible to correctly reproduce the binding mode of inhibitors with more than ten rotatable bonds if the strain in their covalent geometry upon binding is not large. A high degree of convergence towards a unique binding mode in multiple runs of the genetic algorithm is proposed as a necessary condition for successful docking.

Discovery of kinase inhibitors by high-throughput docking and scoring based on a transferable linear interaction energy model.

The linear interaction energy method with continuum electrostatics (LIECE) is evaluated in depth on five kinases. The two multiplicative coefficients for the van der Waals energy and electrostatic free energy are shown to be transferable among different kinases. Moreover, good enrichment factors are obtained for a library of 40375 diverse compounds seeded with 73 known inhibitors of CDK2. Therefore, a general two-parameter LIECE model for kinases is derived by combining large data sets of inhibitors of CDK2, Lck, and p38. This two-parameter model is cross-validated on two kinases not used for fitting; it shows an average error of about 1.5 kcal/mol for the prediction of absolute binding affinity of 37 and 128 known inhibitors of EphB4 and EGFR, respectively. High-throughput docking and ranking by two-parameter LIECE models are shown to be able to identify novel low-micromolar EphB4 and CDK2 inhibitors of low-molecular weight (< or =355 g/mol).

A double‐headed cathepsin B inhibitor devoid of warhead

Most synthetic inhibitors of peptidases have been targeted to the active site for inhibiting catalysis through reversible competition with the substrate or by covalent modification of catalytic groups. Cathepsin B is unique among the cysteine peptidase for the presence of a flexible segment, known as the occluding loop, which can block the primed subsites of the substrate binding cleft. With the occluding loop in the open conformation cathepsin B acts as an endopeptidase, and it acts as an exopeptidase when the loop is closed. We have targeted the occluding loop of human cathepsin B at its surface, outside the catalytic center, using a high‐throughput docking procedure. The aim was to identify inhibitors that would interact with the occluding loop thereby modulating enzyme activity without the help of chemical warheads against catalytic residues. From a large library of compounds, the in silico approach identified [2‐[2‐(2,4‐dioxo‐1,3‐thiazolidin‐3‐yl)ethylamino]‐2‐oxoethyl] 2‐(furan‐2‐carbonylamino) acetate, which fulfills the working hypothesis. This molecule possesses two distinct binding moieties and behaves as a reversible, double‐headed competitive inhibitor of cathepsin B by excluding synthetic and protein substrates from the active center. The kinetic mechanism of inhibition suggests that the occluding loop is stabilized in its closed conformation, mainly by hydrogen bonds with the inhibitor, thus decreasing endoproteolytic activity of the enzyme. Furthermore, the dioxothiazolidine head of the compound sterically hinders binding of the C‐terminal residue of substrates resulting in inhibition of the exopeptidase activity of cathepsin B in a physiopathologically relevant pH range.

Identifying Modulators of CXC Receptors 3 and 4 with Tailored Selectivity Using Multi-Target Docking

The G protein-coupled receptors of the C-X-C subfamily form a group among the chemokine receptors whose endogenous ligands are peptides with a common Cys-X-Cys motif. The CXC chemokine receptors 3 and 4 (CXCR3, CXCR4), which are investigated in this study, are linked to severe diseases such as cancer, multiple sclerosis, and HIV infections. Of particular interest, this receptor pair potentially forms a target for a polypharmacological drug treatment. Considering known ligands from public databases, such dual binders have not been identified yet. We therefore applied large-scale docking to the structure of CXCR4 and a homology model of CXCR3 with the goal to predict such dual binders, as well as compounds selective for either one of the receptors. Using signaling and biochemical assays, we showed that more than 50% of these predictions were correct in each category, yielding ligands with excellent binding efficiencies. These results highlight that docking is a suitable tool for the identification of ligands with tailored binding profiles to GPCRs, even when using homology models. More importantly, we present novel CXCR3-CXCR4 dual modulators that might pave the road to understanding the mechanisms of polypharmacological inhibition of these receptors.

SCUBIDOO: A Large yet Screenable and Easily Searchable Database of Computationally Created Chemical Compounds Optimized toward High Likelihood of Synthetic Tractability.

De novo drug design is widely assisted by computational approaches that enable the generation of a tremendous amount of new virtual molecules within a short time frame. While the novelty of the computationally generated compounds can easily be assessed, such approaches often neglect the synthetic feasibility of the molecules, thus creating a potential hurdle that can be a barrier to further investigation. Therefore, we have developed SCUBIDOO, a freely accessible database concept that currently holds 21 million virtual products originating from a small library of building blocks and a collection of robust organic reactions. This large data set was reduced to three representative and computationally tractable samples denoted as S, M, and L, containing 9994, 99,977, and 999,794 products, respectively. These small sets are useful as starting points for ligand identification and optimization projects. The generated products come with synthesis instructions and alerts of possible side reactions, and we show that they exhibit drug-like properties while still extending into unexplored quadrants of chemical space, thus suggesting novelty. We show multiple examples that demonstrate how SCUBIDOO can facilitate the search around initial hits. This database might be a useful idea generator for early ligand discovery projects since it allows a focus on those molecules that are likely to be synthetically feasible and can therefore be studied further. Together with its modular building block construction principle, this database is also suitable for structure-activity relationship studies or fragment-growing strategies.

Three stories on Eph kinase inhibitors: From in silico discovery to in vivo validation.

Several selective and potent EphB4 inhibitors have been discovered, optimized and biophysically characterized by our groups over the past years. On the outset of these discoveries high throughput docking techniques were applied. Herein, we review the optimization campaigns started from three of these hits (Xan-A1, Pyr-A1 and Qui-A1) with emphasis on their in depth in vitro and in vivo characterization, together with previously unpublished angiogenesis and fluorescence based assays.

Drugging specific conformational states of GPCRs: challenges and opportunities for computational chemistry.

Current advances in structural biology for membrane proteins support the existence of multiple Gprotein-coupled receptor (GPCR) conformations. These conformations can be associated to particular receptor states with definite coupling and signaling capacities. Drugging such receptor states represents an opportunity to discover a new generation of GPCR drugs with unprecedented specificity. However, exploiting recently available structural information to develop these drugs is still challenging. In this context, computational structure-based approaches can inform such drug development. In this review, we examine the potential of these approaches and the challenges they will need to overcome to guide the rational discovery of drugs targeting specific GPCR states.

Binding-Site Compatible Fragment Growing Applied to the Design of β2-Adrenergic Receptor Ligands

Fragment-based drug discovery is intimately linked to fragment extension approaches that can be accelerated using software for de novo design. Although computers allow for the facile generation of millions of suggestions, synthetic feasibility is however often neglected. In this study we computationally extended, chemically synthesized, and experimentally assayed new ligands for the β2-adrenergic receptor (β2AR) by growing fragment-sized ligands. In order to address the synthetic tractability issue, our in silico workflow aims at derivatized products based on robust organic reactions. The study started from the predicted binding modes of five fragments. We suggested a total of eight diverse extensions that were easily synthesized, and further assays showed that four products had an improved affinity (up to 40-fold) compared to their respective initial fragment. The described workflow, which we call growing via merging and for which the key tools are available online, can improve early fragment-based drug discovery projects, making it a useful creative tool for medicinal chemists during structure-activity relationship (SAR) studies.

The allosteric site regulates the voltage sensitivity of muscarinic receptors

Muscarinic receptors (M-Rs) for acetylcholine (ACh) belong to the class A of G protein-coupled receptors. M-Rs are activated by orthosteric agonists that bind to a specific site buried in the M-R transmembrane helix bundle. In the active conformation, receptor function can be modulated either by allosteric modulators, which bind to the extracellular receptor surface or by the membrane potential via an unknown mechanism. Here, we compared the modulation of M1-Rs and M3-Rs induced by changes in voltage to their allosteric modulation by chemical compounds. We quantified changes in receptor signaling in single HEK 293 cells with a FRET biosensor for the Gq protein cycle. In the presence of ACh, M1-R signaling was potentiated by voltage, similarly to positive allosteric modulation by benzyl quinolone carboxylic acid. Conversely, signaling of M3-R was attenuated by voltage or the negative allosteric modulator gallamine. Because the orthosteric site is highly conserved among M-Rs, but allosteric sites vary, we constructed allosteric site M3/M1-R chimeras and analyzed their voltage dependencies. Exchanging the entire allosteric sites eliminated the voltage sensitivity of ACh responses for both receptors, but did not affect their modulation by allosteric compounds. Furthermore, a point mutation in M3-Rs caused functional uncoupling of the allosteric and orthosteric sites and abolished voltage dependence. Molecular dynamics simulations of the receptor variants indicated a subtype-specific crosstalk between both sites, involving the conserved tyrosine lid structure of the orthosteric site. This molecular crosstalk leads to receptor subtype-specific voltage effects.