Andreas Evers

Comparison of Structure- and Ligand-Based Virtual Screening Protocols Considering Hit List Complementarity and Enrichment Factors

Structure‐ and ligand‐based virtual‐screening methods (docking, 2D‐ and 3D‐similarity searching) were analysed for their effectiveness in virtual screening against four different targets: angiotensin‐converting enzyme (ACE), cyclooxygenase 2 (COX‐2), thrombin and human immunodeficiency virus 1 (HIV‐1) protease. The relative performance of the tools was compared by examining their ability to recognise known active compounds from a set of actives and nonactives. Furthermore, we investigated whether the application of different virtual‐screening methods in parallel provides complementary or redundant hit lists. Docking was performed with GOLD, Glide, FlexX and Surflex. The obtained docking poses were rescored by using nine different scoring functions in addition to the scoring functions implemented as objective functions in the docking algorithms. Ligand‐based virtual screening was done with ROCS (3D‐similarity searching), Feature Trees and Scitegic Functional Fingerprints (2D‐similarity searching). The results show that structure‐ and ligand‐based virtual‐screening methods provide comparable enrichments in detecting active compounds. Interestingly, the hit lists that are obtained from different virtual‐screening methods are generally highly complementary. These results suggest that a parallel application of different structure‐ and ligand‐based virtual‐screening methods increases the chance of identifying more (and more diverse) active compounds from a virtual‐screening campaign.

Sequence-derived three-dimensional pharmacophore models for G-protein-coupled receptors and their application in virtual screening.

G-protein-coupled receptors (GPCRs) comprise a large protein family of significant past and current interest of pharmaceutical research. X-ray crystallography and molecular modeling combined with site-directed mutagenesis studies suggest that most family A GPCRs share a small-molecule binding site located in the outer part of the seven-transmembrane (7TM) bundle. Here we describe an automated method to derive sequence-derived three-dimensional (3D) pharmacophore models capturing the key elements for addressing this binding site by a small-molecule ligand. We have generated structure-based pharmacophore models from 10 homology models and 3 X-ray structures of receptor-ligand complexes. These 13 pharmacophores have been dissected into 35 different single-feature pharmacophore elements, each associated with a sequence motif or chemoprint, describing its molecular interaction partner(s) in the receptor. Subsequently, the protein sequences of 270 GPCRs have been searched for the presence of chemoprints and the appropriate single-feature pharmacophores have been assembled into three- to seven-feature 3D-pharmacophore models for each human family A GPCR. These models can be applied for virtual screening and for the design of subfamily directed libraries. A case study demonstrates the successful application of this approach for the identification of potent agonists for the complement component 3a receptor 1 (C3AR1) by virtual screening.

The Potential of P1 Site Alterations in Peptidomimetic Protease Inhibitors as Suggested by Virtual Screening and Explored by the Use of CC-Coupling Reagents†

A synthetic concept is presented that allows the construction of peptide isostere libraries through polymer‐supported C‐acylation reactions. A phosphorane linker reagent is used as a carbanion equivalent; by employing MSNT as a coupling reagent, the C‐acylation can be conducted without racemization. Diastereoselective reduction was effected with L‐selectride. The reagent linker allows the preparation of a norstatine library with full variation of the isosteric positions including the P1 side chain that addresses the protease S1 pocket. Therefore, the concept was employed to investigate the P1 site specificity of peptide isostere inhibitors systematically. The S1 pocket of several aspartic proteases including plasmepsin II and cathepsin D was modeled and docked with ≈500 amino acid side chains. Inspired by this virtual screen, a P1 site mutation library was designed, synthesized, and screened against three aspartic proteases (plasmepsin II, HIV protease, and cathepsin D). The potency of norstatine inhibitors was found to depend strongly on the P1 substituent. Large, hydrophobic residues such as biphenyl, 4‐bromophenyl, and 4‐nitrophenyl enhanced the inhibitory activity (IC50) by up to 70‐fold against plasmepsin II. In addition, P1 variation introduced significant selectivity, as up to 9‐fold greater activity was found against plasmepsin II relative to human cathepsin D. The active P1 site residues did not fit into the crystal structure; however, molecular dynamics simulation suggested a possible alternative binding mode.

Identification of High-Affinity P2Y12 Antagonists Based on a Phenylpyrazole Glutamic Acid Piperazine Backbone

A series of novel, highly potent P2Y₁₂ antagonists as inhibitors of platelet aggregation based on a phenylpyrazole glutamic acid piperazine backbone is described. Exploration of the structural requirements of the substituents by probing the structure-activity relationship along this backbone led to the discovery of the N-acetyl-(S)-proline cyclobutyl amide moiety as a highly privileged motif. Combining the most favorable substituents led to remarkably potent P2Y₁₂ antagonists displaying not only low nanomolar binding affinity to the P2Y₁₂ receptor but also a low nanomolar inhibition of platelet aggregation in the human platelet rich plasma assay with IC₅₀ values below 50 nM. Using a homology and a three-dimensional quantitative structure-activity relationship model, a binding hypothesis elucidating the impact of several structural features was developed.

Design of Novel Exendin-Based Dual Glucagon-like Peptide 1 (GLP-1)/Glucagon Receptor Agonists

Dual activation of the glucagon-like peptide 1 (GLP-1) and glucagon receptor has the potential to lead to a novel therapy principle for the treatment of diabesity. Here, we report a series of novel peptides with dual activity on these receptors that were discovered by rational design. On the basis of sequence analysis and structure-based design, structural elements of glucagon were engineered into the selective GLP-1 receptor agonist exendin-4, resulting in hybrid peptides with potent dual GLP-1/glucagon receptor activity. Detailed structure-activity relationship data are shown. Further modifications with unnatural and modified amino acids resulted in novel metabolically stable peptides that demonstrated a significant dose-dependent decrease in blood glucose in chronic studies in diabetic db/db mice and reduced body weight in diet-induced obese (DIO) mice. Structural analysis by NMR spectroscopy confirmed that the peptides maintain an exendin-4-like structure with its characteristic tryptophan-cage fold motif that is responsible for favorable chemical and physical stability.

Novel Small Molecule Inhibitors of Activated Thrombin Activatable Fibrinolysis Inhibitor (TAFIa) from Natural Product Anabaenopeptin

Anabaenopeptins isolated from cyanobacteria were identified as inhibitors of carboxypeptidase TAFIa. Cocrystal structures of these macrocyclic natural product inhibitors in a modified porcine carboxypeptidase B revealed their binding mode and provided the basis for the rational design of small molecule inhibitors with a previously unknown central urea motif. Optimization based on these design concepts allowed for a rapid evaluation of the SAR and delivered potent small molecule inhibitors of TAFIa with a promising overall profile.

CROSS: An Efficient Workflow for Reaction-Driven Rescaffolding and Side-Chain Optimization Using Robust Chemical Reactions and Available Reagents

A novel procedure (CROSS: Computational Rescaffolding and Optimization using Synthetic Schemes) for in silico rescaffolding and side-chain optimization is reported with explicit consideration of the route of synthesis and availability of compatible chemical reagents. We have defined a set of retrosynthetic disconnections representing robust reactions, amenable for combinatorial chemistry. This rule set is used to generate virtual fragment databases from available reagents. Each reactive center is annotated with its compatibility with regard to the chemical reactions. The rule set is then applied to a new molecule to obtain separate query subunits for rescaffolding by 3D similarity searching in specific reagent-derived fragment databases. Thus, only fragments compatible with the chemistry and shape of the corresponding query moiety are investigated further. The identified fragment hits directly indicate (1) available chemical reagents that can replace the query moiety in the starting molecule and (2) the route for the synthesis of the proposed molecules.

MARS: Computing Three-Dimensional Alignments for Multiple Ligands Using Pairwise Similarities

The three-dimensional (3D) superimposition of molecules of one biological target reflecting their relative bioactive orientation is key for several ligand-based drug design studies (e.g., QSAR studies, pharmacophore modeling). However, with the lack of sufficient ligand-protein complex structures, an experimental alignment is difficult or often impossible to obtain. Several computational 3D alignment tools have been developed by academic or commercial groups to address this challenge. Here, we present a new approach, MARS (Multiple Alignments by ROCS-based Similarity), that is based on the pairwise alignment of all molecules within the data set using the tool ROCS (Rapid Overlay of Chemical Structures). Each pairwise alignment is scored, and the results are captured in a score matrix. The ideal superimposition of the compounds in the set is then identified by the analysis of the score matrix building stepwise a superimposition of all molecules. The algorithm exploits similarities among all molecules in the data set to compute an optimal 3D alignment. This alignment tool presented here can be used for several applications, including pharmacophore model generation, 3D QSAR modeling, 3D clustering, identification of structural outliers, and addition of compounds to an already existing alignment. Case studies are shown, validating the 3D alignments for six different data sets.

Phototoxicity – from molecular descriptors to classification models

Potential photoactivation of certain pharmaceuticals, cosmetic ingredients and natural products by sunlight (e.g., phenothiazines, arylsulfonamides, or coumarins) has to be considered early on in development in order to avoid serious adverse effects (for example phototoxic or photoallergic reactions). Current clinical trial registration guidelines (FDA May 2003 [1], EMEA Dec. 2002 [2]) recommend photosafety testing of molecules if they exhibit strong absorption bands between 290-700nm and if they are significantly partitioned in human skin or eyes. The UV absorption coefficients and the tissue partitioning of a compound are considered as important factors for phototoxic effects. However, the rationalization and prediction of phototoxicity by (quantitative) structure-property relationships ((Q)SPR) offers a valuable strategy to reduce experimental testing if an appropriate precision level of the underlying model is guaranteed. A diverse data set of known phototoxicants and non-phototoxicants including various molecular chemotypes (90 % of them are pharmaceuticals) was compiled. After geometry optimization the maximum absorption wavelength of each compound was calculated by semi-empirical methods followed by subsequent computation of molecular descriptors. Our insilico analysis (e.g., PLS and recursive partitioning) of quantum chemical as well as classical molecular descriptors (e.g., LUMO, HOMO/LUMO gap, electron affinity, ionization energy, molecular fragments, physicochemical descriptors such as logD, pKa and logPeff) has led to predictive photosafety classifiers. Model validation was performed with a proprietary external test set of an in vitro photosafety assay (3T3 neutral red assay). Our photosafety models are currently applied in a prospective manner in the prioritization, classification and labeling of newly designed molecules.

Modulation of Hexadecyl-LPA-Mediated Activation of Mast Cells and Microglia by a Chemical Probe for LPA5.

Mast cells and microglia play a critical role in innate immunity and inflammation and can be activated by a wide range of endogenous and exogenous stimuli. Lysophosphatidic acid (LPA) has recently been reported to activate mast cells and microglia. Using the human mast cell line HMC‐1 and the mouse microglia cell line BV‐2, we show that LPA‐mediated activation can be prevented by blockade of the LPA receptor 5 (LPA5) in both cell lines. The identification of new LPA5‐specific antagonists as tool compounds to probe and modulate the LPA5/LPA axis in relevant in vitro and in vivo assays should contribute to better understanding of the underlying role of LPAs in the development and progression of (neuro‐) inflammatory diseases.