Wolfgang Guba

VolSurf: a new tool for the pharmacokinetic optimization of lead compounds.

A method for the modeling and prediction of pharmacokinetic properties based on computed molecular interaction fields and multivariate statistics has been investigated in different experimental datasets. The program VolSurf was used to correlate 3D molecular structures with physico-chemical and pharmacokinetic properties. In membrane partitioning, VolSurf produced a two-component model explaining 94% of the total variation with a predictive q(2) of 0.90. This result was achieved without conformational sampling and without any quantum-chemical calculation. For the prediction of blood-brain barrier penetration the VolSurf model was able to predict the BBB profile for most of the drugs in the external prediction set. In Caco-2 and MDCK permeation experiments, VolSurf was used with success to establish statistical models and to predict the behaviour of new compounds. The method thus appears as a valuable new property filter in virtual screening and as a novel tool in optimizing the pharmacokinetic profile of pharmaceutically relevant compounds.

β-Secretase (BACE1) Inhibitors with High in Vivo Efficacy Suitable for Clinical Evaluation in Alzheimer’s Disease

An extensive fluorine scan of 1,3-oxazines revealed the power of fluorine(s) to lower the pKa and thereby dramatically change the pharmacological profile of this class of BACE1 inhibitors. The CF3 substituted oxazine 89, a potent and highly brain penetrant BACE1 inhibitor, was able to reduce significantly CSF Aβ40 and 42 in rats at oral doses as low as 1 mg/kg. The effect was long lasting, showing a significant reduction of Aβ40 and 42 even after 24 h. In contrast to 89, compound 1b lacking the CF3 group was virtually inactive in vivo.

Torsion Angle Preferences in Druglike Chemical Space: A Comprehensive Guide

Crystal structure databases offer ample opportunities to derive small molecule conformation preferences, but the derived knowledge is not systematically applied in drug discovery research. We address this gap by a comprehensive and extendable expert system enabling quick assessment of the probability of a given conformation to occur. It is based on a hierarchical system of torsion patterns that cover a large part of druglike chemical space. Each torsion pattern has associated frequency histograms generated from CSD and PDB data and, derived from the histograms, traffic-light rules for frequently observed, rare, and highly unlikely torsion ranges. Structures imported into the corresponding software are annotated according to these rules. We present the concept behind the tree of torsion patterns, the design of an intuitive user interface for the management and usage of the torsion library, and we illustrate how the system helps analyze and understand conformation properties of substructures widely used in medicinal chemistry.

Focused library design in GPCR projects on the example of 5-HT2c agonists: Comparison of structure-based virtual screening with ligand-based search methods

The aim of this study was to investigate the usefulness of structure‐based virtual screening (VS) for focused library design in G protein‐coupled receptors (GPCR) projects on the example of 5‐HT2c agonists. We compared the performance of structure‐based VS against two different homology models using FRED for docking and ScreenScore, FlexX, and PMF for rescoring with the results of 12 ligand‐based similarity searches using four different query compounds and three different similarity metrics (Daylight, FTree, Phacir). The result of the similarity search showed much variation, from an enrichment factor up to 3.2 to worse than random, whereas the structure‐based VS gave a more stable result with a constant enrichment factor around 2. Additionally, actives retrieved by the structure‐based approach were more diverse than the actives among the top scorers of the similarity searches. Based on these results, we suggest basing a focused library design for a GPCR project on a combination of a ligand‐based similarity search and structure‐based docking. Proteins 2005.

A Real-World Perspective on Molecular Design.

We present a series of small molecule drug discovery case studies where computational methods were prospectively employed to impact Roche research projects, with the aim of highlighting those methods that provide real added value. Our brief accounts encompass a broad range of methods and techniques applied to a variety of enzymes and receptors. Most of these are based on judicious application of knowledge about molecular conformations and interactions: filling of lipophilic pockets to gain affinity or selectivity, addition of polar substituents, scaffold hopping, transfer of SAR, conformation analysis, and molecular overlays. A case study of sequence-driven focused screening is presented to illustrate how appropriate preprocessing of information enables effective exploitation of prior knowledge. We conclude that qualitative statements enabling chemists to focus on promising regions of chemical space are often more impactful than quantitative prediction.

Metabotropic Glutamate Receptor 5 Negative Allosteric Modulators: Discovery of 2-Chloro-4-[1-(4-fluorophenyl)-2,5-dimethyl-1H-imidazol-4-ylethynyl]pyridine (Basimglurant, RO4917523), a Promising Novel Medicine for Psychiatric Diseases

Negative allosteric modulators (NAMs) of metabotropic glutamate receptor 5 (mGlu5) have potential for the treatment of psychiatric diseases including depression, fragile X syndrome (FXS), anxiety, obsessive-compulsive disorders, and levodopa induced dyskinesia in Parkinsons disease. Herein we report the optimization of a weakly active screening hit 1 to the potent and selective compounds chloro-4-[1-(4-fluorophenyl)-2,5-dimethyl-1H-imidazol-4-ylethynyl]pyridine (basimglurant, 2) and 2-chloro-4-((2,5-dimethyl-1-(4-(trifluoromethoxy)phenyl)-1H-imidazol-4-yl)ethynyl)pyridine (CTEP, 3). Compound 2 is active in a broad range of anxiety tests reaching the same efficacy but at a 10- to 100-fold lower dose compared to diazepam and is characterized by favorable DMPK properties in rat and monkey as well as an excellent preclinical safety profile and is currently in phase II clinical studies for the treatment of depression and fragile X syndrome. Analogue 3 is the first reported mGlu5 NAM with a long half-life in rodents and is therefore an ideal tool compound for chronic studies in mice and rats.

Benzodioxoles: Novel Cannabinoid-1 Receptor Inverse Agonists for the Treatment of Obesity

The application of the evolutionary fragment-based de novo design tool TOPology Assigning System (TOPAS), starting from a known CB1R (CB-1 receptor) ligand, followed by further refinement principles, including pharmacophore compliance, chemical tractability, and drug likeness, allowed the identification of benzodioxoles as a novel CB1R inverse agonist series. Extensive multidimensional optimization was rewarded by the identification of promising lead compounds, showing in vivo activity. These compounds reversed the CP-55940-induced hypothermia in Naval Medical Research Institute (NMRI) mice and reduced body-weight gain, as well as fat mass, in diet-induced obese Sprague-Dawley rats. Herein, we disclose the tools and strategies that were employed for rapid hit identification, synthesis and generation of structure-activity relationships, ultimately leading to the identification of (+)-[( R)-2-(2,4-dichloride-phenyl)-6-fluoro-2-(4-fluoro-phenyl)-benzo[1,3]dioxol-5-yl]-morpholin-4-yl-methanone ( R)-14g . Biochemical, pharmacokinetic, and pharmacodynamic characteristics of ( R)-14g are discussed.

BACE1 inhibitors: a head group scan on a series of amides.

A series of amides bearing a variety of amidine head groups was investigated as BACE1 inhibitors with respect to inhibitory activity in a BACE1 enzyme as well as a cell-based assay. Determination of their basicity as well as their properties as substrates of P-glycoprotein revealed that a 2-amino-1,3-oxazine head group would be a suitable starting point for further development of brain penetrating compounds for potential Alzheimers disease treatment.

Molecular Field-Derived Descriptors for the Multivariate Modeling of Pharmacokinetic Data

The optimization of pharmacokinetic properties is still one of the greatest challenges in lead optimization, and for the most part it is based on trial and error. As pharmacokinetics is closely linked with physicochemical properties, experimental design and quantitative structure-property modeling are key factors to systematically explore physicochemical property space and to establish stable, predictive models for lead optimization. However, experimental measurements of relevant parameters are often time-consuming, difficult and expensive. Furthermore, in vitro/in vivo approaches require the synthesis of compounds and cannot be used for the priorization of synthesis targets.

De novo design by pharmacophore-based searches in fragment spaces

De novo ligand design supports the search for novel molecular scaffolds in medicinal chemistry projects. This search can either be based on structural information of the targeted active site (structure-based approach) or on similarity to known binders (ligand-based approach). In the absence of structural information on the target, pharmacophores provide a way to find topologically novel scaffolds. Fragment spaces have proven to be a valuable source for molecular structures in de novo design that are both diverse and synthetically accessible. They also offer a simple way to formulate custom chemical spaces. We have implemented a new method which stochastically constructs new molecules from fragment spaces under consideration of a three dimensional pharmacophore. The program has been tested on several published pharmacophores and is shown to be able to reproduce scaffold hops from the literature, which resulted in new chemical entities.