Stefan Senger

Scientific competency questions as the basis for semantically enriched open pharmacological space development

Molecular information systems play an important part in modern data-driven drug discovery. They do not only support decision making but also enable new discoveries via association and inference. In this review, we outline the scientific requirements identified by the Innovative Medicines Initiative (IMI) Open PHACTS consortium for the design of an open pharmacological space (OPS) information system. The focus of this work is the integration of compound-target-pathway-disease/phenotype data for public and industrial drug discovery research. Typical scientific competency questions provided by the consortium members will be analyzed based on the underlying data concepts and associations needed to answer the questions. Publicly available data sources used to target these questions as well as the need for and potential of semantic web-based technology will be presented.

Discovery and structure-activity relationships of a series of pyroglutamic acid amide antagonists of the P2X7 receptor.

A computational lead-hopping exercise identified compound 4 as a structurally distinct P2X(7) receptor antagonist. Structure-activity relationships (SAR) of a series of pyroglutamic acid amide analogues of 4 were investigated and compound 31 was identified as a potent P2X(7) antagonist with excellent in vivo activity in animal models of pain, and a profile suitable for progression to clinical studies.

The Application of the Open Pharmacological Concepts Triple Store (Open PHACTS) to Support Drug Discovery Research

Integration of open access, curated, high-quality information from multiple disciplines in the Life and Biomedical Sciences provides a holistic understanding of the domain. Additionally, the effective linking of diverse data sources can unearth hidden relationships and guide potential research strategies. However, given the lack of consistency between descriptors and identifiers used in different resources and the absence of a simple mechanism to link them, gathering and combining relevant, comprehensive information from diverse databases remains a challenge. The Open Pharmacological Concepts Triple Store (Open PHACTS) is an Innovative Medicines Initiative project that uses semantic web technology approaches to enable scientists to easily access and process data from multiple sources to solve real-world drug discovery problems. The project draws together sources of publicly-available pharmacological, physicochemical and biomolecular data, represents it in a stable infrastructure and provides well-defined information exploration and retrieval methods. Here, we highlight the utility of this platform in conjunction with workflow tools to solve pharmacological research questions that require interoperability between target, compound, and pathway data. Use cases presented herein cover 1) the comprehensive identification of chemical matter for a dopamine receptor drug discovery program 2) the identification of compounds active against all targets in the Epidermal growth factor receptor (ErbB) signaling pathway that have a relevance to disease and 3) the evaluation of established targets in the Vitamin D metabolism pathway to aid novel Vitamin D analogue design. The example workflows presented illustrate how the Open PHACTS Discovery Platform can be used to exploit existing knowledge and generate new hypotheses in the process of drug discovery.

Synthesis and structure-activity relationships of a series of (1H-pyrazol-4-yl)acetamide antagonists of the P2X7 receptor

High-throughput screening identified compound 1 as a potent P2X(7) receptor antagonist suitable for lead optimisation. Structure-activity relationships (SAR) of a series of (1H-pyrazol-4-yl)acetamides were investigated and compound 32 was identified as a potent P2X(7) antagonist with enhanced potency and favourable physicochemical and pharmacokinetic properties.

Using Tversky similarity searches for core hopping: finding the needles in the haystack.

The combination of Daylight fingerprints and the Tversky coefficient is a powerful method for performing core hopping, that is, scaffold (or lead) hopping where the main structural difference between the query and bioactive target molecule is located in the central core of the molecular structure. However, a major disadvantage of this approach is the fact that a large number of false positives (in the context of core hopping) are retrieved. The tool we have developed and which is described here can be used to postprocess the hits from Daylight Tversky similarity searches by fragmenting the molecules and subsequently annotating them in a way that assists the users in removing false positives and enables them to better focus on molecules of interest. To validate our approach, we have selected four biological targets for which scaffold hopping examples have been reported. We present results from searches in databases containing published activity data and the subsequent analysis of the hits aimed at establishing the potential of our approach.

Structure-activity relationships and in vivo activity of (1H-pyrazol-4-yl)acetamide antagonists of the P2X7 receptor

Structure-activity relationships (SAR) of analogues of lead compound 1 were investigated and compound 16 was selected for further study in animal models of pain. Compound 16 was shown to be a potent antihyperalgesic agent in both the rat acute complete Freunds adjuvant (CFA) model of inflammatory pain [Iadarola, M. J.; Douglass, J.; Civelli, O.; Naranjo, J. R. rain Res.1988, 455, 205] and the knee joint model of chronic inflammatory pain [Wilson, A. W.; Medhurst, S. J.; Dixon, C. I.; Bontoft, N. C.; Winyard, L. A.; Brackenborough, K. T.; De Alba, J.; Clarke, C. J.; Gunthorpe, M. J.; Hicks, G. A.; Bountra, C.; McQueen, D. S.; Chessell, I. P. Eur. J. Pain2006, 10, 537].

The discovery of potent and long-acting oral factor Xa inhibitors with tetrahydroisoquinoline and benzazepine P4 motifs.

The discovery and evaluation of potent and long-acting oral sulfonamidopyrrolidin-2-one factor Xa inhibitors with tetrahydroisoquinoline and benzazepine P4 motifs are described. Unexpected selectivity issues versus tissue plasminogen activator in the former series were addressed in the later, delivering a robust candidate for progression towards clinical studies.

Incorporating Commercial and Private Data into an Open Linked Data Platform for Drug Discovery

The Open PHACTS Discovery Platform aims to provide an integrated information space to advance pharmacological research in the area of drug discovery. Effective drug discovery requires comprehensive data coverage, i.e. integrating all available sources of pharmacology data. While many relevant data sources are available on the linked open data cloud, their content needs to be combined with that of commercial datasets and the licensing of these commercial datasets respected when providing access to the data. Additionally, pharmaceutical companies have built up their own extensive private data collections that they require to be included in their pharmacological dataspace. In this paper we discuss the challenges of incorporating private and commercial data into a linked dataspace: focusing on the modelling of these datasets and their interlinking. We also present the graph-based access control mechanism that ensures commercial and private datasets are only available to authorized users.

Compression of molecular interaction fields using wavelet thumbnails: application to molecular alignment.

Molecular interaction fields provide a useful description of ligand binding propensity and have found widespread use in computer-aided drug design, for example, to characterize protein binding sites and in small molecular applications, such as three-dimensional quantitative structure-activity relationships, physicochemical property prediction, and virtual screening. However, the grids on which the field data are stored are typically very large, consisting of thousands of data points, which make them cumbersome to store and manipulate. The wavelet transform is a commonly used data compression technique, for example, in signal processing and image compression. Here we use the wavelet transform to encode molecular interaction fields as wavelet thumbnails, which represent the original grid data in significantly reduced volumes. We describe a method for aligning wavelet thumbnails based on extracting extrema from the thumbnails and subsequently use them for virtual screening. We demonstrate that wavelet thumbnails provide an effective method of capturing the three-dimensional information encoded in a molecular interaction field.

Structure and Property Based Design of Factor Xa Inhibitors: Pyrrolidin-2-Ones with Aminoindane and Phenylpyrrolidine P4 Motifs.

The rational design, syntheses and evaluation of potent sulfonamidopyrrolidin-2-one-based factor Xa inhibitors incorporating aminoindane and phenylpyrrolidine P4 motifs are described. These series delivered highly potent anticoagulant compounds with excellent oral pharmacokinetic profiles; however, significant time dependant P450 inhibition was an issue for the aminoindane series, but this was not observed with the phenylpyrrolidine motif, which produced candidate quality molecules with potential for once-daily oral dosing in humans.