Tina Ritschel

Current progress in Structure-Based Rational Drug Design marks a new mindset in drug discovery

The past decade has witnessed a paradigm shift in preclinical drug discovery with structure-based drug design (SBDD) making a comeback while high-throughput screening (HTS) methods have continued to generate disappointing results. There is a deficit of information between identified hits and the many criteria that must be fulfilled in parallel to convert them into preclinical candidates that have a real chance to become a drug. This gap can be bridged by investigating the interactions between the ligands and their receptors. Accurate calculations of the free energy of binding are still elusive; however progresses were made with respect to how one may deal with the versatile role of water. A corpus of knowledge combining X-ray structures, bioinformatics and molecular modeling techniques now allows drug designers to routinely produce receptor homology models of increasing quality. These models serve as a basis to establish and validate efficient rationales used to tailor and/or screen virtual libraries with enhanced chances of obtaining hits. Many case reports of successful SBDD show how synergy can be gained from the combined use of several techniques. The role of SBDD with respect to two different classes of widely investigated pharmaceutical targets: (a) protein kinases (PK) and (b) G-protein coupled receptors (GPCR) is discussed. Throughout these examples prototypical situations covering the current possibilities and limitations of SBDD are presented.

Statin-Induced Myopathy Is Associated with Mitochondrial Complex III Inhibition

Cholesterol-lowering statins effectively reduce the risk of major cardiovascular events. Myopathy is the most important adverse effect, but its underlying mechanism remains enigmatic. In C2C12 myoblasts, several statin lactones reduced respiratory capacity and appeared to be strong inhibitors of mitochondrial complex III (CIII) activity, up to 84% inhibition. The lactones were in general three times more potent inducers of cytotoxicity than their corresponding acid forms. The Qo binding site of CIII was identified as off-target of the statin lactones. These findings could be confirmed in muscle tissue of patients suffering from statin-induced myopathies, in which CIII enzyme activity was reduced by 18%. Respiratory inhibition in C2C12 myoblasts could be attenuated by convergent electron flow into CIII, restoring respiration up to 89% of control. In conclusion, CIII inhibition was identified as a potential off-target mechanism associated with statin-induced myopathies.

Pharmacophore fingerprint-based approach to binding site subpocket similarity and its application to bioisostere replacement

Bioisosteres have been defined as structurally different molecules or substructures that can form comparable intermolecular interactions, and therefore, fragments that bind to similar protein structures exhibit a degree of bioisosterism. We present KRIPO (Key Representation of Interaction in POckets): a new method for quantifying the similarities of binding site subpockets based on pharmacophore fingerprints. The binding site fingerprints have been optimized to improve their performance for both intra- and interprotein family comparisons. A range of attributes of the fingerprints was considered in the optimization, including the placement of pharmacophore features, whether or not the fingerprints are fuzzified, and the resolution and complexity of the pharmacophore fingerprints (2-, 3-, and 4-point fingerprints). Fuzzy 3-point pharmacophore fingerprints were found to represent the optimal balance between computational resource requirements and the identification of potential replacements. The complete PDB was converted into a database comprising almost 300,000 optimized fingerprints of local binding sites together with their associated ligand fragments. The value of the approach is demonstrated by application to two crystal structures from the Protein Data Bank: (1) a MAP kinase P38 structure in complex with a pyridinylimidazole inhibitor (1A9U) and (2) a complex of thrombin with melagatran (1K22). Potentially valuable bioisosteric replacements for all subpockets of the two studied protein are identified.

Molecular interaction fingerprint approaches for GPCR drug discovery

Protein-ligand interaction fingerprints (IFPs) are binary 1D representations of the 3D structure of protein-ligand complexes encoding the presence or absence of specific interactions between the binding pocket amino acids and the ligand. Various implementations of IFPs have been developed and successfully applied for post-processing molecular docking results for G Protein-Coupled Receptor (GPCR) ligand binding mode prediction and virtual ligand screening. Novel interaction fingerprint methods enable structural chemogenomics and polypharmacology predictions by complementing the increasing amount of GPCR structural data. Machine learning methods are increasingly used to derive relationships between bioactivity data and fingerprint descriptors of chemical and structural information of binding sites, ligands, and protein-ligand interactions. Factors that influence the application of IFPs include structure preparation, binding site definition, fingerprint similarity assessment, and data processing and these factors pose challenges as well possibilities to optimize interaction fingerprint methods for GPCR drug discovery.

3D-e-Chem-VM: Structural Cheminformatics Research Infrastructure in a Freely Available Virtual Machine

3D-e-Chem-VM is an open source, freely available Virtual Machine (http://3d-e-chem.github.io/3D-e-Chem-VM/) that integrates cheminformatics and bioinformatics tools for the analysis of protein–ligand interaction data. 3D-e-Chem-VM consists of software libraries, and database and workflow tools that can analyze and combine small molecule and protein structural information in a graphical programming environment. New chemical and biological data analytics tools and workflows have been developed for the efficient exploitation of structural and pharmacological protein–ligand interaction data from proteomewide databases (e.g., ChEMBLdb and PDB), as well as customized information systems focused on, e.g., G protein-coupled receptors (GPCRdb) and protein kinases (KLIFS). The integrated structural cheminformatics research infrastructure compiled in the 3D-e-Chem-VM enables the design of new approaches in virtual ligand screening (Chemdb4VS), ligand-based metabolism prediction (SyGMa), and structure-based protein binding site comparison and bioisosteric replacement for ligand design (KRIPOdb).

Mitochondrial ADP/ATP exchange inhibition: a novel off-target mechanism underlying ibipinabant-induced myotoxicity.

Cannabinoid receptor 1 (CB1R) antagonists appear to be promising drugs for the treatment of obesity, however, serious side effects have hampered their clinical application. Rimonabant, the first in class CB1R antagonist, was withdrawn from the market because of psychiatric side effects. This has led to the search for more peripherally restricted CB1R antagonists, one of which is ibipinabant. However, this 3,4-diarylpyrazoline derivative showed muscle toxicity in a pre-clinical dog study with mitochondrial dysfunction. Here, we studied the molecular mechanism by which ibipinabant induces mitochondrial toxicity. We observed a strong cytotoxic potency of ibipinabant in C2C12 myoblasts. Functional characterization of mitochondria revealed increased cellular reactive oxygen species generation and a decreased ATP production capacity, without effects on the catalytic activities of mitochondrial enzyme complexes I–V or the complex specific-driven oxygen consumption. Using in silico off-target prediction modelling, combined with in vitro validation in isolated mitochondria and mitoplasts, we identified adenine nucleotide translocase (ANT)-dependent mitochondrial ADP/ATP exchange as a novel molecular mechanism underlying ibipinabant-induced toxicity. Minor structural modification of ibipinabant could abolish ANT inhibition leading to a decreased cytotoxic potency, as observed with the ibipinabant derivative CB23. Our results will be instrumental in the development of new types of safer CB1R antagonists.

Snooker Structure-Based Pharmacophore Model Explains Differences in Agonist and Blocker Binding to Bitter Receptor hTAS2R39

The human bitter taste receptor hTAS2R39 can be activated by many dietary (iso)flavonoids. Furthermore, hTAS2R39 activity can be blocked by 6-methoxyflavanones, 4’-fluoro-6-methoxyflavanone in particular. A structure-based pharmacophore model of the hTAS2R39 binding pocket was built using Snooker software, which has been used successfully before for drug design of GPCRs of the rhodopsin subfamily. For the validation of the model, two sets of compounds, both of which contained actives and inactives, were used: (i) an (iso)flavonoid-dedicated set, and (ii) a more generic, structurally diverse set. Agonists were characterized by their linear binding geometry and the fact that they bound deeply in the hTAS2R39 pocket, mapping the hydrogen donor feature based on T5.45 and N3.36, analogues of which have been proposed to play a key role in activation of GPCRs. Blockers lack hydrogen-bond donors enabling contact to the receptor. Furthermore, they had a crooked geometry, which could sterically hinder movement of the TM domains upon receptor activation. Our results reveal characteristics of hTAS2R39 agonist and bitter blocker binding, which might facilitate the development of blockers suitable to counter the bitterness of dietary hTAS2R39 agonists in food applications.

Steering Siglec-Sialic Acid Interactions on Living Cells using Bioorthogonal Chemistry

Sialic acid sugars that terminate cell-surface glycans form the ligands for the sialic acid binding immunoglobulin-like lectin (Siglec) family, which are immunomodulatory receptors expressed by immune cells. Interactions between sialic acid and Siglecs regulate the immune system, and aberrations contribute to pathologies like autoimmunity and cancer. Sialic acid/Siglec interactions between living cells are difficult to study owing to a lack of specific tools. Here, we report a glycoengineering approach to remodel the sialic acids of living cells and their binding to Siglecs. Using bioorthogonal chemistry, a library of cells with more than sixty different sialic acid modifications was generated that showed dramatically increased binding toward the different Siglec family members. Rational design reduced cross-reactivity and led to the discovery of three selective Siglec-5/14 ligands. Furthermore, glycoengineered cells carrying sialic acid ligands for Siglec-3 dampened the activation of Siglec-3+ monocytic cells through the NF-κB and IRF pathways.

Finding the right approach to big data-driven medicinal chemistry

Data generation in pharmaceutical research has been industrialized without our capacity to manage, disseminate, analyze and base decisions upon these data keeping pace. Like most scientific disciplines, medicinal chemistry is becoming increasingly data intensive and dependent on our capacity to manage and exploit growing data resources. Appropriate data-intensive strategies are required to ensure most value can be gained from all new scientific endeavors by using information technology to improve experimental design, data management, data analysis and communication. Fundamental is the need for drugdiscovery organizations to enable its drug hunters [1] to make decisions informed by the content of their internally generated data and their integration with external data [2]. Addressing these requirements is commonly referred to as the challenge of big data [3], referring to the analysis of datasets too large, unstructured, diverse or rapidly changing to be analyzed conventionally [2]. While synonymous with predictive (data) analytics, big data do not refer to any specific technology or solution, but rather a new scientific environment in which we all work. Disregarded by some as hype, there can be little doubt that our increasing data resources provide rich opportunity, but also numerous challenges such as:

KRIPO – a structure-based pharmacophores approach explains polypharmacological effects

“The most fruitful basis for the discovery of a new drug is to start with an old one” is a citation from Sir James Black’s Nobel laureate (1988). The background of this statement lies in the fact that most drugs are able to bind to multiple protein targets in the human body, this is known as polypharmacology. This behaviour can lead to unwanted side effects, and innovative research to avoid such adverse properties is of great importance. Paradoxically, polypharmacology can also be used to create new therapeutic approaches, as the protein to which a drug binds causing a side effect in one case, can be the main target for another treatment. Many cases report about the problems and opportunities of polypharmacology.