In silico directed chemical probing of the adenosine receptor family

Closing the Gap Between Therapeutic Use and Mode of Action in Remedial Herbs

The ancient tradition of taking parts of a plant or preparing plant extracts for treating certain discomforts and maladies has long been lacking a scientific rationale to support its preparation and still widespread use in several parts of the world. In an attempt to address this challenge, we collected and integrated data connecting metabolites, plants, diseases, and proteins. A mechanistic hypothesis is generated when a metabolite is known to be present in a given plant, that plant is known to be used to treat a certain disease, that disease is known to be linked to the function of a given protein, and that protein is finally known or predicted to interact with the original metabolite. The construction of plant–protein networks from mutually connected metabolites and diseases facilitated the identification of plausible mechanisms of action for plants being used to treat analgesia, hypercholesterolemia, diarrhea, catarrh, and cough. Additional concrete examples using both experimentally known and computationally predicted, and subsequently experimentally confirmed, metabolite–protein interactions to close the connection circle between metabolites, plants, diseases, and proteins offered further proof of concept for the validity and scope of the approach to generate mode of action hypotheses for some of the therapeutic uses of remedial herbs.

2-Aryladenine derivatives as a potent scaffold for A1, A3 and dual A1/A3 adenosine receptor antagonists: Synthesis and structure-activity relationships

From a collection containing more than 1500 academic compounds, in silico screening identified a hit for the human A₁ adenosine receptor containing a new purine scaffold. To study the structure activity relationships of this new chemical series for adenosine receptors, a library of 24 purines was synthesized and tested in radioligand binding assays at human A₁, A_2A, A_2B and A₃ adenosine receptor subtypes. Fourteen molecules showed potent antagonism at A₁, A₃ or dual A₁/A₃ adenosine receptors. This purine scaffold is an important source for novel biochemical tools and/or therapeutic drugs.

Comparative Study of Carborane- and Phenyl-Modified Adenosine Derivatives as Ligands for the A2A and A3 Adenosine Receptors Based on a Rigid in Silico Docking and Radioligand Replacement Assay

Adenosine receptors are involved in many physiological processes and pathological conditions and are therefore attractive therapeutic targets. To identify new types of effective ligands for these receptors, a library of adenosine derivatives bearing a boron cluster or phenyl group in the same position was designed. The ligands were screened in silico to determine their calculated affinities for the A2A and A3 adenosine receptors. An virtual screening protocol based on the PatchDock web server was developed. In the first screening phase, the effects of the functional group (organic or inorganic modulator) on the adenosine ligand affinity for the receptors were determined. Then, the lead compounds were identified for each receptor in the second virtual screening phase. Two pairs of the most promising ligands, compounds 3 and 4, and two ligands with lower affinity scores (compounds 11 and 12, one with a boron cluster and one with a phenyl group) were synthesized and tested in a radioligand replacement assay for affinity to the A2A and A3 receptors. A reasonable correlation of in silico and biological assay results was observed. In addition, the effects of a phenyl group and boron cluster, which is new adenosine modifiers, on the adenosine ligand binding were compared.

Distant polypharmacology among MLP chemical probes

Small molecules are essential tool compounds to probe the role of proteins in biology and advance toward more efficient therapeutics. However, they are used without a complete knowledge of their selectivity across the entire proteome, at risk of confounding their effects due to unknown off-target interactions. Current state-of-the-art computational approaches to predicting the affinity profile of small molecules offer a means to anticipate potential nonobvious selectivity liabilities of chemical probes. The application of in silico target profiling on the full set of chemical probes from the NIH Molecular Libraries Program (MLP) resulted in the identification of biologically relevant in vitro affinities for proteins distantly related to the primary targets of ML006, ML123, ML141, and ML204, helping to lower the risk of their further use in chemical biology.

Design of a general-purpose European compound screening library for EU-OPENSCREEN

This work describes a collaborative effort to define and apply a protocol for the rational selection of a general-purpose screening library, to be used by the screening platforms affiliated with the EU-OPENSCREEN initiative. It is designed as a standard source of compounds for primary screening against novel biological targets, at the request of research partners. Given the general nature of the potential applications of this compound collection, the focus of the selection strategy lies on ensuring chemical stability, absence of reactive compounds, screening-compliant physicochemical properties, loose compliance to drug-likeness criteria (as drug design is a major, but not exclusive application), and maximal diversity/coverage of chemical space, aimed at providing hits for a wide spectrum of drugable targets. Finally, practical availability/cost issues cannot be avoided. The main goal of this publication is to inform potential future users of this library about its conception, sources, and characteristics. The outline of the selection procedure, notably of the filtering rules designed by a large committee of European medicinal chemists and chemoinformaticians, may be of general methodological interest for the screening/medicinal chemistry community. The selection task of 200K molecules out of a pre-filtered set of 1.4M candidates was shared by five independent European research groups, each picking a subset of 40K compounds according to their own in-house methodology and expertise. An in-depth analysis of chemical space coverage of the library serves not only to characterize the collection, but also to compare the various chemoinformatics-driven selection procedures of maximal diversity sets. Compound selections contributed by various participating groups were mapped onto general-purpose self-organizing maps (SOMs) built on the basis of marketed drugs and bioactive reference molecules. In this way, the occupancy of chemical space by the EU-OPENSCREEN library could be directly compared with distributions of known bioactives of various classes. This mapping highlights the relevance of the selection and shows how the consensus reached by merging the five different 40K selections contributes to achieve this relevance. The approach also allows one to readily identify subsets of target- or target-class-oriented compounds from the EU-OPENSCREEN library to suit the needs of the diverse range of potential users. The final EU-OPENSCREEN library, assembled by merging five independent selections of 40K compounds from various expert groups, represents an excellent example of a Europe-wide collaborative effort toward the common objective of building best-in-class European open screening platforms.

Predictive in silico off-target profiling in drug discovery

Drug action can be rationalized as interaction of a molecule with proteins in a regulatory network of targets from a specific biological system. Both drug and side effects are often governed by interaction of the drug molecule with many, often unrelated, targets. Accordingly, arrays of protein–ligand interaction data from numerous in vitro profiling assays today provide growing evidence of polypharmacological drug interactions, even for marketed drugs. In vitro off-target profiling has therefore become an important tool in early drug discovery to learn about potential off-target liabilities, which are sometimes beneficial, but more often safety relevant. The rapidly developing field of in silico profiling approaches is complementing in vitro profiling. These approaches capitalize from large amounts of biochemical data from multiple sources to be exploited for optimizing undesirable side effects in pharmaceutical research. Therefore, current in silico profiling models are nowadays perceived as valuable tools in drug discovery, and promise a platform to support optimally informed decisions.

Prediction of the P. falciparum target space relevant to malaria drug discovery

Malaria is still one of the most devastating infectious diseases, affecting hundreds of millions of patients worldwide. Even though there are several established drugs in clinical use for malaria treatment, there is an urgent need for new drugs acting through novel mechanisms of action due to the rapid development of resistance. Resistance emerges when the parasite manages to mutate the sequence of the drug targets to the extent that the protein can still perform its function in the parasite but can no longer be inhibited by the drug, which then becomes almost ineffective. The design of a new generation of malaria drugs targeting multiple essential proteins would make it more difficult for the parasite to develop full resistance without lethally disrupting some of its vital functions. The challenge is then to identify which set of Plasmodium falciparum proteins, among the millions of possible combinations, can be targeted at the same time by a given chemotype. To do that, we predicted first the targets of the close to 20,000 antimalarial hits identified recently in three independent phenotypic screening campaigns. All targets predicted were then projected onto the genome of P. falciparum using orthologous relationships. A total of 226 P. falciparum proteins were predicted to be hit by at least one compound, of which 39 were found to be significantly enriched by the presence and degree of affinity of phenotypically active compounds. The analysis of the chemically compatible target combinations containing at least one of those 39 targets led to the identification of a priority set of 64 multi-target profiles that can set the ground for a new generation of more robust malaria drugs.

Target deconvolution techniques in modern phenotypic profiling

The past decade has seen rapid growth in the use of diverse compound libraries in classical phenotypic screens to identify modulators of a given process. The subsequent process of identifying the molecular targets of active hits, also called 'target deconvolution', is an essential step for understanding compound mechanism of action and for using the identified hits as tools for further dissection of a given biological process. Recent advances in 'omics' technologies, coupled with in silico approaches and the reduced cost of whole genome sequencing, have greatly improved the workflow of target deconvolution and have contributed to a renaissance of 'modern' phenotypic profiling. In this review, we will outline how both new and old techniques are being used in the difficult process of target identification and validation as well as discuss some of the ongoing challenges remaining for phenotypic screening.

Identification of small molecule inhibitors of amyloid β-induced neuronal apoptosis acting through the imidazoline I(2) receptor

Aberrant activation of signaling pathways plays a pivotal role in central nervous system disorders, such as Alzheimer's disease (AD). Using a combination of virtual screening and experimental testing, novel small molecule inhibitors of tPA-mediated extracellular signal-regulated kinase (Erk)1/2 activation were identified that provide higher levels of neuroprotection from Aβ-induced apoptosis than Memantine, the most recently FDA-approved drug for AD treatment. Subsequent target deconvolution efforts revealed that they all share low micromolar affinity for the imidazoline I(2) receptor, while being devoid of any significant affinity to a list of AD-relevant targets, including the N-methyl-d-aspartate receptor (NMDAR), acetylcholinesterase (AChE), and monoamine oxidase B (MAO-B). Targeting the imidazoline I(2) receptor emerges as a new mechanism of action to inhibit tPA-induced signaling in neurons for the treatment of AD and other neurodegenerative diseases.

New chromene scaffolds for adenosine A(2A) receptors: synthesis, pharmacology and structure-activity relationships

In silico screening of a collection of 1584 academic compounds identified a small molecule hit for the human adenosine A(2A) receptor (pK(i) = 6.2) containing a novel chromene scaffold (3a). To explore the structure-activity relationships of this new chemical series for adenosine receptors, a focused library of 43 2H-chromene-3-carboxamide derivatives was synthesized and tested in radioligand binding assays at human adenosine A(1), A(2A), A(2B) and A(3) receptors. The series was found to be enriched with bioactive compounds for adenosine receptors, with 14 molecules showing submicromolar affinity (pK(i) ≥ 6.0) for at least one adenosine receptor subtype. These results provide evidence that the chromene scaffold, a core structure present in natural products from a wide variety of plants, vegetables, and fruits, constitutes a valuable source for novel therapeutic agents.

A chemocentric approach to the identification of cancer targets

A novel chemocentric approach to identifying cancer-relevant targets is introduced. Starting with a large chemical collection, the strategy uses the list of small molecule hits arising from a differential cytotoxicity screening on tumor HCT116 and normal MRC-5 cell lines to identify proteins associated with cancer emerging from a differential virtual target profiling of the most selective compounds detected in both cell lines. It is shown that this smart combination of differential in vitro and in silico screenings (DIVISS) is capable of detecting a list of proteins that are already well accepted cancer drug targets, while complementing it with additional proteins that, targeted selectively or in combination with others, could lead to synergistic benefits for cancer therapeutics. The complete list of 115 proteins identified as being hit uniquely by compounds showing selective antiproliferative effects for tumor cell lines is provided.

Combination of biological screening in a cellular model of viral latency and virtual screening identifies novel compounds that reactivate HIV-1

Although highly active antiretroviral therapy (HAART) has converted HIV into a chronic disease, a reservoir of HIV latently infected resting T cells prevents the eradication of the virus from patients. To achieve eradication, HAART must be combined with drugs that reactivate the dormant viruses. We examined this problem in an established model of HIV postintegration latency by screening a library of small molecules. Initially, we identified eight molecules that reactivated latent HIV. Using them as templates, additional hits were identified by means of similarity-based virtual screening. One of those hits, 8-methoxy-6-methylquinolin-4-ol (MMQO), proved to be useful to reactivate HIV-1 in different cellular models, especially in combination with other known reactivating agents, without causing T-cell activation and with lower toxicity than that of the initial hits. Interestingly, we have established that MMQO produces Jun N-terminal protein kinase (JNK) activation and enhances the T-cell receptor (TCR)/CD3 stimulation of HIV-1 reactivation from latency but inhibits CD3-induced interleukin-2 (IL-2) and tumor necrosis factor alpha (TNF-α) gene transcription. Moreover, MMQO prevents TCR-induced cell cycle progression and proliferation in primary T cells. The present study documents that the combination of biological screening in a cellular model of viral latency with virtual screening is useful for the identification of novel agents able to reactivate HIV-1. Moreover, we set the bases for a hypothetical therapy to reactivate latent HIV by combining MMQO with physiological or pharmacological TCR/CD3 stimulation.

In Silico Receptorome Screening of Antipsychotic Drugs

The recent availability of a complete interaction matrix between 13 antipsychotic drugs and 34 protein targets (Roth et al. Nat. Rev. Drug Discov. 2004, 3, 353-359) allows to assess the performance of computational methods on their ability to anticipate the entire affinity profile of drugs across multiple targets. The analyses reveal that our current implementations, based on the similarity of drugs against a reference set of small molecules for which pharmacological data is available in the public domain, are able to predict 65 % of the 442 affinities within 1-log unit error, with a level of precision above 92 %. In spite of the relatively small scale of this validation study, the results are indicative that in silico receptorome screening of drugs offers an efficient and cost-effective complement to in vitro screening.