Exploring the effect of PARP-1 flexibility in docking studies

Poly(ADP-ribose)polymerase-1 (PARP-1) is an enzyme belonging to the ADP-ribosyltransferase family. A large body of works has validated PARP-1 as an attractive drug target for different therapeutic areas, including cancers and ischemia. Accordingly, sampling the conformational space of the enzyme is pivotal to understand its functions and improve structure-based drug discovery approaches. In the first part of this study we apply replica exchange molecular dynamic (REMD) simulations to sample the conformational space of the catalytic domain of PARP-1 in the ligand-bound and unbound forms. In the second part, we assess how and to what extend the emerging enzyme flexibility affects the performance of docking experiments of a library of PARP-1 inhibitors. This study pinpoints a putative key role of conformational shifts of Leu324, Tyr325 and Lys242 in opening an additional binding site pocket that affects the binding of ligands to the catalytic cleft of PARP-1. Furthermore, it highlights the improvement of the enrichment factor of active ligands obtained in docking experiments when using conformations generated with REMD simulations of ligand-bound PARP-1.

Chemoisosterism in the proteome

The concept of chemoisosterism of protein environments is introduced as the complementary property to bioisosterism of chemical fragments. In the same way that two chemical fragments are considered bioisosteric if they can bind to the same protein environment, two protein environments will be considered chemoisosteric if they can interact with the same chemical fragment. The basis for the identification of chemoisosteric relationships among protein environments was the increasing amount of crystal structures available currently for protein-ligand complexes. It is shown that one can recover the right location and orientation of chemical fragments constituting the native ligand in a nuclear receptor structure by using only chemoisosteric environments present in enzyme structures. Examples of the potential applicability of chemoisosterism in fragment-based drug discovery are provided.

On the origins of drug polypharmacology

The ability of many drugs, unintended most often, to interact with multiple proteins is commonly referred to as polypharmacology. Could this be a reminiscent chemical signature of early protein evolution?

Identification of pim kinases as novel targets for PJ34 with confounding effects in PARP biology

Small molecules are widely used in chemical biology without complete knowledge of their target profile, at risk of deriving conclusions that ignore potential confounding effects from unknown off-target interactions. The prediction and further experimental confirmation of novel affinities for PJ34 on Pim1 (IC(50) = 3.7 μM) and Pim2 (IC(50) = 16 μM) serine/threonine kinases, together with their involvement in many of the processes relevant to PARP biology, questions the appropriateness of using PJ34 as a chemical tool to probe the biological role of PARP1 and PARP2 at the high micromolar concentrations applied in most studies.

The EU-ADR Web Platform: delivering advanced pharmacovigilance tools

PURPOSE

Pharmacovigilance methods have advanced greatly during the last decades, making post-market drug assessment an essential drug evaluation component. These methods mainly rely on the use of spontaneous reporting systems and health information databases to collect expertise from huge amounts of real-world reports. The EU-ADR Web Platform was built to further facilitate accessing, monitoring and exploring these data, enabling an in-depth analysis of adverse drug reactions risks.

METHODS

The EU-ADR Web Platform exploits the wealth of data collected within a large-scale European initiative, the EU-ADR project. Millions of electronic health records, provided by national health agencies, are mined for specific drug events, which are correlated with literature, protein and pathway data, resulting in a rich drug-event dataset. Next, advanced distributed computing methods are tailored to coordinate the execution of data-mining and statistical analysis tasks. This permits obtaining a ranked drug-event list, removing spurious entries and highlighting relationships with high risk potential.

RESULTS

The EU-ADR Web Platform is an open workspace for the integrated analysis of pharmacovigilance datasets. Using this software, researchers can access a variety of tools provided by distinct partners in a single centralized environment. Besides performing standalone drug-event assessments, they can also control the pipeline for an improved batch analysis of custom datasets. Drug-event pairs can be substantiated and statistically analysed within the platform's innovative working environment.

CONCLUSIONS

A pioneering workspace that helps in explaining the biological path of adverse drug reactions was developed within the EU-ADR project consortium. This tool, targeted at the pharmacovigilance community, is available online at https://bioinformatics.ua.pt/euadr/.

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.

Drug repurposing: far beyond new targets for old drugs

Repurposing drugs requires finding novel therapeutic indications compared to the ones for which they were already approved. This is an increasingly utilized strategy for finding novel medicines, one that capitalizes on previous investments while derisking clinical activities. This approach is of interest primarily because we continue to face significant gaps in the drug-target interactions matrix and to accumulate safety and efficacy data during clinical studies. Collecting and making publicly available as much data as possible on the target profile of drugs offer opportunities for drug repurposing, but may limit the commercial applications by patent applications. Certain clinical applications may be more feasible for repurposing than others because of marked differences in side effect tolerance. Other factors that ought to be considered when assessing drug repurposing opportunities include relevance to the disease in question and the intellectual property landscape. These activities go far beyond the identification of new targets for old drugs.

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.

Myxobacteria: natural pharmaceutical factories

Myxobacteria are amongst the top producers of natural products. The diversity and unique structural properties of their secondary metabolites is what make these social microbes highly attractive for drug discovery. Screening of products derived from these bacteria has revealed a puzzling amount of hits against infectious and non-infectious human diseases. Preying mainly on other bacteria and fungi, why would these ancient hunters manufacture compounds beneficial for us? The answer may be the targeting of shared processes and structural features conserved throughout evolution.

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.

Automatic filtering and substantiation of drug safety signals

Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions.

Adverse drug reactions (ADRs) constitute a major cause of morbidity and mortality worldwide. Due to the relevance of ADRs for both public health and pharmaceutical industry, it is important to develop efficient ways to monitor ADRs in the population. In addition, it is also essential to comprehend why a drug produces an adverse effect. To unravel the molecular mechanisms of ADRs, it is necessary to consider the ADR in the context of current biomedical knowledge that might explain it. Nowadays there are plenty of information sources that can be exploited in order to accomplish this goal. Nevertheless, the fragmentation of information and, more importantly, the diverse knowledge domains that need to be traversed, pose challenges to the task of exploring the molecular mechanisms of ADRs. We present a novel computational framework to aid in the collection and exploration of evidences that support the causal inference of ADRs detected by mining clinical records. This framework was implemented as publicly available tools integrating state-of-the-art bioinformatics methods for the analysis of drugs, targets, biological processes and clinical events. The availability of such tools for in silico experiments will facilitate research on the mechanisms that underlie ADR, contributing to the development of safer drugs.

Linking pharmacology to clinical reports: cyclobenzaprine and its possible association with serotonin syndrome

The link between cyclobenzaprine (Flexeril) administration and serotonin syndrome (SS) is subject to debate. Establishing such a connection is difficult because of the limited number of case reports available and the almost complete ignorance of its preclinical pharmacology. In this context, evidence is provided here that cyclobenzaprine blocks the serotonin and norepinephrine transporters and binds to another set of five serotonin receptors. SS should be considered when indicative signs occur in the context of cyclobenzaprine use.

Multi-targeted activity of maslinic acid as an antimalarial natural compound

Most drugs against malaria that are available or under development target a single process of the parasite infective cycle, favouring the appearance of resistant mutants which are easily spread in areas under chemotherapeutic treatments. Maslinic acid (MA) is a low toxic natural pentacyclic triterpene for which a wide variety of biological and therapeutic activities have been reported. Previous work revealed that Plasmodium falciparum erythrocytic cultures were inhibited by MA, which was able to hinder the maturation from ring to schizont stage and, as a consequence, prevent the release of merozoites and the subsequent invasion. We show here that MA effectively inhibits the proteolytic processing of the merozoite surface protein complex, probably by inhibition of PfSUB1. In addition, MA was also found to inhibit metalloproteases of the M16 family by a non-chelating mechanism, suggesting the possible hindrance of plasmodial metalloproteases belonging to that family, such as falcilysin and apicoplast peptide-processing proteases. Finally, in silico target screening was used to search for other potential binding targets that may have remained undetected. Among the targets identified, the method recovered two for which experimental activity could be confirmed, and suggested several putative new targets to which MA could have affinity. One of these unreported targets, phospholipase A2, was shown to be partially inhibited by MA. These results suggest that MA may behave as a multi-targeted drug against the intra-erythrocytic cycle of Plasmodium, providing a new tool to investigate the synergistic effect of inhibiting several unrelated processes with a single compound, a new concept in antimalarial research.

MeDALL (Mechanisms of the Development of ALLergy): an integrated approach from phenotypes to systems medicine

The origin of the epidemic of IgE-associated (allergic) diseases is unclear. MeDALL (Mechanisms of the Development of ALLergy), an FP7 European Union project (No. 264357), aims to generate novel knowledge on the mechanisms of initiation of allergy and to propose early diagnosis, prevention, and targets for therapy. A novel phenotype definition and an integrative translational approach are needed to understand how a network of molecular and environmental factors can lead to complex allergic diseases. A novel, stepwise, large-scale, and integrative approach will be led by a network of complementary experts in allergy, epidemiology, allergen biochemistry, immunology, molecular biology, epigenetics, functional genomics, bioinformatics, computational and systems biology. The following steps are proposed: (i) Identification of 'classical' and 'novel' phenotypes in existing birth cohorts; (ii) Building discovery of the relevant mechanisms in IgE-associated allergic diseases in existing longitudinal birth cohorts and Karelian children; (iii) Validation and redefinition of classical and novel phenotypes of IgE-associated allergic diseases; and (iv) Translational integration of systems biology outcomes into health care, including societal aspects. MeDALL will lead to: (i) A better understanding of allergic phenotypes, thus expanding current knowledge of the genomic and environmental determinants of allergic diseases in an integrative way; (ii) Novel diagnostic tools for the early diagnosis of allergy, targets for the development of novel treatment modalities, and prevention of allergic diseases; (iii) Improving the health of European citizens as well as increasing the competitiveness and boosting the innovative capacity of Europe, while addressing global health issues and ethical issues.

Cross-pharmacology analysis of G protein-coupled receptors

The degree of applicability of chemogenomic approaches to protein families depends on the accuracy and completeness of pharmacological data and the corresponding level of pharmacological similarity observed among their protein members. The recent public domain availability of pharmacological data for thousands of small molecules on 204 G protein-coupled receptors (GPCRs) provides a firm basis for an in-depth cross-pharmacology analysis of this superfamily. The number of protein targets included in the cross-pharmacology profile of the different GPCRs changes significantly upon varying the ligand similarity and binding affinity criteria. However, with the exception of muscarinic receptors, aminergic GPCRs distinguish themselves from the rest of the members in the family by their remarkably high levels of pharmacological similarity among them. Clusters of non-GPCR targets related by cross-pharmacology with particular GPCRs are identified and the implications for unwanted side-effects, as well as for repurposing opportunities, discussed.

Ligand-based approaches to in silico pharmacology

The development of computational methods that can estimate the various pharmacodynamic and pharmacokinetic parameters that characterise the interaction of drugs with biological systems has been a highly pursued objective over the last 50 years. Among all, methods based on ligand information have emerged as simple, yet highly efficient, approaches to in silico pharmacology. With the recent impact on the identification of new targets for known drugs, they are again the focus of attention in chemical biology and drug discovery.