Drug repositioning: playing dirty to kill pain

Finding new analgesics: Computational pharmacology faces drug discovery challenges

Despite the worldwide prevalence and huge burden of pain, pain is an undertreated phenomenon. Currently used analgesics have several limitations regarding their efficacy and safety. The discovery of analgesics possessing a novel mechanism of action has faced multiple challenges, including a limited understanding of biological processes underpinning pain and analgesia and poor animal-to-human translation. Computational pharmacology is currently employed to face these challenges. In this review, we discuss the theory, methods, and applications of computational pharmacology in pain research. Computational pharmacology encompasses a wide variety of theoretical concepts and practical methodological approaches, with the overall aim of gaining biological insight through data acquisition and analysis. Data are acquired from patients or animal models with pain or analgesic treatment, at different levels of biological organization (molecular, cellular, physiological, and behavioral). Distinct methodological algorithms can then be used to analyze and integrate data. This helps to facilitate the identification of biological molecules and processes associated with pain phenotype, build quantitative models of pain signaling, and extract translatable features between humans and animals. However, computational pharmacology has several limitations, and its predictions can provide false positive and negative findings. Therefore, computational predictions are required to be validated experimentally before drawing solid conclusions. In this review, we discuss several case study examples of combining and integrating computational tools with experimental pain research tools to meet drug discovery challenges.

A clindamycin acetylated derivative with reduced antibacterial activity inhibits articular hyperalgesia and edema by attenuating neutrophil recruitment, NF-κB activation and tumor necrosis factor-α production

We recently demonstrated that clindamycin exhibits activities in acute and chronic models of pain and inflammation. In the present study, we investigated the effects of clindamycin and a clindamycin acetylated derivative (CAD) in models of acute joint inflammation and in a microbiological assay. Joint inflammation was induced in mice by intraarticular (i.a.) injection of zymosan or lipopolysaccharide (LPS). Clindamycin or CAD were administered via the intraperitoneal route 1 h before zymosan or LPS. Paw withdrawal threshold, joint diameter, histological changes, neutrophil recruitment, tumor necrosis factor-α (TNF-α) production and phosphorylation of the IκBα and NF-κB/p65 were evaluated. In vitro assays were used to measure the antibacterial activity of clindamycin and CAD and also their effects on zymosan-induced TNF-α production by RAW264.7 macrophages. Clindamycin exhibited activity against Staphylococcus aureus and Salmonella Typhimurium ATCC® strains at much lower concentrations than CAD. Intraarticular injection of zymosan or LPS induced articular hyperalgesia, edema and neutrophil infiltration in the joints. Zymosan also induced histological changes, NF-κB activation and TNF-α production. Responses induced by zymosan and LPS were inhibited by clindamycin (200 and 400 mg/kg) or CAD (436 mg/kg). Both clindamycin and CAD inhibited in vitro TNF-α production by macrophages. In summary, we provided additional insights of the clindamycin immunomodulatory effects, whose mechanism was associated with NF-κB inhibition and reduced TNF-α production. Such effects were extended to a clindamycin derivative with reduced antibacterial activity, indicating that clindamycin derivatives should be investigated as candidates to drugs that could be useful in the management of inflammatory and painful conditions.

Double-blind, randomized, placebo-controlled crossover trial of alpha-lipoic acid for the treatment of fibromyalgia pain: the IMPALA trial

ABSTRACT

Fibromyalgia is a common and challenging chronic pain disorder with few, if any, highly effective and well-tolerated treatments. Alpha-lipoic acid (ALA) is a nonsedating antioxidant with evidence of efficacy in the treatment of symptomatic diabetic neuropathy that has not been evaluated in the setting of fibromyalgia treatment. Thus, we conducted a single-centre, proof-of-concept, randomized, placebo-controlled, crossover trial of ALA for the treatment of fibromyalgia. Twenty-seven participants were recruited, and 24 participants completed both treatment periods of the trial. The median maximal tolerated dose of ALA in this trial was 1663 mg/day. Treatment-emergent adverse events with ALA were infrequent and not statistically different from placebo. For the primary outcome of pain intensity, and for several other validated secondary outcomes, there were no statistically significant differences between placebo and ALA. A post hoc exploratory subgroup analysis showed a significant interaction between gender and treatment with a significant favourable placebo-ALA difference in pain for men, but not for women. Overall, the results of this trial do not provide any evidence to suggest promise for ALA as an effective treatment for fibromyalgia, which is predominantly prevalent in women. This negative clinical trial represents an important step in a collective strategy to identify new, better tolerated and more effective treatments for fibromyalgia.

In silico health effect prioritization of environmental chemicals through transcriptomics data exploration from a chemo-centric view

With the explosive growth of synthetic compounds, the health effects caused by exogenous chemical exposure have attracted more and more public attention. The prediction of health effect is a never-ending story. Collective resource of transcriptomics data offers an opportunity to understand and identify the multiple health effects of small molecule. Inspired by the fact that environmental chemicals of high health risk frequently share both similar gene expression profile and common structural feature of certain drugs, we here propose a novel computational effect prioritization method for environmental chemicals through transcriptomics data exploration from a chemo-centric view. Specifically, non-negative matrix factorization (NMF) method has been adopted to get the association network linking structural features with transcriptomics characteristics of drugs with specific effects. The model yields 13 pivotal types of effects, so-called components, that represent drug categories with common chemo- and geno- type features. Moreover, the established model effectively prioritizes potential toxic effects for the external chemicals from the endocrine disruptor screening program (EDSP) for their potential estrogenicity and other verified risks. Even if only the highest priority is set for the estrogenic effect, the precision and recall can reach 0.76 and 0.77 respectively for these chemicals. Our effort provides a successful endeavor as to profile potential toxic effects simultaneously for environmental chemicals using both chemical and omics data.

Computational study of zebrafish immune-targeted microarray data for prediction of preventive drug candidates

Viral hemorrhagic septicemia virus (VHSV) is a rhabdovirus reported to cause economic loss in fish farms. Because of the lack of adequate preventative treatments, the identification of multipath genes involved in VHS infection might be an alternative to explore the possibility of using drugs for the seasonal prevention of this fish disease. We propose labeling a category of drug molecules by further classification and interpretation of the Drug Gene Interaction Database using gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment scores. The study investigated disease networks of up-and down-regulated genes to find those with high interaction as substantial genes in pathways among the different disease networks. We prioritized these genes based on their relationship to those associated with VHS infection in the context of human protein-protein interaction networks and disease pathways. Among the 29 genes as potential drug targets, nine were selected as promising druggable genes (ERBB2, FGFR3, ITGA2B, MAP2K1, NGF, NTRK1, PDGFRA, SCN2B, and SERPINC1). PDGFRA is the most important druggable up-and down-regulated gene and is considered an important gene in the IMATINIB pathway. This study findings indicate a promising approach for drug target prediction for VHS treatment, which might be useful for disease therapeutics.

In silico drug repurposing for the identification of potential candidate molecules against arboviruses infection

Arboviral diseases caused by dengue (DENV), Zika (ZIKV) and chikungunya (CHIKV) viruses represent a major public health problem worldwide, especially in tropical areas where millions of infections occur every year. The aim of this research was to identify candidate molecules for the treatment of these diseases among the drugs currently available in the market, through in silico screening and subsequent in vitro evaluation with cell culture models of DENV and ZIKV infections. Numerous pharmaceutical compounds from antibiotics to chemotherapeutic agents presented high in silico binding affinity for the viral proteins, including ergotamine, antrafenine, natamycin, pranlukast, nilotinib, itraconazole, conivaptan and novobiocin. These five last compounds were tested in vitro, being pranlukast the one that exhibited the best antiviral activity. Further in vitro assays for this compound showed a significant inhibitory effect on DENV and ZIKV infection of human monocytic cells and human hepatocytes (Huh-7 cells) with potential abrogation of virus entry. Finally, intrinsic fluorescence analyses suggest that pranlukast may have some level of interaction with three viral proteins of DENV: envelope, capsid, and NS1. Due to its promising results, suitable accessibility in the market and reduced restrictions compared to other pharmaceuticals; the anti-asthmatic pranlukast is proposed as a drug candidate against DENV, ZIKV, and CHIKV, supporting further in vitro and in vivo assessment of the potential of this and other lead compounds that exhibited good affinity scores in silico as therapeutic agents or scaffolds for the development of new drugs against arboviral diseases.

Clindamycin inhibits nociceptive response by reducing tumor necrosis factor-α and CXCL-1 production and activating opioidergic mechanisms

Clindamycin, a bacteriostatic semisynthetic lincosamide, is useful in the management of infections caused by aerobic and anaerobic Gram-positive cocci, including bacteremic pneumonia, streptococcal toxic shock syndrome and sepsis. It has been recently demonstrated that clindamycin inhibits in vitro and in vivo inflammatory cytokine production. In the present study, we investigated the effects of clindamycin in acute and chronic models of pain and inflammation in mice and the underlying mechanisms. Intraperitoneal (i.p.) administration of clindamycin (400 mg/kg) increased the animal's latency to exhibit the nociceptive behavior induced by noxious heat (hot plate model). Intrathecal injection of clindamycin (2, 10 and 50 µg) also increased the animals' latency to exhibit the nociceptive behavior. Tactile hypersensitivity and paw edema induced by intraplantar (i.pl.) injection of carrageenan were attenuated by previous administration of clindamycin (200 and 400 mg/kg, i.p.). Clindamycin (100, 200 and 400 mg/kg, i.p.) also attenuated ongoing tactile hypersensitivity and paw edema induced by i.pl. injection of complete Freund's adjuvant (CFA). The antinociceptive activity of clindamycin (400 mg/kg, i.p.) in the hot plate model was attenuated by previous administration of naltrexone (5 and 10 mg/kg, i.p.), but not glibenclamide or AM251. CFA-induced production of TNF-α and CXCL-1 was reduced by clindamycin (400 mg/kg, i.p.). Concluding, clindamycin exhibits activities in acute and chronic models of pain and inflammation. These effects are associated with reduced production of TNF-α and CXCL-1 and activation of opioidergic mechanisms. Altogether, these results indicate that the clindamycin's immunomodulatory effects may contribute to a pharmacological potential beyond its antibiotic property.

Miltefosine treatment reduces visceral hypersensitivity in a rat model for irritable bowel syndrome via multiple mechanisms

Irritable bowel syndrome (IBS) is a heterogenic, functional gastrointestinal disorder of the gut-brain axis characterized by altered bowel habit and abdominal pain. Preclinical and clinical results suggested that, in part of these patients, pain may result from fungal induced release of mast cell derived histamine, subsequent activation of sensory afferent expressed histamine-1 receptors and related sensitization of the nociceptive transient reporter potential channel V1 (TRPV1)-ion channel. TRPV1 gating properties are regulated in lipid rafts. Miltefosine, an approved drug for the treatment of visceral Leishmaniasis, has fungicidal effects and is a known lipid raft modulator. We anticipated that miltefosine may act on different mechanistic levels of fungal-induced abdominal pain and may be repurposed to IBS. In the IBS-like rat model of maternal separation we assessed the visceromotor response to colonic distension as indirect readout for abdominal pain. Miltefosine reversed post-stress hypersensitivity to distension (i.e. visceral hypersensitivity) and this was associated with differences in the fungal microbiome (i.e. mycobiome). In vitro investigations confirmed fungicidal effects of miltefosine. In addition, miltefosine reduced the effect of TRPV1 activation in TRPV1-transfected cells and prevented TRPV1-dependent visceral hypersensitivity induced by intracolonic-capsaicin in rat. Miltefosine may be an attractive drug to treat abdominal pain in IBS.

Identification of novel analgesics through a drug repurposing strategy

The identification of new indications for approved or failed drugs is a process called drug repositioning or drug repurposing. The motivation includes overcoming the productivity gap that exists in drug development, which is a high-cost–high-risk process. Repositioning also includes rescuing drugs that have safely entered the market but have failed to demonstrate sufficient efficiency for the initial clinical indication. Considering the high prevalence of chronic pain, the lack of sufficient efficacy and the safety issues of current analgesics, repositioning seems to be an attractive approach. This review presents example of drugs that already have been repositioned and highlights new technologies that are available for the identification of additional compounds to stimulate the curiosity of readers for further exploration.

Drug Repurposing Approaches for the Treatment of Influenza Viral Infection: Reviving Old Drugs to Fight Against a Long-Lived Enemy

Influenza viruses still constitute a real public health problem today. To cope with the emergence of new circulating strains, but also the emergence of resistant strains to classic antivirals, it is necessary to develop new antiviral approaches. This review summarizes the state-of-the-art of current antiviral options against influenza infection, with a particular focus on the recent advances of anti-influenza drug repurposing strategies and their potential therapeutic, regulatory and economic benefits. The review will illustrate the multiple ways to reposition molecules for the treatment of influenza, from adventitious discovery to in silico-based screening. These novel antiviral molecules, many of which targeting the host cell, in combination with conventional antiviral agents targeting the virus, will ideally enter the clinics and reinforce the therapeutic arsenal to combat influenza virus infections.

CNS repurposing - Potential new uses for old drugs: Examples of screens for Alzheimer's disease, Parkinson's disease and spasticity

Drug repurposing is recently gaining increasing attention, not just from pharmaceutical companies but also from government agencies in an attempt to generate new medications to address increasing unmet medical needs in a cost effective and expedite manner. There are several approaches to identify novel indications for known drugs. Many are based on rational selection e.g. the known or a new mechanism of action of a drug. This review will focus rather on phenotypic or high content screening of compounds in models that are believed to be predictive of effectiveness of compounds irrespective of their mechanism of action. Three short cases studies of screens for Alzheimer's disease, Parkinson's disease and spasticity will be given as examples. This article is part of the Special Issue entitled 'Drug Repurposing: old molecules, new ways to fast track drug discovery and development for CNS disorders'.

Repositioning of Omarigliptin as a once-weekly intranasal Anti-parkinsonian Agent

Drug repositioning is a revolution breakthrough of drug discovery that presents outstanding privilege with already safer agents by scanning the existing candidates as therapeutic switching or repurposing for marketed drugs. Sitagliptin, vildagliptin, saxagliptin & linagliptin showed antioxidant and neurorestorative effects in previous studies linked to DPP-4 inhibition. Literature showed that gliptins did not cross the blood brain barrier (BBB) while omarigliptin was the first gliptin that crossed it successfully in the present work. LC-MS/MS determination of once-weekly anti-diabetic DPP-4 inhibitors; omarigliptin & trelagliptin in plasma and brain tissue was employed after 2 h of oral administration to rats. The brain/plasma concentration ratio was used to deduce the penetration power through the BBB. Results showed that only omarigliptin crossed the BBB due to its low molecular weight & lipophilic properties suggesting its repositioning as antiparkinsonian agent. The results of BBB crossing will be of interest for researchers interested in Parkinson's disease. A novel intranasal formulation was developed using sodium lauryl sulphate surfactant to solubilize the lipophilic omarigliptin with penetration enhancing & antimicrobial properties. Intranasal administration showed enhanced brain/plasma ratio by 3.3 folds compared to the oral group accompanied with 2.6 folds increase in brain glucagon-like peptide-1 concentration compared to the control group.

Evidence for the involvement of TNF-α, IL-1β and IL-10 in the antinociceptive and anti-inflammatory effects of indole-3-guanylhydrazone hydrochloride, an aromatic aminoguanidine, in rodents

BACKGROUND

Indole-3-guanylhydrazone hydrochloride (LQM01) is a new derivative of aminoguanidine hydrochloride, an aromatic aminoguanidine.

METHODS

Mice were treated with LQM01 (5, 10, 25 or 50 mg/kg, i.p.), vehicle (0.9% saline i.p.) or a standard drug. The mice were subjected to carrageenan-induced pleurisy, abdominal writhing induced by acetic acid, the formalin test and the hot-plate test. The model of non-inflammatory chronic muscle pain induced by saline acid was also used. Mice from the chronic protocol were assessed for withdrawal threshold, muscle strength and motor coordination. LQM01 or vehicle treated mice were evaluated for Fos protein.

RESULTS

LQM01 inhibits TNF-α and IL-1β production, as well as leukocyte recruitment during inflammation process. The level of IL-10 in LQM01-treated mice increased in pleural fluid. In addition, LQM01 decreased the nociceptive behavior in the acetic acid induced writhing test, the formalin test (both phases) and increased latency time on the hot-plate. LQM01 treatment also decreased mechanical hyperalgesia in mice with chronic muscle pain, with no changes in muscle strength and motor coordination. LQM01 reduced the number of Fos positive cells in the superficial dorsal horn. This compound exhibited antioxidant properties in in vitro assays.

CONCLUSIONS

LQM01 has an outstanding anti-inflammatory and analgesic profile, probably mediated through a reduction in proinflammatory cytokines release, increase in IL-10 production and reduction in neuron activity in the dorsal horn of the spinal cord in mice.

GENERAL SIGNIFICANCE

Beneficial effects of LQM01 suggest that it has some important clinical features and can play a role in the management of 'dysfunctional pain' and inflammatory diseases.

Epigenetic actions of environmental factors and promising drugs for cancer therapy

Carcinogenesis is known to be primarily associated with gene mutations. Recently, increasing evidence has suggested that epigenetic events also serve crucial roles in tumor etiology. Environmental factors, including nutrition, toxicants and ethanol, are involved in carcinogenesis through inducing epigenetic modifications, such as DNA methylation, histone deacetylase and miRNA regulation. Studying epigenetic mechanisms has facilitated the development of early diagnostic strategies and potential therapeutic avenues. Modulation at the epigenetic level, including reversing epigenetic modifications using targeted drugs, has demonstrated promise in cancer therapy. Therefore, identifying novel epigenetic biomarkers and therapeutic targets has potential for the future of cancer therapy. The present review discusses the environmental factors involved in epigenetic modifications and potential drug candidates for cancer therapy.

Designing a broad-spectrum integrative approach for cancer prevention and treatment

Targeted therapies and the consequent adoption of "personalized" oncology have achieved notable successes in some cancers; however, significant problems remain with this approach. Many targeted therapies are highly toxic, costs are extremely high, and most patients experience relapse after a few disease-free months. Relapses arise from genetic heterogeneity in tumors, which harbor therapy-resistant immortalized cells that have adopted alternate and compensatory pathways (i.e., pathways that are not reliant upon the same mechanisms as those which have been targeted). To address these limitations, an international task force of 180 scientists was assembled to explore the concept of a low-toxicity "broad-spectrum" therapeutic approach that could simultaneously target many key pathways and mechanisms. Using cancer hallmark phenotypes and the tumor microenvironment to account for the various aspects of relevant cancer biology, interdisciplinary teams reviewed each hallmark area and nominated a wide range of high-priority targets (74 in total) that could be modified to improve patient outcomes. For these targets, corresponding low-toxicity therapeutic approaches were then suggested, many of which were phytochemicals. Proposed actions on each target and all of the approaches were further reviewed for known effects on other hallmark areas and the tumor microenvironment. Potential contrary or procarcinogenic effects were found for 3.9% of the relationships between targets and hallmarks, and mixed evidence of complementary and contrary relationships was found for 7.1%. Approximately 67% of the relationships revealed potentially complementary effects, and the remainder had no known relationship. Among the approaches, 1.1% had contrary, 2.8% had mixed and 62.1% had complementary relationships. These results suggest that a broad-spectrum approach should be feasible from a safety standpoint. This novel approach has potential to be relatively inexpensive, it should help us address stages and types of cancer that lack conventional treatment, and it may reduce relapse risks. A proposed agenda for future research is offered.

An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework

Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format.

Database URL:http://targetmine.mizuguchilab.org

De Novo Design at the Edge of Chaos

Computational medicinal chemistry offers viable strategies for finding, characterizing, and optimizing innovative pharmacologically active compounds. Technological advances in both computer hardware and software as well as biological chemistry have enabled a renaissance of computer-assisted "de novo" design of molecules with desired pharmacological properties. Here, we present our current perspective on the concept of automated molecule generation by highlighting chemocentric methods that may capture druglike chemical space, consider ligand promiscuity for hit and lead finding, and provide fresh ideas for the rational design of customized screening of compound libraries.

Transmembrane TNF-α is sufficient for articular inflammation and hypernociception in a mouse model of gout

Gout manifests as recurrent episodes of acute joint inflammation and pain due to the deposition of monosodium urate (MSU) crystals within the affected tissue in a process dependent on NLRP3 inflammasome activation. The synthesis, activation, and release of IL-1β are crucial for MSU-induced inflammation. The current study evaluated the mechanism by which TNF-α contributed to MSU-induced inflammation. Male C57BL/6J or transgenic mice were used in this study and inflammation was induced by the injection of MSU crystals into the joint. TNF-α was markedly increased in the joint after the injection of MSU. There was inhibition in the infiltration of neutrophils, production of CXCL1 and IL-1β, and decreased hypernociception in mice deficient for TNF-α or its receptors. Pharmacological blockade of TNF-α with Etanercept or pentoxyfylline produced similar results. Mechanistically, TNF-α blockade resulted in lower amounts of IL-1β protein and pro-IL-1β mRNA transcripts in joints. Gene-modified mice that express only transmembrane TNF-α had an inflammatory response similar to that of WT mice and blockade of soluble TNF-α (XPro™1595) did not decrease MSU-induced inflammation. In conclusion, TNF-α drives expression of pro-IL-1β mRNA and IL-1β protein in experimental gout and that its transmembrane form is sufficient to trigger MSU-induced inflammation in mice.

Colorectal cancer drug target prediction using ontology-based inference and network analysis

Identification of novel drug targets is a critical step in drug development. Many recent studies have produced multiple types of data, which provides an opportunity to mine the relationships among them to predict drug targets. In this study, we present a novel integrative approach that combines ontology reasoning with network-assisted gene ranking to predict new drug targets. We utilized colorectal cancer (CRC) as a proof-of-concept use case to illustrate the approach. Starting from FDA-approved CRC drugs and the relationships among disease, drug, gene, pathway, and SNP in an ontology representing PharmGKB data, we inferred 113 potential CRC drug targets. We further prioritized these genes based on their relationships with CRC disease genes in the context of human protein-protein interaction networks. Thus, among the 113 potential drug targets, 15 were selected as the promising drug targets, including some genes that are supported by previous studies. Among them, EGFR, TOP1 and VEGFA are known targets of FDA-approved drugs. Additionally, CCND1 (cyclin D1), and PTGS2 (prostaglandin-endoperoxide synthase 2) have reported to be relevant to CRC or as potential drug targets based on the literature search. These results indicate that our approach is promising for drug target prediction for CRC treatment, which might be useful for other cancer therapeutics.

Identification of Nitazoxanide as a Group I Metabotropic Glutamate Receptor Negative Modulator for the Treatment of Neuropathic Pain: An In Silico Drug Repositioning Study

PURPOSE

Drug repositioning strategies were employed to explore new therapeutic indications for existing drugs that may exhibit dual negative mGluR1/5 modulating activities as potential treatments for neuropathic pain.

METHOD

A customized in silico-in vitro-in vivo drug repositioning scheme was assembled and implemented to search available drug libraries for compounds with dual mGluR1/5 antagonistic activities, that were then evaluated using in vitro functional assays and, for validated hits, in an established animal model for neuropathic pain.

RESULTS

Tizoxanide, the primary active metabolite of the FDA approved drug nitazoxanide, fit in silico pharmacophore models constructed for both mGluR1 and mGluR5. Subsequent calcium (Ca++) mobilization functional assays confirmed that tizoxanide exhibited appreciable antagonist activity for both mGluR1 and mGluR5 (IC50 = 1.8 μM and 1.2 μM, respectively). The in vivo efficacy of nitazoxanide administered by intraperitoneal injection was demonstrated in a rat model for neuropathic pain.

CONCLUSION

The major aim of the present study was to demonstrate the utility of an in silico-in vitro-in vivo drug repositioning protocol to facilitate the repurposing of approved drugs for new therapeutic indications. As an example, this particular investigation successfully identified nitazoxanide and its metabolite tizoxanide as dual mGluR1/5 negative modulators. A key finding is the vital importance for drug screening libraries to include the structures of drug active metabolites, such as those emanating from prodrugs which are estimated to represent 5-7% of marketed drugs.

Implications of the small number of distinct ligand binding pockets in proteins for drug discovery, evolution and biochemical function

Coincidence of the properties of ligand binding pockets in native proteins with those in proteins generated by computer simulations without selection for function shows that pockets are a generic protein feature and the number of distinct pockets is small. Similar pockets occur in unrelated protein structures, an observation successfully employed in pocket-based virtual ligand screening. The small number of pockets suggests that off-target interactions among diverse proteins are inherent; kinases, proteases and phosphatases show this prototypical behavior. The ability to repurpose FDA approved drugs is general, and minor side effects cannot be avoided. Finally, the implications to drug discovery are explored.