Publications
230 results found
Kalash L, Cresser-Brown J, Habchi J, et al., 2018, Structure-based design of allosteric calpain-1 inhibitors populating a novel bioactivity space, European Journal of Medicinal Chemistry, Vol: 157, Pages: 1264-1275, ISSN: 0223-5234
Dimeric calpains constitute a promising therapeutic target for many diseases such as cardiovascular, neurodegenerative and ischaemic disease. The discovery of selective calpain inhibitors, however, has been extremely challenging. Previously, allosteric inhibitors of calpains, such as PD150606, which included a specific α-mercaptoacrylic acid sub-structure, were reported to bind to the penta-EF hand calcium binding domain, PEF(S) of calpain. Although these are selective to calpains over other cysteine proteases, their mode of action has remained elusive due to their ability to inhibit the active site domain with and without the presence of PEF(S), with similar potency. These findings have led to the question of whether the inhibitory response can be attributed to an allosteric mode of action or alternatively to inhibition at the active site. In order to address this problem, we report a structure-based virtual screening protocol as a novel approach for the discovery of PEF(S) binders that populate a novel chemical space. We have identified compound 1, Vidupiprant, which is shown to bind to the PEF(S) domain by the TNS displacement method, and it exhibited specificity in its allosteric mode of inhibition. Compound 1 inhibited the full-length calpain-1 complex with a higher potency (IC50 = 7.5 μM) than the selective, cell-permeable non-peptide calpain inhibitor, PD150606 (IC50 = 19.3 μM), where the latter also inhibited the active site domain in the absence of PEF(S) (IC50 = 17.8 μM). Hence the method presented here has identified known compounds with a novel allosteric mechanism for the inhibition of calpain-1. We show for the first time that the inhibition of enzyme activity can be attributed to an allosteric mode of action, which may offer improved selectivity and a reduced side-effects profile.
Kalash L, Winfield I, Safitri D, et al., 2018, MD-assisted approach for designing multi-target ligands at A2AR and PDE10A that elevate cyclic AMP, 256th National Meeting and Exposition of the American-Chemical-Society (ACS) - Nanoscience, Nanotechnology and Beyond, Publisher: AMER CHEMICAL SOC, ISSN: 0065-7727
Inglese P, Strittmatter N, Doria L, et al., 2018, Mass spectrometry: from imaging to metabolic networks
A deeper understanding of inter-tumorand intra-tumorheterogeneity is a critical factor for the advancement of next generation strategies against cancer. Under the hypothesis that heterogeneous progression of tumorsis mirrored by their metabolic heterogeneity, detection of biochemical mechanisms responsible of the local metabolism becomes crucial.We show that network analysis of co-localized ions from mass spectrometry imaging data provides a detailed chemo-spatial insightinto the metabolic heterogeneity of tumor. Furthermore, module preservation analysis between colorectal cancer patients with and without metastatic recurrence suggests hypotheses on the nature of the different local metabolic pathways.
Hoyles L, Snelling T, Umlai UK, et al., 2018, Microbiome–host systems interactions: protective effects of propionate upon the blood–brain barrier, Microbiome, Vol: 6, ISSN: 2049-2618
Background: Gut microbiota composition and function are symbiotically linked with host health, and altered in metabolic, inflammatory and neurodegenerative disorders. Three recognized mechanisms exist by which the microbiome influences the gut--brain axis: modification of autonomic/sensorimotor connections, immune activation, and neuroendocrine pathway regulation. We hypothesized interactions between circulating gut-derived microbial metabolites and the blood--brain barrier (BBB) also contribute to the gut--brain axis. Propionate, produced from dietary substrates by colonic bacteria, stimulates intestinal gluconeogenesis and is associated with reduced stress behaviours, but its potential endocrine role has not been addressed. Results: After demonstrating expression of the propionate receptor FFAR3 on human brain endothelium, we examined the impact of a physiologically relevant propionate concentration (1 μM) on BBB properties in vitro. Propionate inhibited pathways associated with non-specific microbial infections via a CD14-dependent mechanism, suppressed expression of LRP-1 and protected the BBB from oxidative stress via NRF2 (NFE2L2) signaling. Conclusions: Together, these results suggest gut-derived microbial metabolites interact with the BBB, representing a fourth facet of the gut--brain axis that warrants further attention.
Hoyles L, Snelling T, Umlai U-K, et al., 2018, Propionate has protective and anti-inflammatory effects on the blood–brain barrier, Alzheimer's Research UK Research Conference 2018
Propionate is a short-chain fatty acid (SCFA) produced by the human gut microbiota from dietary substrates, and is biologically active via the G protein coupled receptors FFAR2 and FFAR3. It is taken up from the gut and reaches systemic circulation in micromolar quantities. The blood–brain barrier (BBB) is the major interface between the circulation and central nervous system. FFAR3 is expressed on the vascular endothelium and a likely target for propionate in the BBB. We hypothesized exposure of the BBB to propionate influences barrier integrity and function.Methods and materialsWe investigated the in vitro effects of a physiologically relevant concentration (1 μM) of propionate upon the human immortalised cerebromicrovascular endothelial cell line hCMEC/D3. FFAR3 was present on these cells. We, therefore, performed an unbiased transcriptomic analysis of confluent hCMEC/D3 monolayers treated or not for 24 h with 1 μM propionate, supported by in vitro validation of key findings and assessment of functional endothelial permeability barrier properties.ResultsPropionate treatment had a significant (PFDR < 0.1) effect on the expression of 1136 genes. It inhibited several inflammation-associated pathways: TLR-specific signalling, NFkappaB signalling, and cytosolic DNA-sensing. Functional validation of these findings confirmed the down-regulation of TLR signalling by propionate, achieved primarily through down-regulation of endothelial CD14 expression. Accordingly, propionate prevented LPS-induced increases in paracellular permeability to 70 kDa FITC-dextran and loss of transendothelial electrical resistance. Propionate activated the NFE2L2 (NRF2)-driven protective response against oxidative stress. Confirming these data, propionate limited free reactive oxygen species induction by the mitochondrial respiratory inhibitor rotenone. ConclusionsOur data strongly suggest the SCFA propionate contributes to maintaining BBB integrity and protecting against inflamm
McArthur S, Carvalho A, Fonseca S, et al., 2018, Effects of gut-derived trimethylamines on the blood–brain barrier, Alzheimer's Research UK Research Conference 2018
Introduction: The gut microbiota and its metabolites exert significant effects on host health, with disturbances to composition and function associated with conditions including obesity, type II diabetes and, more recently, Alzheimer’s disease (AD). Communication between microbes and the host can take a number of forms, but central to all of them is a role for gut-derived microbial metabolites, with trimethylamine N-oxide (TMAO) and its precursor trimethylamine (TMA) being important examples. TMA produced by gut bacteria is converted to TMAO in the liver by flavin monooxygenases whereupon it enters the circulation. TMAO was recently identified as potentially important in genetic pathways associated with AD, and has been shown to influence peripheral vascular function. Given these links, the key position of the cerebral vasculature as the major interface between circulating molecules and the brain, and evidence that deficits in blood–brain barrier (BBB) function occur early in AD, we investigated the effects of TMAO and TMA on key BBB properties in vitro and in vivo.Materials and Methods: Male C57Bl/6 mice (n=4-5) were used to examine the effect of TMAO treatment (1.8 mg/kg, 2 h, dose equivalent to circulating human concentrations) upon BBB permeability in vivo, assessed by Evans’ blue dye extravasation. TMA was not investigated as the average mouse plasma concentration of this methylamine is substantially greater than that seen in humans (TMAO-to-TMA ratio 1:10 in mice, 10:1 in humans).Human hCMEC/D3 cerebromicrovascular cells were used as an in vitro model of the BBB to investigate the effects of 24 h treatment with human physiologically relevant doses of TMAO (40 μM) and TMA (0.4 μM), studying (i) functional barrier properties of cell monolayers and (ii) gene expression. Results: Administration of TMAO to mice enhanced BBB integrity above baseline after 2 h treatment (p<0.05). Similarly, in vitro exposure of hCMEC/D3 cells to TMAO enhanc
Hoyles L, Snelling T, Umlai U-K, et al., 2018, Microbiome–host interactions: protective effects of propionate upon the blood–brain barrier, Publisher: biorixiv
Breakdown of foodstuffs by the gut microbiota results in the production of the short-chain fatty acids (SCFAs) acetate, propionate and butyrate. SFCAs are potent bioactive molecules, providing energy for intestinal cells, enhancing satiety and positively influencing metabolic health. They also influence the gut–brain axis. The gut microbiota and/or its bioactive molecules contribute to maintaining the integrity of the blood–brain barrier (BBB), the primary defensive structure of the brain. Propionate is produced by the gut microbiota from the breakdown of glucans found in whole grains, mushrooms and yeast products. It is found in the blood at ≤1 μM. At this physiologically relevant concentration, propionate enhances BBB integrity, mitigating against deleterious inflammatory and oxidative stimuli known to contribute to neurological and psychological diseases. Therefore, there is the potential that dietary supplementation with glucan-containing products may offer protection of the brain against detrimental stimuli.
Glen RC, 2018, Applied Chemoinformatics Achievements and Future Opportunities Foreword, APPLIED CHEMOINFORMATICS: ACHIEVEMENTS AND FUTURE OPPORTUNITIES, Editors: Engel, Gasteiger, Publisher: WILEY-V C H VERLAG GMBH, Pages: XVII-XX, ISBN: 978-3-527-34201-3
Kalash L, Val C, Azuaje J, et al., 2017, Computer-aided design of multi-target ligands at A(1)R, A(2A)R and PDE10A, key proteins in neurodegenerative diseases, Journal of Cheminformatics, Vol: 9, ISSN: 1758-2946
Compounds designed to display polypharmacology may have utility in treating complex diseases, where activity at multiple targets is required to produce a clinical effect. In particular, suitable compounds may be useful in treating neurodegenerative diseases by promoting neuronal survival in a synergistic manner via their multi-target activity at the adenosine A1 and A2A receptors (A1R and A2AR) and phosphodiesterase 10A (PDE10A), which modulate intracellular cAMP levels. Hence, in this work we describe a computational method for the design of synthetically feasible ligands that bind to A1 and A2A receptors and inhibit phosphodiesterase 10A (PDE10A), involving a retrosynthetic approach employing in silico target prediction and docking, which may be generally applicable to multi-target compound design at several target classes. This approach has identified 2-aminopyridine-3-carbonitriles as the first multi-target ligands at A1R, A2AR and PDE10A, by showing agreement between the ligand and structure based predictions at these targets. The series were synthesized via an efficient one-pot scheme and validated pharmacologically as A1R/A2AR–PDE10A ligands, with IC50 values of 2.4–10.0 μM at PDE10A and Ki values of 34–294 nM at A1R and/or A2AR. Furthermore, selectivity profiling of the synthesized 2-amino-pyridin-3-carbonitriles against other subtypes of both protein families showed that the multi-target ligand 8 exhibited a minimum of twofold selectivity over all tested off-targets. In addition, both compounds 8 and 16 exhibited the desired multi-target profile, which could be considered for further functional efficacy assessment, analog modification for the improvement of selectivity towards A1R, A2AR and PDE10A collectively, and evaluation of their potential synergy in modulating cAMP levels.
Inglese P, Strittmatter N, Doria L, et al., 2017, Network analysis of mass spectrometry imaging data from colorectal cancer identifies key metabolites common to metastatic development
<jats:title>Abstract</jats:title><jats:p>A deeper understanding of inter-tumor and intra-tumor heterogeneity is a critical factor for the advancement of next generation strategies against cancer. The heterogeneous morphology exhibited by solid tumors is mirrored by their metabolic heterogeneity. Defining the basic biological mechanisms that underlie tumor cell variability will be fundamental to the development of personalized cancer treatments. Variability in the molecular signatures found in local regions of cancer tissues can be captured through an untargeted analysis of their metabolic constituents. Here we demonstrate that DESI mass spectrometry imaging (MSI) combined with network analysis can provide detailed insight into the metabolic heterogeneity of colorectal cancer (CRC). We show that network modules capture signatures which differentiate tumor metabolism in the core and in the surrounding region. Moreover, module preservation analysis of network modules between patients with and without metastatic recurrence explains the inter-subject metabolic differences associated with diverse clinical outcomes such as metastatic recurrence.</jats:p><jats:sec><jats:title>Significance</jats:title><jats:p>Network analysis of DESI-MSI data from CRC human tissue reveals clinically relevant co-expression ion patterns associated with metastatic susceptibility. This delineates a more complex picture of tumor heterogeneity than conventional hard segmentation algorithms. Using tissue sections from central regions and at a distance from the tumor center, ion co-expression patterns reveal common features among patients who developed metastases (up of > 5 years) not preserved in patients who did not develop metastases. This offers insight into the nature of the complex molecular interactions associated with cancer recurrence. Presently, predicting CRC relapse is challenging, and histopathologically like-for-like cancers freque
Harford-Wright E, Andre-Gregoire G, Jacobs KA, et al., 2017, Pharmacological targeting of apelin impairs glioblastoma growth, Brain, Vol: 140, Pages: 2939-2954, ISSN: 1460-2156
Glioblastoma are highly aggressive brain tumours that are associated with an extremely poor prognosis. Within these tumours exists a subpopulation of highly plastic self-renewing cancer cells that retain the ability to expand ex vivo as tumourspheres, induce tumour growth in mice, and have been implicated in radio- and chemo-resistance. Although their identity and fate are regulated by external cues emanating from endothelial cells, the nature of such signals remains unknown. Here, we used a mass spectrometry proteomic approach to characterize the factors released by brain endothelial cells. We report the identification of the vasoactive peptide apelin as a central regulator for endothelial-mediated maintenance of glioblastoma patient-derived cells with stem-like properties. Genetic and pharmacological targeting of apelin cognate receptor abrogates apelin- and endothelial-mediated expansion of glioblastoma patient-derived cells with stem-like properties in vitro and suppresses tumour growth in vivo. Functionally, selective competitive antagonists of apelin receptor were shown to be safe and effective in reducing tumour expansion and lengthening the survival of intracranially xenografted mice. Therefore, the apelin/apelin receptor signalling nexus may operate as a paracrine signal that sustains tumour cell expansion and progression, suggesting that apelin is a druggable factor in glioblastoma.
Cooper S, Barr AR, Glen R, et al., 2017, NucliTrack: an integrated nuclei tracking application, Bioinformatics, Vol: 33, Pages: 3320-3322, ISSN: 1367-4803
Live imaging studies give unparalleled insight into dynamic single cell behaviours and fate decisions. However, the challenge of reliably tracking single cells over long periods of time limits both the throughput and ease with which such studies can be performed. Here, we present NucliTrack, a cross platform solution for automatically segmenting, tracking and extracting features from fluorescently labelled nuclei. NucliTrack performs similarly to other state-of-the-art cell tracking algorithms, but NucliTrack’s interactive, graphical interface makes it significantly more user friendly.
Hoyles L, Snelling T, Umlai UK, et al., 2017, Propionate has protective and anti-inflammatory effects on the blood–brain barrier, Exploring Human Host-Microbiome Interactions in Health and Disease
Production of short-chain fatty acids (SCFAs) from dietary substrates by the gut microbiota is associated with health, with these metabolites influencing the host via the ‘gut–brain axis’. Micromolar quantities of microbially derived SCFAs are taken up from the gut and reach systemic circulation, where they can influence host gene expression through a variety of largely unknown mechanisms. The blood–brain barrier (BBB) is the major interface between the circulation and central nervous system, and is critically involved in the pathogenesis of neuroinflammatory disorders such as stroke and vascular dementia. We hypothesized exposure of the BBB to SCFAs influences barrier integrity and function.To test our hypothesis, we investigated the in vitro effects of a physiologically relevant concentration (1 μM) of propionate upon the human immortalised cerebromicrovascular endothelial cell line hCMEC/D3. Propionate is produced by the microbiota from dietary glucans, and is biologically active via the G protein coupled receptors FFAR2 and FFAR3. It is a highly potent FFAR2 agonist (agonist activity 3.99) and has close to optimal ligand efficiency (-ΔG=1.19 kcal mol-1 atom-1) for this receptor. Notably, FFAR3 is expressed on the vascular endothelium and a likely target for propionate in the BBB.After confirming the presence of FFAR3 on hCMEC/D3 cells, we undertook an unbiased transcriptomic analysis of confluent hCMEC/D3 monolayers treated or not for 24 h with 1 μM propionate, supported by in vitro validation of key findings and assessment of functional endothelial permeability barrier properties.Propionate treatment had a significant (PFDR < 0.1) effect on the expression of 1136 genes: 553 upregulated, 583 downregulated. Propionate inhibited several inflammation-associated pathways: namely, TLR-specific signalling, NFkappaB signalling, and cytosolic DNA-sensing. Functional validation of these findings confirmed the down-regulation of TLR
McArthur S, Umlai UK, Snelling T, et al., 2017, Effects of gut-derived methylamines on the blood–brain barrier, 2017 Alzheimer's Research UK Conference
Introduction: Composition and functions of the gut microbiota are inextricably linked with host health, and altered in conditions such as obesity and type II diabetes. Central to microbe–host crosstalk are gut-derived microbial metabolites, of which trimethylamine N-oxide (TMAO) and its precursor trimethylamine (TMA) are of particular importance. TMA produced by intestinal microbes is converted to TMAO in the liver by flavin monooxygenases with circulating TMAO being associated with cardiovascular disease and insulin resistance. TMAO was also recently identified as potentially important in genetic pathways associated with Alzheimer’s disease (AD). In considering that deficits in blood–brain barrier (BBB) function occur early in AD, and its position as the major interface between circulating metabolites and the brain, we investigated the effects of TMAO and TMA on key BBB properties in vitro.Materials and Methods: Human hCMEC/D3 cerebromicrovascular cells were used as an in vitro model of the BBB to investigate the effects of 24 h treatment with physiologically relevant doses of TMAO and TMA, studying (i) functional barrier properties of cell monolayers, (ii) Aβ efflux transporters and (iii) gene expression.Results: Exposure of hCMEC/D3 cells to TMAO (40 μM) reinforced barrier integrity by enhancing transendothelial electrical resistance (P <0.001) and reducing paracellular permeability to a 70 kDa dextran tracer (P <0.001). In contrast, while TMA (0.4 μM) enhanced electrical resistance (P <0.001), it significantly increased tracer paracellular permeability (P <0.05), consistent with compromised barrier function. Transporter activity analysis showed TMAO inhibited p-glycoprotein function (P <0.001), which was not seen with TMA; neither metabolite affected BCRP function. Human-genome transcriptomic data are currently being analysed.Conclusions: TMAO and TMA affect BBB function in a metabolite-specific manner, regulating barr
Yang P, Kuc RE, Brame AL, et al., 2017, [Pyr(1)]Apelin-13((1-12)) Is a Biologically Active ACE2 Metabolite of the Endogenous Cardiovascular Peptide [Pyr(1)]Apelin-13, FRONTIERS IN NEUROSCIENCE, Vol: 11, ISSN: 1662-453X
Aims: Apelin is a predicted substrate for ACE2, a novel therapeutic target. Our aim was to demonstrate the endogenous presence of the putative ACE2 product [Pyr1]apelin-13(1–12) in human cardiovascular tissues and to confirm it retains significant biological activity for the apelin receptor in vitro and in vivo. The minimum active apelin fragment was also investigated.Methods and Results: [Pyr1]apelin-13 incubated with recombinant human ACE2 resulted in de novo generation of [Pyr1]apelin-13(1–12) identified by mass spectrometry. Endogenous [Pyr1]apelin-13(1–12) was detected by immunostaining in human heart and lung localized to the endothelium. Expression was undetectable in lung from patients with pulmonary arterial hypertension. In human heart [Pyr1]apelin-13(1–12) (pKi = 8.04 ± 0.06) and apelin-13(F13A) (pKi = 8.07 ± 0.24) competed with [125I]apelin-13 binding with nanomolar affinity, 4-fold lower than for [Pyr1]apelin-13 (pKi = 8.83 ± 0.06) whereas apelin-17 exhibited highest affinity (pKi = 9.63 ± 0.17). The rank order of potency of peptides to inhibit forskolin-stimulated cAMP was apelin-17 (pD2 = 10.31 ± 0.28) > [Pyr1]apelin-13 (pD2 = 9.67 ± 0.04) ≥ apelin-13(F13A) (pD2 = 9.54 ± 0.05) > [Pyr1]apelin-13(1–12) (pD2 = 9.30 ± 0.06). The truncated peptide apelin-13(R10M) retained nanomolar potency (pD2 = 8.70 ± 0.04) but shorter fragments exhibited low micromolar potency. In a β-arrestin recruitment assay the rank order of potency was apelin-17 (pD2 = 10.26 ± 0.09) >> [Pyr1]apelin-13 (pD2 = 8.43 ± 0.08) > apelin-13(R10M) (pD2 = 8.26 ± 0.17) > apelin-13(F13A) (pD2 = 7.98 ± 0.04) ≥ [Pyr1]apelin-13(1–12) (pD2 = 7.84 ± 0.06) >> shorter fragments (pD2 < 6). [Pyr1]apelin-13(1–12) and apelin-13(F13A) contracted human saphenous vein with similar sub-nanomolar potencies and [Pyr1]apelin-13(1–
Inglese P, McKenzie JS, Mroz A, et al., 2017, Deep learning and 3D-DESI imaging reveal the hidden metabolic heterogeneity of cancer, Chemical Science, Vol: 8, Pages: 3500-3511, ISSN: 2041-6539
Visual inspection of tumour tissues does not reveal the complex metabolic changes that differentiate cancer and its sub-types from healthy tissues. Mass spectrometry imaging, which quantifies the underlying chemistry, represents a powerful tool for the molecular exploration of tumour tissues. A 3-dimensional topological description of the chemical properties of the tumour permits the formulation of hypotheses about the biological composition and interactions and the possible causes of its heterogeneous structure. The large amount of information contained in such datasets requires powerful tools for its analysis, visualisation and interpretation. Linear methods for unsupervised dimensionality reduction, such as PCA, are inadequate to capture the complex non-linear relationships present in these data. For this reason, a deep unsupervised neural network based technique, parametric t-SNE, is adopted to map a 3D-DESI-MS dataset from a human colorectal adenocarcinoma biopsy onto a 2-dimensional manifold. This technique allows the identification of clusters not visible with linear methods. The unsupervised clustering of the tumour tissue results in the identification of sub-regions characterised by the abundance of identified metabolites, making possible the formulation of hypotheses to account for their significance and the underlying biological heterogeneity in the tumour.
Yang P, Read C, Kuc RE, et al., 2017, Elabela/toddler is an endogenous agonist of the apelin APJ receptor in the adult cardiovascular system, and exogenous administration of the peptide compensates for the downregulation of its expression in pulmonary arterial hypertension, Circulation, Vol: 135, Pages: 1160-1173, ISSN: 0009-7322
Background—Elabela/Toddler (ELA) is a critical cardiac developmental peptide that acts through the G protein-coupled apelin receptor, despite lack of sequence similarity to the established ligand apelin. Our aim was to investigate the receptor pharmacology, expression pattern and in vivo function of ELA peptides in the adult cardiovascular system, to seek evidence for alteration in pulmonary arterial hypertension (PAH) in which apelin signaling is down-regulated, and to demonstrate attenuation of PAH severity with exogenous administration of ELA in a rat model.Methods—In silico docking analysis, competition binding experiments and down-stream assays were used to characterize ELA receptor binding in human heart and signaling in cells expressing the apelin receptor. ELA expression in human cardiovascular tissues and plasma was determined using RT-qPCR, dual-labelling immunofluorescent staining and immunoassays. Acute cardiac effects of ELA-32 and [Pyr1]apelin-13 were assessed by magnet resonance imaging and cardiac catheterization in anesthetized rats. Cardiopulmonary human and rat tissues from PAH patients and monocrotaline (MCT) and Sugen/hypoxia exposed rats were used to show changes in ELA expression in PAH. The effect of ELA treatment on cardiopulmonary remodeling in PAH was investigated in the MCT rat model.Results—ELA competed for binding of apelin in human heart with overlap for the two peptides indicated by in silico modeling. ELA activated G protein- and Β-arrestin-dependent pathways. We detected ELA expression in human vascular endothelium and plasma. Comparable to apelin, ELA increased cardiac contractility, ejection fraction, cardiac output and elicited vasodilatation in rat in vivo. ELA expression was reduced in cardiopulmonary tissues from PAH patients and PAH rat models, respectively. ELA treatment significantly attenuated elevation of right ventricular systolic pressure and right ventricular hypertrophy and pulmonary vascular re
Weber RJM, Lawson TN, Salek RM, et al., 2016, Computational tools and workflows in metabolomics: An international survey highlights the opportunity for harmonisation through Galaxy, Metabolomics, Vol: 13, ISSN: 1573-3890
Ain QU, Owen RM, Omoto K, et al., 2016, Analysis of differential efficacy and affinity of GABA(A) (alpha 1/alpha 2) selective modulators, Molecular Pharmaceutics, Vol: 13, Pages: 4001-4012, ISSN: 1543-8392
Selective modulators of the γ-amino butyric acid (GABAA) family of receptors have the potential to treat a range of disease states related to cognition, pain, and anxiety. While the development of various α subunit-selective modulators is currently underway for the treatment of anxiety disorders, a mechanistic understanding of the correlation between their bioactivity and efficacy, based on ligand–target interactions, is currently still lacking. In order to alleviate this situation, in the current study we have analyzed, using ligand- and structure-based methods, a data set of 5440 GABAA modulators. The Spearman correlation (ρ) between binding activity and efficacy of compounds was calculated to be 0.008 and 0.31 against the α1 and α2 subunits of GABA receptor, respectively; in other words, the compounds had little diversity in structure and bioactivity, but they differed significantly in efficacy. Two compounds were selected as a case study for detailed interaction analysis due to the small difference in their structures and affinities (ΔpKi(comp1_α1 – comp2_α1) = 0.45 log units, ΔpKi(comp1_α2 – comp2_α2) = 0 log units) as compared to larger relative efficacies (ΔRE(comp1_α1 – comp2_α1) = 1.03, ΔRE(comp1_α2 – comp2_α2) = 0.21). Docking analysis suggested that His-101 is involved in a characteristic interaction of the α1 receptor with both compounds 1 and 2. Residues such as Phe-77, Thr-142, Asn-60, and Arg-144 of the γ chain of the α1γ2 complex also showed interactions with heterocyclic rings of both compounds 1 and 2, but these interactions were disturbed in the case of α2γ2 complex docking results. Binding pocket stability analysis based on molecular dynamics identified three substitutions in the loop C region of the α2 subunit, namely, G200E, I201T, and V202I, causing a reduction in the flexib
Glen RC, Green M, Ginger R, 2016, Skin Lightening Composition, US2016243015 (A1) ― 2016-08-25
Desired skin colour is a major unmet consumer need around the world and especially in Asia. Consumers particularly desire even skin colour, absence of age spots (solar lentigines), absence of hyperpigmentation and lighter overall skin tone. One solution is to use biological actives that reduce the activity of melanocyte cells in skin. These cells, present in the basal layer of the epidermis, make the dark coloured pigment melanin and export it, in small export vesicles called melanosomes, to the neighbouring keratinocytes. It is well described in the literature that compounds which reduce melanin synthesis when topically applied to the skin will reduce skin darkness over time and can generate a more even skin tone. Tyrosinase is a very popular target for the regulation of melanocyte pigment production. However effective inhibitors of tyrosinase are bedevilled by safety issues causing, for example, melanocyte cell death, permanent depigmentation, irritation and allergic reactions. Often effective inhibitors kill melanocytes (for example hydroquinone) or cause sensitisation reactions. There is therefore a great need for safe and effective inhibitors of skin pigment production that work through an alternative safe mechanism. The inventors have observed that selected compounds of the same generic structure: or a salt thereof; wherein R1, R2, R3, R4 and R5 may be independently selected from the group consisting of —H, -halide, and methyl, ethyl, propyl, iso-propyl, butyl, and t-butyl moieties, inhibit melanin production in Melanoderms™.
Glen RC, Read C, Fitzpatrick CM, et al., 2016, Cardiac action of the first G protein biased small molecule apelin agonist, Biochemical Pharmacology, Vol: 116, Pages: 63-72, ISSN: 1873-2968
Apelin peptide analogues displaying bias towards G protein signalling pathways have beneficial cardiovascular actions compared with the native peptide in humans in vivo. Our aim was to determine whether small molecule agonists could retain G protein bias. We have identified a biased small molecule, CMF-019, and characterised it in vitro and in vivo.In competition radioligand binding experiments in heart homogenates, CMF-019 bound to the human, rat and mouse apelin receptor with high affinity (pKi = 8.58 ± 0.04, 8.49 ± 0.04 and 8.71 ± 0.06 respectively). In cell-based functional assays, whereas, CMF-019 showed similar potency for the Gαi pathway to the endogenous agonist [Pyr1]apelin-13 (pD2 = 10.00 ± 0.13 vs 9.34 ± 0.15), in β-arrestin and internalisation assays it was less potent (pD2 = 6.65 ± 0.15 vs 8.65 ± 0.10 and pD2 = 6.16 ± 0.21 vs 9.28 ± 0.10 respectively). Analysis of these data demonstrated a bias of ∼400 for the Gαi over the β-arrestin pathway and ∼6000 over receptor internalisation. CMF-019 was tested for in vivo activity using intravenous injections into anaesthetised male Sprague–Dawley rats fitted with a pressure-volume catheter in the left ventricle. CMF-019 caused a significant increase in cardiac contractility of 606 ± 112 mmHg/s (p < 0.001) at 500 nmol. CMF-019 is the first biased small molecule identified at the apelin receptor and increases cardiac contractility in vivo. We have demonstrated that Gαi over β-arrestin/internalisation bias can be retained in a non-peptide analogue and predict that such bias will have the therapeutic benefit following chronic use. CMF-019 is suitable as a tool compound and provides the basis for design of biased agonists with improved pharmacokinetics for treatment of cardiovascular conditions such as pulmonary arterial hypertension.
Glen RC, Galloway WRJD, Spring DR, et al., 2016, Multiple-parameter optimization in drug discovery: example of the 5-HT1B GPCR, Molecular Informatics, Vol: 35, Pages: 599-605, ISSN: 1868-1743
Early phase drug discovery is a multi-parameter optimisation process. Finding drugable targets, discovering starting points for lead optimisation and creating novel structures with new biological properties within these constraints is challenging. As an example of a drug optimisation strategy, recent work on 5-HT1B antagonists will be described. This is put in the context of the drugability of the target, the desired physicochemical properties of the desired molecules and approaches to compound design to create high affinity, selective molecules that are optimised to have low Central Nervous System (CNS) penetration.
Fechner U, de Graaf C, Torda AE, et al., 2016, 11th German Conference on Chemoinformatics (GCC 2015) : Fulda, Germany. 8-10 November 2015., Journal of Cheminformatics, Vol: 8, Pages: 18-18, ISSN: 1758-2946
Allen CHG, Koutsoukas A, Cortes-Ciriano I, et al., 2016, Improving the prediction of organism-level toxicity through integration of chemical, protein target and cytotoxicity qHTS data, Toxicology Research, Vol: 5, Pages: 883-894, ISSN: 2045-4538
Prediction of compound toxicity is essential because covering the vast chemical space requiring safety assessment using traditional experimentally-based, resource-intensive techniques is impossible. However, such prediction is nontrivial due to the complex causal relationship between compound structure and in vivo harm. Protein target annotations and in vitro experimental outcomes encode relevant bioactivity information complementary to chemicals’ structures. This work tests the hypothesis that utilizing three complementary types of data will afford predictive models that outperform traditional models built using fewer data types. A tripartite, heterogeneous descriptor set for 367 compounds was comprised of (a) chemical descriptors, (b) protein target descriptors generated using an algorithm trained on 190 000 ligand–protein interactions from ChEMBL, and (c) descriptors derived from in vitro cell cytotoxicity dose–response data from a panel of human cell lines. 100 random forests classification models for predicting rat LD50 were built using every combination of descriptors. Successive integration of data types improved predictive performance; models built using the full dataset had an average external correct classification rate of 0.82, compared to 0.73–0.80 for models built using two data types and 0.67–0.78 for models built using one. Pairwise comparisons of models trained on the same data showed that including a third data domain on top of chemistry improved average correct classification rate by 1.4–2.4 points, with p-values <0.01. Additionally, the approach enhanced the models’ applicability domains and proved useful for generating novel mechanism hypotheses. The use of tripartite heterogeneous bioactivity datasets is a useful technique for improving toxicity prediction. Both protein target descriptors – which have the practical value of being derived in silico – and cytotoxicity descriptors derived fro
Mussa HY, Mitchell JBO, Glen RC, 2015, A note on utilising binary features as ligand descriptors, Journal of Cheminformatics, Vol: 7, ISSN: 1758-2946
It is common in cheminformatics to represent the properties of a ligand as a string of 1’s and 0’s, with the intention ofelucidating, inter alia, the relationship between the chemical structure of a ligand and its bioactivity. In this commentarywe note that, where relevant but non-redundant features are binary, they inevitably lead to a classifier capableof capturing only a linear relationship between structural features and activity. If, instead, we were to use relevantbut non-redundant real-valued features, the resulting predictive model would be capable of describing a non-linearstructure-activity relationship. Hence, we suggest that real-valued features, where available, are to be preferred in thisscenario.
Braun H, Kirchmair J, Williamson MJ, et al., 2015, Molecular mechanism of a specific capsid binder resistance caused by mutations outside the binding pocket, Antiviral Research, Vol: 123, Pages: 138-145, ISSN: 1872-9096
Enteroviruses cause various acute and chronic diseases. The most promising therapeutics for these infections are capsid-binding molecules. These can act against a broad spectrum of enteroviruses, but emerging resistant virus variants threaten their efficacy. All known enterovirus variants with high-level resistance toward capsid-binding molecules have mutations of residues directly involved in the formation of the hydrophobic binding site. This is a first report of substitutions outside the binding pocket causing this type of drug resistance: I1207K and I1207R of the viral capsid protein 1 of coxsackievirus B3. Both substitutions completely abolish the antiviral activity of pleconaril (a capsid-binding molecule) but do not affect viral replication rates in vitro. Molecular dynamics simulations indicate that the resistance mechanism is mediated by a conformational rearrangement of R1095, which is a neighboring residue of 1207 located at the heel of the binding pocket. These in
Fuchs JE, Bender A, Glen RC, 2015, Cheminformatics research at the Unilever Centre for molecular science informatics Cambridge, Molecular Informatics, Vol: 34, Pages: 626-633, ISSN: 1611-020X
The Centre for Molecular Informatics, formerly Unilever Centre for Molecular Science Informatics (UCMSI), at the University of Cambridge is a world‐leading driving force in the field of cheminformatics. Since its opening in 2000 more than 300 scientific articles have fundamentally changed the field of molecular informatics. The Centre has been a key player in promoting open chemical data and semantic access. Though mainly focussing on basic research, close collaborations with industrial partners ensured real world feedback and access to high quality molecular data. A variety of tools and standard protocols have been developed and are ubiquitous in the daily practice of cheminformatics. Here, we present a retrospective of cheminformatics research performed at the UCMSI, thereby highlighting historical and recent trends in the field as well as indicating future directions.
Murrell DS, Cortes-Ciriano I, van Westen GJP, et al., 2015, Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules, Journal of Cheminformatics, Vol: 7, ISSN: 1758-2946
BackgroundIn silico predictive models have proved to be valuable for the optimisation of compound potency, selectivity and safety profiles in the drug discovery process.Resultscamb is an R package that provides an environment for the rapid generation of quantitative Structure-Property and Structure-Activity models for small molecules (including QSAR, QSPR, QSAM, PCM) and is aimed at both advanced and beginner R users. camb's capabilities include the standardisation of chemical structure representation, computation of 905 one-dimensional and 14 fingerprint type descriptors for small molecules, 8 types of amino acid descriptors, 13 whole protein sequence descriptors, filtering methods for feature selection, generation of predictive models (using an interface to the R package caret), as well as techniques to create model ensembles using techniques from the R package caretEnsemble). Results can be visualised through high-quality, customisable plots (R package ggplot2).ConclusionsOverall, camb constitutes an open-source framework to perform the following steps: (1) compound standardisation, (2) molecular and protein descriptor calculation, (3) descriptor pre-processing and model training, visualisation and validation, and (4) bioactivity/property prediction for new molecules. camb aims to speed model generation, in order to provide reproducibility and tests of robustness. QSPR and proteochemometric case studies are included which demonstrate camb's application.
Glen R, Davenport A, 2015, Computational design and first-in-human studies of a biased (functionally selective) Apelin GPCR agonist, Publisher: AMER CHEMICAL SOC, ISSN: 0065-7727
Roessler F, Korb O, Glen R, et al., 2015, Knowledge-based approach to the parameterization of small molecule force fields based on crystal structures, Publisher: AMER CHEMICAL SOC, ISSN: 0065-7727
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.