Dataset Information

Multiscale modelling of relationships between protein classes and drug behavior across all diseases using the CANDO platform.

ABSTRACT: We have examined the effect of eight different protein classes (channels, GPCRs, kinases, ligases, nuclear receptors, proteases, phosphatases, transporters) on the benchmarking performance of the CANDO drug discovery and repurposing platform (http://protinfo.org/cando). The first version of the CANDO platform utilizes a matrix of predicted interactions between 48278 proteins and 3733 human ingestible compounds (including FDA approved drugs and supplements) that map to 2030 indications/diseases using a hierarchical chem and bio-informatic fragment based docking with dynamics protocol (> one billion predicted interactions considered). The platform uses similarity of compound-proteome interaction signatures as indicative of similar functional behavior and benchmarking accuracy is calculated across 1439 indications/diseases with more than one approved drug. The CANDO platform yields a significant correlation (0.99, p-value < 0.0001) between the number of proteins considered and benchmarking accuracy obtained indicating the importance of multitargeting for drug discovery. Average benchmarking accuracies range from 6.2 % to 7.6 % for the eight classes when the top 10 ranked compounds are considered, in contrast to a range of 5.5 % to 11.7 % obtained for the comparison/control sets consisting of 10, 100, 1000, and 10000 single best performing proteins. These results are generally two orders of magnitude better than the average accuracy of 0.2% obtained when randomly generated (fully scrambled) matrices are used. Different indications perform well when different classes are used but the best accuracies (up to 11.7% for the top 10 ranked compounds) are achieved when a combination of classes are used containing the broadest distribution of protein folds. Our results illustrate the utility of the CANDO approach and the consideration of different protein classes for devising indication specific protocols for drug repurposing as well as drug discovery.

SUBMITTER: Sethi G

PROVIDER: S-EPMC5903852 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Multiscale modelling of relationships between protein classes and drug behavior across all diseases using the CANDO platform.

Sethi Geetika G Chopra Gaurav G Samudrala Ram R

Mini reviews in medicinal chemistry 20150101 8

We have examined the effect of eight different protein classes (channels, GPCRs, kinases, ligases, nuclear receptors, proteases, phosphatases, transporters) on the benchmarking performance of the CANDO drug discovery and repurposing platform (http://protinfo.org/cando). The first version of the CANDO platform utilizes a matrix of predicted interactions between 48278 proteins and 3733 human ingestible compounds (including FDA approved drugs and supplements) that map to 2030 indications/diseases u ...[more]

PMID: 25694071

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Project description:Objective:Rapid eye movement sleep behavior disorder (RBD) is characterized by dream enactment and loss of muscle atonia during rapid eye movement sleep. RBD is closely related to ?-synucleinopathies including Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. Many studies have investigated the markers of imaging and neurophysiological, genetic, cognitive, autonomic function of RBD and their predictive value for neurodegenerative diseases. This report reviewed the progress of these studies and discussed their limitations and future research directions. Data Sources:Using the combined keywords: "RBD", "neurodegenerative disease", "Parkinson disease", and "magnetic resonance imaging", the PubMed/MEDLINE literature search was conducted up to January 1, 2018. Study Selection:A total of 150 published articles were initially identified citations. Of the 150 articles, 92 articles were selected after further detailed review. This study referred to all the important English literature in full. Results:Single-nucleotide polymorphisms in SCARB2 (rs6812193) and MAPT (rs12185268) were significantly associated with RBD. The olfactory loss, autonomic dysfunction, marked electroencephalogram slowing during both wakefulness and rapid eye movement sleep, and cognitive impairments were potential predictive markers for RBD conversion to neurodegenerative diseases. Traditional structural imaging studies reported relatively inconsistent results, whereas reduced functional connectivity between the left putamen and substantia nigra and dopamine transporter uptake demonstrated by functional imaging techniques were relatively consistent findings. Conclusions:More longitudinal studies should be conducted to evaluate the predictive value of biomarkers of RBD. Moreover, because the glucose and dopamine metabolisms are not specific for assessing cognitive cognition, the molecular metabolism directly related to cognition should be investigated. There is a need for more treatment trials to determine the effectiveness of interventions of RBD on preventing the conversion to neurodegenerative diseases.

Dataset Information

Multiscale modelling of relationships between protein classes and drug behavior across all diseases using the CANDO platform.

Publications

Multiscale modelling of relationships between protein classes and drug behavior across all diseases using the CANDO platform.

Similar Datasets

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