MAPPS: A Web-Based Tool for Metabolic Pathway Prediction and Network Analysis in the Postgenomic Era

Riaz, Muhammad Rizwan; Preston, Gail; Mithani, Aziz

doi:10.1021/acssynbio.9b00397

Cited by 17 publications

(7 citation statements)

References 70 publications

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“…Recently, some noteworthy web-based tools for network analysis centered on metabolomics data or metabolic pathways have been developed, such as the Metabolic network Analysis and Pathway Prediction Server (MAPPS) and the integrated Metabolomics Analysis Platform (iMAP). MAPPS provides various analytical resources including pathway prediction based on public databases, metabolic reachability, metabolite-specific reactions, network building and comparison [24]. iMAP also provides functions for network construction, visualization, and analysis with a user-friendly interface [25].…”

Section: Network Structure Visualization and Analysismentioning

confidence: 99%

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Network Analysis in Systems Epidemiology

Park

Choi

2021

JPMPH

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Traditional epidemiological studies have identified a number of risk factors for various diseases using regression-based methods that examine the association between an exposure and an outcome (i.e., one-to-one correspondences). One of the major limitations of this approach is the "black-box" aspect of the analysis, in the sense that this approach cannot fully explain complex relationships such as biological pathways. With high-throughput data in current epidemiology, comprehensive analyses are needed. The network approach can help to integrate multi-omics data, visualize their interactions or relationships, and make inferences in the context of biological mechanisms. This review aims to introduce network analysis for systems epidemiology, its procedures, and how to interpret its findings.

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Section: Network Structure Visualization and Analysismentioning

confidence: 99%

“…Although both tools focus primarily on metabolite data, these tools allow users to analyze omics data with additional transcriptomics or proteomics data sets. However, the papers presenting those tools still describe the use of Cytoscape for topological analysis or more personalized modifications [24,25].…”

Section: Network Structure Visualization and Analysismentioning

confidence: 99%

Network Analysis in Systems Epidemiology

Park

Choi

2021

JPMPH

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“…Ruppin and colleagues leveraged large-scale genomics and RNA sequencing data to generate statistical evidence for synthetic lethality, leading to the prediction of novel combination therapy that were retrospectively tested in clinical trials [22][23][24] . The MAPPS framework from Riaz et al provides a drug target identification functionality based on KEGG metabolic networks based on a predefined lists of source and target metabolite lists 25 .…”

Section: Introductionmentioning

confidence: 99%

piTracer - Automatic reconstruction of molecular cascades for the identification of synergistic drug targets

Gomari

Achkar

Benedetti

et al. 2023

Preprint

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Cancer cells frequently undergo metabolic reprogramming as a mechanism of resistance against chemotherapeutic drugs. Metabolomic profiling provides a direct readout of metabolic changes and can thus be used to identify these tumor escape mechanisms. Here, we introduce piTracer, a computational tool that uses multi-scale molecular networks to identify potential combination therapies from pre- and post-treatment metabolomics data. We first demonstrate piTracer's core ability to reconstruct cellular cascades by inspecting well-characterized molecular pathways and previously studied associations between genetic variants and metabolite levels. We then apply a new gene ranking algorithm on differential metabolomic profiles from human breast cancer cells after glutaminase inhibition. Four of the automatically identified gene targets were experimentally tested by simultaneous inhibition of the respective targets and glutaminase. Of these combination treatments, two were be confirmed to induce synthetic lethality in the cell line. In summary, piTracer integrates the molecular monitoring of escape mechanisms into comprehensive pathway networks to accelerate drug target identification. The tool is open source and can be accessed at https://github.com/krumsieklab/pitracer.

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“…There are various tools available for this purpose, including the prediction of chokepoints for drug-target identification. This process involves identifying metabolic reactions that either consume a unique substrate or produce a unique product, which can then be used as potential drug targets [11][12][13]. In general, both the non-structural and structural proteins of HCV are crucial to the viral life cycle and represent critical targets for antiviral therapies.…”

Section: Introductionmentioning

confidence: 99%

Computational Medicinal Chemistry applications to cure Asian-prevalent strain of Hepatitis C Virus

Hussain

Haider

Khalid

et al. 2023

Preprint

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Hepatitis C Virus (HCV), affecting millions of people worldwide, is the leading cause of the liver disorder, cirrhosis, and hepatocellular carcinoma. HCV is genetically diverse having eight gen-otypes and several subtypes predominant in different regions of the globe. The HCV NS3/4A protease is a primary therapeutic target for HCV with various FDA-approved antivirals and several clinical developments. However, available protease inhibitors (PIs) have lower potency against HCV genotype 3 (GT3), prevalent in South Asia. In this study, the incumbent computational tools were utilized to understand and explore interactions of the HCV GT3 receptor with the potential inhibitors after the virtual screening of one million compounds retrieved from the ZINC database. The molecular dynamics, pharmacological studies, and experimental studies uncovered the potential PIs as ZINC000224449889, ZINC000224374291, and ZINC000224374456 and derivative of ZINC000224374456 from the ZINC library. The study revealed that these top hit compounds exhibited good binding and better pharmacokinetics properties that might be considered the most promising compound against HCV GT3 protease. Viability test, on primary healthy Human Gingival Fibroblasts (HGFs) and cancerous AGS cell line were also performed to assess their safety profile after administration. In addition, Surface Plasmon Resonance (SPR) was also performed for determination of affinity and kinetics of synthesized compounds with target proteins.

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MAPPS: A Web-Based Tool for Metabolic Pathway Prediction and Network Analysis in the Postgenomic Era

Cited by 17 publications

References 70 publications

Network Analysis in Systems Epidemiology

Network Analysis in Systems Epidemiology

piTracer - Automatic reconstruction of molecular cascades for the identification of synergistic drug targets

Computational Medicinal Chemistry applications to cure Asian-prevalent strain of Hepatitis C Virus

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