Molecular interaction networks and drug development: Novel approach to drug target identification and drug repositioning

Article Genetics & Heredity

A dynamic single cell-based framework for digital twins to prioritize disease genes and drug targets

Xinxiu Li et al.

Summary: This study presents a scalable framework for modeling dynamic changes in medical digital twins on cellulome- and genome-wide scales, in order to prioritize upstream regulators (URs) for biomarker and drug discovery.

GENOME MEDICINE (2022)

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Article Mathematical & Computational Biology

Comprehensive network medicine-based drug repositioning via integration of therapeutic efficacy and side effects

Paola Paci et al.

Summary: Despite advancements in modern medicine, cardiovascular disease continues to be the leading cause of death and illness worldwide. This article highlights the need for new approaches to improve drug treatments for cardiovascular disease. The study focuses on using computational methods based on omics data to reposition drugs and considers the side effects of drug candidates. The method provides a list of drug candidates for cardiovascular disease that are unlikely to produce common adverse side effects, and this approach can be applicable to other diseases as well.

NPJ SYSTEMS BIOLOGY AND APPLICATIONS (2022)

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Article Multidisciplinary Sciences

Identification of potent inhibitors of SARS-CoV-2 infection by combined pharmacological evaluation and cellular network prioritization

J. J. Patten et al.

Summary: The study evaluated pharmacologically active compounds with known biological targets for inhibiting SARS-CoV-2 infection. Through cell and tissue models, they identified several active small molecules and gained insights into host-virus interactions. The findings provide a rigorous approach for identifying potential treatments for viral diseases through the evaluation of host factor dependencies.

ISCIENCE (2022)

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Review Biochemical Research Methods

Deciphering molecular interactions by proximity labeling

Wei Qin et al.

Summary: This article introduces the proximity labeling technology for studying and applying molecular interactions. By fusing baits with promiscuous enzymes, endogenous molecules interacting with them can be tagged and identified by mass spectrometry or nucleic acid sequencing. PL technology has been used to map protein-protein, protein-RNA, and protein-DNA interactions.

NATURE METHODS (2021)

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Article Mathematical & Computational Biology

Gene co-expression in the interactome: moving from correlation toward causation via an integrated approach to disease module discovery

Paola Paci et al.

Summary: This study integrates co-expression network analysis with human interactome network to predict novel disease genes and relationships. Switch genes associated with specific disorders tend to form subnetworks in the interactome network, allowing efficient screening of potential new disease gene associations. The findings provide insights on elucidating the molecular basis of human disease and revealing commonalities between seemingly unrelated diseases.

NPJ SYSTEMS BIOLOGY AND APPLICATIONS (2021)

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Article Multidisciplinary Sciences

Individualized interactomes for network-based precision medicine in hypertrophic cardiomyopathy with implications for other clinical pathophenotypes

Bradley A. Maron et al.

Summary: This study analyzed tissue from patients with obstructive hypertrophic cardiomyopathy and heart failure to develop individualized protein-protein interaction networks using RNA-Seq technology. The findings showed that this approach can distinguish between different types of cardiomyopathy and provide key insights into patient-level pathobiology and clinically relevant characteristics of complex diseases.

NATURE COMMUNICATIONS (2021)

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Article Multidisciplinary Sciences

Network medicine framework for identifying drug-repurposing opportunities for COVID-19

Deisy Morselli Gysi et al.

Summary: The study utilized multiple algorithms to rank a large number of drugs, finding that combining the consensus of various predictive methods significantly improves the success rate of drug screening and proposes new medications for treating COVID-19. Furthermore, it was discovered that the majority of drugs successfully reducing viral infection do not bind to the target proteins of SARS-CoV-2, suggesting a network-based mechanism rather than docking strategies.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2021)

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Article Biochemistry & Molecular Biology