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The Experts below are selected from a list of 73830 Experts worldwide ranked by ideXlab platform

Daniel J. Blumenthal - One of the best experts on this subject based on the ideXlab platform.

Brian R. Koch - One of the best experts on this subject based on the ideXlab platform.

John E. Bowers - One of the best experts on this subject based on the ideXlab platform.

Zhaoyang Hu - One of the best experts on this subject based on the ideXlab platform.

Ye Fang - One of the best experts on this subject based on the ideXlab platform.

  • Label-Free Cell Phenotypic Drug Discovery
    Combinatorial Chemistry & High Throughput Screening, 2014
    Co-Authors: Ye Fang
    Abstract:

    Phenotypic screen holds great potential in the discovery of new small molecule probes and drugs, as it permits interrogating small molecules with native targets and pathways in model organisms and disease relevant cells. In recent years, Label-Free cell phenotypic profiling has emerged as an alternative for drug discovery. This paper provides the rationale for phenotypic screens, discusses the basics of Label-Free cell phenotypic profiling technologies, and provides some guidelines as to how to use these techniques to facilitate drug discovery.

  • Label-Free drug discovery
    Frontiers in Pharmacology, 2014
    Co-Authors: Ye Fang
    Abstract:

    Current drug discovery is dominated by label-dependent molecular approaches, which screen drugs in the context of a predefined and target-based hypothesis in vitro. Given that target-based discovery has not transformed the industry, phenotypic screen that identifies drugs based on a specific phenotype of cells, tissues, or animals has gained renewed interest. However, owing to the intrinsic complexity in drug-target interactions, there is often a significant gap between the phenotype screened and the ultimate molecular mechanism of action sought. This paper presents a Label-Free strategy for early drug discovery. This strategy combines Label-Free cell phenotypic profiling with computational approaches, and holds promise to bridge the gap by offering a kinetic and holistic representation of the functional consequences of drugs in disease relevant cells that is amenable to mechanistic deconvolution.

  • Troubleshooting and deconvoluting Label-Free cell phenotypic assays in drug discovery.
    Journal of Pharmacological and Toxicological Methods, 2013
    Co-Authors: Ye Fang
    Abstract:

    Abstract Introduction: Central to drug discovery and development is to comprehend the target(s), potency, efficacy and safety of drug molecules using pharmacological assays. Owing to their ability to provide a holistic view of drug actions in native cells, Label-Free biosensor-enabled cell phenotypic assays have been emerging as new generation phenotypic assays for drug discovery. Despite the benefits associated with wide pathway coverage, high sensitivity, high information content, non-invasiveness and real-time kinetics, Label-Free cell phenotypic assays are often viewed to be a blackbox in the era of target-centric drug discovery. Methods: This article first reviews the biochemical and biological complexity of drug-target interactions, and then discusses the key characteristics of Label-Free cell phenotypic assays and presents a five-step strategy to troubleshooting and deconvoluting the Label-Free cell phenotypic profiles of drugs. Results: Drug-target interactions are intrinsically complicated. Label-Free cell phenotypic signatures of drugs mirror the innate complexity of drug-target interactions, and can be effectively deconvoluted using the five-step strategy. Discussion: The past decades have witnessed dramatic expansion of pharmacological assays ranging from molecular to phenotypic assays, which is coincident with the realization of the innate complexity of drug-target interactions. The clinical features of a drug are defined by how it operates at the system level and by its distinct polypharmacology, ontarget, phenotypic and network pharmacology. Approaches to examine the biochemical, cellular and molecular mechanisms of action of drugs are essential to increase the efficiency of drug discovery and development. Label-Free cell phenotypic assays and the troubleshooting and deconvoluting approach presented here may hold great promise in drug discovery and development.

  • The development of Label-Free cellular assays for drug discovery
    Expert Opinion on Drug Discovery, 2011
    Co-Authors: Ye Fang
    Abstract:

    Introduction: The need to improve drug research and development productivity continues to drive innovation in pharmacological assays. Technologies that can leverage the advantages of both molecular and phenotypic assays would hold great promise for discovery of new medicines. Areas covered: This article briefly reviews current Label-Free platforms for cell-based assays and is primarily focused on fundamental aspects of these assays using dynamic mass redistribution technology as an example. The article also presents strategies for relating Label-Free profiles to molecular modes of actions of drugs. Expert opinion: Emerging evidence suggests that Label-Free cellular assays are phenotypic in nature, yet permit molecular mechanistic deconvolution. Together with unique competency in throughput, sensitivity and pathway coverages, Label-Free cellular assays allow users to screen drugs against endogenous receptors in native cells (including disease relevant primary cells) and determine the molecular modes of act...

  • Label-Free Biosensors for Cell Biology
    International journal of electrochemistry, 2011
    Co-Authors: Ye Fang
    Abstract:

    Label-Free biosensors for studying cell biology have finally come of age. Recent developments have advanced the biosensors from low throughput and high maintenance research tools to high throughput and low maintenance screening platforms. In parallel, the biosensors have evolved from an analytical tool solely for molecular interaction analysis to powerful platforms for studying cell biology at the whole cell level. This paper presents historical development, detection principles, and applications in cell biology of Label-Free biosensors. Future perspectives are also discussed.