Overview

We are an interdisciplinary lab combining methods in data analytics, chemical biology and proteomics to 1) elucidate the general principles governing how biomolecular interactions are organized and regulated to carry out cellular functions, with a focus on 2) understanding how the organization is modulated in human diseases and perturbed by chemicals. A tenet guiding our research is cellular activities arise from a myriad of physical interactions between proteins with metabolites, nucleic acids, lipids and other proteins that are regulated in time and space. As such, we develop novel experimental techniques and computational methods for system profiling of biomolecular interaction networks underlying various cellular phenotypes. We also integrate our interaction data with other “omics” data to understand the interplay between different regulatory systems in the cells with applications for cell biology, toxicology and pharmacology. Our research activities can be broadly categorized under:

Development of internOmics tools and technologies

 We had the privilege of contributing to the extension of CETSA (Cellular Thermal Shift Assay) with protein mass spectrometry for label-free identification of drug and metabolite interaction with endogenous proteins (Huber et al., Nature 2015). Recently, we developed a novel technique for elucidating the complex and temporal network of protein-protein interactions in the cell. This biophysics-based method, termed Thermal Proximity Co-aggregation (TPCA) profiling (Tan et al. Science 2018), arguably is the only method applicable for the system-wide study of protein complex dynamics in primary cell and tissues presently. We are further developing TPCA and associated computational methods toward constructing cell- and context-specific interaction networks. Concurrently, we develop computational approaches to integrate our physical interaction data with other “omics” data for deciphering the interplay between different regulatory systems. These “omics” interaction assays and data integration methods collectively refer by us as internOmics.

Fig. 1. Principle of Thermal Proximity Co-aggregation for proteome-wide mapping of protein-protein interaction. Interacting proteins in cells co-aggregate upon heat denaturation that can be quantified from their solubility profile across different temperatures. For more information, please refer to our proof-of-concept paper in Science and the perspective article on the work.

Mechanism-of-action studies and target discovery

Our lab studies how chemicals can perturb proteins and rewire biomolecular interaction networks leading to diseased phenotypes, and conversely, how chemicals (drug inclusive) can be used to alter cellular behaviors for therapeutic or industrial purposes. Toward these goals, we deploy existing and develop novel internOmics tools for in-depth mechanism-of-action (MOA) characterization of repurposed drugs and bioactive compounds. We seek to identify the initiating binding events and elucidating their downstream pathways, and work closely with collaborators to expedite experimental validation. We are particularly interested in elucidating the MOA and charting the biosynthesis pathway of bioactive natural products. Through this chemical biology approach, we hope to complement the genetic approach to expedite the discovery of new drug targets and biology. Working closely with collaborators, we are also deploying our internOmics tools to study how cellular networks are (re)wired in different cellular states and diseased conditions, with the goal of identifying the protein complexes driving disease progression for prognosis and therapeutic intervention.

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