Integral membrane proteins (IMPs) are of both fundamental scientific and medical importance, because they govern the flow of nutrients and information across cell membranes and because they comprise the largest class of therapeutic drug targets. However, the structural and biophysical characterization of IMPs lags far behind that of other protein classes, due to the inability to reliably produce significant quantities of IMPs for experimental studies. The fundamental gap in knowledge is that no framework currently exists for understanding the connection between the amino-acid and nucleotide sequence of an IMP and its expression level, and the fundamental gap in technology is that no successful strategies exist for the general prediction and improvement IMP expression levels. The current work will remove these fundamental gaps in knowledge and technology via the innovative combination of (i) experimental methods to characterize IMP expression levels, spanning across multiple protein families and expression systems, (ii) rigorous data-driven strategies to disentangle the role of diverse IMP sequence properties on expression, and (iii) coarse-grained molecular dynamics methods to enable the simulation - on unbiased biological timescales - of key mechanistic steps that act as bottlenecks to IMP expression. The proposed collaboration of the Miller and Clemons laboratories at Caltech is uniquely positioned to succeed in this effort, creating the opportunity for a new paradigm for the rational expression of IMPs. Success of the proposed research will have transformational impact by providing powerful and accessible computational tools for increased IMP expression to the research community, by advancing the fundamental characterization of this large and important class of proteins, and by accelerating medical and pharmaceutical applications.
The largest class of molecules targeted by therapeutic drugs are integral membrane proteins (IMPs), which are central to biology as they facilitate the delivery of nutrients and information across cellular membranes; yet their biophysical characterization has been slow due to the difficulty of reliably producing significant quantities for experimental studies. The proposed work aims to bridge a fundamental gap in knowledge by identifying the connection between the genetically encoded sequence of an IMP and the amount that can be produced. The work is enabled by a unique team which will use a diverse array of techniques, including molecular dynamics, computational data sciences, and experimental biochemistry, to develop tools that will broadly enable the scientific community.
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| Niesen, Michiel J M; Wang, Connie Y; Van Lehn, Reid C et al. (2017) Structurally detailed coarse-grained model for Sec-facilitated co-translational protein translocation and membrane integration. PLoS Comput Biol 13:e1005427 |
