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Computational Design and Simulation of a Cyclized Dimeric Multipass Transmembrane Protein

Undergraduate #23
Discipline: Chemistry and Chemical Sciences
Subcategory: Biochemistry (not Cell and Molecular Biology and Genetics)

Jonathan Aldana-Mendoza - California State University, Los Angeles
Co-Author(s): Marco Mravic, University of California, San Francisco;William DeGrado, University of California, San Francisco



Transmembrane (TM) proteins play critical roles in cell surface markers, receptors, and can serve as channels for molecular transport. Therefore characterizing this structural class of proteins is important for understanding a wide variety of cellular functions. With the influx of solved structures of alpha helical TM proteins, we are better equipped to address the unique structural characteristics of these proteins. We hypothesize that a de novo design and synthesis of a tm protein cold be carried out with accurate atomic level prediction of its tertiary structure. We based our design on the characterized GX6¬¬G motif of alpha-helical proteins; to set parameters for searching naturally occurring alpha-helices in the PDB. Then using these naturally occurring proteins to analyze any sequence preference given the alpha-helical structure. We plan on validating our design and simulation through the synthesis of this peptide using solid phase Fmoc synthesis. Structure analysis will be performed on the product through circular dichroism, infrared/vibrational, and NMR spectroscopy. The synthesis and accurate prediction of this alpha-helical tm protein, will demonstrate our capacity to predict structures of tm proteins that contain the sequence/structural motifs through in cooperation in a rational design. Enabling us to rationally design tm proteins, or small molecules that target tm proteins, and therefore have powerful therapeutic potential.

Funder Acknowledgement(s): NIH Grant # GM 49001, CSU-LSAMP is supported by the National Science Foundation under Grant # HRD-1302873 and the CSU Office of the Chancellor

Faculty Advisor: Marco Mravic, wiilai.degrado@ucs.edu

Role: I participated in all parts of the research.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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