CHARMM-GUI
Post-doctoral position in simulations of mechano-sensing ion channels
CHARMM-GUI, Chicago, Illinois, United States, 60290
CHARMM is a versatile program for atomic-level simulation of
many-particle systems, particularly macromolecules of
biological interest. - M. Karplus
Post-doctoral position in simulations of mechano-sensing ion channels
Date
2020-10-11 Location
University of Chicago Description
The individual will investigate how mechano-sensors perceive pressure and send signals that enable us to feel pain, hear, and sense when our muscles are moving or our lungs are filling. A failure in sensing can lead to deafness as well as pulmonary and respiratory diseases. The focus is on advancing our unique computational capabilities and identify the factors that govern the open-to-close transition of mechano-sensing ion channels including the 10,000 residue PIEZO1 in collaboration with experimental groups. The capabilities are centered around our new MD program Upside, an algorithm that can cooperatively fold proteins with an accuracy comparable to all-atom methods but in cpu-hours (1, 2). The use of an innovative global side chain packing calculation at every step smooths the energy surface, which largely explains the 10^3-10^4 fold speed up compared to standard MD and our ability to conduct dozens of AFM-induced unfolding simulations of 1000 residue membrane proteins (3, 4). Candidates should be versed in python and C, and running MD simulations, preferably with membrane proteins. References. 1. Jumper, J. M., N. F. Faruk, K. F. Freed, and T. R. Sosnick. 2018. Trajectory-based training enables protein simulations with accurate folding and Boltzmann ensembles in cpu-hours. PLoS Comput Biol 14(12):e1006578. 2. Jumper, J. M., N. F. Faruk, K. F. Freed, and T. R. Sosnick. 2018. Accurate calculation of side chain packing and free energy with applications to protein molecular dynamics. PLoS Comput Biol 14(12):e1006342. 3. Wang, Z., J. M. Jumper, K. F. Freed, and T. R. Sosnick. 2019. On the Interpretation of Force-Induced Unfolding Studies of Membrane Proteins Using Fast Simulations. Biophys J 117(8):1429-1144. 4. Wang, Z., J. M. Jumper, S. Wang, K. F. Freed, and T. R. Sosnick. 2018. A Membrane Burial Potential with H-Bonds and Applications to Curved Membranes and Fast Simulations. Biophys J 115(10):1872-1884. How to Apply
Please send CV and names of 3 references to Tobin Sosnick at trsosnic@uchicago.edu
#J-18808-Ljbffr
2020-10-11 Location
University of Chicago Description
The individual will investigate how mechano-sensors perceive pressure and send signals that enable us to feel pain, hear, and sense when our muscles are moving or our lungs are filling. A failure in sensing can lead to deafness as well as pulmonary and respiratory diseases. The focus is on advancing our unique computational capabilities and identify the factors that govern the open-to-close transition of mechano-sensing ion channels including the 10,000 residue PIEZO1 in collaboration with experimental groups. The capabilities are centered around our new MD program Upside, an algorithm that can cooperatively fold proteins with an accuracy comparable to all-atom methods but in cpu-hours (1, 2). The use of an innovative global side chain packing calculation at every step smooths the energy surface, which largely explains the 10^3-10^4 fold speed up compared to standard MD and our ability to conduct dozens of AFM-induced unfolding simulations of 1000 residue membrane proteins (3, 4). Candidates should be versed in python and C, and running MD simulations, preferably with membrane proteins. References. 1. Jumper, J. M., N. F. Faruk, K. F. Freed, and T. R. Sosnick. 2018. Trajectory-based training enables protein simulations with accurate folding and Boltzmann ensembles in cpu-hours. PLoS Comput Biol 14(12):e1006578. 2. Jumper, J. M., N. F. Faruk, K. F. Freed, and T. R. Sosnick. 2018. Accurate calculation of side chain packing and free energy with applications to protein molecular dynamics. PLoS Comput Biol 14(12):e1006342. 3. Wang, Z., J. M. Jumper, K. F. Freed, and T. R. Sosnick. 2019. On the Interpretation of Force-Induced Unfolding Studies of Membrane Proteins Using Fast Simulations. Biophys J 117(8):1429-1144. 4. Wang, Z., J. M. Jumper, S. Wang, K. F. Freed, and T. R. Sosnick. 2018. A Membrane Burial Potential with H-Bonds and Applications to Curved Membranes and Fast Simulations. Biophys J 115(10):1872-1884. How to Apply
Please send CV and names of 3 references to Tobin Sosnick at trsosnic@uchicago.edu
#J-18808-Ljbffr