This research will probe how our body?s mechano-sensors perceive pressure and send signals that enable us to feel pain, hear, and sense when our muscles are moving, our lungs are filling, and even when our stomachs are full. A failure in sensing can lead to deafness as well as pulmonary and respiratory diseases. Our body?s perception of force at the atomic level is a complicated process. Our pressure transducing mechano-sensors are proteins that are embedded in the outer layer, or membrane, of a cell. How the sensors and other membrane-imbedded proteins respond to force provides information on how they move and function. Computer simulations are an integral part of modern biological research as they augment many experimental studies and provide a test bed for our ideas on how biological molecules function. Computer simulations will be developed in this project to model the pressure sensing of different types of sensors and generally, the response of membrane proteins to force and pressure. The goal is to produce computational tools that have the detail, flexibility, and accuracy to conduct realistic simulations of the ?mechanobiology of membrane proteins.? This project will enhance the training of a diverse STEM workforce, including graduate students and postdoctoral scholars, and extend our nation?s leadership in biophysics.

Force, tension, and pressure are the major ingredients in mechanobiology. These quantities are often thought of macroscopically, but they are equally applicable at the molecular scale. The goal is to advance the unique computational capabilities of the researchers so as to accurately simulate the force-induced unfolding of membrane proteins and identify the factors that govern the open-to-close transition of mechano-sensing ion channels. The capabilities are centered around the researchers' new molecular dynamics program ?Upside?, an algorithm that can cooperatively fold small proteins with an accuracy comparable to all-atom methods but in CPU-hours using only physical principles. Upside employs 6 atoms per residue with the side chains being represented by directional-dependent beads whose packing probabilities have the lowest free energy. The use of this innovative, instantly equilibrated global side chain packing calculation at every step smooths the energy surface as side-chain friction is nearly eliminated. This largely explains the 103-104 fold speed up compared to standard MD and our ability to tackle the study of larger proteins. Critical to the success is the proper balancing of energy terms, achieved by training all force field parameters simultaneously. To conduct realistic simulations of mechano-sensing channels, the lateral pressure imposed by the membrane or ?force-from-lipids?, will be incorporated into the Upside algorithm as this factor is key to controlling the opening of the mechano-sensing ion channels.

This project is supported by the Molecular Biophysics Cluster of the Division of Molecular and Cellular Biosciences in Biological Sciences Directorate.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

National Science Foundation (NSF)
Division of Molecular and Cellular Biosciences (MCB)
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Jaroslaw Majewski
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University of Chicago
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