Mechanosensitive channel proteins (MscL) proteins are viable pharmaceutical drug targets for development of precursors or antibiotics. To this end, understanding the gating mechanism of MscL is necessary to achieve rational drug design. Although many research articles have been published in the last 10 years using variable techniques including FRET and the state-of-the-art molecular simulations techniques, there is still much unknown about the function of the drug targets, such as the essential role of lipids in the mechanosensitive channel gating. Particularly, a fully open-channel MscL structure has not been experimentally determined or modelled, hindering the pace of discovering novel modulators which can trigger and then stabilize the open-channel structures of MscL.
Given the vital role of MscL drug targets in the development of novel antibiotics, it is of a great interest to continue to elucidate the MscL gating mechanisms and based on that to screen or de novo design novel chemicals to modulate the functions of MscL proteins. There are two goals for this Research Topic: (i) to understand the gating mechanisms of MscL proteins using variable molecular modeling and simulation techniques, and ideally some high-quality open-channel structures can be predicted; (ii) to conduct virtual screening or de novo design novel modulators of MscL gating mechanism, and ideally the function of those modulators can be confirmed experimentally or validated using in silico methods.
We welcome Original Research, Review, Mini Review and Perspective articles on themes including, but not limited to:
• Application of molecular simulations and free energy analysis studying the detailed MscL gating mechanisms
• Studying the essential role of lipids in mechanosensitive channel gating
• Simulation of the MscL gating procedure
• Determination and/or modelling of the open-channel MscL structures
• Identification of residues which are essential for MscL gating
• Identification of allosteric ligand binding sites
• Discovery of novel chemicals to modulate MscL gating using virtual screening and de novo design
• Application of machine learning and deep learning to study the structure, dynamics and function of MscL proteins
Mechanosensitive channel proteins (MscL) proteins are viable pharmaceutical drug targets for development of precursors or antibiotics. To this end, understanding the gating mechanism of MscL is necessary to achieve rational drug design. Although many research articles have been published in the last 10 years using variable techniques including FRET and the state-of-the-art molecular simulations techniques, there is still much unknown about the function of the drug targets, such as the essential role of lipids in the mechanosensitive channel gating. Particularly, a fully open-channel MscL structure has not been experimentally determined or modelled, hindering the pace of discovering novel modulators which can trigger and then stabilize the open-channel structures of MscL.
Given the vital role of MscL drug targets in the development of novel antibiotics, it is of a great interest to continue to elucidate the MscL gating mechanisms and based on that to screen or de novo design novel chemicals to modulate the functions of MscL proteins. There are two goals for this Research Topic: (i) to understand the gating mechanisms of MscL proteins using variable molecular modeling and simulation techniques, and ideally some high-quality open-channel structures can be predicted; (ii) to conduct virtual screening or de novo design novel modulators of MscL gating mechanism, and ideally the function of those modulators can be confirmed experimentally or validated using in silico methods.
We welcome Original Research, Review, Mini Review and Perspective articles on themes including, but not limited to:
• Application of molecular simulations and free energy analysis studying the detailed MscL gating mechanisms
• Studying the essential role of lipids in mechanosensitive channel gating
• Simulation of the MscL gating procedure
• Determination and/or modelling of the open-channel MscL structures
• Identification of residues which are essential for MscL gating
• Identification of allosteric ligand binding sites
• Discovery of novel chemicals to modulate MscL gating using virtual screening and de novo design
• Application of machine learning and deep learning to study the structure, dynamics and function of MscL proteins
