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Certain proteins have the propensity to bind to negatively curved membranes and generate negative membrane curvature. The mechanism of action of these proteins is much less studied and understood than those that sense and generate positive curvature. In this work, we use implicit membrane modeling to explore the mechanism of an important negative curvature sensing and generating protein: the main ESCRT III subunit Snf7. We find that Snf7 monomers alone can sense negative curvature and that curvature sensitivity increases for dimers and trimers. We have observed spontaneous bending of Snf7 oligomers into circular structures with preferred radius of ~20 nm. The preferred curvature of Snf7 filaments is further confirmed by the simulations of preformed spirals on a cylindrical membrane surface. Snf7 filaments cannot bind with the same interface to flat and curved membranes. We find that even when a filament has the preferred radius, it is always less stable on the flat membrane surface than on the interior cylindrical membrane surface. This provides an additional energy for membrane bending which has not been considered in the spiral spring model. Furthermore, the rings on the cylindrical spirals are bridged together by helix 4 and hence are extra stabilized compared to the spirals on the flat membrane surface.

 

Proton transport in aqueous systems occurs by making and breaking covalent bonds, a process that classical force fields cannot reproduce. Various attempts have been made to remedy this deficiency, by valence bond theory or instantaneous proton transfers, but the ability of such methods to provide a realistic picture of this fundamental process has not been fully evaluated. Here we compare an ab initio molecular dynamics (AIMD) simulation of an excess proton in water to a simulation of a classical H3O+ in TIP3P water. The energy gap upon instantaneous proton transfer from H3O+ to an acceptor water molecule is much higher in the classical simulation than in the AIMD configurations evaluated with the same classical potential. The origins of this discrepancy are identified by comparing the solvent structures around the excess proton in the two systems. One major structural difference is in the tilt angle of the water molecules that accept an hydrogen bond from H3O+. The lack of lone pairs in TIP3P produces a tilt angle that is too large and generates an unfavorable geometry after instantaneous proton transfer. This problem can be alleviated by the use of TIP5P, which gives a tilt angle much closer to the AIMD result. Another important factor that raises the energy gap is the different optimal distance in water-water vs H3O+-water H-bonds. In AIMD the acceptor is gradually polarized and takes a hydronium-like configuration even before proton transfer actually happens. Ways to remedy some of these problems in classical simulations are discussed.

 

Acid ionization constants (pK a ’s) of titratable amino acid side chains have received a large amount of experimental and theoretical attention. In many situations, however, the rates of protonation and deprotonation, k on and k off , may also be important, for example, in understanding the mechanism of action of proton channels or membrane proteins that couple proton transport to other processes. Protonation and deprotonation involve the making and breaking of covalent bonds, which cannot be studied by classical force fields. However, environment effects on the rates should be captured by such methods. Here, we present an approach for estimating deprotonation rates based on Warshel’s extension of Marcus’s theory of electron transfer, with input from molecular simulations. The missing bond dissociation energy is represented by a constant term determined by fitting the pK a value in solution. The statistics of the energy gap between protonated and deprotonated states is used to compute free energy curves of the two states and, thus, free energy barriers, from which the rate can be deduced. The method is applied to Glu, Asp, and His in bulk solution and select membrane proteins: the M2 proton channel, bacteriorhodopsin, and cytochrome c oxidase.