Exploring the origin of the ion selectivity of the KcsA potassium channel.
The availability of structural information about biological ion channels provides an opportunity to gain a detailed understanding of the control of ion selectivity by biological systems. However, accomplishing this task by computer simulation approaches is very challenging. First, although the activation barriers for ion transport can be evaluated by microscopic simulations, it is hard to obtain accurate results by such approaches. Second, the selectivity is related to the actual ion current and not directly to the individual activation barriers. Thus, it is essential to simulate the ion currents and this cannot be accomplished at present by microscopic MD approaches. In order to address this challenge, we developed and refined an approach capable of evaluating ion current while still reflecting the realistic features of the given channel. Our method involves generation of semimacroscopic free energy surfaces for the channel/ions system and Brownian dynamics (BD) simulations of the corresponding ion current. In contrast to most alternative macroscopic models, our approach is able to reproduce the difference between the free energy surfaces of different ions and thus to address the selectivity problem. Our method is used in a study of the selectivity of the KcsA channel toward the K+ and Na+ ions. The BD simulations with the calculated free energy profiles produce an appreciable selectivity. To the best of our knowledge, this is the first time that the trend in the selectivity in the ion current is produced by a computer simulation approach. Nevertheless, the calculated selectivity is still smaller than its experimental estimate. Recognizing that the calculated profiles are not perfect, we examine how changes in these profiles can account for the observed selectivity. It is found that the origin of the selectivity is more complex than generally assumed. The observed selectivity can be reproduced by increasing the barrier at the exit and the entrance of the selectivity filter, but the necessary changes in the barrier approach the limit of the error in the PDLD/S-LRA calculations. Other options that can increase the selectivity are also considered, including the difference between the Na+...Na+ and K+...K+ interaction. However, this interesting effect does not appear to lead to a major difference in selectivity since the Na+ ions at the limit of strong interaction tend to move in a less concerted way than the K+ ions. Changes in the relative binding energies at the different binding sites are also not so effective in changing the selectivity. Finally, it is pointed out that using the calculated profiles as a starting point and forcing the model to satisfy different experimentally based constraints, should eventually provide more detailed understanding of the different complex factors involved in ion selectivity of biological channels.
Burykin
Anton
A
Department of Chemistry, University of Southern California, Los Angeles, California 90089-1062, USA.
Kato
Mitsunori
M
Warshel
Arieh
A
D000465:Algorithms; D001426:Bacterial Proteins / Q000737:chemistry* / Q000378:metabolism; D001667:Binding, Competitive; D002414:Cations, Monovalent / Q000737:chemistry / Q000378:metabolism; D003198:Computer Simulation; D011188:Potassium / Q000737:chemistry / Q000378:metabolism; D015221:Potassium Channels / Q000737:chemistry* / Q000378:metabolism; D012964:Sodium / Q000737:chemistry / Q000378:metabolism; D013816:Thermodynamics
D001426:Bacterial Proteins; D002414:Cations, Monovalent; D015221:Potassium Channels; C107790:prokaryotic potassium channel; D012964:Sodium; D011188:Potassium