A Heuristic Derived from Analysis of the Ion Channel Structural Proteome Permits the Rapid Identification of Hydrophobic Gates

Abstract

Ion channel proteins control ionic flux across biological membranes through conformational changes in their transmembrane pores. An exponentially increasing number of channel structures captured in different conformational states are now being determined. However, these newlyresolved structures are commonly classified as either open or closed based solely on the physical dimensions of their pore and it is now known that more accurate annotation of their conductive state requires an additional assessment of the effect of pore hydrophobicity. A narrow hydrophobic gate region may disfavour liquid-phase water, leading to local de-wetting which will form an energetic barrier to water and ion permeation without steric occlusion of the pore. Here we quantify the combined influence of radius and hydrophobicity on pore de-wetting by applying molecular dynamics simulations and machine learning to nearly 200 ion channel structures. This allows us to propose a simple simulation-free heuristic model that rapidly and accurately predicts the presence of hydrophobic gates. This not only enables the functional annotation of new channel structures as soon as they are determined, but may also facilitate the design of novel nanopores controlled by hydrophobic gates. Significance statement:Ion channels are nanoscale protein pores in cell membranes. An exponentially increasing number of structures for channels means that computational methods for predicting their functional state are needed. Hydrophobic gates in ion channels result in local de-wetting of pores which functionally closes them to water and ion permeation. We use simulations of water behaviour within nearly 200 different ion channel structures to explore how the radius and hydrophobicity of pores determine their hydration vs. de-wetting behaviour. Machine learning-assisted analysis of these simulations enables us to propose a simple model for this relationship. This allows us to present an easy method for the rapid prediction of the functional state of new channel structures as they emerge.biorxiv_global_text_v28_figs_SI.docx

Induced Polarization in MD Simulations of the 5HT3Receptor Channel

“…Whilst exploring permeation free energy profiles with AMOEBA we observed apparently favorable hydrophobic contacts of the protein with Cl -. This correlates with other recent studies of anions at air/water interfaces, with structural studies of Clbinding sites in Clchannels and Cltransport proteins, and with the properties of novel anionophores (biotin [6]uril hexaesters) which exploit C-H hydrogen bond donors in order to favor the transport of softer, more polarizable anions such as chloride over hard anions such as bicarbonate 72 . This merits further investigations into how the use of polarizable force fields may modify our understanding of anion selectivity in biological ion channels.…”

“…The comparison of the three different water models for four different conformational states of the 5HT3R channel demonstrates that previous conclusions derived about hydrophobic gating in these channels are quite robust regarding the choice of water model. This is important as such simulations are now being increasingly employed to functionally annotate the rapidly increasing number of ion channel structures that are being solved 6,15,18 . Our study indicates that such simulation-based annotation of potential hydrophobic gates is qualitatively robust in distinguishing between closed and open states.…”

“…The permeation of ions through a sub-nm diameter pore is influenced by both the pore radius and the local hydrophobicity of the pore lining 6 . Thus, although permeation can occur through polar regions only just larger than the radius of the permeating ion, a hydrophobic pore region of comparable dimensions may undergo spontaneous de-wetting [7][8][9] to present an energetic barrier to permeation without complete steric occlusion.…”

“…The concept of hydrophobic gating has been explored in a number of different channels, in particular several members of the pentameric ligand-gated ion channels (pLGICs), including the nicotinic acetylcholine receptor 13 , GLIC 11,14 , and 5-HT3 (serotonin) receptor [15][16][17] , as well as several different classes of tetrameric cation channels. Building on these studies, we have developed a computational tool (CHAP) capable of predicting the conductive state of a pore 18 as well as a heuristic approach based upon CHAP analysis of simulations of water for the current ion channel proteome 6 .…”

CHAP: A versatile tool for the structural and functional annotation of ion channel pores

“…The analysis performed by CHAP is computationally inexpensive compared to more complex simulation techniques such as computational electrophysiology (Kutzner et al, 2011) and is therefore highly suitable for the high-throughput analysis of the rapidly growing number of ion channel structures. The utility of this approach is demonstrated in a recent study (Rao et al, 2018) employing CHAP to investigate the prevalence of hydrophobic gates in ~200 different ion channel structures.…”