Molecular modeling of ion channels: structural predictions

Computational methods and theory for ion channel research

Ion channels are fundamental biological devices that act as gates in order to ensure selective ion transport across cellular membranes; their operation constitutes the molecular mechanism through which basic biological functions, such as nerve signal transmission and muscle contraction, are carried out. Here, we review recent results in the field of computational research on ion channels, covering theoretical advances, state-of-the-art simulation approaches, and frontline modeling techniques. We also report on few selected applications of continuum and atomistic methods to characterize the mechanisms of permeation, selectivity, and gating in biological and model channels.

Medicinal Chemistry of Potassium Channel Modulators: An Update of Recent Progress (2011-2017)

BACKGROUND

Potassium (K+) channels participate in many physiological processes, cardiac function, cell proliferation, neuronal signaling, muscle contractility, immune function, hormone secretion, osmotic pressure, changes in gene expression, and are involved in critical biological functions, and in a variety of diseases. Potassium channels represent a large family of tetrameric membrane proteins. Potassium channels activation reduces excitability, whereas channel inhibition increases excitability.

OBJECTIVE

Small molecule K+ channel activators and inhibitors interact with voltage-gated, inward rectifying, and two-pore tandem potassium channels. Due to their involvement in biological functions, and in a variety of diseases, small molecules as potassium channel modulators have received great scientific attention.

METHODS

In this review, we have compiled the literature, patents and patent applications (2011 to 2017) related to different chemical classes of potassium channel openers and blockers as therapeutic agents for the treatment of various diseases. Many different chemical classes of selective small molecule have emerged as potassium channel modulators over the past years.

CONCLUSION

This review discussed the current understanding of medicinal chemistry research in the field of potassium channel modulators to update the key advances in this field.

HCN Channels: New Therapeutic Targets for Pain Treatment

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are highly regulated proteins which respond to different cellular stimuli. The HCN currents (I_h) mediated by HCN1 and HCN2 drive the repetitive firing in nociceptive neurons. The role of HCN channels in pain has been widely investigated as targets for the development of new therapeutic drugs, but the comprehensive design of HCN channel modulators has been restricted due to the lack of crystallographic data. The three-dimensional structure of the human HCN1 channel was recently reported, opening new possibilities for the rational design of highly-selective HCN modulators. In this review, we discuss the structural and functional properties of HCN channels, their pharmacological inhibitors, and the potential strategies for designing new drugs to block the HCN channel function associated with pain perception.

Genome-wide Membrane Protein Structure Prediction

Transmembrane proteins allow cells to extensively communicate with the external world in a very accurate and specific way. They form principal nodes in several signaling pathways and attract large interest in therapeutic intervention, as the majority pharmaceutical compounds target membrane proteins. Thus, according to the current genome annotation methods, a detailed structural/functional characterization at the protein level of each of the elements codified in the genome is also required. The extreme difficulty in obtaining high-resolution three-dimensional structures, calls for computational approaches. Here we review to which extent the efforts made in the last few years, combining the structural characterization of membrane proteins with protein bioinformatics techniques, could help describing membrane proteins at a genome-wide scale. In particular we analyze the use of comparative modeling techniques as a way of overcoming the lack of high-resolution three-dimensional structures in the human membrane proteome.

Computational methods of studying the binding of toxins from venomous animals to biological ion channels: theory and applications

The discovery of new drugs that selectively block or modulate ion channels has great potential to provide new treatments for a host of conditions. One promising avenue revolves around modifying or mimicking certain naturally occurring ion channel modulator toxins. This strategy appears to offer the prospect of designing drugs that are both potent and specific. The use of computational modeling is crucial to this endeavor, as it has the potential to provide lower cost alternatives for exploring the effects of new compounds on ion channels. In addition, computational modeling can provide structural information and theoretical understanding that is not easily derivable from experimental results. In this review, we look at the theory and computational methods that are applicable to the study of ion channel modulators. The first section provides an introduction to various theoretical concepts, including force-fields and the statistical mechanics of binding. We then look at various computational techniques available to the researcher, including molecular dynamics, brownian dynamics, and molecular docking systems. The latter section of the review explores applications of these techniques, concentrating on pore blocker and gating modifier toxins of potassium and sodium channels. After first discussing the structural features of these channels, and their modes of block, we provide an in-depth review of past computational work that has been carried out. Finally, we discuss prospects for future developments in the field.

Molecular mechanisms of cyclic nucleotide-gated ion channel gating

Cyclic nucleotide-gated ion channels (CNGs) are distributed most widely in the neuronal cell. Great progress has been made in molecular mechanisms of CNG channel gating in the recent years. Results of many experiments have indicated that the stoichiometry and assembly of CNG channels affect their property and gating. Experiments of CNG mutants and analyses of cysteine accessibilities show that cyclic nucleotide-binding domains (CNBD) bind cyclic nucleotides and subsequently conformational changes occurred followed by the concerted or cooperative conformational change of all four subunits during CNG gating. In order to provide theoretical assistances for further investigation on CNG channels, especially regarding the disease pathogenesis of ion channels, this paper reviews the latest progress on mechanisms of CNG channels, functions of subunits, processes of subunit assembly, and conformational changes of subunit regions during gating.

Computational prediction of atomic structures of helical membrane proteins aided by EM maps

Integral membrane proteins pose a major challenge for protein-structure prediction because only approximately 100 high-resolution structures are available currently, thereby impeding the development of rules or empirical potentials to predict the packing of transmembrane alpha-helices. However, when an intermediate-resolution electron microscopy (EM) map is available, it can be used to provide restraints which, in combination with a suitable computational protocol, make structure prediction feasible. In this work we present such a protocol, which proceeds in three stages: 1), generation of an ensemble of alpha-helices by flexible fitting into each of the density rods in the low-resolution EM map, spanning a range of rotational angles around the main helical axes and translational shifts along the density rods; 2), fast optimization of side chains and scoring of the resulting conformations; and 3), refinement of the lowest-scoring conformations with internal coordinate mechanics, by optimizing the van der Waals, electrostatics, hydrogen bonding, torsional, and solvation energy contributions. In addition, our method implements a penalty term through a so-called tethering map, derived from the EM map, which restrains the positions of the alpha-helices. The protocol was validated on three test cases: GpA, KcsA, and MscL.

Membrane protein prediction methods

We survey computational approaches that tackle membrane protein structure and function prediction. While describing the main ideas that have led to the development of the most relevant and novel methods, we also discuss pitfalls, provide practical hints and highlight the challenges that remain. The methods covered include: sequence alignment, motif search, functional residue identification, transmembrane segment and protein topology predictions, homology and ab initio modeling. In general, predictions of functional and structural features of membrane proteins are improving, although progress is hampered by the limited amount of high-resolution experimental information available. While predictions of transmembrane segments and protein topology rank among the most accurate methods in computational biology, more attention and effort will be required in the future to ameliorate database search, homology and ab initio modeling.

K+ conduction in the selectivity filter of potassium channels is monitored by the charge distribution along their sequence

Potassium channels display a high conservation of sequence of the selectivity filter (SF), yet nature has designed a variety of channels that present a wide range of absolute rates of K(+) permeation. In KcsA, the structural archetype for K channels, under physiological concentrations, two K(+) ions reside in the SF in configurations 1,3 (up state) and 2,4 (down state) and ion conduction is believed to follow a throughput cycle involving a transition between these states. Using free-energy calculations of KcsA, Kv1.2, and mutant channels, we show that this transition is characterized by a channel-dependent energy barrier. This barrier is strongly influenced by the charges partitioned along the sequence of each channel. These results unveil therefore how, for similar structures of the SF, the rate of K(+) turnover may be fine-tuned within the family of potassium channels.

cAMP Modulation of the cytoplasmic domain in the HCN2 channel investigated by molecular simulations

The hyperpolarization-activated cyclic nucleotide-modulated (HCN) cation channels are opened by membrane hyperpolarization, while their activation is modulated by the binding of cyclic adenosine monophosphate (cAMP) in the cytoplasm. Here we investigate the molecular basis of cAMP channel modulation by performing molecular dynamics simulations of a segment comprising the C-linker and the cyclic nucleotide binding domain (CNBD) in the presence and absence of cAMP, based on the available crystal structure of HCN2 from mouse. In presence of cAMP, the protein undergoes an oscillation of the quaternary structure on the order of 10 ns, not observed in the apoprotein. In contrast, the absence of ligand causes conformational rearrangements within the CNBDs, driving these domains to a more flexible state, similar to that described in CNBDs of other proteins. This increased flexibility causes a rather disordered movement of the CNBDs, resulting in an inhibitory effect on the channel. We propose that the cAMP-triggered large-scale oscillation plays an important role for the channel's function, being coupled to a motion of the C-linker which, in turn, modulates the gating of the channel.

Ion conduction and selectivity in K(+) channels

Potassium (K(+)) channels are tetrameric membrane-spanning proteins that provide a selective pore for the conductance of K(+) across the cell membranes. These channels are most remarkable in their ability to discriminate K(+) from Na(+) by more than a thousandfold and conduct at a throughput rate near diffusion limit. The recent progress in the structural characterization of K(+) channel provides us with a unique opportunity to understand their function at the atomic level. With their ability to go beyond static structures, molecular dynamics simulations based on atomic models can play an important role in shaping our view of how ion channels carry out their function. The purpose of this review is to summarize the most important findings from experiments and computations and to highlight a number of fundamental mechanistic questions about ion conduction and selectivity that will require further work.

Structural basis of gating of CNG channels

Cyclic nucleotide-gated (CNG) ion channels, underlying sensory transduction in vertebrate photoreceptors and olfactory sensory neurons, require cyclic nucleotides to open. Here, we present structural models of the tetrameric CNG channel pore from bovine rod in both open and closed states, as obtained by combining homology modeling-based techniques, experimentally derived spatial constraints and structural patterns present in the PDB database. Gating is initiated by an anticlockwise rotation of the N-terminal region of the C-linker, which is then, transmitted through the S6 transmembrane helices to the P-helix, and in turn from this to the pore lumen, which opens up from 2 to 5A thus allowing for ion permeation. The approach, here presented, is expected to provide a general methodology for model ion channels and their gating when structural templates are available and an extensive electrophysiological analysis has been performed.

Filter flexibility and distortion in a bacterial inward rectifier K+ channel: simulation studies of KirBac1.1

The bacterial channel KirBac1.1 provides a structural homolog of mammalian inward rectifier potassium (Kir) channels. The conformational dynamics of the selectivity filter of Kir channels are of some interest in the context of possible permeation and gating mechanisms for this channel. Molecular dynamics simulations of KirBac have been performed on a 10-ns timescale, i.e., comparable to that of ion permeation. The results of five simulations (total simulation time 50 ns) based on three different initial ion configurations and two different model membranes are reported. These simulation data provide evidence for limited (<0.1 nm) filter flexibility during the concerted motion of ions and water molecules within the filter, such local changes in conformation occurring on an approximately 1-ns timescale. In the absence of K(+) ions, the KirBac selectivity filter undergoes more substantial distortions. These resemble those seen in comparable simulations of other channels (e.g., KcsA and KcsA-based homology models) and are likely to lead to functional closure of the channel. This suggests filter distortions may provide a mechanism of K-channel gating in addition to changes in the hydrophobic gate formed at the intracellular crossing point of the M2 helices. The simulation data also provide evidence for interactions of the "slide" (pre-M1) helix of KirBac with phospholipid headgroups.

Structure prediction of small transmembrane helix bundles

In this work, we will introduce a novel computational approach to predict the structures of small helical hetero-oligomeric transmembrane bundles. The approach is based on the generation and evaluation of a large library of randomly generated helix bundle conformations. This library will be evaluated by energy-dependent distributions of the structural parameters of the conformations. The approach enables us to model a subunit of cytochrome c oxidase (occ), consisting of four TM helices, to an accuracy of 1.7A and the transducer protein of the sensory Rhodopsin II-transducer complex to an accuracy of 2.3A when including two transducer-contacting Rhodopsin helices. As the approach does not afford a unique solution for each protein, experimental data would be needed to discriminate the possible models. In addition to predicting the structure of helix bundles, one can also gain insight into possible higher-energy conformations or flexible regions of the protein.

Discrimination of native loop conformations in membrane proteins: decoy library design and evaluation of effective energy scoring functions

The recent determination of crystal structures for several important membrane proteins opens the way for comparative modeling of their membrane-spanning regions. However, the ability to predict correctly the structures of loop regions, which may be critical, for example, in ligand binding, remains a considerable challenge. To meet this challenge, accurate scoring methods have to discriminate between candidate conformations of an unknown loop structure. Some success in loop prediction has been reported for globular proteins; however, the proximity of membrane protein loops to the lipid bilayer casts doubt on the applicability of the same scoring methods to this problem. In this work, we develop "decoy libraries" of non-native folds generated, using the structures of two membrane proteins, with molecular dynamics and Monte Carlo techniques over a range of temperatures. We introduce a new approach for decoy library generation by constructing a flat distribution of conformations covering a wide range of Calpha-root-mean-square deviation (RMSD) from the native structure; this removes possible bias in subsequent scoring stages. We then score these decoy conformations with effective energy functions, using increasingly more cpu-intensive implicit solvent models, including (1) simple Coulombic electrostatics with constant or distance-dependent dielectrics; (2) atomic solvation parameters; (3) the effective energy function (EEF1) of Lazaridis and Karplus; (4) generalized Born/Analytical Continuum Solvent; and (5) finite-difference Poisson-Boltzmann energy functions. We show that distinction of native-like membrane protein loops may be achieved using effective energies with the assumption of a homogenous environment; thus, the absence of the adjacent lipid bilayer does not affect the scoring ability. In particular, the Analytical Continuum Solvent and finite-difference Poisson-Boltzmann energy functions are seen to be the most powerful scoring functions. Interestingly, the use of the uncharged states of ionizable sidechains is shown to aid prediction, particularly for the simplest energy functions.