Tethered protein display identifies a novel Kir3.2 (GIRK2) regulator from protein scaffold libraries

Aquaporin ion conductance properties defined by membrane environment, protein structure, and cell physiology

Aquaporins (AQPs) are multifunctional transmembrane channel proteins permeable to water and an expanding array of solutes. AQP-mediated ion channel activity was first observed when purified AQP0 from bovine lens was incorporated into lipid bilayers. Electrophysiological properties of ion-conducting AQPs since discovered in plants, invertebrates, and mammals have been assessed using native, reconstituted, and heterologously expressed channels. Accumulating evidence is defining amino acid residues that govern differential solute permeability through intrasubunit and central pores of AQP tetramers. Rings of charged and hydrophobic residues around pores influence AQP selectivity, and are candidates for further work to define motifs that distinguish ion conduction capability, versus strict water and glycerol permeability. Similarities between AQP ion channels thus far include large single channel conductances and long open times, but differences in ionic selectivity, permeability to divalent cations, and mechanisms of gating (e.g., by voltage, pH, and cyclic nucleotides) are unique to subtypes. Effects of lipid environments in modulating parameters such as single channel amplitude could explain in part the variations in AQP ion channel properties observed across preparations. Physiological roles of the ion-conducting AQP classes span diverse processes including regulation of cell motility, organellar pH, neural development, signaling, and nutrient acquisition. Advances in computational methods can generate testable predictions of AQP structure-function relationships, which combined with innovative high-throughput assays could revolutionize the field in defining essential properties of ion-conducting AQPs, discovering new AQP ion channels, and understanding the effects of AQP interactions with proteins, signaling cascades, and membrane lipids.

Therapeutic potential of targeting G protein-gated inwardly rectifying potassium (GIRK) channels in the central nervous system

G protein-gated inwardly rectifying potassium channels (Kir3/GirK) are important for maintaining resting membrane potential, cell excitability and inhibitory neurotransmission. Coupled to numerous G protein-coupled receptors (GPCRs), they mediate the effects of many neurotransmitters, neuromodulators and hormones contributing to the general homeostasis and particular synaptic plasticity processes, learning, memory and pain signaling. A growing number of behavioral and genetic studies suggest a critical role for the appropriate functioning of the central nervous system, as well as their involvement in many neurologic and psychiatric conditions, such as neurodegenerative diseases, mood disorders, attention deficit hyperactivity disorder, schizophrenia, epilepsy, alcoholism and drug addiction. Hence, GirK channels emerge as a very promising tool to be targeted in the current scenario where these conditions already are or will become a global public health problem. This review examines recent findings on the physiology, function, dysfunction, and pharmacology of GirK channels in the central nervous system and highlights the relevance of GirK channels as a worthful potential target to improve therapies for related diseases.

Investigating Potassium Channels in Budding Yeast: A Genetic Sandbox

Like all species, the model eukaryote Saccharomyces cerevisiae, or Bakers' yeast, concentrates potassium in the cytosol as an electrogenic osmolyte and enzyme cofactor. Yeast are capable of robust growth on a wide variety of potassium concentrations, ranging from 10 µM to 2.5 M, due to the presence of a high-affinity potassium uptake system and a battery of cation exchange transporters. Genetic perturbation of either of these systems retards yeast growth on low or high potassium, respectively. However, these potassium-sensitized yeast are a powerful genetic tool, which has been leveraged for diverse studies. Notably, the potassium-sensitive cells can be transformed with plasmids encoding potassium channels from bacteria, plants, or mammals, and subsequent changes in growth rate have been found to correlate with the activity of the introduced potassium channel. Discoveries arising from the use of this assay over the past three decades have increased our understanding of the structure-function relationships of various potassium channels, the mechanisms underlying the regulation of potassium channel function and trafficking, and the chemical basis of potassium channel modulation. In this article, we provide an overview of the major genetic tools used to study potassium channels in S. cerevisiae, a survey of seminal studies utilizing these tools, and a prospective for the future use of this elegant genetic approach.

An Integrated Framework Advancing Membrane Protein Modeling and Design

Membrane proteins are critical functional molecules in the human body, constituting more than 30% of open reading frames in the human genome. Unfortunately, a myriad of difficulties in overexpression and reconstitution into membrane mimetics severely limit our ability to determine their structures. Computational tools are therefore instrumental to membrane protein structure prediction, consequently increasing our understanding of membrane protein function and their role in disease. Here, we describe a general framework facilitating membrane protein modeling and design that combines the scientific principles for membrane protein modeling with the flexible software architecture of Rosetta3. This new framework, called RosettaMP, provides a general membrane representation that interfaces with scoring, conformational sampling, and mutation routines that can be easily combined to create new protocols. To demonstrate the capabilities of this implementation, we developed four proof-of-concept applications for (1) prediction of free energy changes upon mutation; (2) high-resolution structural refinement; (3) protein-protein docking; and (4) assembly of symmetric protein complexes, all in the membrane environment. Preliminary data show that these algorithms can produce meaningful scores and structures. The data also suggest needed improvements to both sampling routines and score functions. Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design.

Computational modeling of membrane proteins

The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1-2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug-specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans-membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α-helical MPs as well as β-barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge-based scoring functions. Moreover, de novo methods have benefited from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade.