Insights into channel dysfunction from modelling and molecular dynamics simulations

Molecular dynamics: a powerful tool for studying the medicinal chemistry of ion channel modulators

Molecular dynamics (MD) simulations allow researchers to investigate the behavior of desired biological targets at ever-decreasing costs with ever-increasing precision. Among the biological macromolecules, ion channels are remarkable transmembrane proteins, capable of performing special biological processes and revealing a complex regulatory matrix, including modulation by small molecules, either endogenous or exogenous. Recently, given the developments in ion channel structure determination and accessibility of bio-computational techniques, MD and related tools are becoming increasingly popular in the intense research area regarding ligand-channel interactions. This review synthesizes and presents the most important fields of MD involvement in investigating channel-molecule interactions, including, but not limited to, deciphering the binding modes of ligands to their ion channel targets and the mechanisms through which chemical compounds exert their effect on channel function. Special attention is devoted to the importance of more elaborate methods, such as free energy calculations, while principles regarding drug design and discovery are highlighted. Several technical aspects involving the creation and simulation of channel-molecule MD systems (ligand parameterization, proper membrane setup, system building, etc.) are also presented.

Advances in L-Type Calcium Channel Structures, Functions and Molecular Modeling

L-type Calcium Channels (LTCCs), also termed as Ca_v1, belong to voltage-gated calcium channels (VGCCs/Ca_vs), which play a critical role in a wide spectrum of physiological processes, including neurotransmission, cell cycle, muscular contraction, cardiac action potential and gene expression. Aberrant regulation of calcium channels is involved in neurological, cardiovascular, muscular and psychiatric disorders. Accordingly, LTCCs have been regarded as important drug targets, and a number of LTCC drugs are in clinical use. In this review, the recent development of structures and biological functions of LTCCs are introduced. Moreover, the representative modulators and ligand binding sites of LTCCs are discussed. Finally, molecular modeling and Computer-aided Drug Design (CADD) methods for understanding structure-function relations of LTCCs are summarized.

An integrative methodology based on protein-protein interaction networks for identification and functional annotation of disease-relevant genes applied to channelopathies

Background

Biologically data-driven networks have become powerful analytical tools that handle massive, heterogeneous datasets generated from biomedical fields. Protein-protein interaction networks can identify the most relevant structures directly tied to biological functions. Functional enrichments can then be performed based on these structural aspects of gene relationships for the study of channelopathies. Channelopathies refer to a complex group of disorders resulting from dysfunctional ion channels with distinct polygenic manifestations. This study presents a semi-automatic workflow using protein-protein interaction networks that can identify the most relevant genes and their biological processes and pathways in channelopathies to better understand their etiopathogenesis. In addition, the clinical manifestations that are strongly associated with these genes are also identified as the most characteristic in this complex group of diseases.

Results

In particular, a set of nine representative disease-related genes was detected, these being the most significant genes in relation to their roles in channelopathies. In this way we attested the implication of some voltage-gated sodium (SCN1A, SCN2A, SCN4A, SCN4B, SCN5A, SCN9A) and potassium (KCNQ2, KCNH2) channels in cardiovascular diseases, epilepsies, febrile seizures, headache disorders, neuromuscular, neurodegenerative diseases or neurobehavioral manifestations. We also revealed the role of Ankyrin-G (ANK3) in the neurodegenerative and neurobehavioral disorders as well as the implication of these genes in other systems, such as the immunological or endocrine systems.

Conclusions

This research provides a systems biology approach to extract information from interaction networks of gene expression. We show how large-scale computational integration of heterogeneous datasets, PPI network analyses, functional databases and published literature may support the detection and assessment of possible potential therapeutic targets in the disease. Applying our workflow makes it feasible to spot the most relevant genes and unknown relationships in channelopathies and shows its potential as a first-step approach to identify both genes and functional interactions in clinical-knowledge scenarios of target diseases.

Methods

An initial gene pool is previously defined by searching general databases under a specific semantic framework. From the resulting interaction network, a subset of genes are identified as the most relevant through the workflow that includes centrality measures and other filtering and enrichment databases.

Multiscale Simulations of Biological Membranes: The Challenge To Understand Biological Phenomena in a Living Substance

Biological membranes are tricky to investigate. They are complex in terms of molecular composition and structure, functional over a wide range of time scales, and characterized by nonequilibrium conditions. Because of all of these features, simulations are a great technique to study biomembrane behavior. A significant part of the functional processes in biological membranes takes place at the molecular level; thus computer simulations are the method of choice to explore how their properties emerge from specific molecular features and how the interplay among the numerous molecules gives rise to function over spatial and time scales larger than the molecular ones. In this review, we focus on this broad theme. We discuss the current state-of-the-art of biomembrane simulations that, until now, have largely focused on a rather narrow picture of the complexity of the membranes. Given this, we also discuss the challenges that we should unravel in the foreseeable future. Numerous features such as the actin-cytoskeleton network, the glycocalyx network, and nonequilibrium transport under ATP-driven conditions have so far received very little attention; however, the potential of simulations to solve them would be exceptionally high. A major milestone for this research would be that one day we could say that computer simulations genuinely research biological membranes, not just lipid bilayers.

GABAA receptor family: overview on structural characterization

The pentameric γ-aminobutyric acid type A receptors are ion channels activated by ligands, which intervene in the rapid inhibitory transmission in the mammalian CNS. Due to their rich pharmacology and therapeutic potential, it is essential to understand their structure and function thoroughly. This deep characterization was hampered by the lack of experimental structural information for many years. Thus, computational techniques have been extensively combined with experimental data, in order to undertake the study of γ-aminobutyric acid type A receptors and their interaction with drugs. Here, we review the exciting journey made to assess the structures of these receptors and outline major outcomes. Finally, we discuss the brand new structure of the α1β2γ2 subtype and the amazing advances it brings to the field.

Spacial models of malfunctioned protein complexes help to elucidate signal transduction critical for insulin release

Mutations in gene KCNJ11 encoding the Kir6.2 subunit of the ATP-sensitive potassium channel (KATP), a representative of a quite complex biosystem, may affect insulin release from pancreatic beta-cells. Both gain and loss of channel activity are observed, which lead to varied clinical phenotypes ranging from neonatal diabetes to congenital hyperinsulinism. In order to understand the mechanisms of the channel function better we mapped, based on the literature review, known medically relevant Kir6.2/SUR1 mutations into recently (2017) determined CryoEM 3D structures of this complex. We used a clustering algorithm to find hots spots in the 3D structure, thus we may hypothesize about their nano-mechanical role in the channel gating and the insulin level control. We also adapted a simple model of the channel gating to cover all currently known factors that can influence the KATP biosystem functions.