Computational modeling of membrane proteins

On Biophysical Properties and Sensitivity to Gap Junction Blockers of Connexin 39 Hemichannels Expressed in HeLa Cells

Although connexins (Cxs) are broadly expressed by cells of mammalian organisms, Cx39 has a very restricted pattern of expression and the biophysical properties of Cx39-based channels [hemichannels (HCs) and gap junction channels (GJCs)] remain largely unknown. Here, we used HeLa cells transfected with Cx39 (HeLa-Cx39 cells) in which intercellular electrical coupling was not detected, indicating the absence of GJCs. However, functional HCs were found on the surface of cells exposed to conditions known to increase the open probability of other Cx HCs (e.g., extracellular divalent cationic-free solution (DCFS), extracellular alkaline pH, mechanical stimulus and depolarization to positive membrane potentials). Cx39 HCs were blocked by some traditional Cx HC blockers, but not by others or a pannexin1 channel blocker. HeLa-Cx39 cells showed similar resting membrane potentials (RMPs) to those of parental cells, and exposure to DCFS reduced RMPs in Cx39 transfectants, but not in parental cells. Under these conditions, unitary events of ~75 pS were frequent in HeLa-Cx39 cells and absent in parental cells. Real-time cellular uptake experiments of dyes with different physicochemical features, as well as the application of a machine-learning approach revealed that Cx39 HCs are preferentially permeable to molecules characterized by six categories of descriptors, namely: (1) electronegativity, (2) ionization potential, (3) polarizability, (4) size and geometry, (5) topological flexibility and (6) valence. However, Cx39 HCs opened by mechanical stimulation or alkaline pH were impermeable to Ca²⁺. Molecular modeling of Cx39-based channels suggest that a constriction present at the intracellular portion of the para helix region co-localizes with an electronegative patch, imposing an energetic and steric barrier, which in the case of GJCs may hinder channel function. Results reported here demonstrate that Cx39 form HCs and add to our understanding of the functional roles of Cx39 HCs under physiological and pathological conditions in cells that express them.

Conjecture Regarding Posttranslational Modifications to the Arabidopsis Type I Proton-Pumping Pyrophosphatase (AVP1)

Agbiotechnology uses genetic engineering to improve the output and value of crops. Altering the expression of the plant Type I Proton-pumping Pyrophosphatase (H⁺-PPase) has already proven to be a useful tool to enhance crop productivity. Despite the effective use of this gene in translational research, information regarding the intracellular localization and functional plasticity of the pump remain largely enigmatic. Using computer modeling several putative phosphorylation, ubiquitination and sumoylation target sites were identified that may regulate Arabidopsis H⁺-PPase (AVP1- Arabidopsis Vacuolar Proton-pump 1) subcellular trafficking and activity. These putative regulatory sites will direct future research that specifically addresses the partitioning and transport characteristics of this pump. We posit that fine-tuning H⁺-PPases activity and cellular distribution will facilitate rationale strategies for further genetic improvements in crop productivity.

Molecular Modelling Approaches for the Analysis of Histamine Receptors and Their Interaction with Ligands

Several experimental techniques to analyse histamine receptors are available, e.g. pharmacological characterisation of known or new compounds by different types of assays or mutagenesis studies. To obtain insights into the histamine receptors on a molecular and structural level, crystal structures have to be determined and molecular modelling studies have to be performed. It is widely accepted to generate homology models of the receptor of interest based on an appropriate crystal structure as a template and to refine the resulting models by molecular dynamic simulations. A lot of modelling techniques, e.g. docking, QSAR or interaction fingerprint methods, are used to predict binding modes of ligands and pharmacological data, e.g. affinity or even efficacy. However, within the last years, molecular dynamic simulations got more and more important: First of all, molecular dynamic simulations are very helpful to refine the binding mode of a ligand to a histamine receptor, obtained by docking studies. Furthermore, with increasing computational performance it got possible to simulate complete binding pathways of ions or ligands from the aqueous extracellular phase into the allosteric or orthosteric binding pocket of histamine receptors.

Coarse-Grained Simulations of Membrane Insertion and Folding of Small Helical Proteins Using the CABS Model

The CABS coarse-grained model is a well-established tool for modeling globular proteins (predicting their structure, dynamics, and interactions). Here we introduce an extension of the CABS representation and force field (CABS-membrane) to the modeling of the effect of the biological membrane environment on the structure of membrane proteins. We validate the CABS-membrane model in folding simulations of 10 short helical membrane proteins not using any knowledge about their structure. The simulations start from random protein conformations placed outside the membrane environment and allow for full flexibility of the modeled proteins during their spontaneous insertion into the membrane. In the resulting trajectories, we have found models close to the experimental membrane structures. We also attempted to select the correctly folded models using simple filtering followed by structural clustering combined with reconstruction to the all-atom representation and all-atom scoring. The CABS-membrane model is a promising approach for further development toward modeling of large protein-membrane systems.

Structural modeling of G-protein coupled receptors: An overview on automatic web-servers

Despite the significant efforts and discoveries during the last few years in G protein-coupled receptor (GPCR) expression and crystallization, the receptors with known structures to date are limited only to a small fraction of human GPCRs. The lack of experimental three-dimensional structures of the receptors represents a strong limitation that hampers a deep understanding of their function. Computational techniques are thus a valid alternative strategy to model three-dimensional structures. Indeed, recent advances in the field, together with extraordinary developments in crystallography, in particular due to its ability to capture GPCRs in different activation states, have led to encouraging results in the generation of accurate models. This, prompted the community of modelers to render their methods publicly available through dedicated databases and web-servers. Here, we present an extensive overview on these services, focusing on their advantages, drawbacks and their role in successful applications. Future challenges in the field of GPCR modeling, such as the predictions of long loop regions and the modeling of receptor activation states are presented as well.

Statistical prediction of protein structural, localization and functional properties by the analysis of its fragment mass distributions after proteolytic cleavage

Structural, localization and functional properties of unknown proteins are often being predicted from their primary polypeptide chains using sequence alignment with already characterized proteins and consequent molecular modeling. Here we suggest an approach to predict various structural and structure-associated properties of proteins directly from the mass distributions of their proteolytic cleavage fragments. For amino-acid-specific cleavages, the distributions of fragment masses are determined by the distributions of inter-amino-acid intervals in the protein, that in turn apparently reflect its structural and structure-related features. Large-scale computer simulations revealed that for transmembrane proteins, either α-helical or β -barrel secondary structure could be predicted with about 90% accuracy after thermolysin cleavage. Moreover, 3/4 intrinsically disordered proteins could be correctly distinguished from proteins with fixed three-dimensional structure belonging to all four SCOP structural classes by combining 3–4 different cleavages. Additionally, in some cases the protein cellular localization (cytosolic or membrane-associated) and its host organism (Firmicute or Proteobacteria) could be predicted with around 80% accuracy. In contrast to cytosolic proteins, for membrane-associated proteins exhibiting specific structural conformations, their monotopic or transmembrane localization and functional group (ATP-binding, transporters, sensors and so on) could be also predicted with high accuracy and particular robustness against missing cleavages.

Pred-binding: large-scale protein-ligand binding affinity prediction

Drug target interactions (DTIs) are crucial in pharmacology and drug discovery. Presently, experimental determination of compound-protein interactions remains challenging because of funding investment and difficulties of purifying proteins. In this study, we proposed two in silico models based on support vector machine (SVM) and random forest (RF), using 1589 molecular descriptors and 1080 protein descriptors in 9948 ligand-protein pairs to predict DTIs that were quantified by Ki values. The cross-validation coefficient of determination of 0.6079 for SVM and 0.6267 for RF were obtained, respectively. In addition, the two-dimensional (2D) autocorrelation, topological charge indices and three-dimensional (3D)-MoRSE descriptors of compounds, the autocorrelation descriptors and the amphiphilic pseudo-amino acid composition of protein are found most important for Ki predictions. These models provide a new opportunity for the prediction of ligand-receptor interactions that will facilitate the target discovery and toxicity evaluation in drug development.

Living on the edge: Simulations of bacterial outer-membrane proteins

Gram-negative bacteria are distinguished in part by a second, outer membrane surrounding them. This membrane is distinct from others, possessing an outer leaflet composed not of typical phospholipids but rather large, highly charged molecules known as lipopolysaccharides. Therefore, modeling the structure and dynamics of proteins embedded in the outer membrane requires careful consideration of their native environment. In this review, we examine how simulations of such outer-membrane proteins have evolved over the last two decades, culminating most recently in detailed, highly accurate atomistic models of the outer membrane. We also draw attention to how the simulations have coupled with experiments to produce novel insights unattainable through a single approach. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Simulations of outer membrane channels and their permeability

Channels in the outer membrane of Gram-negative bacteria provide essential pathways for the controlled and unidirectional transport of ions, nutrients and metabolites into the cell. At the same time the outer membrane serves as a physical barrier for the penetration of noxious substances such as antibiotics into the bacteria. Most antibiotics have to pass through these membrane channels to either reach cytoplasmic bound targets or to further cross the hydrophobic inner membrane. Considering the pharmaceutical significance of antibiotics, understanding the functional role and mechanism of these channels is of fundamental importance in developing strategies to design new drugs with enhanced permeation abilities. Due to the biological complexity of membrane channels and experimental limitations, computer simulations have proven to be a powerful tool to investigate the structure, dynamics and interactions of membrane channels. Considerable progress has been made in computer simulations of membrane channels during the last decade. The goal of this review is to provide an overview of the computational techniques and their roles in modeling the transport across outer membrane channels. A special emphasis is put on all-atom molecular dynamics simulations employed to better understand the transport of molecules. Moreover, recent molecular simulations of ion, substrate and antibiotics translocation through membrane pores are briefly summarized. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Deletion of a Predicted β-Sheet Domain within the Amino Terminus of Herpes Simplex Virus Glycoprotein K Conserved among Alphaherpesviruses Prevents Virus Entry into Neuronal Axons

We have shown previously that herpes simplex virus 1 (HSV-1) lacking expression of the entire glycoprotein K (gK) or expressing gK with a 38-amino-acid deletion (gKΔ31-68 mutation) failed to infect ganglionic neurons after ocular infection of mice. We constructed a new model for the predicted three-dimensional structure of gK, revealing that the gKΔ31-68 mutation spans a well-defined β-sheet structure within the amino terminus of gK, which is conserved among alphaherpesviruses. The HSV-1(McKrae) gKΔ31-68 virus was tested for the ability to enter into ganglionic neuronal axons in cell culture of explanted rat ganglia using a novel virus entry proximity ligation assay (VEPLA). In this assay, cell surface-bound virions were detected by the colocalization of gD and its cognate receptor nectin-1 on infected neuronal surfaces. Capsids that have entered into the cytoplasm were detected by the colocalization of the virion tegument protein UL37, with dynein required for loading of virion capsids onto microtubules for retrograde transport to the nucleus. HSV-1(McKrae) gKΔ31-68 attached to cell surfaces of Vero cells and ganglionic axons in cell culture as efficiently as wild-type HSV-1(McKrae). However, unlike the wild-type virus, the mutant virus failed to enter into the axoplasm of ganglionic neurons. This work suggests that the amino terminus of gK is a critical determinant for entry into neuronal axons and may serve similar conserved functions for other alphaherpesviruses.

IMPORTANCE

Alphaherpesviruses, unlike beta- and gammaherpesviruses, have the unique ability to infect and establish latency in neurons. Glycoprotein K (gK) and the membrane protein UL20 are conserved among all alphaherpesviruses. We show here that a predicted β-sheet domain, which is conserved among alphaherpesviruses, functions in HSV-1 entry into neuronal axons, suggesting that it may serve similar functions for other herpesviruses. These results are in agreement with our previous observations that deletion of this gK domain prevents the virus from successfully infecting ganglionic neurons after ocular infection of mice.

Membrane-bound selenoproteins

SIGNIFICANCE

Selenoproteins employ selenium to supplement the chemistry available through the common 20 amino acids. These powerful enzymes are affiliated with redox biology, often in connection with the detection, management, and signaling of oxidative stress. Among them, membrane-bound selenoproteins play prominent roles in signaling pathways, Ca(2+) regulation, membrane complexes integrity, and biosynthesis of lipophilic molecules.

RECENT ADVANCES

The number of selenoproteins whose physiological roles, protein partners, expression, evolution, and biosynthesis are characterized is steadily increasing, thus offering a more nuanced view of this specialized family. This review focuses on human membrane selenoproteins, particularly the five least characterized ones: selenoproteins I, K, N, S, and T.

CRITICAL ISSUES

Membrane-bound selenoproteins are the least understood, as it is challenging to provide the membrane-like environment required for their biochemical and biophysical characterization. Hence, their studies rely mostly on biological rather than structural and biochemical assays. Another aspect that has not received much attention is the particular role that their membrane association plays in their physiological function.

FUTURE DIRECTIONS

Findings cited in this review show that it is possible to infer the structure and the membrane-binding mode of these lesser-studied selenoproteins and design experiments to examine the role of the rare amino acid selenocysteine.

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.