Computational Approaches for Revealing the Structure of Membrane Transporters: Case Study on Bilitranslocase

Challenges of Protein-Protein Docking of the Membrane Proteins

Despite the recent advances in the determination of high-resolution membrane protein (MP) structures, the structural and functional characterization of MPs remains extremely challenging, mainly due to the hydrophobic nature, low abundance, poor expression, purification, and crystallization difficulties associated with MPs. Whereby the major challenges/hurdles for MP structure determination are associated with the expression, purification, and crystallization procedures. Although there have been significant advances in the experimental determination of MP structures, only a limited number of MP structures (approximately less than 1% of all) are available in the Protein Data Bank (PDB). Therefore, the structures of a large number of MPs still remain unresolved, which leads to the availability of widely unplumbed structural and functional information related to MPs. As a result, recent developments in the drug discovery realm and the significant biological contemplation have led to the development of several novel, low-cost, and time-efficient computational methods that overcome the limitations of experimental approaches, supplement experiments, and provide alternatives for the characterization of MPs. Whereby the fine tuning and optimizations of these computational approaches remains an ongoing endeavor.Computational methods offer a potential way for the elucidation of structural features and the augmentation of currently available MP information. However, the use of computational modeling can be extremely challenging for MPs mainly due to insufficient knowledge of (or gaps in) atomic structures of MPs. Despite the availability of numerous in silico methods for 3D structure determination the applicability of these methods to MPs remains relatively low since all methods are not well-suited or adequate for MPs. However, sophisticated methods for MP structure predictions are constantly being developed and updated to integrate the modifications required for MPs. Currently, different computational methods for (1) MP structure prediction, (2) stability analysis of MPs through molecular dynamics simulations, (3) modeling of MP complexes through docking, (4) prediction of interactions between MPs, and (5) MP interactions with its soluble partner are extensively used. Towards this end, MP docking is widely used. It is notable that the MP docking methods yet few in number might show greater potential in terms of filling the knowledge gap. In this chapter, MP docking methods and associated challenges have been reviewed to improve the applicability, accuracy, and the ability to model macromolecular complexes.

Homology Modeling of Transporter Proteins

Membrane transporter proteins are divided into channels/pores and carriers and constitute protein families of physiological and pharmacological importance. Several presently used therapeutic compounds elucidate their effects by targeting membrane transporter proteins, including anti-arrhythmic, anesthetic, antidepressant, anxiolytic and diuretic drugs. The lack of three-dimensional structures of human transporters hampers experimental studies and drug discovery. In this chapter, the use of homology modeling for generating structural models of membrane transporter proteins is reviewed. The increasing number of atomic resolution structures available as templates, together with improvements in methods and algorithms for sequence alignments, secondary structure predictions, and model generation, in addition to the increase in computational power have increased the applicability of homology modeling for generating structural models of transporter proteins. Different pitfalls and hints for template selection, multiple-sequence alignments, generation and optimization, validation of the models, and the use of transporter homology models for structure-based virtual ligand screening are discussed.

Performance Assessment of the Network Reconstruction Approaches on Various Interactomes

Beyond the list of molecules, there is a necessity to collectively consider multiple sets of omic data and to reconstruct the connections between the molecules. Especially, pathway reconstruction is crucial to understanding disease biology because abnormal cellular signaling may be pathological. The main challenge is how to integrate the data together in an accurate way. In this study, we aim to comparatively analyze the performance of a set of network reconstruction algorithms on multiple reference interactomes. We first explored several human protein interactomes, including PathwayCommons, OmniPath, HIPPIE, iRefWeb, STRING, and ConsensusPathDB. The comparison is based on the coverage of each interactome in terms of cancer driver proteins, structural information of protein interactions, and the bias toward well-studied proteins. We next used these interactomes to evaluate the performance of network reconstruction algorithms including all-pair shortest path, heat diffusion with flux, personalized PageRank with flux, and prize-collecting Steiner forest (PCSF) approaches. Each approach has its own merits and weaknesses. Among them, PCSF had the most balanced performance in terms of precision and recall scores when 28 pathways from NetPath were reconstructed using the listed algorithms. Additionally, the reference interactome affects the performance of the network reconstruction approaches. The coverage and disease- or tissue-specificity of each interactome may vary, which may result in differences in the reconstructed networks.

Prediction of Transmembrane Regions, Cholesterol, and Ganglioside Binding Sites in Amyloid-Forming Proteins Indicate Potential for Amyloid Pore Formation

Besides amyloid fibrils, amyloid pores (APs) represent another mechanism of amyloid induced toxicity. Since hypothesis put forward by Arispe and collegues in 1993 that amyloid-beta makes ion-conducting channels and that Alzheimer's disease may be due to the toxic effect of these channels, many studies have confirmed that APs are formed by prefibrillar oligomers of amyloidogenic proteins and are a common source of cytotoxicity. The mechanism of pore formation is still not well-understood and the structure and imaging of APs in living cells remains an open issue. To get closer to understand AP formation we used predictive methods to assess the propensity of a set of 30 amyloid-forming proteins (AFPs) to form transmembrane channels. A range of amino-acid sequence tools were applied to predict AP domains of AFPs, and provided context on future experiments that are needed in order to contribute toward a deeper understanding of amyloid toxicity. In a set of 30 AFPs we predicted their amyloidogenic propensity, presence of transmembrane (TM) regions, and cholesterol (CBM) and ganglioside binding motifs (GBM), to which the oligomers likely bind. Noteworthy, all pathological AFPs share the presence of TM, CBM, and GBM regions, whereas the functional amyloids seem to show just one of these regions. For comparative purposes, we also analyzed a few examples of amyloid proteins that behave as biologically non-relevant AFPs. Based on the known experimental data on the β-amyloid and α-synuclein pore formation, we suggest that many AFPs have the potential for pore formation. Oligomerization and α-TM helix to β-TM strands transition on lipid rafts seem to be the common key events.

Guardians of the Cell: State-of-the-Art of Membrane Proteins from a Computational Point-of-View

Membrane proteins (MPs) encompass a large family of proteins with distinct cellular functions, and although representing over 50% of existing pharmaceutical drug targets, their structural and functional information is still very scarce. Over the last years, in silico analysis and algorithm development were essential to characterize MPs and overcome some limitations of experimental approaches. The optimization and improvement of these methods remain an ongoing process, with key advances in MPs' structure, folding, and interface prediction being continuously tackled. Herein, we discuss the latest trends in computational methods toward a deeper understanding of the atomistic and mechanistic details of MPs.

Alien Domains Shaped the Modular Structure of Plant NLR Proteins

Plant innate immunity mostly relies on nucleotide-binding (NB) and leucine-rich repeat (LRR) intracellular receptors to detect pathogen-derived molecules and to induce defense responses. A multitaxa reconstruction of NB-domain associations allowed us to identify the first NB–LRR arrangement in the Chlorophyta division of the Viridiplantae. Our analysis points out that the basic NOD-like receptor (NLR) unit emerged in Chlorophytes by horizontal transfer and its diversification started from Toll/interleukin receptor–NB–LRR members. The operon-based genomic structure of Chromochloris zofingiensis NLR copies suggests a functional origin of NLR clusters. Moreover, the transmembrane signatures of NLR proteins in the unicellular alga C. zofingiensis support the hypothesis that the NLR-based immunity system of plants derives from a cell-surface surveillance system. Taken together, our findings suggest that NLRs originated in unicellular algae and may have a common origin with cell-surface LRR receptors.

Structural Analysis and Dynamic Processes of the Transmembrane Segment Inside Different Micellar Environments-Implications for the TM4 Fragment of the Bilitranslocase Protein

The transmembrane (TM) proteins are gateways for molecular transport across the cell membrane that are often selected as potential targets for drug design. The bilitranslocase (BTL) protein facilitates the uptake of various anions, such as bilirubin, from the blood into the liver cells. As previously established, there are four hydrophobic transmembrane segments (TM1-TM4), which constitute the structure of the transmembrane channel of the BTL protein. In our previous studies, the 3D high-resolution structure of the TM2 and TM3 transmembrane fragments of the BTL in sodium dodecyl sulfate (SDS) micellar media were solved using Nuclear Magnetic Resonance (NMR) spectroscopy and molecular dynamics simulations (MD). The high-resolution 3D structure of the fourth transmembrane region (TM4) of the BTL was evaluated using NMR spectroscopy in two different micellar media, anionic SDS and zwitterionic DPC (dodecylphosphocholine). The presented experimental data revealed the existence of an α -helical conformation in the central part of the TM4 in both micellar media. In the case of SDS surfactant, the α -helical conformation is observed for the Pro258-Asn269 region. The use of the zwitterionic DPC micelle leads to the formation of an amphipathic α -helix, which is characterized by the extension of the central α -helix in the TM4 fragment to Phe257-Thr271. The complex character of the dynamic processes in the TM4 peptide within both surfactants was analyzed based on the relaxation data acquired on 15 N and 31 P isotopes. Contrary to previously published and present observations in the SDS micelle, the zwitterionic DPC environment leads to intensive low-frequency molecular dynamic processes in the TM4 fragment.

MBOAT7 is anchored to endomembranes by six transmembrane domains

Membrane bound O-acyltransferase domain- containing 7 (MBOAT7, also known as LPIAT1) is a protein involved in the acyl chain remodeling of phospholipids via the Lands' cycle. The MBOAT7 is a susceptibility risk genetic locus for non-alcoholic fatty liver disease (NAFLD) and mental retardation. Although it has been shown that MBOAT7 is associated to membranes, the MBOAT7 topology remains unknown. To solve the topological organization of MBOAT7, we performed: A) solubilization of the total membrane fraction of cells overexpressing the recombinant MBOAT7-V5, which revealed MBOAT7 is an integral protein strongly attached to endomembranes; B) in silico analysis by using 22 computational methods, which predicted the number and localization of transmembrane domains of MBOAT7 with a range between 5 and 12; C) in vitro analysis of living cells transfected with GFP-tagged MBOAT7 full length and truncated forms, using a combination of Western Blotting, co-immunofluorescence and Fluorescence Protease Protection (FPP) assay; D) in vitro analysis of living cells transfected with FLAG-tagged MBOAT7 full length forms, using a combination of Western Blotting, selective membrane permeabilization followed by indirect immunofluorescence. All together, these data revealed that MBOAT7 is a multispanning transmembrane protein with six transmembrane domains. Based on our model, the predicted catalytic dyad of the protein, composed of the conserved asparagine in position 321 (Asn-321) and the preserved histidine in position 356 (His-356), has a lumenal localization. These data are compatible with the role of MBOAT7 in remodeling the acyl chain composition of endomembranes.

An In Silico Approach for Assessment of the Membrane Transporter Activities of Phenols: A Case Study Based on Computational Models of Transport Activity for the Transporter Bilitranslocase

Phenols are the most abundant naturally accessible antioxidants present in a human normal diet. Since numerous beneficial applications of phenols as preventive agents in various diseases were revealed, the evaluation of phenols bioavailability is of high interest of researchers, consumers and drug manufacturers. The hydrophilic nature of phenols makes a cell membrane penetration difficult, which imply an alternative way of uptake via membrane transporters. However, the structural and functional data of membrane transporters are limited, thus the in silico modelling is really challenging and urgent tool in elucidation of transporter ligands. Focus of this research was a particular transporter bilitranslocase (BTL). BTL has a broad tissue expression (vascular endothelium, absorptive and excretory epithelia) and can transport wide variety of poly-aromatic compounds. With available BTL data (pKi [mmol/L] for 120 organic compounds) a robust and reliable QSAR models for BTL transport activity were developed and extrapolated on 300 phenolic compounds. For all compounds the transporter profiles were assessed and results show that dietary phenols and some drug candidates are likely to interact with BTL. Moreover, synopsis of predictions from BTL models and hits/predictions of 20 transporters from Metrabase and Chembench platforms were revealed. With such joint transporter analyses a new insights for elucidation of BTL functional role were acquired. Regarding limitation of models for virtual profiling of transporter interactions the computational approach reported in this study could be applied for further development of reliable in silico models for any transporter, if in vitro experimental data are available.

Advances in Protein Super-Secondary Structure Prediction and Application to Protein Structure Prediction

Due to the advancement in various sequencing technologies, the gap between the number of protein sequences and the number of experimental protein structures is ever increasing. Community-wide initiatives like CASP have resulted in considerable efforts in the development of computational methods to accurately model protein structures from sequences. Sequence-based prediction of super-secondary structure has direct application in protein structure prediction, and there have been significant efforts in the prediction of super-secondary structure in the last decade. In this chapter, we first introduce the protein structure prediction problem and highlight some of the important progress in the field of protein structure prediction. Next, we discuss recent methods for the prediction of super-secondary structures. Finally, we discuss applications of super-secondary structure prediction in structure prediction/analysis of proteins. We also discuss prediction of protein structures that are composed of simple super-secondary structure repeats and protein structures that are composed of complex super-secondary structure repeats. Finally, we also discuss the recent trends in the field.

Comparative Analysis of TM and Cytoplasmic β-barrel Conformations Using Joint Descriptor

Macroscopic descriptors have become valuable as coarse-grained features of complex proteins and are complementary to microscopic descriptors. Proteins macroscopic geometric features provide effective clues in the quantification of distant similarity and close dissimilarity searches for structural comparisons. In this study, we performed a systematic comparison of β-barrels, one of the important classes of protein folds in various transmembrane (TM) proteins against cytoplasmic barrels to estimate the conformational features using a joint-based descriptor. The approach uses joint coordinates and dihedral angles (β and γ) based on the β-strand joints and loops to determine the arrangements and propensities at the local and global levels. We then confirmed that there is a clear preference in the overall β and γ distribution, arrangements of β-strands and loops, signature patterns, and the number of strand effects between TM and cytoplasmic β-barrel geometries. As a robust and simple approach, we determine that the joint-based descriptor could provide a reliable static structural comparison aimed at macroscopic level between complex protein conformations.

Membrane Transporters for Bilirubin and Its Conjugates: A Systematic Review

Background: Bilirubin is a highly-hydrophobic tetrapyrrole which binds to plasma albumin. It is conjugated in the liver to glucuronic acid, and the water-soluble glucuronides are excreted in urine and bile. The membrane transporters of bilirubin diglucuronide are well-known. Still undefined are however the transporters performing the uptake of bilirubin from the blood into the liver, a process known to be fast and not rate-limited. The biological importance of this process may be appraised by considering that in normal adults 200–300 mg of bilirubin are produced daily, as a result of the physiologic turnover of hemoglobin and cellular cytochromes. Nevertheless, research in this field has yielded controversial and contradicting results. We have undertaken a systematic review of the literature, believing in its utility to improve the existing knowledge and promote further advancements.

Methods: We have sourced the PubMed database until 30 June 2017 by applying 5 sequential searches. Screening and eligibility criteria were applied to retain research articles reporting results obtained by using bilirubin molecules in membrane transport assays in vitro or by assessing serum bilirubin levels in in vivo experiments.

Results: We have identified 311 articles, retaining 44, reporting data on experimental models having 6 incremental increases of complexity (isolated proteins, membrane vesicles, cells, organ fragments, in vivo rodents, and human studies), demonstrating the function of 19 membrane transporters, encoded by either SLCO or ABC genes. Three other bilirubin transporters have no gene, though one, i.e., bilitranslocase, is annotated in the Transporter Classification Database.

Conclusions: This is the first review that has systematically examined the membrane transporters for bilirubin and its conjugates. Paradoxically, the remarkable advancements in the field of membrane transport of bilirubin have pointed to the elusive mechanism(s) enabling bilirubin to diffuse into the liver as if no cellular boundary existed.