Modulate Protein Function Research Articles

Exploiting locational and topological overlap model to identify modules in protein interaction networks

BackgroundClustering molecular network is a typical method in system biology, which is effective in predicting protein complexes or functional modules. However, few studies have realized that biological molecules are spatial-temporally regulated to form a dynamic cellular network and only a subset of interactions take place at the same location in cells.ResultsIn this study, considering the subcellular localization of proteins, we first construct a co-localization human protein interaction network (PIN) and systematically investigate the relationship between subcellular localization and biological functions. After that, we propose a Locational and Topological Overlap Model (LTOM) to preprocess the co-localization PIN to identify functional modules. LTOM requires the topological overlaps, the common partners shared by two proteins, to be annotated in the same localization as the two proteins. We observed the model has better correspondence with the reference protein complexes and shows more relevance to cancers based on both human and yeast datasets and two clustering algorithms, ClusterONE and MCL.ConclusionTaking into consideration of protein localization and topological overlap can improve the performance of module detection from protein interaction networks.

Identification of a nine-miRNA signature for the prognosis of Uveal Melanoma

The present study aims to construct a miRNA-based predictive signature of Uveal melanoma (UM) based on the database of the cancer genome atlas (TCGA). We obtained miRNA expression profiles and clinical information of 80 UM patients from TCGA, and randomly divided them into a training and a testing set. After data processing and forward screening, a total of 204 miRNAs with prognostic value were then examined by the Cox proportional hazard regression model in the training set. Receiver operating curve (ROC) analysis was applied to validate the accuracy of the signature. The biological relevance of putative miRNA target genes was also analyzed using the bioinformatics method. As a result, a linear prognostic model consisting of 9 miRNAs (miR-195, miR-224, miR-365a, miR-365b, miR-452, miR-4709, miR-7702, miR-513c, miR-873) was developed to divide UM patients into a high- and a low-risk group. Patients assigned to the high-risk group had significantly shorter overall survival than those in the low-risk group, which was further confirmed by the Area under curve (AUC) value of 0.858 at 5 year obtained from ROC. Gene Ontology (GO) analysis indicated that predicted target genes of these miRNAs are primarily associated with the modulation of protein expression and function, such as the activity of ubiquitin protein ligase and protein kinase. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that these genes were involved in multiple signaling pathways linked to carcinogenesis. The tumor specific 9-miRNA signature was also verified in the testing and entire set. In summary, based on UM data of TCGA, we identified and validated a 9-miRNA-based prognostic signature.

SNFM: A semi-supervised NMF algorithm for detecting biological functional modules.

Unraveling protein functional modules from protein-protein interaction networks is a crucial step to better understand cellular mechanisms. In the past decades, numerous algorithms have been proposed to identify potential protein functional modules or complexes from protein-protein interaction (PPI) networks. Unfortunately, the number of PPIs is rather limited, and some interactions are false positive. Therefore, the algorithms that only utilize PPI networks may not obtain the expected results related to functional modules. In this study, we propose a novel semi-supervised functional module detection method based on non-negative matrix factorization(NMF)(SNFM), which incorporate high-quality supervised PPI links from complexes as prior information.Our method outperforms all the other competitors with improvements on performance by around 15.4% in Precision, 28.9% in Recall, 27.1% in F-score (on DIP data set) by using PCDq as gold standards.

Covalent binders in drug discovery.

Covalent modulation of protein function can have multiple utilities including therapeutics, and probes to interrogate biology. While this field is still viewed with scepticism due to the potential for (idiosyncratic) toxicities, significant strides have been made in terms of understanding how to tune electrophilicity to selectively target specific residues. Progress has also been made in harnessing the potential of covalent binders to uncover novel biology and to provide an enhanced utility as payloads for Antibody Drug Conjugates. This perspective covers the tenets and applications of covalent binders.

Chirality Effect on Cholesterol Modulation of Protein Function.

Cholesterol is a key steroidal, lipid biomolecule found abundantly in plasma membranes of eukaryotic cells. It is an important structural component of cellular membranes and regulates membrane fluidity and permeability. Cholesterol is also essential for normal functioning of key proteins including ion-channels, G protein-coupled receptors (GPCRs), membrane bound steroid receptors, and receptor kinases. It is thought that cholesterol exerts its actions via specific binding to chiral proteins and lipids as well as through non-specific physiochemical interactions. Distinguishing between the specific and the non-specific interactions can be difficult. Although much remains unclear, progress has been made in recent years by utilizing ent-cholesterol, the enantiomer of natural cholesterol (nat-cholesterol) as a probe. Ent-Cholesterol is the non-superimposable mirror image of nat-cholesterol and exhibits identical physiochemical properties as nat-cholesterol. Hence, if the biological effects of cholesterol result solely due to membrane effects, it is expected that there will be no difference between ent-cholesterol and nat-cholesterol. However, when direct binding with chiral proteins and lipids is involved, the enantiomer is expected to potentially elicit significantly different, measurable effects due to formation of diastereomeric complexes. In this chapter, we have reviewed the literature related to ent-cholesterol and its use as a probe for various biophysical and biological interactions of cholesterol.

Regulation of BK Channel Activity by Cholesterol and Its Derivatives.

Cholesterol (CLR) is an essential structural lipid in the plasma membrane of animal cells. In addition, CLR has been widely recognized as a critical modulator of protein function, including ion channels. Voltage- and Ca2+-gated K+ (BK) channels control a wide variety of physiological processes, including cell excitability, smooth muscle contractility, sensory perception, neurotransmitter release, and hormone secretion. Thus, disruption of BK currents has been implicated in the pathophysiology of prevalent human diseases. The current chapter reviews the literature documenting CLR modulation of BK channel function at a variety of levels ranging from organ systems to artificial lipid bilayers. We discuss the use of CLR isomers and structural analogs as a tool to help in discerning the mechanisms underlying CLR-driven modification of BK current. The chapter is finalized with an overview of the phenomenology and potential mechanisms that govern CLR control over the alcohol (ethyl alcohol, ethanol) sensitivity of BK channels. Studies on CLR regulation of BK currents may ultimately pave the way for novel therapeutic approaches to combat prevalent pathophysiological and morbid conditions.

Does prenylation predict progression in NAFLD?

Non-alcoholic fatty liver disease (NAFLD) often develops in concert with related metabolic diseases, such as obesity, dyslipidemia and insulin resistance. Prolonged lipid accumulation and inflammation can progress to non-alcoholic steatohepatitis (NASH). Although factors associated with the development of NAFLD are known, triggers for the progression of NAFLD to NASH are poorly understood. Recent findings published in The Journal of Pathology reveal the possible regulation of NASH progression by metabolites of the mevalonate pathway. Mevalonate can be converted into the isoprenoids farnesyldiphosphate (FPP) and geranylgeranyl diphosphate (GGPP). GGPP synthase (GGPPS), the enzyme that converts FPP to GGPP, is dysregulated in humans and mice during NASH. Both FPP and GGPP can be conjugated to proteins through prenylation, modifying protein function and localization. Deletion or knockdown of GGPPS favors FPP prenylation (farnesylation) and augments the function of liver kinase B1, an upstream kinase of AMP-activated protein kinase (AMPK). Despite increased AMPK activation, livers in Ggpps-deficient mice on a high-fat diet poorly oxidize lipids due to mitochondrial dysfunction. Although work from Liu et al provides evidence as to the potential importance of the prenylation portion of the mevalonate pathway during NAFLD, future studies are necessary to fully grasp any therapeutic or diagnostic potential. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Integrating Combinatorial Lipid Nanoparticle and Chemically Modified Protein for Intracellular Delivery and Genome Editing.

The use of protein to precisely manipulate cell signaling is an effective approach for controlling cell fate and developing precision medicine. More recently, programmable nucleases, such as CRISPR/Cas9, have shown extremely high potency for editing genetic flow of mammalian cells, and for treating genetic disorders. The therapeutic potential of proteins with an intracellular target, however, is mostly challenged by their low cell impermeability. Therefore, a developing delivery system to transport protein to the site of action in a spatiotemporal controlled manner is of great importance to expand the therapeutic index of the protein. In this Account, we first summarize our most recent advances in designing combinatorial lipid nanoparticles with diverse chemical structures for intracellular protein delivery. By designing parallel Michael addition or ring-opening reaction of aliphatic amines, we have generated a combinatorial library of cationic lipids, and identified several leading nanoparticle formulations for intracellular protein delivery both in vitro and in vivo. Moreover, we optimized the chemical structure of lipids to control lipid degradation and protein release inside cells for CRISPR/Cas9 genome-editing protein delivery. In the second part of this Account, we survey our recent endeavor in developing a chemical approach to modify protein, in particular, coupled with the nanoparticle delivery platform, to improve protein delivery for targeted diseases treatment and genome editing. Chemical modification of protein is a useful tool to modulate protein function and to improve the therapeutic index of protein drugs. Herein, we mostly summarize our recent advances on designing chemical approaches to modify protein with following unique findings: (1) chemically modified protein shows selective turn-on activity based on the specific intracellular microenvironment, with which we were able to protein-based targeted cancer therapy; (2) the conjugation of hyaluronic acid (HA) to protein allows cancer cell surface receptor-targeted delivery of protein; (3) the introduction of nonpeptidic boronic acid into protein enabled cell nucleus targeted delivery; this is the first report that a nonpeptidic signal can direct protein to subcellular compartment; and (4) the fusion of protein with negatively supercharged green fluorescent protein (GFP) facilitates the self-assembly of protein with lipid nanoparticle for genome-editing protein delivery. At the end of the Account, we give a perspective of expanding the chemistry that could be integrated to design biocompatible lipid nanocarriers for protein delivery and genome editing in vitro and in vivo, as well as the chemical approaches that we can harness to modulate protein activity in live cells for targeted diseases treatment.

3′ UTRs in the Eye of the TIGER

Many human genes generate mRNAs with alternative 3' untranslated regions (3' UTRs), which can modulate protein function. In a recent Cell paper, Ma and Mayr (2018) unveil a major membraneless organelle, termed the TIS granule-endoplasmic reticulum (TIGER), which enables specific 3' UTRs to encipher protein localization.

Deciphering the SUMO code in the kidney.

SUMOylation of proteins is an important regulatory element in modulating protein function and has been implicated in the pathogenesis of numerous human diseases such as cancers, neurodegenerative diseases, brain injuries, diabetes, and familial dilated cardiomyopathy. Growing evidence has pointed to a significant role of SUMO in kidney diseases such as DN, RCC, nephritis, AKI, hypertonic stress and nephrolithiasis. Recently, emerging studies in podocytes demonstrated that SUMO might have a protective role against podocyte apoptosis. However, the SUMO code responsible for beneficial outcome in the kidney remains to be decrypted. Our recent experiments have revealed that the expression of both SUMO and SUMOylated proteins is appreciably elevated in hypoxia‐induced tubular epithelial cells (TECs) as well as in the unilateral ureteric obstruction (UUO) mouse model, suggesting a role of SUMO in TECs injury and renal fibrosis. In this review, we attempt to decipher the SUMO code in the development of kidney diseases by summarizing the defined function of SUMO and looking forward to the potential role of SUMO in kidney diseases, especially in the pathology of renal fibrosis and CKD, with the goal of developing strategies that maximize correct interpretation in clinical therapy and prognosis.

Artificial intelligence-based inspection of contact shock of a functional protein on a silicon substrate

For the development of next-generation biomedical devices, it is necessary to understand the precise interactions between proteins and solid surfaces. However, current approaches only allow these interactions to be roughly estimated. Here, using artificial intelligence-based targeting and computer simulations, we assessed the binding behavior of approximately 80 tetrapeptides in the active site of papain adsorbed on a semiconductor surface. The contact shock of papain resulted in different peptides becoming compatible (i.e. fitting into the active site) and others losing this compatibility. Therefore, we propose contact shock as a potentially powerful approach to modify protein function. Moreover, the structural information for tetrapeptides that were insensitive to structural changes of papain could be valuable for drug design. From our decision trees, we found that the shock changed the main factors that determined compatibility.

Proteomic analysis of microbial induced redox-dependent intestinal signaling

Intestinal homeostasis is regulated in-part by reactive oxygen species (ROS) that are generated in the colonic mucosa following contact with certain lactobacilli. Mechanistically, ROS can modulate protein function through the oxidation of cysteine residues within proteins. Recent advances in cysteine labeling by the Isotope Coded Affinity Tags (ICATs) technique has facilitated the identification of cysteine thiol modifications in response to stimuli. Here, we used ICATs to map the redox protein network oxidized upon initial contact of the colonic mucosa with Lactobacillus rhamnosus GG (LGG). We detected significant LGG-specific redox changes in over 450 proteins, many of which are implicated to function in cellular processes such as endosomal trafficking, epithelial cell junctions, barrier integrity, and cytoskeleton maintenance and formation. We particularly noted the LGG-specific oxidation of Rac1, which is a pleiotropic regulator of many cellular processes. Together, these data reveal new insights into lactobacilli-induced and redox-dependent networks involved in intestinal homeostasis.

A Hybrid ACO-Graph Entropy for Functional Modules Detection from Protein–Protein Interaction Network

Recent high-throughput experiments have generated protein-protein interaction data on a genomic scale, yielding the complete protein-protein interaction network for several organisms. Various graph clustering algorithms have been applied to protein interaction networks for detecting protein functional modules. Although the previous algorithms are scalable and robust, their accuracy is still limited because of the complex connectivity found in protein interaction networks. The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. The adapted ACO (ACO-PFMDA) has obtained feasible solution but not as magnificent as those reported in the literature. Some shortcomings were identified and addressed by proposing a Modified Ant Colony Optimization Algorithm (ACO-PFMDM), which introduces two new scheme for controlling the two main parameters of ACO to solve PFMDP. Experiments on one popular benchmark dataset namely Saccharomyces cerevisiae which taken from two popular databases DIP and MIPS has been performed. The experimental result have proved that ACO-PFMDM have improved the overall performance of protein functional module detection. The search process of ACO-PFMDM has converged effectively compared to some state-of-art algorithms. Moreover, the proposed dynamic update of the heuristic parameters based on entropy has generated high quality tours and it can guide ants toward the effective solutions space in the initial search stages.

Protein structure and computational drug discovery.

The first protein structures revealed a complex web of weak interactions stabilising the three-dimensional shape of the molecule. Small molecule ligands were then found to exploit these same weak binding events to modulate protein function or act as substrates in enzymatic reactions. As the understanding of ligand-protein binding grew, it became possible to firstly predict how and where a particular small molecule might interact with a protein, and then to identify putative ligands for a specific protein site. Computer-aided drug discovery, based on the structure of target proteins, is now a well-established technique that has produced several marketed drugs. We present here an overview of the various methodologies being used for structure-based computer-aided drug discovery and comment on possible future developments in the field.

Regulation of ER-mitochondria contacts by Parkin via Mfn2.

Parkin, an E3 ubiquitin ligase and a Parkinson's disease (PD) related gene, translocates to impaired mitochondria and drives their elimination via autophagy, a process known as mitophagy. Mitochondrial pro-fusion protein Mitofusins (Mfn1 and Mfn2) were found to be a target for Parkin mediated ubiquitination. Mfns are transmembrane GTPase embedded in the outer membrane of mitochondria, which are required on adjacent mitochondria to mediate fusion. In mammals, Mfn2 also forms complexes that are capable of tethering mitochondria to endoplasmic reticulum (ER), a structural feature essential for mitochondrial energy metabolism, calcium (Ca2+) transfer between the organelles and Ca2+ dependent cell death. Despite its fundamental physiological role, the molecular mechanisms that control ER-mitochondria cross talk are obscure. Ubiquitination has recently emerged as a powerful tool to modulate protein function, via regulation of protein subcellular localization and protein ability to interact with other proteins. Ubiquitination is also a reversible mechanism, which can be actively controlled by opposing ubiquitination-deubiquitination events. In this work we found that in Parkin deficient cells and parkin mutant human fibroblasts, the tether between ER and mitochondria is decreased. We identified the site of Parkin dependent ubiquitination and showed that the non-ubiquitinatable Mfn2 mutant fails to restore ER-mitochondria physical and functional interaction. Finally, we took advantage of an established in vivo model of PD to demonstrate that manipulation of ER-mitochondria tethering by expressing an ER-mitochondria synthetic linker is sufficient to rescue the locomotor deficit associated to an in vivo Drosophila model of PD.

Mn Porphyrin-Based Redox-Active Drugs: Differential Effects as Cancer Therapeutics and Protectors of Normal Tissue Against Oxidative Injury.

After approximatelty three decades of research, two Mn(III) porphyrins (MnPs), MnTE-2-PyP5+ (BMX-010, AEOL10113) and MnTnBuOE-2-PyP5+ (BMX-001), have progressed to five clinical trials. In parallel, another similarly potent metal-based superoxide dismutase (SOD) mimic-Mn(II)pentaaza macrocycle, GC4419-has been tested in clinical trial on application, identical to that of MnTnBuOE-2-PyP5+-radioprotection of normal tissue in head and neck cancer patients. This clearly indicates that Mn complexes that target cellular redox environment have reached sufficient maturity for clinical applications. Recent Advances: While originally developed as SOD mimics, MnPs undergo intricate interactions with numerous redox-sensitive pathways, such as those involving nuclear factor κB (NF-κB) and nuclear factor E2-related factor 2 (Nrf2), thereby impacting cellular transcriptional activity. An increasing amount of data support the notion that MnP/H2O2/glutathione (GSH)-driven catalysis of S-glutathionylation of protein cysteine, associated with modification of protein function, is a major action of MnPs on molecular level. Differential effects of MnPs on normal versus tumor cells/tissues, which support their translation into clinic, arise from differences in their accumulation and redox environment of such tissues. This in turn results in different yields of MnP-driven modifications of proteins. Thus far, direct evidence for such modification of NF-κB, mitogen-activated protein kinases (MAPK), phosphatases, Nrf2, and endogenous antioxidative defenses was provided in tumor, while indirect evidence shows the modification of NF-κB and Nrf2 translational activities by MnPs in normal tissue. Studies that simultaneously explore differential effects in same animal are lacking, while they are essential for understanding of extremely intricate interactions of metal-based drugs with complex cellular networks of normal and cancer cells/tissues.

Sodium nitrite augments lungS-nitrosylation and reverses chronic hypoxic pulmonary hypertension in juvenile rats

Deficient nitric oxide (NO) signaling plays a critical role in the pathogenesis of chronic neonatal pulmonary hypertension (PHT). Physiological NO signaling is regulated by S-nitrosothiols (SNOs), which act both as a reservoir for NO and as a reversible modulator of protein function. We have previously reported that therapy with inhaled NO (iNO) increased peroxynitrite-mediated nitration in the juvenile rat lung, although having minimal reversing effects on vascular remodeling. We hypothesized that sodium nitrite (NaNO2) would be superior to iNO in enhancing lung SNOs, thereby contributing to reversal of chronic hypoxic PHT. Rat pups were exposed to air or hypoxia (13% O2) from postnatal days 1 to 21. Dose-response prevention studies were conducted from days 1-21 to determine the optimal dose of NaNO2. Animals then received rescue therapy with daily subcutaneous NaNO2 (20 mg/kg), vehicle, or were continuously exposed to iNO (20 ppm) from days 14-21. Chronic PHT secondary to hypoxia was both prevented and reversed by treatment with NaNO2. Rescue NaNO2 increased lung NO and SNO contents to a greater extent than iNO, without causing nitration. Seven lung SNO proteins upregulated by treatment with NaNO2 were identified by multiplex tandem mass tag spectrometry, one of which was leukotriene A4 hydrolase (LTA4H). Rescue therapy with a LTA4H inhibitor, SC57461A (10 mg·kg-1·day-1 sc), partially reversed chronic hypoxic PHT. We conclude that NaNO2 was superior to iNO in increasing tissue NO and SNO generation and reversing chronic PHT, in part via upregulated SNO-LTA4H.

High O-linked N-acetylglucosamine transferase expression predicts poor survival in patients with early stage lung adenocarcinoma.

Tumor cell heterogeneity can make selection of appropriate interventions to lung cancer a challenge. Novel biomarkers predictive of disease risk and treatment response are needed to improve personalized treatment strategies. O-GlcNAcylation, the attachment of β-N-acetylglucosamine (O-GlcNAc) to serine or threonine residues of intracellular proteins, modulates protein functions and is implicated in cancer pathogenesis. O-GlcNAc-transferase (OGT) and O-GlcNAcase (OGA) catalyze O-GlcNAc addition and removal, respectively. We used immunohistochemistry to explore the utility of OGT, OGA, and O-GlcNAc as potential biomarkers for lung adenocarcinoma. We found that high OGT expression is associated with poor overall survival (OS) in both stage I patients (P=0.032) and those at variable stages of disease (P=0.029), and with poor recurrence-free survival (RFS) in stage I patients (P=0.035). High OGT expression is also associated with poorer OS in patients with EGFR wild-type tumors at variable stages (P=0.038). Multivariate analysis indicated that OGT expression is an independent prognostic factor for RFS (HR 2.946, 95% CI: 1.411–6.150, P=0.004) and OS (HR 2.002, 95% CI: 1.183–3.391, P=0.010) in stage I patients. Our findings indicate OGT is a promising biomarker for further classifying early stage lung adenocarcinomas.

A Network Hierarchy-Based method for functional module detection in protein–protein interaction networks

In the post-genomic era, one of the important tasks is to identify protein complexes and functional modules from high-throughput protein–protein interaction data, so that we can systematically analyze and understand the molecular functions and biological processes of cells. Although a lot of functional module detection studies have been proposed, how to design correctly and efficiently functional modules detection algorithms is still a challenging and important scientific problem in computational biology. In this paper, we present a novel Network Hierarchy-Based method to detect functional modules in PPI networks (named NHB-FMD). NHB-FMD first constructs the hierarchy tree corresponding to the PPI network and then encodes the tree such that genetic algorithm is employed to obtain the hierarchy tree with Maximum Likelihood. After that functional module partitioning is performed based on it and the best partitioning is selected as the result. Experimental results in the real PPI networks have shown that the proposed algorithm not only significantly outperforms the state-of-the-art methods but also can detect protein modules more effectively and accurately.

Lipid Modulation of Membrane Protein Function

In the last decade, native mass spectrometry has emerged as a powerful tool for studying the interactions of lipids and other small molecules with integral membrane proteins and their complexes. In this issue of Cell Chemical Biology, Pyle etal. (2018) establishes the role of phosphatidyl-inositol in dimerization and activity of a eukaryotic purine transporter (UapA).