Structure-function relationship of cytoplasmic and nuclear IκB proteins: an in silico analysis

Effect of reactive oxygen, nitrogen, and sulfur species on signaling pathways in atherosclerosis

Atherosclerosis is a chronic inflammatory disease in which fats, lipids, cholesterol, calcium, proliferating smooth muscle cells, and immune cells accumulate in the intima of the large arteries, forming atherosclerotic plaques. A complex interplay of various vascular and immune cells takes place during the initiation and progression of atherosclerosis. Multiple reports indicate that tight control of reactive oxygen species (ROS), reactive nitrogen species (RNS), and reactive sulfur species (RSS) production is critical for maintaining vascular health. Unrestricted ROS and RNS generation may lead to activation of various inflammatory signaling pathways, facilitating atherosclerosis. Given these deleterious consequences, it is important to understand how ROS and RNS affect the signaling processes involved in atherogenesis. Conversely, RSS appears to exhibit an atheroprotective potential and can alleviate the deleterious effects of ROS and RNS. Herein, we review the literature describing the effects of ROS, RNS, and RSS on vascular smooth muscle cells, endothelial cells, and macrophages and focus on how changes in their production affect the initiation and progression of atherosclerosis. This review also discusses the contribution of ROS, RNS, and RSS in mediating various post-translational modifications, such as oxidation, nitrosylation, and sulfation, of the molecules involved in inflammatory signaling.

A phellinus igniarius polysaccharide/chitosan-arginine hydrogel for promoting diabetic wound healing

Inadequate angiogenesis and inflammation at the wound site have always been a major threat to skin wounds, especially for diabetic wounds that are difficult to heal. Therefore, hydrogel dressings with angiogenesis and antibacterial properties are very necessary in practical applications. This study reported a hydrogel (PCA) based on L-arginine conjugated chitosan (CA) and aldehyde functionalized polysaccharides of Phellinus igniarius (OPPI) as an antibacterial and pro-angiogenesis dressing for wound repair in diabetes for the first time. and discussed its possible mechanism for promoting wound healing. The results showed that PCA had good antioxidant, antibacterial, biological safety and other characteristics, and effectively promoted the healing course of diabetic wound model. In detail, the H&E and Masson staining results showed that PCA promoted normal epithelial formation and collagen deposition. The Western blot results confirmed that PCA decreased the inflammation by inhibiting the IKBα/NF-κB signaling pathway and enhanced angiogenesis by adjusting the level of HIF-1α. In conclusion, PCA is a promising candidate for promoting wound healing in diabetes. Graphic abstract.

USP39 Regulates NF-κB-Mediated Inflammatory Responses through Deubiquitinating K48-Linked IκBα

IκBα is a critical protein that inhibits NF-κB nuclear translocation and impairs NF-κB-mediated signaling. The abundance of IκBα determines the activation and restoration of the inflammatory response. However, posttranslational regulation of IκBα remains to be fully understood. In this study, we identified ubiquitin-specific protease 39 (USP39) as a negative regulator in the NF-κB inflammatory response by stabilizing basal IκBα. The expression of USP39 in macrophages was reduced under LPS-induced inflammation. Knockdown or knockout of USP39 in macrophages significantly increased the expression and secretion of proinflammatory cytokines upon exposure to LPS or Escherichia coli, whereas reexpression of exogenous USP39 in USP39-deficient macrophages rescued the effect. Moreover, USP39-defective mice were more sensitive to LPS or E. coli-induced systemic sepsis. Mechanistically, USP39 interacted with and stabilized IκBα by reducing K48-linked polyubiquination of IκBα. Taken together, to our knowledge, our study for the first time revealed the inhibitory function of USP39 in the NF-κB inflammatory response, providing a previously unknown mechanism for control of inflammatory cytokine induction in the cellular anti-inflammatory response.

Amyotrophic lateral sclerosis disease-related mutations disrupt the dimerization of superoxide dismutase 1 - A comparative molecular dynamics simulation study

More than 150 genes are involved in amyotrophic lateral sclerosis (ALS), with superoxide dismutase 1 (SOD1) being one of the most studied. Mutations in SOD1 gene, which encodes the enzyme SOD1 is the second most prevalent and studied cause of familial ALS. SOD1 is a ubiquitous, homodimeric metalloenzyme that forms a critical component of the cellular defense against reactive oxygen species. Several mutations in the SOD1 enzyme cause misfolding, dimerization instability, and increased aggregate formation in ALS. However, there is a lack of information on the dimerization of SOD1 monomers and the mechanistic underpinnings on how the pathogenic mutations disrupt the dimerization mechanism. Here, we presented microsecond-scale molecular dynamics (MD) simulations to unravel how interface-based mutations compromise SOD1 dimerization and provide mechanistic understanding into the corresponding process using WT and three interface-based mutant systems (A4V, T54R, and I113T). Structural stability analysis showed that the mutant systems displayed disparate variations in the catalytic sites which may directly alter the stability and activity of the SOD1 enzyme. Based on the dynamic network analysis and principal component analysis, it has been identified that the mutations weakened the correlated motions along the dimer interface and altered the protein conformational behavior, thus weakening the stability of dimer formation. Moreover, the simulation results identified crucial residues such as G51, D52, G114, I151, and Q153 in establishing the dimerization interaction network, which were weakened or absent in the presence of interfacial mutants. Surface potential analysis on mutant systems also displayed changes in the dimerization potential, thus showing the unfavorable dimer formation. Furthermore, network analysis identified the hotspot residues necessary for SOD1 signal transduction which were surprisingly found in the catalytic sites rather than the anticipated dimerization interface.

Syntaxin 4 Mediates NF-κB Signaling and Chemokine Ligand Expression via Specific Interaction With IκBβ

Enrichment of human islets with syntaxin 4 (STX4) improves functional β-cell mass through a nuclear factor-κB (NF-κB)-dependent mechanism. However, the detailed mechanisms underlying the protective effect of STX4 are unknown. For determination of the signaling events linking STX4 enrichment and downregulation of NF-κB activity, STX4 was overexpressed in human islets, EndoC-βH1 and INS-1 832/13 cells in culture, and the cells were challenged with the proinflammatory cytokines interleukin-1β, tumor necrosis factor-α, and interferon-γ individually and in combination. STX4 expression suppressed cytokine-induced proteasomal degradation of IκBβ but not IκBα. Inhibition of IKKβ prevented IκBβ degradation, suggesting that IKKβ phosphorylates IκBβ. Moreover, the IKKβ inhibitor, as well as a proteosomal degradation inhibitor, prevented the loss of STX4 caused by cytokines. This suggests that STX4 may be phosphorylated by IKKβ in response to cytokines, targeting STX4 for proteosomal degradation. Expression of a stabilized form of STX4 further protected IκBβ from proteasomal degradation, and like wild-type STX4, stabilized STX4 coimmunoprecipitated with IκBβ and the p50-NF-κB. This work proposes a novel pathway wherein STX4 regulates cytokine-induced NF-κB signaling in β-cells via associating with and preventing IκBβ degradation, suppressing chemokine expression, and protecting islet β-cells from cytokine-mediated dysfunction and demise.

Molecular modelling analysis of T219A mutant envelope protein revealed novel virulence enhancing factors in Dengue virus isolated from Kerala state, India

Dengue virus (DENV) is an emerging health threat and its envelope glycoprotein E, is involved in the anchoring and fusion mechanisms. Anchoring followed by conformational changes of E-protein are responsible for the fusion and entry of DENV into host. The variation in the conformation of the E-protein due to mutations, results in its altered binding with antibodies (Abs) and also its receptors. This leads to failure of neutralization of DENV and enhance the infection. In our earlier studies we have identified T219A mutation in the E-protein of DENV and the present study is focused on the impact of this mutation on the conformation of E-protein and also its binding variation with Abs and Fc-γ receptor. A comparative molecular modelling studies of wild type and T219A mutant E-proteins revealed that, the mutation induced several conformational variations in the E-protein and resulted in the variable binding orientation with altered affinities. Further, the mutation was also observed to enhance the fusion mechanism by Fc-γ receptors that mediate the efficient entry of DENV into host cell through altered membrane fusion mechanism. Such conformational variations of E-protein could be the responsible factors for enhanced virulence of DENV infections.

Caspase Recruitment Domain-Containing Protein 9 Expression is a Novel Prognostic Factor for Lung Adenocarcinoma

Purpose

Caspase recruitment domain-containing protein 9 (CARD9) is expressed at high levels in bone marrow cells and has a crucial role in innate immunity. Current studies indicate that CARD9 also plays a key role in tumor progression, but there are few reports on the role of CARD9 in lung cancer. The aim of this study was to clarify the role of CARD9 in lung adenocarcinoma.

Patients and Methods

Lung adenocarcinoma tumor samples from 74 patients who underwent complete resection at Kobe University Hospital from January 2014 to December 2014 were analyzed by immunohistochemistry. The role of CARD9 in cancer cells was analyzed using lung cancer cell lines treated with CARD9 siRNA.

Results

High expression of CARD9 was observed in 32.4% of tumors, and compared to low expression of CARD9, high expression was associated with poorer overall survival (P = 0.0365). Univariate and multivariate analyses showed that high expression of CARD9 was an independent prognostic factor. Knockdown of CARD9 in lung adenocarcinoma cells inhibited proliferation but did not increase apoptosis. In addition, CARD9 activated the NF-κB pathway in a lung adenocarcinoma cell line.

Conclusion

CARD9 was shown to be an independent prognostic factor of poor outcome for lung cancer and may represent a molecular target for treatment.

NF-κB Inhibitors Attenuate MCAO Induced Neurodegeneration and Oxidative Stress-A Reprofiling Approach

Stroke is the leading cause of morbidity and mortality worldwide. About 87% of stroke cases are ischemic, which disrupt the physiological activity of the brain, thus leading to a series of complex pathophysiological events. Despite decades of research on neuroprotectants to probe for suitable therapies against ischemic stroke, no successful results have been obtained, and new alternative approaches are urgently required in order to combat this pathological torment. To address these problems, drug repositioning/reprofiling is explored extensively. Drug repurposing aims to identify new uses for already established drugs, and this makes it an attractive commercial strategy. Nuclear factor-kappa beta (NF-κB) is reported to be involved in many physiological and pathological conditions, such as neurodegeneration, neuroinflammation, and ischemia/reperfusion (I/R) injury. In this study, we examined the neuroprotective effects of atorvastatin, cephalexin, and mycophenolate against the NF-κB in ischemic stroke, as compared to the standard NF-κB inhibitor caeffic acid phenethyl ester (CAPE). An in-silico docking analysis was performed and their potential neuroprotective activities in the in vivo transient middle cerebral artery occlusion (t-MCAO) rat model was examined. The percent (%) infarct area and 28-point composite neuro score were examined, and an immunohistochemical analysis (IHC) and enzyme-linked immunosorbent assay (ELISA) were further performed to validate the neuroprotective role of these compounds in stroke as well as their potential as antioxidants. Our results demonstrated that these novels NF-κB inhibitors could attenuate ischemic stroke-induced neuronal toxicity by targeting NF-κB, a potential therapeutic approach in ischemic stroke.

Ovariectomy provokes inflammatory and cardiovascular effects of endotoxemia in rats: Dissimilar benefits of hormonal supplements

The female gender is protected against immunological complications of endotoxemia. Here we investigated whether gonadal hormone depletion by ovariectomy (OVX) uncovers inflammatory and cardiovascular effects of endotoxemia and whether these effects are reversed by hormone replacement therapies. Changes in inflammatory cytokines, blood pressure (BP), left ventricular (LV) function, and cardiac autonomic activity caused by lipopolysaccharide (LPS) in conscious female rats with different hormonal states were determined. In contrast to no effects in sham-operated females, treatment of OVX rats with LPS (i) decreased BP, (ii) increased spectral low-frequency/high-frequency ratio of HRV, denoting enhanced cardiac sympathetic dominance, (iii) attenuated reflex tachycardic responses to sodium nitroprusside, and (iv) increased systolic contractility (dP/dt_max). The developed hypotension was (i) fully eliminated in estrogen (E₂)-pretreated OVX rats, (ii) partially counteracted after selective activation of estrogen receptor-α (PPT) or β (DPN). All estrogenic compounds abrogated LPS enhancement of cardiac sympathetic drive. However, PPT was more successful than E2 or DPN in compromising LPS depression in baroreflex activity and elevation in dP/dt_max. Molecular studies showed that PPT was most effective in attenuating the upregulated myocardial expressions of NF-κB and iNOS in endotoxic OVX rats. Myocardial expression of the defensive HSP70 was comparably increased by all estrogenic products. Except for improved cardiac spectral activity, none of these functional or molecular entities was affected by medroxyprogesterone acetate (MPA). Overall, our data suggest diverse therapeutic advantages for gonadal hormones in the worsened endotoxic complications in rats with surgical menopause, with probably more favorable role for ERα agonism within this context.

Association of Fluorescent Protein Pairs and Its Significant Impact on Fluorescence and Energy Transfer

Fluorescent proteins (FPs) are commonly used in pairs to monitor dynamic biomolecular events through changes in proximity via distance dependent processes such as Förster resonance energy transfer (FRET). The impact of FP association is assessed by predicting dimerization sites in silico and stabilizing the dimers by bio-orthogonal covalent linkages. In each tested case dimerization changes inherent fluorescence, including FRET. GFP homodimers demonstrate synergistic behavior with the dimer being brighter than the sum of the monomers. The homodimer structure reveals the chromophores are close with favorable transition dipole alignments and a highly solvated interface. Heterodimerization (GFP with Venus) results in a complex with ≈87% FRET efficiency, significantly below the 99.7% efficiency predicted. A similar efficiency is observed when the wild-type FPs are fused to a naturally occurring protein-protein interface system. GFP complexation with mCherry results in loss of mCherry fluorescence. Thus, simple assumptions used when monitoring interactions between proteins via FP FRET may not always hold true, especially under conditions whereby the protein-protein interactions promote FP interaction.

BCL3 expression promotes resistance to alkylating chemotherapy in gliomas

The response of patients with gliomas to alkylating chemotherapy is heterogeneous. However, there are currently no universally accepted predictors of patient response to these agents. We identify the nuclear factor κB (NF-κB) co-regulator B cell CLL/lymphoma 3 (BCL-3) as an independent predictor of response to temozolomide (TMZ) treatment. In glioma patients with tumors that have a methylated O⁶-methylguanine DNA methyltransferase (MGMT) promoter, high BCL-3 expression was associated with a poor response to TMZ. Mechanistically, BCL-3 promoted a more malignant phenotype by inducing an epithelial-to-mesenchymal transition in glioblastomas through promoter-specific NF-κB dimer exchange. Carbonic anhydrase II (CAII) was identified as a downstream factor promoting BCL-3-mediated resistance to chemotherapy. Experiments in glioma xenograft mouse models demonstrated that the CAII inhibitor acetazolamide enhanced survival of TMZ-treated animals. Our data suggest that BCL-3 might be a useful indicator of glioma response to alkylating chemotherapy and that acetazolamide might be repurposed as a chemosensitizer for treating TMZ-resistant gliomas.

iGHBP: Computational identification of growth hormone binding proteins from sequences using extremely randomised tree

A soluble carrier growth hormone binding protein (GHBP) that can selectively and non-covalently interact with growth hormone, thereby acting as a modulator or inhibitor of growth hormone signalling. Accurate identification of the GHBP from a given protein sequence also provides important clues for understanding cell growth and cellular mechanisms. In the postgenomic era, there has been an abundance of protein sequence data garnered, hence it is crucial to develop an automated computational method which enables fast and accurate identification of putative GHBPs within a vast number of candidate proteins. In this study, we describe a novel machine-learning-based predictor called iGHBP for the identification of GHBP. In order to predict GHBP from a given protein sequence, we trained an extremely randomised tree with an optimal feature set that was obtained from a combination of dipeptide composition and amino acid index values by applying a two-step feature selection protocol. During cross-validation analysis, iGHBP achieved an accuracy of 84.9%, which was ~7% higher than the control extremely randomised tree predictor trained with all features, thus demonstrating the effectiveness of our feature selection protocol. Furthermore, when objectively evaluated on an independent data set, our proposed iGHBP method displayed superior performance compared to the existing method. Additionally, a user-friendly web server that implements the proposed iGHBP has been established and is available at http://thegleelab.org/iGHBP.

Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery

The advent of advanced molecular modeling software, big data analytics, and high-speed processing units has led to the exponential evolution of modern drug discovery and better insights into complex biological processes and disease networks. This has progressively steered current research interests to understanding protein-protein interaction (PPI) systems that are related to a number of relevant diseases, such as cancer, neurological illnesses, metabolic disorders, etc. However, targeting PPIs are challenging due to their "undruggable" binding interfaces. In this review, we focus on the current obstacles that impede PPI drug discovery, and how recent discoveries and advances in in silico approaches can alleviate these barriers to expedite the search for potential leads, as shown in several exemplary studies. We will also discuss about currently available information on PPI compounds and systems, along with their usefulness in molecular modeling. Finally, we conclude by presenting the limits of in silico application in drug discovery and offer a perspective in the field of computer-aided PPI drug discovery.

PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions

Proinflammatory cytokines have the capacity to increase inflammatory reaction and play a central role in first line of defence against invading pathogens. Proinflammatory inducing peptides (PIPs) have been used as an antineoplastic agent, an antibacterial agent and a vaccine in immunization therapies. Due to the advancement in sequence technologies that resulted an avalanche of protein sequence data. Therefore, it is necessary to develop an automated computational method to enable fast and accurate identification of novel PIPs within the vast number of candidate proteins and peptides. To address this, we proposed a new predictor, PIP-EL, for predicting PIPs using the strategy of ensemble learning (EL). Our benchmarking dataset is imbalanced. Thus, we applied a random under-sampling technique to generate 10 balanced models for each composition. Technically, PIP-EL is the fusion of 50 independent random forest (RF) models, where each of the five different compositions, including amino acid, dipeptide, composition-transition-distribution, physicochemical properties, and amino acid index contains 10 RF models. PIP-EL achieves the Matthews' correlation coefficient (MCC) of 0.435 in a 5-fold cross-validation test, which is ~2-5% higher than that of the individual classifiers and hybrid feature-based classifier. Furthermore, we evaluate the performance of PIP-EL on the independent dataset, showing that our method outperforms the existing method and two different machine learning methods developed in this study, with an MCC of 0.454. These results indicate that PIP-EL will be a useful tool for predicting PIPs and for researchers working in the field of peptide therapeutics and immunotherapy. The user-friendly web server, PIP-EL, is freely accessible.

iBCE-EL: A New Ensemble Learning Framework for Improved Linear B-Cell Epitope Prediction

Identification of B-cell epitopes (BCEs) is a fundamental step for epitope-based vaccine development, antibody production, and disease prevention and diagnosis. Due to the avalanche of protein sequence data discovered in postgenomic age, it is essential to develop an automated computational method to enable fast and accurate identification of novel BCEs within vast number of candidate proteins and peptides. Although several computational methods have been developed, their accuracy is unreliable. Thus, developing a reliable model with significant prediction improvements is highly desirable. In this study, we first constructed a non-redundant data set of 5,550 experimentally validated BCEs and 6,893 non-BCEs from the Immune Epitope Database. We then developed a novel ensemble learning framework for improved linear BCE predictor called iBCE-EL, a fusion of two independent predictors, namely, extremely randomized tree (ERT) and gradient boosting (GB) classifiers, which, respectively, uses a combination of physicochemical properties (PCP) and amino acid composition and a combination of dipeptide and PCP as input features. Cross-validation analysis on a benchmarking data set showed that iBCE-EL performed better than individual classifiers (ERT and GB), with a Matthews correlation coefficient (MCC) of 0.454. Furthermore, we evaluated the performance of iBCE-EL on the independent data set. Results show that iBCE-EL significantly outperformed the state-of-the-art method with an MCC of 0.463. To the best of our knowledge, iBCE-EL is the first ensemble method for linear BCEs prediction. iBCE-EL was implemented in a web-based platform, which is available at http://thegleelab.org/iBCE-EL. iBCE-EL contains two prediction modes. The first one identifying peptide sequences as BCEs or non-BCEs, while later one is aimed at providing users with the option of mining potential BCEs from protein sequences.

AIPpred: Sequence-Based Prediction of Anti-inflammatory Peptides Using Random Forest

The use of therapeutic peptides in various inflammatory diseases and autoimmune disorders has received considerable attention; however, the identification of anti-inflammatory peptides (AIPs) through wet-lab experimentation is expensive and often time consuming. Therefore, the development of novel computational methods is needed to identify potential AIP candidates prior to in vitro experimentation. In this study, we proposed a random forest (RF)-based method for predicting AIPs, called AIPpred (AIP predictor in primary amino acid sequences), which was trained with 354 optimal features. First, we systematically studied the contribution of individual composition [amino acid-, dipeptide composition (DPC), amino acid index, chain-transition-distribution, and physicochemical properties] in AIP prediction. Since the performance of the DPC-based model is significantly better than that of other composition-based models, we applied a feature selection protocol on this model and identified the optimal features. AIPpred achieved an area under the curve (AUC) value of 0.801 in a 5-fold cross-validation test, which was ∼2% higher than that of the control RF predictor trained with all DPC composition features, indicating the efficiency of the feature selection protocol. Furthermore, we evaluated the performance of AIPpred on an independent dataset, with results showing that our method outperformed an existing method, as well as 3 different machine learning methods developed in this study, with an AUC value of 0.814. These results indicated that AIPpred will be a useful tool for predicting AIPs and might efficiently assist the development of AIP therapeutics and biomedical research. AIPpred is freely accessible at www.thegleelab.org/AIPpred.

PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine

Accurately identifying bacteriophage virion proteins from uncharacterized sequences is important to understand interactions between the phage and its host bacteria in order to develop new antibacterial drugs. However, identification of such proteins using experimental techniques is expensive and often time consuming; hence, development of an efficient computational algorithm for the prediction of phage virion proteins (PVPs) prior to in vitro experimentation is needed. Here, we describe a support vector machine (SVM)-based PVP predictor, called PVP-SVM, which was trained with 136 optimal features. A feature selection protocol was employed to identify the optimal features from a large set that included amino acid composition, dipeptide composition, atomic composition, physicochemical properties, and chain-transition-distribution. PVP-SVM achieved an accuracy of 0.870 during leave-one-out cross-validation, which was 6% higher than control SVM predictors trained with all features, indicating the efficiency of the feature selection method. Furthermore, PVP-SVM displayed superior performance compared to the currently available method, PVPred, and two other machine-learning methods developed in this study when objectively evaluated with an independent dataset. For the convenience of the scientific community, a user-friendly and publicly accessible web server has been established at www.thegleelab.org/PVP-SVM/PVP-SVM.html.

DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest

DNase I hypersensitive sites (DHSs) are genomic regions that provide important information regarding the presence of transcriptional regulatory elements and the state of chromatin. Therefore, identifying DHSs in uncharacterized DNA sequences is crucial for understanding their biological functions and mechanisms. Although many experimental methods have been proposed to identify DHSs, they have proven to be expensive for genome-wide application. Therefore, it is necessary to develop computational methods for DHS prediction. In this study, we proposed a support vector machine (SVM)-based method for predicting DHSs, called DHSpred (DNase I Hypersensitive Site predictor in human DNA sequences), which was trained with 174 optimal features. The optimal combination of features was identified from a large set that included nucleotide composition and di- and trinucleotide physicochemical properties, using a random forest algorithm. DHSpred achieved a Matthews correlation coefficient and accuracy of 0.660 and 0.871, respectively, which were 3% higher than those of control SVM predictors trained with non-optimized features, indicating the efficiency of the feature selection method. Furthermore, the performance of DHSpred was superior to that of state-of-the-art predictors. An online prediction server has been developed to assist the scientific community, and is freely available at: http://www.thegleelab.org/DHSpred.html.

MLACP: machine-learning-based prediction of anticancer peptides

Cancer is the second leading cause of death globally, and use of therapeutic peptides to target and kill cancer cells has received considerable attention in recent years. Identification of anticancer peptides (ACPs) through wet-lab experimentation is expensive and often time consuming; therefore, development of an efficient computational method is essential to identify potential ACP candidates prior to in vitro experimentation. In this study, we developed support vector machine- and random forest-based machine-learning methods for the prediction of ACPs using the features calculated from the amino acid sequence, including amino acid composition, dipeptide composition, atomic composition, and physicochemical properties. We trained our methods using the Tyagi-B dataset and determined the machine parameters by 10-fold cross-validation. Furthermore, we evaluated the performance of our methods on two benchmarking datasets, with our results showing that the random forest-based method outperformed the existing methods with an average accuracy and Matthews correlation coefficient value of 88.7% and 0.78, respectively. To assist the scientific community, we also developed a publicly accessible web server at www.thegleelab.org/MLACP.html.

Negative pressure wound therapy inhibits inflammation and upregulates activating transcription factor-3 and downregulates nuclear factor-κB in diabetic patients with foot ulcerations

BACKGROUND

Negative pressure wound therapy (NPWT) is one of the most important treatments for diabetic foot, but the underlying mechanisms of its benefits still remain elusive. This study aims to evaluate the inflammatory signals involved in the effects of negative pressure therapy on diabetic foot ulcers.

METHODS

We enrolled 22 patients with diabetic foot ulceration, 11 treated with NPWT and the other 11 treated with traditional debridement. All patients were treated and observed for 1 week. Granulation tissues were harvested and analyzed in both groups, and then were histologically and immunohistochemically analyzed. Enzyme-linked immunosorbent assay, Western blot analysis, and real-time PCR were performed to evaluate the expression of interleukin-6 (IL-6), tumor necrosis factor α (TNF-α), inducible nitric oxide synthase (iNOS), nuclear factor-κB (NF-κB) p65, I_k B-α, and activating transcription factor-3 (ATF-3).

RESULTS

After 7 days of treatment, NPWT could obviously promote diabetic wound healing because of the mild inflammation and the dense cell-deposited matrix. Meanwhile, NPWT significantly decreased the expression of TNF-α, IL-6, and iNOS (all P < .05). The result of Western blotting and real-time PCR indicated that NPWT obviously decreased the level of I_k B-α and NF-κB p65, and increased the level of ATF-3 (all P < .05).

CONCLUSION

NPWT exerts an anti-inflammatory effect, possibly through the suppression of proinflammatory enzymes and cytokines resulting from I_k B-α inhibition and ATF-3 activation, which may prevent the activation of the NF-κB pathway in human diabetic foot wounds.

BRCA1 affects protein phosphatase 6 signalling through its interaction with ANKRD28

The tumour suppressor BRCA1 (breast and ovarian cancer-susceptibility gene 1) is implicated in several nuclear processes including DNA repair, transcription regulation and chromatin remodelling. BRCA1 also has some cytoplasmic functions including a pro-apoptotic activity. We identified ANKRD28 (ankyrin repeat domain 28) as a novel BRCA1-interacting protein in a yeast two-hybrid screen and confirmed this interaction by reciprocal immunoprecipitations of the two overexpressed proteins. Endogenous interaction between BRCA1 and ANKRD28 was also observed by co-immunoprecipitation and located in the cytoplasm by proximity ligation assay. The main site of interaction of ANKRD28 on BRCA1 is located in its intrinsically disordered scaffold central region. Whereas ANKRD28 silencing results in a destabilization of IκBε (inhibitor of nuclear factor κBε) through its activation of PP6 (protein phosphatase 6) co-regulator upon TNFα (tumour necrosis factor α) stimulation, BRCA1 overexpression stabilizes IκBε. A truncated form of BRCA1 that does not interact with ANKRD28 has no such effect. Our findings suggest that BRCA1 is a novel modulator of PP6 signalling via its interaction with ANKRD28. This new cytoplasmic process might participate in BRCA1 tumour-suppressor function.

NFκB-inducing kinase inhibits NFκB activity specifically in neurons of the CNS

The control of NFκB in CNS neurons appears to differ from that in other cell types. Studies have reported induction of NFκB in neuronal cultures and immunostaining in vivo, but others have consistently detected little or no transcriptional activation by NFκB in brain neurons. To test if neurons lack some component of the signal transduction system for NFκB activation, we transfected cortical neurons with several members of this signaling system along with a luciferase-based NFκB-reporter plasmid; RelA was cotransfected in some conditions. No component of the NFκB pathway was permissive for endogenous NFκB activity, and none stimulated the activity of exogenous RelA. Surprisingly, however, the latter was inhibited by cotransfection of NFκB-inducing kinase (NIK). Fluorescence imaging of RelA indicated that co-expression of NIK sequestered RelA in the cytoplasm, similar to the effect of IκBα. NIK-knockout mice showed elevated expression of an NFκB-reporter construct in neurons in vivo. Cortical neurons cultured from NIK-knockout mice showed elevated expression of an NFκB-reporter transgene. Consistent with data from other cell types, a C-terminal fragment of NIK suppressed RelA activity in astrocytes as well as neurons. Therefore, the inhibitory ability of the NIK C-terminus was unbiased with regard to cell type. However, inhibition of NFκB by full-length NIK is a novel outcome that appears to be specific to CNS neurons. This has implications for unique aspects of transcription in the CNS, perhaps relevant to aspects of development, neuroplasticity, and neuroinflammation. Full-length NIK was found to inhibit (down arrow) transcriptional activation of NFκB in neurons, while it elevated (up arrow) activity in astrocytes. Deletion constructs corresponding to the N-terminus or C-terminus also inhibited NFκB in neurons, while only the C-terminus did so in astrocytes. One possible explanation is that the inhibition in neurons occurs via two different mechanisms, including the potential for a neuron-specific protein (e.g., one of the 14-3-3 class) to create a novel complex in neurons, whereas the C-terminus may interact directly with NFκB. [Structure of NIK is based on Liu J., Sudom A., Min X., Cao Z., Gao X., Ayres M., Lee F., Cao P., Johnstone S., Plotnikova O., Walker N., Chen G., and Wang Z. (2012) Structure of the nuclear factor κB-inducing kinase (NIK) kinase domain reveals a constitutively active conformation. J Biol Chem. 287, 27326-27334); N-terminal lobe is oriented at top].

Structural Mechanism behind Distinct Efficiency of Oct4/Sox2 Proteins in Differentially Spaced DNA Complexes

The octamer-binding transcription factor 4 (Oct4) and sex-determining region Y (SRY)-box 2 (Sox2) proteins induce various transcriptional regulators to maintain cellular pluripotency. Most Oct4/Sox2 complexes have either 0 base pairs (Oct4/Sox2^0bp) or 3 base pairs (Oct4/Sox2^3bp) separation between their DNA-binding sites. Results from previous biochemical studies have shown that the complexes separated by 0 base pairs are associated with a higher pluripotency rate than those separated by 3 base pairs. Here, we performed molecular dynamics (MD) simulations and calculations to determine the binding free energy and per-residue free energy for the Oct4/Sox2^0bp and Oct4/Sox2^3bp complexes to identify structural differences that contribute to differences in induction rate. Our MD simulation results showed substantial differences in Oct4/Sox2 domain movements, as well as secondary-structure changes in the Oct4 linker region, suggesting a potential reason underlying the distinct efficiencies of these complexes during reprogramming. Moreover, we identified key residues and hydrogen bonds that potentially facilitate protein-protein and protein-DNA interactions, in agreement with previous experimental findings. Consequently, our results confess that differential spacing of the Oct4/Sox2 DNA binding sites can determine the magnitude of transcription of the targeted genes during reprogramming.

Activating transcription factor 3 represses inflammatory responses by binding to the p65 subunit of NF-κB

Activating transcription factor 3 (ATF3) is induced by inflammatory responses, cell death, cytokines, and oxidative stress conditions. ATF3 is a negative regulator in the Toll-like receptor 4 signalling pathway. The principal molecule in this pathway is nuclear factor κB (NF-κB) that translocates into the nucleus to initiate the transcription of inflammatory mediators. However, scarce data are available regarding the interaction of ATF3 and p65, a part of the NF-κB dimer. Therefore, we studied the mechanism of regulation of p65 by ATF3 in RAW 264.7 cells. First, LPS-mediated NF-κB activation was confirmed, and then the direct interaction of ATF3 and p65 was observed through immunoprecipitation (IP). The presence of histone deacetylase 1 (HDAC1) was also detected in the complex. In ATF3 deficient cells, NF-κB activity was up-regulated and HDAC1 was not detected by IP. These observations suggest that p65 is attenuated by ATF3 such that ATF3 recruits HDAC1 to the ATF3/p65 complex and facilitates the deacetylation of p65. Likewise, inflammatory response genes were induced by translocated NF-κB in ATF3-deficient cells. Cumulatively, we uncovered a novel mechanism for the negative regulation of NF-κB by ATF3 via direct interaction with p65.

In silico mechanistic analysis of IRF3 inactivation and high-risk HPV E6 species-dependent drug response

The high-risk human papillomavirus E6 (hrHPV E6) protein has been widely studied due to its implication in cervical cancer. In response to viral threat, activated kinases phosphorylate the IRF3 autoinhibitory domain, inducing type1 interferon production. HPV circumvents the antiviral response through the possible E6 interaction with IRF3 and abrogates p53's apoptotic activity by recruiting E6-associated protein. However, the molecular mechanism of IRF3 inactivation by hrHPV E6 has not yet been delineated. Therefore, we explored this mechanism through in silico examination of protein-protein and protein-ligand docking, binding energy differences, and computational alanine mutagenesis. Our results suggested that the LxxLL motifs of IRF3 binds within the hydrophobic pocket of E6, precluding Ser-patch phosphorylation, necessary for IRF3 activation and interferon induction. This model was further supported by molecular dynamics simulation. Furthermore, protein-ligand docking and drug resistance modeling revealed that the polar patches in the pocket of E6, which are crucial for complex stability and ligand binding, are inconsistent among hrHPV species. Such variabilities pose a risk of treatment failure owing to point mutations that might render drugs ineffective, and allude to multi-drug therapy. Overall, this study reveals a novel perspective of innate immune suppression in HPV infections and suggests a plausible therapeutic intervention.

Mapping the Interaction of B Cell Leukemia 3 (BCL-3) and Nuclear Factor κB (NF-κB) p50 Identifies a BCL-3-mimetic Anti-inflammatory Peptide

The NF-κB transcriptional response is tightly regulated by a number of processes including the phosphorylation, ubiquitination, and subsequent proteasomal degradation of NF-κB subunits. The IκB family protein BCL-3 stabilizes a NF-κB p50 homodimer·DNA complex through inhibition of p50 ubiquitination. This complex inhibits the binding of the transcriptionally active NF-κB subunits p65 and c-Rel on the promoters of NF-κB target genes and functions to suppress inflammatory gene expression. We have previously shown that the direct interaction between p50 and BCL-3 is required for BCL-3-mediated inhibition of pro-inflammatory gene expression. In this study we have used immobilized peptide array technology to define regions of BCl-3 that mediate interaction with p50 homodimers. Our data show that BCL-3 makes extensive contacts with p50 homodimers and in particular with ankyrin repeats (ANK) 1, 6, and 7, and the N-terminal region of Bcl-3. Using these data we have designed a BCL-3 mimetic peptide based on a region of the ANK1 of BCL-3 that interacts with p50 and shares low sequence similarity with other IκB proteins. When fused to a cargo carrying peptide sequence this BCL-3-derived peptide, but not a mutated peptide, inhibited Toll-like receptor-induced cytokine expression in vitro. The BCL-3 mimetic peptide was also effective in preventing inflammation in vivo in the carrageenan-induced paw edema mouse model. This study demonstrates that therapeutic strategies aimed at mimicking the functional activity of BCL-3 may be effective in the treatment of inflammatory disease.

The nuclear IκB family protein IκBNS influences the susceptibility to experimental autoimmune encephalomyelitis in a murine model

The nuclear IκB family protein IκB_NS is expressed in T cells and plays an important role in Interferon (IFN)-γ and Interleukin (IL)-2 production. IκB-ζ, the most similar homolog of IκB_NS, plays an important role in the generation of T helper (Th)17 cells in cooperation with RORγt, a master regulator of Th17 cells. Thus, IκB-ζ deficient mice are resistant to Th17-dependent experimental autoimmune encephalomyelitis (EAE). However, IκB-ζ deficient mice develop the autoimmune-like Sjögren syndrome with aging. Here we found that IκB_NS-deficient (Nfkbid^−/−) mice show resistance against developing Th17-dependent EAE. We found that Nfkbid^−/− T cells have decreased expression of IL-17-related genes and RORγt in response to Transforming Growth Factor (TGF)-β1 and IL-6 stimulation. Thus, IκB_NS plays a pivotal role in the generation of Th17 cells and in the control of Th17-dependent EAE.

Cross-species analysis reveals evolving and conserved features of the nuclear factor κB (NF-κB) proteins

NF-κB is a key regulator of immune gene expression in metazoans. It is currently unclear what changes occurred in NF-κB during animal evolution and what features remained conserved. To address this question, we compared the biochemical and functional properties of NF-κB proteins derived from human and the starlet sea anemone (Nematostella vectensis) in 1) a high-throughput assay of in vitro preferences for DNA sequences, 2) ChIP analysis of in vivo recruitment to the promoters of target genes, 3) a LUMIER-assisted examination of interactions with cofactors, and 4) a transactivation assay. We observed a remarkable evolutionary conservation of the DNA binding preferences of the animal NF-κB orthologs. We also show that NF-κB dimerization properties, nuclear localization signals, and binding to cytosolic IκBs are conserved. Surprisingly, the Bcl3-type nuclear IκB proteins functionally pair up only with NF-κB derived from their own species. The basis of the differential NF-κB recognition by IκB subfamilies is discussed.

Negative regulatory approaches to the attenuation of Toll-like receptor signaling

Toll-like receptors (TLRs) are pivotal components of the innate immune response, which is responsible for eradicating invading microorganisms through the induction of inflammatory molecules. These receptors are also involved in responding to harmful endogenous molecules and have crucial roles in the activation of the innate immune system and shaping the adaptive immune response. However, TLR signaling pathways must be tightly regulated because undue TLR stimulation may disrupt the fine balance between pro- and anti-inflammatory responses. Such disruptions may harm the host through the development of autoimmune and inflammatory diseases, such as rheumatoid arthritis and systemic lupus erythematosus. Several studies have investigated the regulatory pathways of TLRs that are essential for modulating proinflammatory responses. These studies reported several pathways and molecules that act individually or in combination to regulate immune responses. In this review, we have summarized recent advancements in the elucidation of the negative regulation of TLR signaling. Moreover, this review covers the modulation of TLR signaling at multiple levels, including adaptor complex destabilization, phosphorylation and ubiquitin-mediated degradation of signal proteins, manipulation of other receptors, and transcriptional regulation. Lastly, synthetic inhibitors have also been briefly discussed to highlight negative regulatory approaches in the treatment of inflammatory diseases.

Evolutionary, structural and functional interplay of the IκB family members

A primary level of control for nuclear factor kappa B (NF-κB) is effected through its interactions with the inhibitor protein, inhibitor of kappa B (IκB). Several lines of evidence confirm the existence of multiple forms of IκB that appear to regulate NF-κB by distinct mechanisms. Therefore, we performed a comprehensive bioinformatics analysis to understand the evolutionary history and intrinsic functional diversity of IκB family members. Phylogenetic relationships were constructed to trace the evolution of the IκB family genes. Our phylogenetic analysis revealed 10 IκB subfamily members that clustered into 5 major clades. Since the ankyrin (ANK) domain appears to be more ancient than the Rel homology domain (RHD), our phylogenetic analysis suggests that some undefined ancestral set of ANK repeats acquired an RHD before any duplication and was later duplicated and then diverged into the different IκB subfamilies. Functional analysis identified several functionally divergent sites in the ANK repeat domains (ARDs) and revealed that this region has undergone strong purifying selection, suggesting its functional importance in IκB genes. Structural analysis showed that the major variations in the number of ANK repeats and high conformational changes in the finger loop ARD region contribute to the differing binding partner specificities, thereby leading to distinct IκB functions. In summary, our study has provided useful information about the phylogeny and structural and functional divergence of the IκB family. Additionally, we identified a number of amino acid sites that contribute to the predicted functional divergence of these proteins.

Zerumbone attenuates the severity of acute necrotizing pancreatitis and pancreatitis-induced hepatic injury

This paper investigated the potential effects of zerumbone pretreatment on an acute necrotizing pancreatitis rat model induced by sodium taurocholate. The pancreatitis injury was evaluated by serum AMY, sPLA2, and pancreatic pathological score. Pancreatitis-induced hepatic injury was measured by ALT, AST, and hepatic histopathology. The expression of I-κBα and NF-κB protein was evaluated by western blot and immunohistochemistry assay while ICAM-1 and IL-1β mRNA were examined by RT-PCR. The results showed that AMY, sPLA2, ALT, and AST levels and histopathological assay of pancreatic and hepatic tissues were significantly reduced following administration of zerumbone. Applying zerumbone also has been shown to inhibit NF-κB protein and downregulation of ICAM-1 and IL-1β mRNA. The present paper suggests that treatment of zerumbone on rat attenuates the severity of acute necrotizing pancreatitis and pancreatitis-induced hepatic injury, via inhibiting NF-κB activation and downregulating the expression of ICAM-1 and IL-1β.

In silico approach to inhibition of signaling pathways of Toll-like receptors 2 and 4 by ST2L

Toll-like receptors (TLRs) activate a potent immunostimulatory response. There is clear evidence that overactivation of TLRs leads to infectious and inflammatory diseases. Recent biochemical studies have shown that the membrane-bound form of ST2 (ST2L), a member of the Toll-like/IL-1 receptor superfamily, negatively regulates MyD88-dependent TLR signaling pathways by sequestrating the adapters MyD88 and Mal (TIRAP). Specifically, ST2L attenuates the recruitment of Mal and MyD88 adapters to their receptors through its intracellular TIR domain. Thus, ST2L is a potent molecule that acts as a key regulator of endotoxin tolerance and modulates innate immunity. So far, the inhibitory mechanism of ST2L at the molecular level remains elusive. To develop a working hypothesis for the interactions between ST2L, TLRs (TLR1, 2, 4, and 6), and adapter molecules (MyD88 and Mal), we constructed three-dimensional models of the TIR domains of TLR4, 6, Mal, and ST2L based on homology modeling. Since the crystal structures of the TIR domains of TLR1, 2 as well as the NMR solution structure of MyD88 are known, we utilized these structures in our analysis. The TIR domains of TLR1, 2, 4, 6, MyD88, Mal and ST2L were subjected to molecular dynamics (MD) simulations in an explicit solvent environment. The refined structures obtained from the MD simulations were subsequently used in molecular docking studies to probe for potential sites of interactions. Through protein-protein docking analysis, models of the essential complexes involved in TLR2 and 4 signaling and ST2L inhibiting processes were developed. Our results suggest that ST2L may exert its inhibitory effect by blocking the molecular interface of Mal and MyD88 adapters mainly through its BB-loop region. Our predicted oligomeric signaling models may provide a basis for the understanding of the assembly process of TIR domain interactions, which has thus far proven to be difficult via in vivo studies.

Similar Structures but Different Roles - An Updated Perspective on TLR Structures

Toll-like receptors (TLRs) are pattern recognition receptors that recognize conserved structures in pathogens, trigger innate immune responses, and prime antigen-specific adaptive immunity. Elucidation of crystal structures of TLRs interacting with their ligands such as TLR1-2 with triacylated lipopeptide, TLR2-6 with diacylated lipopeptide, TLR4-MD-2 with LPS, and TLR3 with double-stranded RNA (dsRNA) have enabled an understanding of the initiation of TLR signaling. Agonistic ligands such as LPS, dsRNA, and lipopeptides induce "m" shaped TLR dimers in which C-termini converge at the center. Such central convergence is necessary to bring the two intracellular receptor TIR domains closer together and promote their dimerization, which serves as an essential step in downstream signaling. In this review, we summarize TLR ECD structures that have been reported to date with special emphasis on ligand recognition and activation mechanism.

Toll-like receptor modulators: a patent review (2006-2010)

INTRODUCTION

The immune response is mediated via two parallel immune components, innate and adaptive, whose effector functions are highly integrated and coordinated for the protection of the human body against invading pathogens and transformed cells. The discovery of pathogen recognition receptors (PRRs), most notably toll-like receptors (TLRs), in innate immunity has evoked increased interest in the therapeutic handling of the innate immune system. TLRs are germ line-encoded receptors that play a potent role in the recognition of a diverse variety of ligands ranging from hydrophilic nucleic acids to lipopolysaccharide (LPS) or peptidoglycan (PGN) structures in pathogens.

AREAS COVERED

This review discusses recent updates (2006-2010) in completed, ongoing and planned clinical trials of TLR immunomodulator-based therapies for the treatment of infectious diseases, inflammatory disorders and cancer.

EXPERT OPINION

Since the discovery of human TLRs, modulating immune responses using TLR agonists or antagonists for therapeutic purposes has provoked intense activity in the pharmaceutical industry. The ability of TLRs to initiate and propagate inflammation makes them attractive therapeutic targets. We are now at the stage of evaluating such molecules in human diseases. Additionally, there is also extensive literature available on TLRs in diseased states. These data provide a basis for the identification of novel immunomodulators (agonists and antagonists) for the therapeutic targeting of TLRs.