Peptides modulating conformational changes in secreted chaperones: from in silico design to preclinical proof of concept. Proc Natl Acad Sci U S A. 2009;106:13797-13801. [PMID: 19666568 DOI: 10.1073/pnas.0906514106]

Bioinformatics and Computer Simulation approaches to the discovery and analysis of Bioactive Peptides

The traditional process of separating and purifying bioactive peptides is laborious and time-consuming. Using a traditional process to identify is difficult, and there is a lack of fast and accurate activity evaluation methods. How to extract bioactive peptides quickly and efficiently is still the focus of bioactive peptides research. In order to improve the present situation of the research, bioinformatics techniques and peptidome methods are widely used in this field. At the same time, bioactive peptides have their own specific pharmacokinetic characteristics, so computer simulation methods have incomparable advantages in studying the pharmacokinetics and pharmacokinetic-pharmacodynamic correlation models of bioactive peptides. The purpose of this review is to summarize the combined applications of bioinformatics and computer simulation methods in the study of bioactive peptides, with focuses on the role of bioinformatics in simulating the selection of enzymatic hydrolysis and precursor proteins, activity prediction, molecular docking, physicochemical properties, and molecular dynamics. Our review shows that new bioactive peptide molecular sequences with high activity can be obtained by computer-aided design. The significance of the pharmacokinetic-pharmacodynamic correlation model in the study of bioactive peptides is emphasized. Finally, some problems and future development potential of bioactive peptides binding new technologies are prospected.

The Potential of Hsp90 in Targeting Pathological Pathways in Cardiac Diseases

Heat shock protein 90 (Hsp90) is a molecular chaperone that interacts with up to 10% of the proteome. The extensive involvement in protein folding and regulation of protein stability within cells makes Hsp90 an attractive therapeutic target to correct multiple dysfunctions. Many of the clients of Hsp90 are found in pathways known to be pathogenic in the heart, ranging from transforming growth factor β (TGF-β) and mitogen activated kinase (MAPK) signaling to tumor necrosis factor α (TNFα), G_s and G_q g-protein coupled receptor (GPCR) and calcium (Ca²⁺) signaling. These pathways can therefore be targeted through modulation of Hsp90 activity. The activity of Hsp90 can be targeted through small-molecule inhibition. Small-molecule inhibitors of Hsp90 have been found to be cardiotoxic in some cases however. In this regard, specific targeting of Hsp90 by modulation of post-translational modifications (PTMs) emerges as an attractive strategy. In this review, we aim to address how Hsp90 functions, where Hsp90 interacts within pathological pathways, and current knowledge of small molecules and PTMs known to modulate Hsp90 activity and their potential as therapeutics in cardiac diseases.

ReFOLD3: refinement of 3D protein models with gradual restraints based on predicted local quality and residue contacts

ReFOLD3 is unique in its application of gradual restraints, calculated from local model quality estimates and contact predictions, which are used to guide the refinement of theoretical 3D protein models towards the native structures. ReFOLD3 achieves improved performance by using an iterative refinement protocol to fix incorrect residue contacts and local errors, including unusual bonds and angles, which are identified in the submitted models by our leading ModFOLD8 model quality assessment method. Following refinement, the likely resulting improvements to the submitted models are recognized by ModFOLD8, which produces both global and local quality estimates. During the CASP14 prediction season (May-Aug 2020), we used the ReFOLD3 protocol to refine hundreds of 3D models, for both the refinement and the main tertiary structure prediction categories. Our group improved the global and local quality scores for numerous starting models in the refinement category, where we ranked in the top 10 according to the official assessment. The ReFOLD3 protocol was also used for the refinement of the SARS-CoV-2 targets as a part of the CASP Commons COVID-19 initiative, and we provided a significant number of the top 10 models. The ReFOLD3 web server is freely available at https://www.reading.ac.uk/bioinf/ReFOLD/.

COMTOP: Protein Residue-Residue Contact Prediction through Mixed Integer Linear Optimization

Protein contact prediction helps reconstruct the tertiary structure that greatly determines a protein’s function; therefore, contact prediction from the sequence is an important problem. Recently there has been exciting progress on this problem, but many of the existing methods are still low quality of prediction accuracy. In this paper, we present a new mixed integer linear programming (MILP)-based consensus method: a Consensus scheme based On a Mixed integer linear opTimization method for prOtein contact Prediction (COMTOP). The MILP-based consensus method combines the strengths of seven selected protein contact prediction methods, including CCMpred, EVfold, DeepCov, NNcon, PconsC4, plmDCA, and PSICOV, by optimizing the number of correctly predicted contacts and achieving a better prediction accuracy. The proposed hybrid protein residue–residue contact prediction scheme was tested in four independent test sets. For 239 highly non-redundant proteins, the method showed a prediction accuracy of 59.68%, 70.79%, 78.86%, 89.04%, 94.51%, and 97.35% for top-5L, top-3L, top-2L, top-L, top-L/2, and top-L/5 contacts, respectively. When tested on the CASP13 and CASP14 test sets, the proposed method obtained accuracies of 75.91% and 77.49% for top-L/5 predictions, respectively. COMTOP was further tested on 57 non-redundant α-helical transmembrane proteins and achieved prediction accuracies of 64.34% and 73.91% for top-L/2 and top-L/5 predictions, respectively. For all test datasets, the improvement of COMTOP in accuracy over the seven individual methods increased with the increasing number of predicted contacts. For example, COMTOP performed much better for large number of contact predictions (such as top-5L and top-3L) than for small number of contact predictions such as top-L/2 and top-L/5. The results and analysis demonstrate that COMTOP can significantly improve the performance of the individual methods; therefore, COMTOP is more robust against different types of test sets. COMTOP also showed better/comparable predictions when compared with the state-of-the-art predictors.

Peptides to combat viral infectious diseases

Viral infectious diseases have resulted in millions of deaths throughout history and have created a significant public healthcare burden. Tremendous efforts have been placed by the scientific communities, health officials and government organizations to detect, treat, and prevent viral infection. However, the complicated life cycle and rapid genetic mutations of viruses demand continuous development of novel medicines with high efficacy and safety profiles. Peptides provide a promising outlook as a tool to combat the spread and re-emergence of viral infection. This article provides an overview of five viral infectious diseases with high global prevalence: influenza, chronic hepatitis B, acquired immunodeficiency syndrome, severe acute respiratory syndrome, and coronavirus disease 2019. The current and potential peptide-based therapies, vaccines, and diagnostics for each disease are discussed.

An updated patent review of anticancer Hsp90 inhibitors (2013-present)

INTRODUCTION

Heat shock protein 90 (Hsp90) is one of the most critical chaperones amenable to mediating the folding and maturation of more than 300 client proteins. In normal cells, Hsp90 chaperone cycle is required for regulating multiple cellular processes to maintain homeostasis. However, extremely overexpressed Hsp90 in neoplastic cells results in the dysregulation of client proteins, many of which are indispensable to the accumulation of cancer hallmarks, such as infinite proliferation and increased invasiveness. Consequently, modulation of Hsp90 activity has been considered as a potential strategy for cancer treatment.

AREAS COVERED

This review recapitulated recent patents' progress in the development of Hsp90 inhibitors with potent antitumor activities during 2013 to present. Besides, the structural-activity relationships of the patented inhibitors and their structural similarity were also discussed.

EXPERT OPINION

Hsp90, as an anticancer target, has been investigated for several decades. The first generation of Hsp90 inhibitors exhibited potent antitumor activities in preclinical trials but were trapped in different phases of clinical trials. The second generation of Hsp90 inhibitors has been identified with increased specificity and security through structure modification. Moreover, these inhibitors may offer opportunities for studies of Hsp90 chaperone and development of Hsp90 inhibition therapy.

Extracellular gp96 is a crucial mediator for driving immune hyperactivation and liver damage

Liver failure leads to the massive necrosis of hepatocytes, releasing large amounts of intracellular components including damage-associated molecular patterns (DAMPs). We found that extracellular gp96 levels in serum were elevated in patients with chronic hepatitis B infection (CHB) and acute-on-chronic liver failure (ACLF). Meanwhile, the gp96 level positively correlated with hepatic necroinflammation. We employed two mouse liver damage and liver failure models induced by lipopolysaccharide (LPS) plus d-galactosamine (d-Galn), and concanavalin A (ConA) to identify the function of extracellular gp96. As a result, the inhibition of extracellular gp96 by a specific peptide efficiently mitigated both LPS/d-Galn- and ConA-induced liver injury and immune hyperactivation, whereas exogenous gp96 aggravated the symptoms of hepatic injury in mice but not in Kupffer cells-ablated mice. The exposure of Kupffer cells to gp96 induced the secretion of pro-inflammatory cytokines. Collectively, our data demonstrate that gp96 released from necrotic hepatocytes aggravates immune hyperactivation and promotes liver damage and possibly the development of liver failure mainly by activating Kupffer cells.

A peptide-based inhibitor of gp96 suppresses HBsAg expression and HBV replication by upregulation of p53

In hepatitis B virus (HBV) infection, the virus produces redundant hepatitis B surface antigen (HBsAg) that plays a key role in driving T-cell tolerance and viral persistence. However, currently available anti-HBV agents have no direct effect on HBsAg transcription and protein expression. In this study, we designed a heat shock protein gp96 inhibitor p37 with the cell penetrating peptide PTD (protein transduction domain of trans-activator of transcription), which mediated p37 internalization into hepatocytes. PTD-p37 effectively suppressed HBsAg expression and viral replication both in vitro and in vivo. We further provide evidence that PTD-p37 suppressed HBV enhancer/promoter activity via p53 upregulation. Moreover, PTD-p37 had antiviral activity against a lamivudine-resistant HBV strain. Considering that suppression of HBsAg expression is a major goal for treatment of HBV infection, our results provide a basis for developing a new therapeutic approaches targeting host factors against viral expression.

Gp96 Peptide Antagonist gp96-II Confers Therapeutic Effects in Murine Intestinal Inflammation

Background

The expression of heat shock protein gp96 is strongly correlated with the degree of tissue inflammation in ulcerative colitis and Crohn’s disease, thereby leading us to the hypothesis that inhibition of expression via gp96-II peptide prevents intestinal inflammation.

Methods

We employed daily injections of gp96-II peptide in two murine models of intestinal inflammation, the first resulting from five daily injections of IL-12/IL-18, the second via a single intrarectal application of TNBS (2,4,6-trinitrobenzenesulfonic acid). We also assessed the effectiveness of gp96-II peptide in murine and human primary cell culture.

Results

In the IL-12/IL-18 model, all gp96-II peptide-treated animals survived until day 5, whereas 80% of placebo-injected animals died. gp96-II peptide reduced IL-12/IL-18-induced plasma IFNγ by 89%, IL-1β by 63%, IL-6 by 43% and tumor necrosis factor (TNF) by 70% compared to controls. The clinical assessment Disease Activity Index of intestinal inflammation severity was found to be significantly lower in the gp96-II-treated animals when compared to vehicle-injected mice. gp96-II peptide treatment in the TNBS model limited weight loss to 5% on day 7 compared with prednisolone treatment, whereas placebo-treated animals suffered a 20% weight loss. Histological disease severity was reduced equally by prednisolone (by 40%) and gp96-II peptide (35%). Mice treated with either gp96-II peptide or prednisolone exhibited improved endoscopic scores compared with vehicle-treated control mice: vascularity, fibrin, granularity, and translucency scores were reduced by up to 49% by prednisolone and by up to 30% by gp96-II peptide. In vitro, gp96-II peptide reduced TLR2-, TLR4- and IL-12/IL-18-induced cytokine expression in murine splenocytes, with declines in constitutive IL-6 (54%), lipopolysaccharide-induced TNF (48%), IL-6 (81%) and in Staphylococcus epidermidis-induced TNF (67%) and IL-6 (81%), as well as IL-12/IL-18-induced IFNγ (75%). gp96-II peptide reduced IL–1β, IL-6, TNF and GM-CSF in human peripheral blood mononuclear cells to a similar degree without affecting cell viability, whereas RANTES, IL-25 and MIF were twofold to threefold increased.

Conclusion

gp96-II peptide protects against murine intestinal inflammation by regulating inflammation in vivo and in vitro, pointing to its promise as a novel treatment for inflammatory bowel disease.

RRCRank: a fusion method using rank strategy for residue-residue contact prediction

Background

In structural biology area, protein residue-residue contacts play a crucial role in protein structure prediction. Some researchers have found that the predicted residue-residue contacts could effectively constrain the conformational search space, which is significant for de novo protein structure prediction. In the last few decades, related researchers have developed various methods to predict residue-residue contacts, especially, significant performance has been achieved by using fusion methods in recent years. In this work, a novel fusion method based on rank strategy has been proposed to predict contacts. Unlike the traditional regression or classification strategies, the contact prediction task is regarded as a ranking task. First, two kinds of features are extracted from correlated mutations methods and ensemble machine-learning classifiers, and then the proposed method uses the learning-to-rank algorithm to predict contact probability of each residue pair.

Results

First, we perform two benchmark tests for the proposed fusion method (RRCRank) on CASP11 dataset and CASP12 dataset respectively. The test results show that the RRCRank method outperforms other well-developed methods, especially for medium and short range contacts. Second, in order to verify the superiority of ranking strategy, we predict contacts by using the traditional regression and classification strategies based on the same features as ranking strategy. Compared with these two traditional strategies, the proposed ranking strategy shows better performance for three contact types, in particular for long range contacts. Third, the proposed RRCRank has been compared with several state-of-the-art methods in CASP11 and CASP12. The results show that the RRCRank could achieve comparable prediction precisions and is better than three methods in most assessment metrics.

Conclusions

The learning-to-rank algorithm is introduced to develop a novel rank-based method for the residue-residue contact prediction of proteins, which achieves state-of-the-art performance based on the extensive assessment.

Electronic supplementary material

The online version of this article (10.1186/s12859-017-1811-9) contains supplementary material, which is available to authorized users.

Experimental Anti-Inflammatory Drug Semapimod Inhibits TLR Signaling by Targeting the TLR Chaperone gp96

Semapimod, a tetravalent guanylhydrazone, suppresses inflammatory cytokine production and has potential in a variety of inflammatory and autoimmune disorders. The mechanism of action of Semapimod is not well understood. In this study, we demonstrate that in rat IEC-6 intestinal epithelioid cells, Semapimod inhibits activation of p38 MAPK and NF-κB and induction of cyclooxygenase-2 by TLR ligands, but not by IL-1β or stresses. Semapimod inhibits TLR4 signaling (IC50 ≈0.3 μmol) and acts by desensitizing cells to LPS; it fails to block responses to LPS concentrations of ≥5 μg/ml. Inhibition of TLR signaling by Semapimod is almost instantaneous: the drug is effective when applied simultaneously with LPS. Semapimod blocks cell-surface recruitment of the MyD88 adapter, one of the earliest events in TLR signaling. gp96, the endoplasmic reticulum-localized chaperone of the HSP90 family critically involved in the biogenesis of TLRs, was identified as a target of Semapimod using ATP-desthiobiotin pulldown and mass spectroscopy. Semapimod inhibits ATP-binding and ATPase activities of gp96 in vitro (IC50 ≈0.2-0.4 μmol). On prolonged exposure, Semapimod causes accumulation of TLR4 and TLR9 in perinuclear space, consistent with endoplasmic reticulum retention, an anticipated consequence of impaired gp96 chaperone function. Our data indicate that Semapimod desensitizes TLR signaling via its effect on the TLR chaperone gp96. Fast inhibition by Semapimod is consistent with gp96 participating in high-affinity sensing of TLR ligands in addition to its role as a TLR chaperone.

Protein Residue Contacts and Prediction Methods

In the field of computational structural proteomics, contact predictions have shown new prospects of solving the longstanding problem of ab initio protein structure prediction. In the last few years, application of deep learning algorithms and availability of large protein sequence databases, combined with improvement in methods that derive contacts from multiple sequence alignments, have shown a huge increase in the precision of contact prediction. In addition, these predicted contacts have also been used to build three-dimensional models from scratch.In this chapter, we briefly discuss many elements of protein residue-residue contacts and the methods available for prediction, focusing on a state-of-the-art contact prediction tool, DNcon. Illustrating with a case study, we describe how DNcon can be used to make ab initio contact predictions for a given protein sequence and discuss how the predicted contacts may be analyzed and evaluated.

Blockage of conformational changes of heat shock protein gp96 on cell membrane by a α-helix peptide inhibits HER2 dimerization and signaling in breast cancer

Cell membrane translocation of heat shock protein gp96 from the endoplasmic reticulum has been observed in multiple tumors and is associated with tumor malignancy. However, the cancer-intrinsic function and the related mechanism of cell membrane gp96 as a pro-oncogenic chaperone remain further elucidated. In this study, we found that inhibition of gp96 intramolecular conformational changes by a single α-helix peptide p37 dramatically increased its binding to HER2, whereas decreased HER2 dimerization, phosphorylation and downstream signaling. Targeting cell membrane gp96 promoted HER2 ubiquitination and subsequent lysosomal degradation, which led to decreased cell growth and increased apoptosis, and inhibited tumor growth in vivo. We also demonstrate that gp96 inhibitory peptide p37 synergized with trastuzumab to suppress cell growth and induce apoptosis. Our work demonstrates that blocking gp96 conformational changes directs HER2 for cellular degradation, and represents a new therapeutic strategy for inhibiting HER2 signaling in cancer.

Expression of heat-shock protein gp96 in gallbladder cancer and its prognostic clinical significance

PURPOSE

To detect the expression and prognostic clinical significance of heat-shock protein gp96 (HSP gp96) in gallbladder cancer.

METHODS

Immunohistochemistry was used to detect and compare the rate of HSP gp96 expression in 107 samples of gallbladder cancer, 70 of gallbladder adenoma and 67 of chronic cholecystitis. The association of clinicopathological factors and patients' survival were calculated by univariate and multivariate (Cox proportional hazard regression method) analysis.

RESULTS

The expression positive rate of HSP gp96 was 90.7% (97/107) in gallbladder cancer, 71.4% (50/70) in gallbladder adenoma and 47.76% (32/67) in chronic cholecystitis respectively. The positive rate of HSP gp96 in gallbladder cancer tissues was significantly higher than that in gallbladder adenoma and chronic cholecystitis tissues (P < 0.01). Multivariate and Cox regression analysis showed that positive of HSP gp96 (P = 0.026) expression was an independent poor prognostic predictor in gallbladder cancer.

CONCLUSIONS

HSP gp96-positive expression is closely correlated with poor survival in gallbladder cancer.

Human α1-Antitrypsin Binds to Heat-Shock Protein gp96 and Protects from Endogenous gp96-Mediated Injury In vivo

The extracellular form of the abundant heat-shock protein, gp96, is involved in human autoimmune pathologies. In patients with type 1 diabetes, circulating gp96 is found to be elevated, and is bound to the acute-phase protein, α1-antitrypsin (AAT). The two molecules also engage intracellularly during the physiological folding of AAT. AAT therapy promotes pancreatic islet survival in both transplantation and autoimmune diabetes models, and several clinical trials are currently examining AAT therapy for individuals with type 1 diabetes. However, its mechanism of action is yet unknown. Here, we examine whether the protective activity of AAT is related to binding of extracellular gp96. Primary mouse islets, macrophages, and dendritic cells were added recombinant gp96 in the presence of clinical-grade human AAT (hAAT, Glassia™, Kamada Ltd., Israel). Islet function was evaluated by insulin release. The effect of hAAT on IL-1β/IFNγ-induced gp96 cell-surface levels was also evaluated. In vivo, skin transplantation was performed for examination of robust immune responses, and systemic inflammation was induced by cecal puncture. Endogenous gp96 was inhibited by gp96-inhibitory peptide (gp96i, Compugen Ltd., Israel) in an allogeneic islet transplantation model. Our findings indicate that hAAT binds to gp96 and diminishes gp96-induced inflammatory responses; e.g., hAAT-treated gp96-stimulated islets released less pro-inflammatory cytokines (IL-1β by 6.16-fold and TNFα by 2.69-fold) and regained gp96-disrupted insulin release. hAAT reduced cell activation during both skin transplantation and systemic inflammation, as well as lowered inducible surface levels of gp96 on immune cells. Finally, inhibition of gp96 significantly improved immediate islet graft function. These results suggest that hAAT is a regulator of gp96-mediated inflammatory responses, an increasingly appreciated endogenous damage response with relevance to human pathologies that are exacerbated by tissue injury.

A study and benchmark of DNcon: a method for protein residue-residue contact prediction using deep networks

BACKGROUND

In recent years, the use and importance of predicted protein residue-residue contacts has grown considerably with demonstrated applications such as drug design, protein tertiary structure prediction and model quality assessment. Nevertheless, reported accuracies in the range of 25-35% stubbornly remain the norm for sequence based, long range contact predictions on hard targets. This is in spite of a prolonged effort on behalf of the community to improve the performance of residue-residue contact prediction. A thorough study of the quality of current residue-residue contact predictions and the evaluation metrics used as well as an analysis of current methods is needed to stimulate further advancement in contact prediction and its application. Such a study will better explain the quality and nature of residue-residue contact predictions generated by current methods and as a result lead to better use of this contact information.

RESULTS

We evaluated several sequence based residue-residue contact predictors that participated in the tenth Critical Assessment of protein Structure Prediction (CASP) experiment. The evaluation was performed using standard assessment techniques such as those used by the official CASP assessors as well as two novel evaluation metrics (i.e., cluster accuracy and cluster count). An in-depth analysis revealed that while most residue-residue contact predictions generated are not accurate at the residue level, there is quite a strong contact signal present when allowing for less than residue level precision. Our residue-residue contact predictor, DNcon, performed particularly well achieving an accuracy of 66% for the top L/10 long range contacts when evaluated in a neighbourhood of size 2. The coverage of residue-residue contact areas was also greater with DNcon when compared to other methods. We also provide an analysis of DNcon with respect to its underlying architecture and features used for classification.

CONCLUSIONS

Our novel evaluation metrics demonstrate that current residue-residue contact predictions do contain a strong contact signal and are of better quality than standard evaluation metrics indicate. Our method, DNcon, is a robust, state-of-the-art residue-residue sequence based contact predictor and excelled under a number of evaluation schemes. It is available as a web service at http://iris.rnet.missouri.edu/dncon/.

The molecular chaperone apolipoprotein J/clusterin as a sensor of oxidative stress: implications in therapeutic approaches - a mini-review

BACKGROUND

Organisms are constantly exposed to physiological and environmental stresses and therefore require an efficient surveillance of genome and proteome quality in order to prevent disruption of homeostasis. Central to the intra- and extracellular proteome surveillance system are the molecular chaperones that contribute to both proteome maintenance and clearance. The conventional protein product of the apolipoprotein J/clusterin (CLU) gene is a heterodimeric secreted glycoprotein (also termed as sCLU) with a ubiquitous expression in human tissues. CLU exerts a small heat shock protein-like stress-induced chaperone activity and has been functionally implicated in numerous physiological processes as well as in ageing and most age-related diseases including tumorigenesis, neurodegeneration, and cardiovascular and metabolic syndromes.

OBJECTIVE

The CLU gene is differentially regulated by a wide variety of stimuli due to the combined presence of many distinct regulatory elements in its promoter that make it an extremely sensitive cellular biosensor of environmental and/or oxidative stress. Downstream to CLU gene induction, the CLU protein seems to actively intervene in pathological states of increased oxidative injury due to its chaperone-related property to inhibit protein aggregation and precipitation (a main feature of oxidant injury), as well as due to its reported distribution in both extra- and, most likely, intracellular compartments.

CONCLUSION

On the basis of these findings, CLU has emerged as a unique regulator of cellular proteostasis. Nevertheless, it seemingly exerts a dual function in pathology. For instance, in normal cells and during early phases of carcinogenesis, CLU may inhibit tumor progression as it contributes to suppression of proteotoxic stress. In advanced neoplasia, however, it may offer a significant survival advantage in the tumor by suppressing many therapeutic stressors and enhancing metastasis. This review will critically present a synopsis of recent novel findings that relate to the function of this amazing molecule and support the notion that CLU is a biosensor of oxidative injury; a common link between ageing and all pathologies where CLU has been implicated. Potential future perspectives, implications and opportunities for translational research and the development of new therapies will be discussed.

Predicting protein residue-residue contacts using deep networks and boosting

MOTIVATION

Protein residue-residue contacts continue to play a larger and larger role in protein tertiary structure modeling and evaluation. Yet, while the importance of contact information increases, the performance of sequence-based contact predictors has improved slowly. New approaches and methods are needed to spur further development and progress in the field.

RESULTS

Here we present DNCON, a new sequence-based residue-residue contact predictor using deep networks and boosting techniques. Making use of graphical processing units and CUDA parallel computing technology, we are able to train large boosted ensembles of residue-residue contact predictors achieving state-of-the-art performance.

AVAILABILITY

The web server of the prediction method (DNCON) is available at http://iris.rnet.missouri.edu/dncon/.

CONTACT

chengji@missouri.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A novel angiopoietin-derived peptide displays anti-angiogenic activity and inhibits tumour-induced and retinal neovascularization

BACKGROUND AND PURPOSE

Pathological angiogenesis is associated with various human diseases, such as cancer, autoimmune diseases and retinopathy. The angiopoietin (Ang)-Tie2 system plays critical roles in several steps of angiogenic remodelling. Here, we have investigated the anti-angiogenic effect of a novel angiopoietin-derived peptide.

EXPERIMENTAL APPROACH

Using computational methods, we identified peptides from helical segments within angiopoietins, which were predicted to inhibit their activity. These peptides were tested using biochemical methods and models of angiogenesis. The peptide with best efficacy, A11, was selected for further characterization as an anti-angiogenic compound.

KEY RESULTS

The potent anti-angiogenic activity of A11 was demonstrated in a multicellular assay of angiogenesis and in the chorioallantoic membrane model. A11 bound to angiopoietins and reduced the binding of Ang-2 to Tie2. A11 was also significantly reduced vascular density in a model of tumour-induced angiogenesis. Its ability to inhibit Ang-2 but not Ang-1-induced endothelial cell migration, and to down-regulate Tie2 levels in tumour microvessels, suggests that A11 targets the Ang-Tie2 pathway. In a rat model of oxygen-induced retinopathy, A11 strongly inhibited retinal angiogenesis. Moreover, combination of A11 with an anti-VEGF antibody showed a trend for further inhibition of angiogenesis, suggesting an additive effect.

CONCLUSIONS AND IMPLICATIONS

Our results indicate that A11 is a potent anti-angiogenic compound, through modulation of the Ang-Tie2 system, underlining its potential as a therapeutic agent for the treatment of ocular and tumour neovascularization, as well as other pathological conditions that are dependent on angiogenesis.

Chaperone gp96-independent inhibition of endotoxin response by chaperone-based peptide inhibitors

HSP90 chaperones a large number of proteins, and it plays essential roles in multiple signaling pathways to maintain protein homeostasis in the cytosol. In addition, HSP90 has been implicated in mediating recognition of lipopolysaccharide (LPS). However, no pharmacologic agents have been developed to interrogate this pathway. Herein we demonstrate that a peptide-based inhibitor that was previously reported to inhibit the master Toll-like receptor-chaperone gp96, an endoplasmic reticulum paralog of HSP90, in fact blocks HSP90-LPS interaction. It inhibited the binding of LPS to the cell surface of both wild type and gp96-null cells and thereby abrogated the cellular response to LPS but not to other Toll-like receptor ligands. We also generated a series of peptide derivatives (named peptide inhibitors of endotoxin responsiveness (PIERs)) from the N-terminal helix structure of HSP90 and demonstrated their effectiveness in blocking LPS activity. PIER inhibition of LPS signaling was partially reversed by CD14 expression. Moreover, we found that a cell-permeable PIER abrogated HSP90 function and caused degradation of multiple known HSP90 client proteins in cancer cells. Thus, targeting HSP90 is a promising modality for treatment of both LPS-mediated pathology and cancer.

The molecular chaperone gp96/GRP94 interacts with Toll-like receptors and integrins via its C-terminal hydrophobic domain

The structural basis for molecular chaperones to discern misfolded proteins has long been an enigma. As the endoplasmic reticulum paralogue of the cytosolic HSP90, gp96 (GRP94, HSP90b1) is an essential molecular chaperone for Toll-like receptors (TLRs) and integrins. However, little is known about its client-binding domain (CBD). Herein, we provide genetic and biochemical evidence to definitively demonstrate that a C-terminal loop structure, formed by residues 652-678, is the critical region of CBD for both TLRs and integrins. Deletion of this region affects neither the intrinsic ATPase activity nor the overall conformation of gp96. However, without it, the chaperoning function of gp96 collapses. We also find a critical Met pair (Met(658)-Met(662)) for the folding of integrins but not TLRs. Moreover, we find that the TLR binding to gp96 is also dependent on the C-terminal dimerization domain but not the N-terminal ATP-binding pocket of gp96. Our study has unveiled surprisingly the exquisite specificity of gp96 in substrate binding and suggests a manipulation of its CBD as an alternative strategy for targeted therapy of a variety of diseases.

A conformation ensemble approach to protein residue-residue contact

Background

Protein residue-residue contact prediction is important for protein model generation and model evaluation. Here we develop a conformation ensemble approach to improve residue-residue contact prediction. We collect a number of structural models stemming from a variety of methods and implementations. The various models capture slightly different conformations and contain complementary information which can be pooled together to capture recurrent, and therefore more likely, residue-residue contacts.

Results

We applied our conformation ensemble approach to free modeling targets from both CASP8 and CASP9. Given a diverse ensemble of models, the method is able to achieve accuracies of. 48 for the top L/5 medium range contacts and. 36 for the top L/5 long range contacts for CASP8 targets (L being the target domain length). When applied to targets from CASP9, the accuracies of the top L/5 medium and long range contact predictions were. 34 and. 30 respectively.

Conclusions

When operating on a moderately diverse ensemble of models, the conformation ensemble approach is an effective means to identify medium and long range residue-residue contacts. An immediate benefit of the method is that when tied with a scoring scheme, it can be used to successfully rank models.

Using peptides to study protein-protein interactions

Protein-protein interactions (PPIs) govern all aspects of cell function and, as such, are a major target for research and therapeutic intervention. A major rate-limiting step in PPI research is the expression and purification of full-length proteins. The use of peptides to study PPIs significantly facilitates the structural and biophysical characterization of PPIs as well as the effort to develop drugs to control PPIs. Here we describe examples for the use of peptides to study PPI and some of the important experimental methods that are used in the field. Peptides have proved to be excellent tools to study PPIs and have been contributing both for understanding mechanisms of PPIs as well as for drug design for PPI modulation.

Computational approaches to therapeutic peptide discovery

The development of peptides with therapeutic activities can be based on naturally occurring peptides or alternatively on de novo design. The discovery of natural peptides is often a matter of serendipity. In part, this is because natural peptides are typically proteolytically cleaved out from precursor proteins, a feature that averts the direct benefits of the genomic revolution. The first part of this review describes attempts to create a more systematic identification of natural peptides relying on a two step process. In the initial step, an in silico peptidome is predicted through the use of machine learning. Then, various computational biology tools are tailored to focus on peptides predicted to have the desired biological activity; for example, activating a GPCR or modulating the cellular arm of the immune system. The second part of the review is devoted to de novo peptide design and focuses on arguably the simplest scenario in which the designed peptide corresponds to a contiguous protein subsequence. Amongst these peptides, those corresponding to helical segments are prominent, mainly due to their relative ability to fold independently. Inspired by the clinical success of viral entry inhibitors, which are peptides corresponding to helical segments in viral envelope proteins, a computational tool for the identification of intramolecular helix-helix interactions was developed. Using this approach, peptides having anti-cancer, anti-angiogenic, and anti-inflammatory activities have been recently rationally designed and biologically characterized.

Computational design of peptide ligands

Peptides possess several attractive features when compared to small molecule and protein therapeutics, such as high structural compatibility with target proteins, the ability to disrupt protein-protein interfaces, and small size. Efficient design of high-affinity peptide ligands via rational methods has been a major obstacle to the development of this potential drug class. However, structural insights into the architecture of protein-peptide interfaces have recently culminated in several computational approaches for the rational design of peptides that target proteins. These methods provide a valuable alternative to experimental high-resolution structures of target protein-peptide complexes, bringing closer the dream of in silico designed peptides for therapeutic applications.

Correlation between gp96 expression and the surgical outcome in patients with esophageal squamous cell carcinoma

BACKGROUND

Heat-shock protein gp96 plays an important role in antitumor immunoreactions. Gp96 has a close relationship with antitumor immunity. This study evaluated the correlation between gp96 expression and the prognosis in esophageal squamous cell carcinoma.

METHODS

Seventy-eight patients with primarily resected esophageal squamous cell carcinoma were enrolled onto this study, and gp96 expression was evaluated by immunohistochemical staining. The association of clinicopathological factors and patients' survival was calculated by univariate (log rank test) and multivariate (Cox proportional hazard regression method) analyses.

RESULTS

Fifty-seven (73%) of 78 cases were gp96 positive, and 21 were negative (27%). The survival of patients with gp96-negative disease was significantly shorter (5-year survival, 22.9 months) than with gp96-positive disease (45.8 months; P = 0.049), and the multivariate analysis showed that gp96 negativity is an independent risk factor for poor survival (hazard ratio, 2.577; P = 0.040). Gp96-negative cases had more metastatic lymph nodes than did negative cases, especially in T1 cases (4.8 in gp96-negative cases vs. 0.84 in gp96-positive cases; P = 0.064)

CONCLUSIONS

The downregulation of gp96 expression is closely correlated with poor survival in esophageal squamous cell carcinoma.

Clinical significance of clusterin expression in esophageal squamous cell carcinoma

AIM: To investigate the expression of clusterin mRNA in esophageal squamous cell carcinoma (ESCC), measure preoperative and postoperative serum clusterin protein levels in ESCC patients, and evaluate their correlations with clinicopathological parameters in ESCC.

METHODS: The expression of full-length clusterin mRNA in ESCC tissue was detected by semi-quantitative reverse transcription-polymerase chain reaction (RT-PCR). Serum clusterin level was measured by enzyme-linked immunosorbent assay (ELISA).

RESULTS: The expression of clusterin mRNA was significantly down-regulated in ESCC tissue compared with matched tumor-adjacent non-cancerous tissue. The median level of serum clusterin in postoperative ESCC patients was significantly higher than that in preoperative patients (25.71 mg/L vs 3.23 mg/L, P < 0.0001). The level of serum clusterin is correlated with tumor size, but not with age, gender, tumor differentiation, tumor grade, lymph node metastasis and biochemical parameters.

CONCLUSION: The expression of clusterin mRNA is down-regulated in ESCC. Serum clusterin level decreases in ESCC patients. Clusterin might be a potential tumor suppressor gene in ESCC. Dynamic measurement of serum clusterin level might aid to evaluate the progression of ESCC.

Reducing phylogenetic bias in correlated mutation analysis

Correlated mutation analysis (CMA) is a sequence-based approach for ab initio protein contact map prediction. The basis of this approach is the observed correlation between mutations in interacting amino acid residues. These correlations are often estimated by either calculating the Pearson's correlation coefficient (PCC) or the mutual information (MI) between columns in a multiple sequence alignment (MSA) of the protein of interest and its homologs. A major challenge of CMA is to filter out the background noise originating from phylogenetic relatedness between sequences included in the MSA. Recently, a procedure to reduce this background noise was demonstrated to improve an MI-based predictor. Herein, we tested whether a similar approach can also improve the performance of the classical PCC-based method. Indeed, performance improvements were achieved for all four major SCOP classes. Furthermore, the results reveal that the improved PCC-based method is superior to MI-based methods for proteins having MSAs of up to 100 sequences.