Identification of SRC as a potent drug target for asthma, using an integrative approach of protein interactome analysis and in silico drug discovery

Quantum chemical, spectroscopic and molecular docking investigations of potential pulmonary fibrosis drug methyl 2-chloro 4-iodonicotinate

In this work, the methyl 2-chloro 4-iodonicotinate (MCIN) was investigated to study the structural, spectroscopic and electronic properties using density functional theory (DFT) quantum chemical calculations. The most stable structure of MCIN was optimized by DFT/B3LYP method with a LanLD2Z basis set. The optimized parameters and vibrational wavenumbers were determined. The vibrational task of the molecule was done by potential energy distribution calculations. The ¹³ C NMR spectrum of the MCIN molecule was simulated by the Gauge-Invariant-Atomic Orbital method using a dimethyl sulfoxide solution and the isotropic chemical shift values of the molecule were calculated and observed. Ultraviolet-visible spectra were simulated and observed. The pharmaceutical activity was predicted using frontier molecular orbital and natural bond orbital analysis. The reactive sites of the MCIN molecule were determined using Mulliken atomic charge distribution, molecular electrostatic potential surface and the local reactivity analysis. The molecular docking analysis confirms that the title molecule can be used in drug design for the treatment of pulmonary fibrosis.

Clinical relevance of CERK and SPHK1 in breast cancer and their association with metastasis and drug resistance

Despite numerous reports on the altered sphingolipids metabolism in human cancers, their clinical significance in breast cancer remains obscure. Previously, we identified the high levels of sphingolipids, ceramide phosphates and sphingosine phosphates, and the genes involved in their synthesis, CERK and SPHK1, in breast cancer patients. The present study aimed to determine the correlations of CERK and SPHK1 with clinical outcomes as well as metastasis and drug resistance markers. Both local and TCGA cohorts were analysed. High-confidence regulatory interaction network was constructed to find association of target genes with metastasis and drug resistance. Furthermore, correlations of CERK and SPHK1 with selected metastasis and drug resistance markers were validated in both cohorts. Overexpression of CERK and SPHK1 was associated with nodal metastasis, late tumor stage and high proliferation potency. In addition, increased CERK expression was also indicative of poor patient survival. Computational network analysis revealed the association of CERK and SPHK1 with known metastasis markers MMP-2 and MMP-9 and drug resistance markers ABCC1 and ABCG2. Correlation analysis confirmed the associations of target genes with these markers in both local as well as TCGA cohort. The above findings suggest clinical utility of CERK and SPHK1 as potential biomarkers in breast cancer patients and thus could provide novel leads in the development of therapeutics.

Oxidation-Dependent Activation of Src Kinase Mediates Epithelial IL-33 Production and Signaling during Acute Airway Allergen Challenge

The respiratory epithelium forms the first line of defense against inhaled pathogens and acts as an important source of innate cytokine responses to environmental insults. One critical mediator of these responses is the IL-1 family cytokine IL-33, which is rapidly secreted upon acute epithelial injury as an alarmin and induces type 2 immune responses. Our recent work highlighted the importance of the NADPH oxidase dual oxidase 1 (DUOX1) in acute airway epithelial IL-33 secretion by various airborne allergens associated with H2O2 production and reduction-oxidation-dependent activation of Src kinases and epidermal growth factor receptor (EGFR) signaling. In this study, we show that IL-33 secretion in response to acute airway challenge with house dust mite (HDM) allergen critically depends on the activation of Src by a DUOX1-dependent oxidative mechanism. Intriguingly, HDM-induced epithelial IL-33 secretion was dramatically attenuated by small interfering RNA- or Ab-based approaches to block IL-33 signaling through its receptor IL1RL1 (ST2), indicating that HDM-induced IL-33 secretion includes a positive feed-forward mechanism involving ST2-dependent IL-33 signaling. Moreover, activation of type 2 cytokine responses by direct airway IL-33 administration was associated with ST2-dependent activation of DUOX1-mediated H2O2 production and reduction-oxidation-based activation of Src and EGFR and was attenuated in Duox1 -/- and Src +/- mice, indicating that IL-33-induced epithelial signaling and subsequent airway responses involve DUOX1/Src-dependent pathways. Collectively, our findings suggest an intricate relationship between DUOX1, Src, and IL-33 signaling in the activation of innate type 2 immune responses to allergens, involving DUOX1-dependent epithelial Src/EGFR activation in initial IL-33 secretion and in subsequent IL-33 signaling through ST2 activation.

Src-dependent EGFR transactivation regulates lung inflammation via downstream signaling involving ERK1/2, PI3Kδ/Akt and NFκB induction in a murine asthma model

The molecular mechanisms underlying asthma pathogenesis are poorly characterized. In this study, we investigated (1) whether Src mediates epidermal growth factor receptor (EGFR) transactivation; (2) if ERK1/2, PI3Kδ/Akt and NF-κB are signaling effectors downstream of Src/EGFR activation; and (3) if upstream inhibition of Src/EGFR is more effective in downregulating the allergic inflammation than selective inhibition of downstream signaling pathways. Allergic inflammation resulted in increased phosphorylation of EGFR, Akt, ERK1/2 and IκB in the lung tissues from ovalbumin (OVA)-challenged BALB/c mice. Treatment with inhibitors of Src (SU6656) or EGFR (AG1478) reduced EGFR phosphorylation and downstream signaling which resulted in the inhibition of the OVA-induced inflammatory cell influx in bronchoalveolar lavage fluid (BALF), perivascular and peribronchial inflammation, fibrosis, goblet cell hyper/metaplasia and airway hyper-responsiveness. Treatment with pathway-selective inhibitors for ERK1/2 (PD89059) and PI3Kδ/Akt (IC-87114) respectively, or an inhibitor of NF-κB (BAY11-7085) also reduced the OVA-induced asthmatic phenotype but to a lesser extent compared to Src/EGFR inhibition. Thus, Src via EGFR transactivation and subsequent downstream activation of multiple pathways regulates the allergic airway inflammatory response. Furthermore, a broader upstream inhibition of Src/EGFR offers an attractive therapeutic alternative in the treatment of asthma relative to selectively targeting the individual downstream signaling effectors.

Computational analysis of multimorbidity between asthma, eczema and rhinitis

Background

The mechanisms explaining the co-existence of asthma, eczema and rhinitis (allergic multimorbidity) are largely unknown. We investigated the mechanisms underlying multimorbidity between three main allergic diseases at a molecular level by identifying the proteins and cellular processes that are common to them.

Methods

An in silico study based on computational analysis of the topology of the protein interaction network was performed in order to characterize the molecular mechanisms of multimorbidity of asthma, eczema and rhinitis. As a first step, proteins associated to either disease were identified using data mining approaches, and their overlap was calculated. Secondly, a functional interaction network was built, allowing to identify cellular pathways involved in allergic multimorbidity. Finally, a network-based algorithm generated a ranked list of newly predicted multimorbidity-associated proteins.

Results

Asthma, eczema and rhinitis shared a larger number of associated proteins than expected by chance, and their associated proteins exhibited a significant degree of interconnectedness in the interaction network. There were 15 pathways involved in the multimorbidity of asthma, eczema and rhinitis, including IL4 signaling and GATA3-related pathways. A number of proteins potentially associated to these multimorbidity processes were also obtained.

Conclusions

These results strongly support the existence of an allergic multimorbidity cluster between asthma, eczema and rhinitis, and suggest that type 2 signaling pathways represent a relevant multimorbidity mechanism of allergic diseases. Furthermore, we identified new candidates contributing to multimorbidity that may assist in identifying new targets for multimorbid allergic diseases.

Kinases as Novel Therapeutic Targets in Asthma and Chronic Obstructive Pulmonary Disease

Multiple kinases play a critical role in orchestrating the chronic inflammation and structural changes in the respiratory tract of patients with asthma and chronic obstructive pulmonary disease (COPD). Kinases activate signaling pathways that lead to contraction of airway smooth muscle and release of inflammatory mediators (such as cytokines, chemokines, growth factors) as well as cell migration, activation, and proliferation. For this reason there has been great interest in the development of kinase inhibitors as anti-inflammatory therapies, particular where corticosteroids are less effective, as in severe asthma and COPD. However, it has proven difficult to develop selective kinase inhibitors that are both effective and safe after oral administration and this has led to a search for inhaled kinase inhibitors, which would reduce systemic exposure. Although many kinases have been implicated in inflammation and remodeling of airway disease, very few classes of drug have reached the stage of clinical studies in these diseases. The most promising drugs are p38 MAP kinases, isoenzyme-selective PI3-kinases, Janus-activated kinases, and Syk-kinases, and inhaled formulations of these drugs are now in development. There has also been interest in developing inhibitors that block more than one kinase, because these drugs may be more effective and with less risk of losing efficacy with time. No kinase inhibitors are yet on the market for the treatment of airway diseases, but as kinase inhibitors are improved from other therapeutic areas there is hope that these drugs may eventually prove useful in treating refractory asthma and COPD.

Multiple target drug cocktail design for attacking the core network markers of four cancers using ligand-based and structure-based virtual screening methods

BACKGROUND

Computer-aided drug design has a long history of being applied to discover new molecules to treat various cancers, but it has always been focused on single targets. The development of systems biology has let scientists reveal more hidden mechanisms of cancers, but attempts to apply systems biology to cancer therapies remain at preliminary stages. Our lab has successfully developed various systems biology models for several cancers. Based on these achievements, we present the first attempt to combine multiple-target therapy with systems biology.

METHODS

In our previous study, we identified 28 significant proteins--i.e., common core network markers--of four types of cancers as house-keeping proteins of these cancers. In this study, we ranked these proteins by summing their carcinogenesis relevance values (CRVs) across the four cancers, and then performed docking and pharmacophore modeling to do virtual screening on the NCI database for anti-cancer drugs. We also performed pathway analysis on these proteins using Panther and MetaCore to reveal more mechanisms of these cancer house-keeping proteins.

RESULTS

We designed several approaches to discover targets for multiple-target cocktail therapies. In the first one, we identified the top 20 drugs for each of the 28 cancer house-keeping proteins, and analyzed the docking pose to further understand the interaction mechanisms of these drugs. After screening for duplicates, we found that 13 of these drugs could target 11 proteins simultaneously. In the second approach, we chose the top 5 proteins with the highest summed CRVs and used them as the drug targets. We built a pharmacophore and applied it to do virtual screening against the Life-Chemical library for anti-cancer drugs. Based on these results, wet-lab bio-scientists could freely investigate combinations of these drugs for multiple-target therapy for cancers, in contrast to the traditional single target therapy.

CONCLUSIONS

Combination of systems biology with computer-aided drug design could help us develop novel drug cocktails with multiple targets. We believe this will enhance the efficiency of therapeutic practice and lead to new directions for cancer therapy.

Re-analysis of protein data reveals the germination pathway and up accumulation mechanism of cell wall hydrolases during the radicle protrusion step of seed germination in Podophyllum hexandrum- a high altitude plant

Podophyllum hexandrum Royle is an important high-altitude plant of Himalayas with immense medicinal value. Earlier, it was reported that the cell wall hydrolases were up accumulated during radicle protrusion step of Podophyllum seed germination. In the present study, Podophyllum seed Germination protein interaction Network (PGN) was constructed by using the differentially accumulated protein (DAP) data set of Podophyllum during the radicle protrusion step of seed germination, with reference to Arabidopsis protein-protein interaction network (AtPIN). The developed PGN is comprised of a giant cluster with 1028 proteins having 10,519 interactions and a few small clusters with relevant gene ontological signatures. In this analysis, a germination pathway related cluster which is also central to the topology and information dynamics of PGN was obtained with a set of 60 key proteins. Among these, eight proteins which are known to be involved in signaling, metabolism, protein modification, cell wall modification, and cell cycle regulation processes were found commonly highlighted in both the proteomic and interactome analysis. The systems-level analysis of PGN identified the key proteins involved in radicle protrusion step of seed germination in Podophyllum.

Network analysis identifies protein clusters of functional importance in juvenile idiopathic arthritis

Introduction

Our objective was to utilise network analysis to identify protein clusters of greatest potential functional relevance in the pathogenesis of oligoarticular and rheumatoid factor negative (RF-ve) polyarticular juvenile idiopathic arthritis (JIA).

Methods

JIA genetic association data were used to build an interactome network model in BioGRID 3.2.99. The top 10% of this protein:protein JIA Interactome was used to generate a minimal essential network (MEN). Reactome FI Cytoscape 2.83 Plugin and the Disease Association Protein-Protein Link Evaluator (Dapple) algorithm were used to assess the functionality of the biological pathways within the MEN and to statistically rank the proteins. JIA gene expression data were integrated with the MEN and clusters of functionally important proteins derived using MCODE.

Results

A JIA interactome of 2,479 proteins was built from 348 JIA associated genes. The MEN, representing the most functionally related components of the network, comprised of seven clusters, with distinct functional characteristics. Four gene expression datasets from peripheral blood mononuclear cells (PBMC), neutrophils and synovial fluid monocytes, were mapped onto the MEN and a list of genes enriched for functional significance identified. This analysis revealed the genes of greatest potential functional importance to be PTPN2 and STAT1 for oligoarticular JIA and KSR1 for RF-ve polyarticular JIA. Clusters of 23 and 14 related proteins were derived for oligoarticular and RF-ve polyarticular JIA respectively.

Conclusions

This first report of the application of network biology to JIA, integrating genetic association findings and gene expression data, has prioritised protein clusters for functional validation and identified new pathways for targeted pharmacological intervention.

Identification of key nodes of type 2 diabetes mellitus protein interactome and study of their interactions with phloridzin

Network biology-inspired approaches could be used effectively in probing regulatory processes by which small molecules intervene with disease mechanisms. The present study aims at identification of key targets of type 2 diabetes mellitus (T2DM) by network analysis of the underlying protein interactome, and probing for mechanisms by which phloridzin could be critical at altering the disease phenotype. Towards this goal, we constructed a protein-protein interaction network associated with T2DM, starting from candidate genes and systems-level interactions data available. The relevance of the network constructed was verified with the help of gene ontology, node deletion, and biological essentiality studies. Using a network analysis method, MAPK1, EP300, and SMAD2 were identified as the most central proteins of potential therapeutic value. Phloridzin, a known antidiabetic agent, potentially interacts with proteins central to T2DM mechanisms. The structural understanding of interaction of phloridzin with these proteins of relevance to T2DM could provide better insight into its regulatory mechanisms and help in developing better therapeutic agents. The molecular docking results suggest that phloridzin is potentially involved in making critical interactions with MAPK1. These results could further be validated by experimental studies and could be used to design therapeutic agents for T2DM intervention.

Prospecting for novel plant-derived molecules of Rauvolfia serpentina as inhibitors of Aldose Reductase, a potent drug target for diabetes and its complications

Aldose Reductase (AR) is implicated in the development of secondary complications of diabetes, providing an interesting target for therapeutic intervention. Extracts of Rauvolfia serpentina, a medicinal plant endemic to the Himalayan mountain range, have been known to be effective in alleviating diabetes and its complications. In this study, we aim to prospect for novel plant-derived inhibitors from R. serpentina and to understand structural basis of their interactions. An extensive library of R. serpentina molecules was compiled and computationally screened for inhibitory action against AR. The stability of complexes, with docked leads, was verified using molecular dynamics simulations. Two structurally distinct plant-derived leads were identified as inhibitors: indobine and indobinine. Further, using these two leads as templates, 16 more leads were identified through ligand-based screening of their structural analogs, from a small molecules database. Thus, we obtained plant-derived indole alkaloids, and their structural analogs, as potential AR inhibitors from a manually curated dataset of R. serpentina molecules. Indole alkaloids reported herein, as a novel structural class unreported hitherto, may provide better insights for designing potential AR inhibitors with improved efficacy and fewer side effects.