Assessment of NORMs (238U, 232Th, 40K) and radiation hazard indices in Beldih apatite mine region of Purulia district, West Bengal, India.

The radiation arising from naturally occurring radioactive materials (NORMs) is the foremost contributor to the collective dose received by the global population. The present study aims to measure the natural background radiation level and the associated gamma radiation dose in air in the Beldih apatite mine region of Purulia district, India. This study is primarily focused on the determination of 238U, 232Th and 40K activities in the sub-surface soil of the study area. The measurements were carried out using a High Purity Germanium (HPGe) detector-based gamma-ray spectrometer with a relative efficiency of 80%. To achieve uniformity in exposure estimations, radium equivalent activity has been calculated. Additionally, the internal hazard index, external hazard index, radioactivity level index and gamma dose rates have been evaluated to estimate the radiation hazard levels in the study area. The comparison of obtained concentrations and hazard indices with global data (UNSCEAR. (2008). Sources, effects and risks of ionizing radiation. United nations scientific committee on the effects of atomic radiation (report to the general assembly, with Annexes).) suggests that this region lies in a relatively high background radiation zone.

Estimation of gross α-ß and tritium activities in groundwater samples using LSC-TDCR technique in and around the geothermal region of Eastern India.

The present study is an attempt to assess the radiogenic quality of groundwater on the basis of gross α, gross ß and tritium (3H or H-3) activities in the Bakreswar-Tantloi geothermal region of Chotanagpur Plateau, West Bengal and Jharkhand, India. The aforesaid parameters in groundwater samples were measured using liquid scintillation counting triple to double coincidence ratio (LSC-TDCR) technique. Groundwater samples collected from Bakreswar-Tantloi geothermal region show gross α activities from below the minimum detectable activity (BMDA) to 0.5 ± 0.05 Bq/L, gross ß activities from BMDA to 0.2 ± 0.01 Bq/L and H-3 activities from BMDA to 63.42 Bq/L. The average gross α, gross ß and H-3 activities are also within the permissible limits prescribed by the World Health Organization (WHO). Though the annual effective doses in some samples were higher than the reference dose level of 0.1 mSv, the overall result suggests that the groundwater in the Bakreswar-Tantloi geothermal region is radiologically safe considering the radionuclides covered in this study.

Site percolation in distorted square and simple cubic lattices with flexible number of neighbors.

This paper exhibits a Monte Carlo study on site percolation using the Newmann-Ziff algorithm in distorted square and simple cubic lattices where each site is allowed to be directly linked with any other site if the Euclidean separation between the pair is at most a certain distance d, called the connection threshold. Distorted lattices are formed from regular lattices by a random but controlled dislocation of the sites with the help of a parameter α, called the distortion parameter. The distinctive feature of this study is the relaxation of the restriction of forming bonds with only the nearest neighbors. Owing to this flexibility and the intricate interplay between the two parameters α and d, the site percolation threshold may either increase or decrease with distortion. The dependence of the percolation threshold on the average degree of a site has been explored to show that the obtained results are consistent with those on percolation in regular lattices with an extended neighborhood and continuum percolation.

Percolation in a simple cubic lattice with distortion.

Site percolation in a distorted simple cubic lattice is characterized numerically employing the Newman-Ziff algorithm. Distortion is administered in the lattice by systematically and randomly dislocating its sites from their regular positions. The amount of distortion is tunable by a parameter called the distortion parameter. In this model, two occupied neighboring sites are considered connected only if the distance between them is less than a predefined value called the connection threshold. It is observed that the percolation threshold always increases with distortion if the connection threshold is equal to or greater than the lattice constant of the regular lattice. On the other hand, if the connection threshold is less than the lattice constant, the percolation threshold first decreases and then increases steadily as distortion is increased. It is shown that the variation of the percolation threshold can be well explained by the change in the fraction of occupied bonds with distortion. The values of the relevant critical exponents of the transition strongly indicate that percolation in regular and distorted simple cubic lattices belong to the same universality class. It is also demonstrated that this model is intrinsically distinct from the site-bond percolation model.

A comprehensive meta-analysis and prioritization study to identify vitiligo associated coding and non-coding SNV candidates using web-based bioinformatics tools.

Vitiligo is a prevalent depigmentation disorder affecting around 1% of the general population. So far, various Genome Wide Association Studies (GWAS) and Candidate Gene Association Studies (CGAS) have identified several single nucleotide variants (SNVs) as a risk factor for vitiligo. Nonetheless, little has been discerned regarding their direct functional significance to the disease pathogenesis. In this study, we did extensive data mining and downstream analysis using several experimentally validated datasets like GTEx Portal and web tools like rSNPBase, RegulomeDB, HaploReg and STRING to prioritize 13 SNVs from a set of 291SNVs that have been previously reported to be associated with vitiligo. We also prioritized their underlying/target genes and tried annotating their functional contribution to vitiligo pathogenesis. Our analysis revealed genes like FGFR10P, SUOX, CDK5RAP1 and RERE that have never been implicated in vitiligo previously to have strong potentials to contribute to the disease pathogenesis. The study is the first of its kind to prioritize and functionally annotate vitiligo-associated GWAS and CGAS SNVs and their underlying/target genes, based on functional data available in the public domain database.

Multi-view clustering for multi-omics data using unified embedding.

In real world applications, data sets are often comprised of multiple views, which provide consensus and complementary information to each other. Embedding learning is an effective strategy for nearest neighbour search and dimensionality reduction in large data sets. This paper attempts to learn a unified probability distribution of the points across different views and generates a unified embedding in a low-dimensional space to optimally preserve neighbourhood identity. Probability distributions generated for each point for each view are combined by conflation method to create a single unified distribution. The goal is to approximate this unified distribution as much as possible when a similar operation is performed on the embedded space. As a cost function, the sum of Kullback-Leibler divergence over the samples is used, which leads to a simple gradient adjusting the position of the samples in the embedded space. The proposed methodology can generate embedding from both complete and incomplete multi-view data sets. Finally, a multi-objective clustering technique (AMOSA) is applied to group the samples in the embedded space. The proposed methodology, Multi-view Neighbourhood Embedding (MvNE), shows an improvement of approximately 2-3% over state-of-the-art models when evaluated on 10 omics data sets.

A Multi-View Deep Neural Network Model for Chemical-Disease Relation Extraction From Imbalanced Datasets.

Understanding the chemical-disease relations (CDR) is a crucial task in various biomedical domains. Manual mining of these information from biomedical literature is costly and time-consuming. To address these issues, various researches have been carried out to design an efficient automatic tool. In this paper, we propose a multi-view based deep neural network model for CDR task. Typically, multiple representations (or views) of the datasets are not available for this task. So, we train multiple conceptually different deep neural network models on the dataset to generate different abstract features, treated as different views. A novel loss function, "Penalized LF", is defined to address the problem of imbalance dataset. The proposed loss function is generic in nature. The model is designed as a combination of Convolution Neural Network (CNN) and Bidirectional Long Short Term Memory (Bi-LSTM) network along with a Multi-Layer Perceptron (MLP). To show the efficacy of our proposed model, we have compared it with six baseline models and other state-of-the-art techniques, on "chemicals-and-disease-DFE" dataset, a free text dataset created by Li et al. from BioCreative V Chemical Disease Relation dataset. Results show that the proposed model attains highest F1-score for individual classes, proving its efficiency in handling class imbalance problem in the dataset. To further demonstrate the efficacy of the proposed model, we have presented results on BioCreative V dataset and two Protein-Protein Interaction Identification (PPI) datasets, viz., AiMed and BioInfer. All these results are also compared with the state-of-the-art models.

Influenza A Virus Protein NS1 Exhibits Strain-Independent Conformational Plasticity.

Influenza A virus (IAV) nonstructural protein 1 (NS1), a potent antagonist of the host immune response, is capable of interacting with RNA and a wide range of cellular proteins. NS1 consists of an RNA-binding domain (RBD) and an effector domain (ED) separated by a flexible linker region (LR). H5N1-NS1 has a characteristic 5-residue deletion in the LR, with either G (minor group) or E (major group) at the 71st position, and non-H5N1-NS1 contains E71 with an intact linker. Based on the orientation of the ED with respect to the RBD, previous crystallographic studies have shown that minor group H5N1-NS1(G71), a non-H5N1-NS1 [H6N6-NS1(E71)], and the LR deletion mutant H6N6-NS1(Δ80-84/E71) mimicking the major group H5N1-NS1 exhibit "open," "semiopen," and "closed" conformations, respectively, suggesting that NS1 exhibits a strain-dependent conformational preference. Here we report the first crystal structure of a naturally occurring H5N1-NS1(E71) and show that it adopts an open conformation similar to that of the minor group of H5N1-NS1 [H5N1-NS1(G71)]. We also show that H6N6-NS1(Δ80-84/E71) under a different crystallization condition and H6N6-NS1(Δ80-84/G71) also exhibit open conformations, suggesting that NS1 can adopt an open conformation irrespective of E or G at the 71st position. Our single-molecule fluorescence resonance energy transfer (FRET) analysis to investigate the conformational preference of NS1 in solution showed that all NS1 constructs predominantly exist in an open conformation. Further, our coimmunoprecipitation and binding studies showed that they all bind to cellular factors with similar affinities. Taken together, our studies suggest that NS1 exhibits strain-independent structural plasticity that allows it to interact with a wide variety of cellular ligands during viral infection.IMPORTANCE IAV is responsible for several pandemics over the last century and continues to infect millions annually. The frequent rise in drug-resistant strains necessitates exploring novel targets for developing antiviral drugs that can reduce the global burden of influenza infection. Because of its critical role in the replication and pathogenesis of IAV, nonstructural protein 1 (NS1) is a potential target for developing antivirals. Previous studies suggested that NS1 adopts strain-dependent "open," "semiopen," and "closed" conformations. Here we show, based on three crystal structures, that NS1 irrespective of strain differences can adopt an open conformation. We further show that NS1 from different strains primarily exists in an open conformation in solution and binds to cellular proteins with a similar affinity. Together, our findings suggest that conformational polymorphism facilitated by a flexible linker is intrinsic to NS1, and this may be the underlying factor allowing NS1 to bind several cellular factors during IAV replication.

A multiobjective multi-view cluster ensemble technique: Application in patient subclassification.

Recent high throughput omics technology has been used to assemble large biomedical omics datasets. Clustering of single omics data has proven invaluable in biomedical research. For the task of patient sub-classification, all the available omics data should be utilized combinedly rather than treating them individually. Clustering of multi-omics datasets has the potential to reveal deep insights. Here, we propose a late integration based multiobjective multi-view clustering algorithm which uses a special perturbation operator. Initially, a large number of diverse clustering solutions (called base partitionings) are generated for each omic dataset using four clustering algorithms, viz., k means, complete linkage, spectral and fast search clustering. These base partitionings of multi-omic datasets are suitably combined using a special perturbation operator. The perturbation operator uses an ensemble technique to generate new solutions from the base partitionings. The optimal combination of multiple partitioning solutions across different views is determined after optimizing the objective functions, namely conn-XB, for checking the quality of partitionings for different views, and agreement index, for checking agreement between the views. The search capability of a multiobjective simulated annealing approach, namely AMOSA is used for this purpose. Lastly, the non-dominated solutions of the different views are combined based on similarity to generate a single set of non-dominated solutions. The proposed algorithm is evaluated on 13 multi-view cancer datasets. An elaborated comparative study with several baseline methods and five state-of-the-art models is performed to show the effectiveness of the algorithm.

Percolation in a distorted square lattice.

This paper presents a Monte Carlo study of percolation in a distorted square lattice, in which the adjacent sites are not equidistant. Starting with an undistorted lattice, the position of the lattice sites are shifted through a tunable parameter α to create a distorted empty lattice. In this model, two occupied neighboring sites are considered to be connected to each other in order to belong to the same cluster, if the distance between them is less than or equal to a certain value, called connection threshold d. While spanning becomes difficult in distorted lattices as is manifested by the increment of the percolation threshold p_{c} with α, an increased connection threshold d makes it easier for the system to percolate. The scaling behavior of the order parameter studied through relevant critical exponents, and the fractal dimension d_{f} of the percolating cluster at p_{c} suggest that this new type of percolation may belong to the same universality class as ordinary percolation. This model can be very useful in various realistic applications since it is almost impossible to find a natural system that is perfectly ordered.

A Stack-based Ensemble Framework for Detecting Cancer MicroRNA Biomarkers.

MicroRNA (miRNA) plays vital roles in biological processes like RNA splicing and regulation of gene expression. Studies have revealed that there might be possible links between oncogenesis and expression profiles of some miRNAs, due to their differential expression between normal and tumor tissues. However, the automatic classification of miRNAs into different categories by considering the similarity of their expression values has rarely been addressed. This article proposes a solution framework for solving some real-life classification problems related to cancer, miRNA, and mRNA expression datasets. In the first stage, a multiobjective optimization based framework, non-dominated sorting genetic algorithm II, is proposed to automatically determine the appropriate classifier type, along with its suitable parameter and feature combinations, pertinent for classifying a given dataset. In the second page, a stack-based ensemble technique is employed to get a single combinatorial solution from the set of solutions obtained in the first stage. The performance of the proposed two-stage approach is evaluated on several cancer and RNA expression profile datasets. Compared to several state-of-the-art approaches for classifying different datasets, our method shows supremacy in the accuracy of classification.

The Opposing Actions of Arabidopsis CHROMOSOME TRANSMISSION FIDELITY7 and WINGS APART-LIKE1 and 2 Differ in Mitotic and Meiotic Cells.

Sister chromatid cohesion, which is mediated by the cohesin complex, is essential for the proper segregation of chromosomes during mitosis and meiosis. Stable binding of cohesin with chromosomes is regulated in part by the opposing actions of CTF7 (CHROMOSOME TRANSMISSION FIDELITY7) and WAPL (WINGS APART-LIKE). In this study, we characterized the interaction between Arabidopsis thaliana CTF7 and WAPL by conducting a detailed analysis of wapl1-1 wapl2 ctf7 plants. ctf7 plants exhibit major defects in vegetative growth and development and are completely sterile. Inactivation of WAPL restores normal growth, mitosis, and some fertility to ctf7 plants. This shows that the CTF7/WAPL cohesin system is not essential for mitosis in vegetative cells and suggests that plants may contain a second mechanism to regulate mitotic cohesin. WAPL inactivation restores cohesin binding and suppresses ctf7-associated meiotic cohesion defects, demonstrating that WAPL and CTF7 function as antagonists to regulate meiotic sister chromatid cohesion. The ctf7 mutation only had a minor effect on wapl-associated defects in chromosome condensation and centromere association. These results demonstrate that WAPL has additional roles that are independent of its role in regulating chromatin-bound cohesin.

Unique structure and dynamics of the EphA5 ligand binding domain mediate its binding specificity as revealed by X-ray crystallography, NMR and MD simulations.

The 16 EphA and EphB receptors represent the largest family of receptor tyrosine kinases, and their interactions with 9 ephrin-A and ephrin-B ligands initiate bidirectional signals controlling many physiological and pathological processes. Most interactions occur between receptor and ephrins of the same class, and only EphA4 can bind all A and B ephrins. To understand the structural and dynamic principles that enable Eph receptors to utilize the same jellyroll ß-sandwich fold to bind ephrins, the VAPB-MSP domain, peptides and small molecules, we have used crystallography, NMR and molecular dynamics (MD) simulations to determine the first structure and dynamics of the EphA5 ligand-binding domain (LBD), which only binds ephrin-A ligands. Unexpectedly, despite being unbound, the high affinity ephrin-binding pocket of EphA5 resembles that of other Eph receptors bound to ephrins, with a helical conformation over the J-K loop and an open pocket. The openness of the pocket is further supported by NMR hydrogen/deuterium exchange data and MD simulations. Additionally, the EphA5 LBD undergoes significant picosecond-nanosecond conformational exchanges over the loops, as revealed by NMR and MD simulations, but lacks global conformational exchanges on the microsecond-millisecond time scale. This is markedly different from the EphA4 LBD, which shares 74% sequence identity and 87% homology. Consequently, the unbound EphA5 LBD appears to comprise an ensemble of open conformations that have only small variations over the loops and appear ready to bind ephrin-A ligands. These findings show how two proteins with high sequence homology and structural similarity are still able to achieve distinctive binding specificities through different dynamics, which may represent a general mechanism whereby the same protein fold can serve for different functions. Our findings also suggest that a promising strategy to design agonists/antagonists with high affinity and selectivity might be to target specific dynamic states of the Eph receptor LBDs.

Design and Synthesis of Potent Bivalent Peptide Agonists Targeting the EphA2 Receptor.

Designing potent and selective peptides and small molecules that target Eph receptor tyrosine kinases remains a challenge and new strategies are needed for developing novel and potent ligands for these receptors. In this study, we performed a structure-activity relationship study of a previously identified 12 amino acid-long peptide, SWL, by alanine scanning to identify residues important for receptor binding. To further enhance and optimize the receptor binding affinity of the SWL peptide, we applied the concept of bivalent ligand design to synthesize several SWL-derived dimeric peptides as novel ligands capable of binding simultaneously to two EphA2 receptor molecules. The dimeric peptides possess higher receptor binding affinity than the original monomeric SWL peptide, consistent with bivalent binding. The most potent dimeric peptide, a SWL dimer with a 6 carbon linker, has about 13 fold increased potency compared to SWL. Furthermore, similar to SWL, the dimeric peptide is an agonist and can promote EphA2 tyrosine phosphorylation (activation) in cultured cells.

Targeted delivery of paclitaxel to EphA2-expressing cancer cells.

PURPOSE: YSA is an EphA2-targeting peptide that effectively delivers anticancer agents to prostate cancer tumors. Here, we report on how we increased the drug-like properties of this delivery system. EXPERIMENTAL DESIGN: By introducing non-natural amino acids, we have designed two new EphA2 targeting peptides: YNH, where norleucine and homoserine replace the two methionine residues of YSA, and dYNH, where a D-tyrosine replaces the L-tyrosine at the first position of the YNH peptide. We describe the details of the synthesis of YNH and dYNH paclitaxel conjugates (YNH-PTX and dYNH-PTX) and their characterization in cells and in vivo. RESULTS: dYNH-PTX showed improved stability in mouse serum and significantly reduced tumor size in a prostate cancer xenograft model and also reduced tumor vasculature in a syngeneic orthotopic allograft mouse model of renal cancer compared with vehicle or paclitaxel treatments. CONCLUSION: This study reveals that targeting EphA2 with dYNH drug conjugates could represent an effective way to deliver anticancer agents to a variety of tumor types.

Design, synthesis and characterization of novel small molecular inhibitors of ephrin-B2 binding to EphB4.

EphB4 is a member of the large Eph receptor tyrosine kinase family. By interacting with its preferred ligand ephrin-B2, which is also a transmembrane protein, EphB4 plays a role in a variety of physiological and pathological processes ranging from bone remodeling to cancer malignancy. EphB4-ephrin-B2 binding occurs at sites of contact between cells. Ephrin-B2 causes EphB4 clustering and increased kinase activity to generate downstream signals that affect cell behavior. Previous work identified a high-affinity antagonistic peptide that targets EphB4, named TNYL-RAW. This peptide is 15 amino acid long, has a molecular weight of ~1700 Da and binds to the ephrin-binding pocket of EphB4. Here we report the structure-based design and chemical synthesis of two novel small molecules of ~600-700 Da, which were designed starting from the small and functionally critical C-terminal portion of the TNYL-RAW peptide. These compounds inhibit ephrin-B2 binding to EphB4 at low micromolar concentrations. Additionally, although the ephrin-B2 ligand can interacts with multiple other Eph receptors besides EphB4, the two compounds retain the high selectivity of the TNYL-RAW peptide in targeting EphB4. TNYL-RAW peptide displacement experiments using the more potent of the two compounds, compound 5, suggest a competitive mode of inhibition. These EphB4 antagonistic compounds can serve as promising templates for the further development of small molecule drugs targeting EphB4.

High-throughput screen using a single-cell tyrosine phosphatase assay reveals biologically active inhibitors of tyrosine phosphatase CD45.

Many cellular signaling events are regulated by tyrosine phosphorylation and mediated by the opposing actions of protein tyrosine kinases and phosphatases. Protein tyrosine phosphatases are emerging as drug targets, but poor cell permeability of inhibitors has limited the development of drugs targeting these enzymes [Tautz L, et al. (2006) Expert Opin Ther Targets 10:157-177]. Here we developed a method to monitor tyrosine phosphatase activity at the single-cell level and applied it to the identification of cell-permeable inhibitors. The method takes advantage of the fluorogenic properties of phosphorylated coumaryl amino propionic acid (pCAP), an analog of phosphotyrosine, which can be incorporated into peptides. Once delivered into cells, pCAP peptides were dephosphorylated by protein tyrosine phosphatases, and the resulting cell fluorescence could be monitored by flow cytometry and high-content imaging. The robustness and sensitivity of the assay was validated using peptides preferentially dephosphorylated by CD45 and T-cell tyrosine phosphatase and available inhibitors of these two enzymes. The assay was applied to high-throughput screening for inhibitors of CD45, an important target for autoimmunity and infectious diseases [Hermiston ML, et al. (2003) Annu Rev Immunol 21:107-137]. We identified four CD45 inhibitors that showed activity in T cells and macrophages. These results indicate that our assay can be applied to primary screening for inhibitors of CD45 and of other protein tyrosine phosphatases to increase the yield of biologically active inhibitors.

Novel targeted system to deliver chemotherapeutic drugs to EphA2-expressing cancer cells.

The efficacy of anticancer drugs is often limited by their systemic toxicities and adverse side effects. We report that the EphA2 receptor is overexpressed preferentially in several human cancer cell lines compared to normal tissues and that an EphA2 targeting peptide (YSAYPDSVPMMS) can be effective in delivering anticancer agents to such tumors. Hence, we report on the synthesis and characterizations of a novel EphA2-targeting agent conjugated with the chemotherapeutic drug paclitaxel. We found that the peptide-drug conjugate is dramatically more effective than paclitaxel alone at inhibiting tumor growth in a prostate cancer xenograft model, delivering significantly higher levels of drug to the tumor site. We believe these studies open the way to the development of a new class of therapeutic compounds that exploit the EphA2 receptor for drug delivery to cancer cells.

PEGylation potentiates the effectiveness of an antagonistic peptide that targets the EphB4 receptor with nanomolar affinity.

The EphB4 receptor tyrosine kinase together with its preferred ligand, ephrin-B2, regulates a variety of physiological and pathological processes, including tumor progression, pathological forms of angiogenesis, cardiomyocyte differentiation and bone remodeling. We previously reported the identification of TNYL-RAW, a 15 amino acid-long peptide that binds to the ephrin-binding pocked of EphB4 with low nanomolar affinity and inhibits ephrin-B2 binding. Although ephrin-B2 interacts promiscuously with all the EphB receptors, the TNYL-RAW peptide is remarkably selective and only binds to EphB4. Therefore, this peptide is a useful tool for studying the biological functions of EphB4 and for imaging EphB4-expressing tumors. Furthermore, TNYL-RAW could be useful for treating pathologies involving EphB4-ephrin-B2 interaction. However, the peptide has a very short half-life in cell culture and in the mouse blood circulation due to proteolytic degradation and clearance by the kidneys and reticuloendothelial system. To overcome these limitations, we have modified TNYL-RAW by fusion with the Fc portion of human IgG1, complexation with streptavidin or covalent coupling to a 40 KDa branched polyethylene glycol (PEG) polymer. These modified forms of TNYL-RAW all have greatly increased stability in cell culture, while retaining high binding affinity for EphB4. Furthermore, PEGylation most effectively increases peptide half-life in vivo. Consistent with increased stability, submicromolar concentrations of PEGylated TNYL-RAW effectively impair EphB4 activation by ephrin-B2 in cultured B16 melanoma cells as well as capillary-like tube formation and capillary sprouting in co-cultures of endothelial and epicardial mesothelial cells. Therefore, PEGylated TNYL-RAW may be useful for inhibiting pathological forms of angiogenesis through a novel mechanism involving disruption of EphB4-ephrin-B2 interactions between endothelial cells and supporting perivascular mesenchymal cells. Furthermore, the PEGylated peptide is suitable for other cell culture and in vivo applications requiring prolonged EphB4 receptor targeting.

Structure-activity relationship analysis of peptides targeting the EphA2 receptor.

The EphA2 receptor tyrosine kinase has emerged as a promising new therapeutic target in cancer because of its high level of expression in tumors. EphA2-specific antibodies have been used to deliver drugs and toxins to tumor cells, leading to inhibition of tumor growth and metastatic dissemination. We previously identified two related peptides, YSA and SWL, that selectively bind to the ligand-binding domain of EphA2 but not other Eph receptors and could therefore be useful as selective targeting agents. Here we characterize the two peptides and a series of derivatives. On the basis of systematic amino acid replacements, only five YSA residues appear to be critical for high-affinity receptor binding. Furthermore, a peptide comprising only the first five residues of YSA retains selectivity for EphA2. Similar to ephrin-A1, the physiological ligand for EphA2, both YSA and SWL activate EphA2 and inhibit downstream oncogenic signaling pathways in PC3 cancer cells. The two peptides and derivatives are quite stable in conditioned cell culture medium and show promise for delivering drugs and imaging agents to EphA2-expressing tumors.