Navneet Kumar Yadav

Erratum to “Next Generation Sequencing: Potential and Application in Drug Discovery”

Through this erratum the authors declare that two coauthors were missing in the article entitled “Next generation sequencing: potential and application in drug discovery”. The correct list of the authors and their affiliations are as shown above.

Anti-breast tumor activity of Eclipta extract in-vitro and in-vivo: novel evidence of endoplasmic reticulum specific localization of Hsp60 during apoptosis

Major challenges for current therapeutic strategies against breast cancer are associated with drug-induced toxicities. Considering the immense potential of bioactive phytochemicals to deliver non-toxic, efficient anti-cancer therapeutics, we performed bio-guided fractionation of Eclipta alba extract and discovered that particularly the chloroform fraction of Eclipta alba (CFEA) is selectively inducing cytotoxicity to breast cancer cells over non-tumorigenic breast epithelial cells. Our unbiased mechanistic hunt revealed that CFEA specifically activates the intrinsic apoptotic pathway by disrupting the mitochondrial membrane potential, upregulating Hsp60 and downregulating the expression of anti-apoptotic protein XIAP. By utilizing Hsp60 specific siRNA, we identified a novel pro-apoptotic role of Hsp60 and uncovered that following CFEA treatment, upregulated Hsp60 is localized in the endoplasmic reticulum (ER). To our knowledge, this is the first evidence of ER specific localization of Hsp60 during cancer cell apoptosis. Further, our LC-MS approach identified that luteolin is mainly attributed for its anti-cancer activities. Moreover, oral administration of CFEA not only offers potential anti-breast cancer effects in-vivo but also mitigates tumor induced hepato-renal toxicity. Together, our studies offer novel mechanistic insight into the CFEA mediated inhibition of breast cancer and may potentially open up new avenues for further translational research.

Next Generation Sequencing: Potential and Application in Drug Discovery

The world has now entered into a new era of genomics because of the continued advancements in the next generation high throughput sequencing technologies, which includes sequencing by synthesis-fluorescent in situ sequencing (FISSEQ), pyrosequencing, sequencing by ligation using polony amplification, supported oligonucleotide detection (SOLiD), sequencing by hybridization along with sequencing by ligation, and nanopore technology. Great impacts of these methods can be seen for solving the genome related problems of plant and animal kingdom that will open the door of a new era of genomics. This may ultimately overcome the Sanger sequencing that ruled for 30 years. NGS is expected to advance and make the drug discovery process more rapid.

Saraca indica Bark Extract Shows In Vitro Antioxidant, Antibreast Cancer Activity and Does Not Exhibit Toxicological Effects

Medicinal plants are used as a complementary and alternative medicine in treatment of various diseases including cancer worldwide, because of their ease of accessibility and cost effectiveness. Multicomposed mixture of compounds present in a plant extract has synergistic activity, increases the therapeutic potential many folds, compensates toxicity, and increases bioavailability. Saraca indica (family Caesalpiniaceae) is one of the most ancient sacred plants with medicinal properties, exhibiting a number of pharmacological effects. Antioxidant, antibreast cancer activity and toxicological evaluation of Saraca indica bark extract (SIE) were carried out in the present study. The results of the study indicated that this herbal preparation has antioxidant and antibreast cancer activity. Toxicological studies suggest that SIE is safer to use and may have a potential to be used as complementary and alternative medicine for breast cancer therapy.

Alcoholic Extract of Eclipta alba Shows In Vitro Antioxidant and Anticancer Activity without Exhibiting Toxicological Effects.

As per WHO estimates, 80% of people around the world use medicinal plants for the cure and prevention of various diseases including cancer owing to their easy availability and cost effectiveness. Eclipta alba has long been used in Ayurveda to treat liver diseases, eye ailments, and hair related disorders. The promising medicinal value of E. alba prompted us to study the antioxidant, nontoxic, and anticancer potential of its alcoholic extract. In the current study, we evaluated the in vitro cytotoxic and antioxidant effect of the alcoholic extract of Eclipta alba (AEEA) in multiple cancer cell lines along with control. We have also evaluated its effect on different in vivo toxicity parameters. Here, we found that AEEA was found to be most active in most of the cancer cell lines but it significantly induced apoptosis in human breast cancer cell lines by disrupting mitochondrial membrane potential and DNA damage. Moreover, AEEA treatment inhibited migration in both MCF 7 and MDA-MB-231 cells in a dose dependent manner. Further, AEEA possesses robust in vitro antioxidant activity along with high total phenolic and flavonoid contents. In summary, our results indicate that Eclipta alba has enormous potential in complementary and alternative medicine for the treatment of cancer.

An overview of data mining algorithms in drug induced toxicity prediction.

The growth in chemical diversity has increased the need to adjudicate the toxicity of different chemical compounds raising the burden on the demand of animal testing. The toxicity evaluation requires time consuming and expensive undertaking, leading to the deprivation of the methods employed for screening chemicals pointing towards the need to develop more efficient toxicity assessment systems. Computational approaches have reduced the time as well as the cost for evaluating the toxicity and kinetic behavior of any chemical. The accessibility of a large amount of data and the intense need of turning this data into useful information have attracted the attention towards data mining. Machine Learning, one of the powerful data mining techniques has evolved as the most effective and potent tool for exploring new insights on combinatorial relationships among various experimental data generated. The article accounts on some sophisticated machine learning algorithms like Artificial Neural Networks (ANN), Support Vector Machine (SVM), k-mean clustering and Self Organizing Maps (SOM) with some of the available tools used for classification, sorting and toxicological evaluation of data, clarifying, how data mining and machine learning interact cooperatively to facilitate knowledge discovery. Addressing the association of some commonly used expert systems, we briefly outline some real world applications to consider the crucial role of data set partitioning.

Hematological malignancies: role of miRNAs and their in silico aspects

Hematological malignancies is a broad term that includes blood cell cancers including chronic lymphocytic leukemia (CLL), chronic myeloid leukemia (CML), acute myeloid leukemia (AML), Myelodysplastic syndrome, acute lymphocytic leukemia (ALL), multiple myelomas (MM) and lymphomas. miRNAs are ~22-nt long non-coding RNAs that play a very important role in gene regulation by binding to mRNA at their complementary sequence. These miRNAs are conceptually connected with various signal and pathway networks that make them capable of regulating various diseases including hematological malignancies. These miRNAs are not only playing regulatory roles in hematological malignancies, but are also providing new potent markers for efficient diagnosis and prognosis for hematological malignancies patients. Since the discovery of very first miRNA, the importance and role of miRNAs have been established in various fields, and there is a need to search for new potent miRNAs and their targets. A large amount of sequence data have been generated in last few years, which has further generated the need to develop efficient and reliable computational tools to analyze and extract out relevant information promptly from raw data. Here, we review various possible roles played by miRNA in hematological malignancies, principles involved in miRNA gene identification, target prediction and their preceding role in hematological malignancies research.

Alternative methods in toxicology: CFU assays application, limitation and future prospective

Abstract Blood is a fluid connective tissue which plays a vital role for normal body function. It consist different type of blood cells which is continuously reproduce inside the bone marrow from hematopoietic system. Xenobiotics could be specifically toxic to the hematopoietic system and they can cause hematological disorders by disturbing the normal functions. In vitro hematopoietic colony-forming cell assays play a crucial role to evaluate potential toxic effects of new xenobiotics and also helpful in bridging the gap between preclinical toxicology studies in animal models and clinical investigations. Use of these assays in conjunction with, high-throughput screening reduces the cost and time associated with these assays. This article provides a critical view over in vitro hematopoietic colony-forming cell assays in assessment of hematotoxicity.

LC-MS/MS method for the simultaneous quantification of luteolin, wedelolactone and apigenin in mice plasma using hansen solubility parameters for liquid-liquid extraction: Application to pharmacokinetics of Eclipta alba chloroform fraction

Eclipta alba (Bhringraj) in ayurveda has been widely used as a traditional medicine for its multi-therapeutic properties for ages. Luteolin (LTL), wedelolactone (WDL) and apigenin (APG) are the three main bioactive phytochemicals present in Eclipta alba extract. However there was a lack of sensitive bioanalytical method for the pharmacokinetics of these free compounds in plasma which majorly contributes for their activities after oral administration of Eclipta alba. The present study aims to develop a sensitive, rapid and reliable liquid chromatography tandem mass spectrometry (LC-MS/MS) method for the simultaneous estimation of mice plasma concentrations of LTL, WDL and APG using quercetin as an internal standard for the pharmacokinetic analysis. Analytes were separated on Phenomenex Luna C18 (150 × 4.6 mm, 3.0 μm) column with mobile phase containing methanol: acetonitrile (90: 10, v/v) and 0.1% formic acid in 10 mM ammonium formate buffer in the ratio of 70: 30 (v/v) in isocratic mode. Liquid-liquid extraction was optimized using Hansen solubility parameters and diethyl ether finalized as an extraction solvent for the recovery ranging from 61 to 76% for all analytes in mice plasma. The validated method has an accuracy and precision over the linearity range of 0.1-200 ng/mL with a correlation coefficient (r2) of ≥0.997. The intra and inter-day assay accuracy was between 98.17 and 107% and 95.83-107.89% respectively and the intra and inter day assay precision ranged from 0.37-6.05% and 1.85-10.76%, respectively for all the analytes. This validated method can be used for future clinical investigation studies of Eclipta alba extracts.

microRNAs: role in leukemia and their computational perspective

MicroRNAs (miRNAs) belong to the family of noncoding RNAs (ncRNAs) and had gained importance due to its role in complex biochemical pathways. Changes in the expression of protein coding genes are the major cause of leukemia. Role of miRNAs as tumor suppressors has provided a new insight in the field of leukemia research. Particularly, the miRNAs mediated gene regulation involves the modulation of multiple mRNAs and cooperative action of different miRNAs to regulate a particular gene expression. This highly complex array of regulatory pathway network indicates the great possibility in analyzing and identifying novel findings. Owing to the conventional, slow experimental identification process of miRNAs and their targets, the last decade has witnessed the development of a large amount of computational approaches to deal with the complex interrelations present within biological systems. This article describes the various roles played by miRNAs in regulating leukemia and the role of computational approaches in exploring new possibilities. WIREs RNA 2015, 6:65–78. doi: 10.1002/wrna.1256