Pritish Kumar Varadwaj

Primary responses to salt stress in a halophyte, smooth cordgrass (Spartina alterniflora Loisel.)

The response of a grass halophyte Spartina alterniflora at early stages of salt stress was investigated through generation and systematic analysis of expressed sequence tags (ESTs) from both leaf and root tissues. Random EST sequencing produced 1,227 quality ESTs, which were clustered into 127 contigs, and 368 were singletons. Of the 495 unigenes, 27% represented genes for stress response. Comparison of the 368 singletons against the Oryza sativa gene index showed that >85% of these genes had similarity with the rice unigenes. Moreover, the phylogenetic analysis of an EST similar to myo-inositol 1-phosphate synthase of Spartina and some selected grasses and halophytes showed closeness of Spartina with maize and rice. Transcript abundance analysis involving eight known genes of various metabolic pathways and nine transcription factor genes showed temporal and tissue-dependent variation in expression under salinity. Reverse northern analysis of a few selected unknown and ribosomal genes exhibited much higher abundance of transcripts in response to salt stress. The results provide evidence that, in addition to several unknown genes discovered in this study, genes involved in ion transport, osmolyte production, and house-keeping functions may play an important role in the primary responses to salt stress in this grass halophyte.

Flavonoids as Multi-target Inhibitors for Proteins Associated with Ebola Virus: In Silico Discovery Using Virtual Screening and Molecular Docking Studies

Ebola virus is a single-stranded, negative-sense RNA virus that causes severe hemorrhagic fever in humans and non-human primates. This virus is unreceptive to a large portion of the known antiviral drugs, and there is no valid treatment as on date for disease created by this pathogen. Looking into its ability to create a pandemic scenario across globe, there is an utmost need for new drugs and therapy to combat this life-threatening infection. The current study deals with the evaluation of the inhibitory activity of flavonoids against the four selected Ebola virus receptor proteins, using in silico studies. The viral proteins VP40, VP35, VP30 and VP24 were docked with small molecules obtained from flavonoid class and its derivatives and evaluated on the basis of energetics, stereochemical considerations and pharmacokinetic properties to identify potential lead compounds. The results showed that both top-ranking screened flavonoids, i.e., Gossypetin and Taxifolin, showed better docking scores and binding energies in all the EBOV receptors when compared to those of the reported compound. All the screened flavonoids have known antiviral activity, acceptable pharmacokinetic properties and are being used on human and thus can be taken as anti-Ebola therapy without the time lag for clinical trial.

Structural insights into conformational stability of both wild-type and mutant EZH2 receptor

Polycomb group (PcG) proteins have been observed to maintain the pattern of histone by methylation of the histone tail responsible for the gene expression in various cellular processes, of which enhancer of zeste homolog 2 (EZH2) acts as tumor suppressor. Overexpression of EZH2 results in hyper activation found in a variety of cancer. Point mutation on two important residues were induced and the results were compared between the wild type and mutant EZH2. The mutation of Y641 and A677 present in the active region of the protein alters the interaction of the top ranked compound with the newly modeled binding groove of the SET domain, giving a GLIDE score of −12.26 kcal/mol, better than that of the wild type at −11.664 kcal/mol. In depth analysis were carried out for understanding the underlying molecular mechanism using techniques viz. molecular dynamics, principal component analysis, residue interaction network and free energy landscape analysis, which showed that the mutated residues changed the overall conformation of the system along with the residue-residue interaction network. The insight from this study could be of great relevance while designing new compounds for EZH2 enzyme inhibition and the effect of mutation on the overall binding mechanism of the system.

Novel DOT1L ReceptorNatural Inhibitors Involved in Mixed Lineage Leukemia: a Virtual Screening, Molecular Docking and Dynamics Simulation Study

BACKGROUND The human protein methyl-transferase DOT1L catalyzes the methylation of histone H3 on lysine 79 (H3K79) at homeobox genes and is also involved in a number of significant processes ranging from gene expression to DNA-damage response and cell cycle progression. Inhibition of DOT1L activity by shRNA or small-molecule inhibitors has been established to prevent proliferation of various MLL-rearranged leukemia cells in vitro, establishing DOT1L an attractive therapeutic target for mixed lineage leukemia (MLL). Most of the drugs currently in use for the MLL treatment are reported to have low efficacy, hence this study focused on various natural compounds which exhibit minimal toxic effects and high efficacy for the target receptor. MATERIALS AND METHODS Structures of human protein methyl-transferase DOT1L and natural compound databases were downloaded from various sources. Virtual screening, molecular docking, dynamics simulation and drug likeness studies were performed for those natural compounds to evaluate and analyze their anti-cancer activity. RESULTS The top five screened compounds possessing good binding affinity were identified as potential high affinity inhibitors against DOT1Ls active site. The top ranking molecule amongst the screened ligands had a Glide g-score of -10.940 kcal/mol and Glide e-model score of -86.011 with 5 hydrogen bonds and 12 hydrophobic contacts. This ligands behaviour also showed consistency during the simulation of protein-ligand complex for 20000 ps, which is indicative of its stability in the receptor pocket. CONCLUSIONS The ligand obtained out of this screening study can be considered as a potential inhibitor for DOT1L and further can be treated as a lead for the drug designing pipeline.

Systemic Review on Chronic Myeloid Leukemia: Therapeutic Targets, Pathways and Inhibitors

Chronic Myeloid Leukemia (CML) is a stem cell disorder, characterized by the translocation of 9th chromosome of Abelson (ABL) gene to the 22th chromosome of breakpoint cluster region (BCR) gene. Consequently, translocation results into the chimeric oncogene BCR-ABL which encodes the BCR-ABL oncoprotein. CML is mainly a disease of adults but it can occur in any stage of life and it accounts around 15% of the all the types of leukemia. Various methods have been used to combat this disease like Chemotherapy, Radiation therapy; tyrosine kinase inhibitors etc., Imatinib as a tyrosine kinase inhibitor has dramatically improved the survival rate of CML patients, hence can be referred as first generation drug against the CML. Later on, recurrence of the disease in some treated patients has also been seen probably due to mutation in oncogenes. Researchers have started to find out more efficient tyrosine kinase inhibitors which can work on mutated oncoprotein and which can be referred as second or third generation drugs. In this review, special emphasis have been given to the carcinogenic mechanism of abnormal fusion of the BCR-ABL genes, current therapeutic options to prevent this disease, and Systems Biology approach to explore the CML associated biochemical pathways. Various advantages and disadvantages of the all therapeutic options to combat CML have also been discussed.

In Silico Identification of Novel Glucagon Receptor Antagonist for theTreatment of Type 2 Diabetes Mellitus

Type 2 diabetes mellitus is caused mainly due to an imbalance in the relationship between glucagon and insulin levels in plasma. To counteract the actions of insulin and maintain normoglycemia during the fasting state by inducing hepatic glucose production are the major biological action of glucagon. Glucagon exerts its action through activation of the glucagon receptor (GCGR). These observations have prompted interest in blockade of GCGR activity for the control of over production of hepatic glucose or the treatment of type 2 diabetes mellitus. In the present study, a large virtual library of compounds was screened against the crystal structure of GCGR to identify a favorable therapeutic choice of GCGR antagonist. The interactions of lead compound with the active site of GCGR were analyzed and molecular dynamics study was also performed to check its stability in the receptor pocket. The proposed lead compound was also compared with some already reported GCGR antagonists for their binding affinity and other pharmacological properties. As a conclusion of this study, we have identified a compound STOCK1N82694 as potent GCGR antagonist for the treatment of type 2 diabetes mellitus.

Detection of Splice Sites Using Support Vector Machine

Automatic identification and annotation of exon and intron region of gene, from DNA sequences has been an important research area in field of computational biology. Several approaches viz. Hidden Markov Model (HMM), Artificial Intelligence (AI) based machine learning and Digital Signal Processing (DSP) techniques have extensively and independently been used by various researchers to cater this challenging task. In this work, we propose a Support Vector Machine based kernel learning approach for detection of splice sites (the exon-intron boundary) in a gene. Electron-Ion Interaction Potential (EIIP) values of nucleotides have been used for mapping character sequences to corresponding numeric sequences. Radial Basis Function (RBF) SVM kernel is trained using EIIP numeric sequences. Furthermore this was tested on test gene dataset for detection of splice site by window (of 12 residues) shifting. Optimum values of window size, various important parameters of SVM kernel have been optimized for a better accuracy. Receiver Operating Characteristic (ROC) curves have been utilized for displaying the sensitivity rate of the classifier and results showed 94.82% accuracy for splice site detection on test dataset.

Structure-Based Drug Designing and Simulation Studies for Finding Novel Inhibitors of Heat Shock Protein (HSP70) as Suppressors for Psoriasis

Psoriasis is a chronic immune-mediated inflammatory skin disorder. Heat shock proteins (HSPs) have been witnessed as a potential drug target for inhibition of psoriatic cell differentiation. The expression level of HSP is increased when the cells get exposed to elevated temperature, oxidative stress and nutritional deficiencies and thus plays major role in psoriatic progression pathway. Immunoreactivity intensity distribution index scores for HSP70 expression is significantly higher in psoriatic patients compared to normal. In the present work, the 3D structure of human Hsp70 has been taken. Inhibition of HSP70 can control the severity of psoriasis up to many folds; thus, virtual screening was performed against lead-like, drug-like and some natural product of ZINC database. The screened ligands were further introduced to ADMET prediction and simulations to see the drug proficiency and likeness property. The molecular dynamic of system was found stable during simulation trajectory and not much of significant changes occurred in the conformation of the protein–ligand complex. Thus, present study in all probability might prove useful for future design of new derivatives with higher potency and specificity.

Epigenetics and Its Role in Human Cancer

Cancer is often associated with heritable epigenetic changes, which are characterized by the change in gene expression profile without changing the underlying DNA sequence. The most prominent epigenetic modification is methylation of DNA, which to a large extent is connected to modifications of histone proteins. Epigenetic modifications resulting in a normal gene are reversible, thus endow functional flexibility and diversity to the genome, and these modifications can be cured with selective epigenetic target inhibitors. The role of epigenetics in human cancer has been vastly studied and reported in recent decade with emerging evidences about the significance of epigenetic alterations to comprehend various cellular mechanisms. The cellular mechanisms which are crucial for controlling the growth and progression were seen to be impaired by epigenetic changes, which result into development of various human cancer diseases. Although several targets for cancer epigenetics have been identified and annotated in recent past, the development of novel anticancer treatments for these targets is still in nascent stage. By recognizing the spectrum of cancer epigenetics, an array of new drug discoveries has been possible these days. In this chapter, we presented an overview of such epigenetic modifications which occurs and resulted into human cancer and the relationship between those epigenetic enzyme classes and cancer types, with a note on preclinical utilizations of inhibitors for the treatment of such cancer types. This chapter focuses on the practical understanding of human cancer epigenetics and its perspective use for drug designing.

Parameters Involved in Autophosphorylation in Chronic Myeloid Leukemia: a Systems Biology Approach.

BACKGROUND Chronic myeloid leukemia (CML) is a stem cell disorder characterized by the fusion of two oncogenes namely BCR and ABL with their aberrant expression. Autophosphorylation of BCR-ABL oncogenes results in proliferation of CML. The study deals with estimation of rate constant involved in each step of the cellular autophosphorylation process, which are consequently playing important roles in the proliferation of cancerous cells. MATERIALS AND METHODS A mathematical model was proposed for autophosphorylation of BCR-ABL oncogenes utilizing ordinary differential equations to enumerate the rate of change of each responsible system component. The major difficulty to model this process is the lack of experimental data, which are needed to estimate unknown model parameters. Initial concentration data of each substrate and product for BCR-ABL systems were collected from the reported literature. All parameters were optimized through time interval simulation using the fminsearch algorithm. RESULTS The rate of change versus time was estimated to indicate the role of each state variable that are crucial for the systems. The time wise change in concentration of substrate shows the convergence of each parameter in autophosphorylation process. CONCLUSIONS The role of each constituent parameter and their relative time dependent variations in autophosphorylation process could be inferred.