High-throughput virtual screening of potential inhibitors of GPR52 using docking and biased sampling method for Huntington's disease therapy.

Huntington's disease (HD) is a rare and progressive neurodegenerative disorder caused by polyglutamine (poly-Q) mutations of the huntingtin (HTT) gene resulting in chorea, cognitive, and psychiatric dysfunctions. Being a monogenic condition, reducing the levels of the mutated huntingtin protein (mHTT) holds promise as an effective therapeutic approach. GPR52, an orphan G-protein coupled receptor (GPCR), enriched in the striatum, is a novel target for slowing down the progression of HD by lowering the mHTT levels. Therefore, the study focuses on identifying potent small-molecule inhibitors for GPR52 using a combination of robust high-throughput virtual screening (HTVS) and pharmacokinetics profiling followed by fast pulling of ligand (FPL) and umbrella sampling (US) simulations. Initially, screening a library of 2,36,545 compounds was done against the binding pocket of GPR52. Based on binding affinity, stereochemical and non-bonded interactions, and pharmacokinetic profiling, 50 compounds were shortlisted. Selected hit compounds 1, 2, and 3 were subjected to FPL simulations with applied external bias potential to investigate their unique dissociation pathways and intermolecular interactions over time. Subsequently, the US simulations were performed on the selected hit compounds to estimate their binding free energy (ΔG). The analysis of the trajectories obtained from simulations revealed that the residues TYR34, TYR185, GLY187, ASP188, ILE189, SER299, PHE300, and THR303 within the active site of GPR52 were significant for efficient ligand binding through the formation of various hydrogen bond interactions and hydrophobic contacts. Out of the three hit compounds, compound 3 had the lowest ΔG of - 20.82 ± 0.44 kcal/mol. The study identified compounds 1, 2, and 3 as potential molecules that can be developed as GPR52 inhibitors holding promise for lowering mHTT levels.

A high-throughput structural dynamics approach for identification of potential agonists of FFAR4 for type 2 diabetes mellitus therapy.

Diabetes mellitus is a metabolic disorder that persists as a global threat to the world. A G-protein coupled receptor (GPCR), free fatty acid receptor 4 (FFAR4), has emerged as a potential target for type 2 diabetes mellitus (T2DM) and obesity-related disorders. The current study has investigated the FFAR4, deploying 3-dimensional structure modeling, molecular docking, machine learning, and high-throughput virtual screening methods to unravel the receptor's crucial and non-crucial binding site residues. We screened four lakh compounds and shortlisted them based on binding energy, stereochemical considerations, non-bonded interactions, and pharmacokinetic profiling. Out of the screened compounds, four compounds were selected for ligand-bound simulations. The molecular dynamic simulations were carried out for 1µs for native FFAR4 and 500 ns each for complexes of FFAR4 with compound 1, compound 2, compound 3, and compound 4. Our findings showed that in addition to reported binding site residues ARG99, ARG183, and VAL98 in known agonists like TUG-891, the amino acids ARG22, ARG24, THR23, TRP305, and GLU43 were also critical binding site residues. These amino acids impart stability to the FFAR4 complexes and contribute to the stronger binding affinity of the compounds. The study also indicated that aromatic residues like PHE211 are crucial for recognizing the active site's pi-pi and C-C double bonds. Since FFAR4 is a membrane protein, the simulation studies give an insight into the mechanisms of the crucial protein-lipid and lipid-water interactions. The analysis of the molecular dynamics trajectories showed all four compounds as potential hit molecules that can be developed further into potential agonists for T2DM therapy. Amongst the four compounds, compound 4 showed relatively better binding affinity, stronger non-bonded interactions, and a stable complex.Communicated by Ramaswamy H. Sarma.

Identification of prognostic markers and potential therapeutic targets using gene expression profiling and simulation studies in pancreatic cancer.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) has a 5-year relative survival rate of less than 10% making it one of the most fatal cancers. A lack of early measures of prognosis, challenges in molecular targeted therapy, ineffective adjuvant chemotherapy, and strong resistance to chemotherapy cumulatively make pancreatic cancer challenging to manage. OBJECTIVE: The present study aims to enhance understanding of the disease mechanism and its progression by identifying prognostic biomarkers, potential drug targets, and candidate drugs that can be used for therapy in pancreatic cancer. METHODS: Gene expression profiles from the GEO database were analyzed to identify reliable prognostic markers and potential drug targets. The disease's molecular mechanism and biological pathways were studied by investigating gene ontologies, KEGG pathways, and survival analysis to understand the strong prognostic power of key DEGs. FDA-approved anti-cancer drugs were screened through cell line databases, and docking studies were performed to identify drugs with high affinity for ARNTL2 and PIK3C2A. Molecular dynamic simulations of drug targets ARNTL2 and PIK3C2A in their native state and complex with nilotinib were carried out for 100 ns to validate their therapeutic potential in PDAC. RESULTS: Differentially expressed genes that are crucial regulators, including SUN1, PSMG3, PIK3C2A, SCRN1, and TRIAP1, were identified. Nilotinib as a candidate drug was screened using sensitivity analysis on CCLE and GDSC pancreatic cancer cell lines. Molecular dynamics simulations revealed the underlying mechanism of the binding of nilotinib with ARNTL2 and PIK3C2A and the dynamic perturbations. It validated nilotinib as a promising drug for pancreatic cancer. CONCLUSION: This study accounts for prognostic markers, drug targets, and repurposed anti-cancer drugs to highlight their usefulness for translational research on developing novel therapies. Our results revealed potential and prospective clinical applications in drug targets ARNTL2, EGFR, and PI3KC2A for pancreatic cancer therapy.

Computational Methods for Structure-Based Drug Design Through System Biology.

The advances in computational chemistry and biology, computer science, structural biology, and molecular biology go in parallel with the rapid progress in target-based systems. This technique has become a powerful tool in medicinal chemistry for the identification of hit molecules. The recent developments in target-based systems have played a major role in the creation of libraries of compounds, and it has also been widely applied for the design of molecular docking methods. The main advantage of this method is that it hits the fragment that has the strongest binding, has relatively small size, and leads to better compounds in terms of pharmacokinetic properties when compared with virtual screening (VS) and high-throughput screening (HTS) hits. De novo design is an essential aspect of target-based systems and requires the synthesis of chemical to allow the design of promising compound.

Novel Toxin-antitoxin System Xn-mazEF from Xenorhabdus nematophila: Identification, Characterization and Functional Exploration.

BACKGROUND: Xenorhabdus nematophila maintains species-specific mutual interaction with nematodes of Steinernema genus. Type II Toxin Antitoxin (TA) systems, the mazEF TA system controls stress and programmed cell death in bacteria. OBJECTIVE: This study elucidates the functional characterization of Xn-mazEF, a mazEF homolog in X. nematophila by computational and in vitro approaches. METHODS: 3D- structural models for Xn-MazE toxin and Xn-MazF antitoxin were generated, validated and characterized for protein - RNA interaction analysis. Further biological and cellular functions of Xn-MazF toxin were also predicted. Molecular dynamics simulations of 50ns for Xn- MazF toxin complexed with nucleic acid units (DU, RU, RC, and RU) were performed. The MazF toxin and complete MazEF operon were endogenously expressed and monitored for the killing of Escherichia coli host cells under arabinose induced tightly regulated system. RESULTS: Upon induction, E. coli expressing toxin showed rapid killing within four hours and attained up to 65% growth inhibition, while the expression of the entire operon did not show significant killing. The observation suggests that the Xn-mazEF TA system control transcriptional regulation in X. nematophila and helps to manage stress or cause toxicity leading to programmed death of cells. CONCLUSION: The study provides insights into structural and functional features of novel toxin, Xn- MazF and provides an initial inference on control of X. nematophila growth regulated by TA systems.

CytoMegaloVirus Infection Database: A Public Omics Database for Systematic and Comparable Information of CMV.

CytoMegaloVirus (CMV) is known to cause infection in humans and may remain dormant throughout the life span of an individual. CMV infection has been reported to be fatal in patients with weak immunity. It is transmitted through blood, saliva, urine, semen and breast milk. Although medications are available to treat the infected patients, there is no cure for CMV. This concern prompted us to construct a comprehensive database having exhaustive information regarding CMV, its infections and therapies to be available on a single platform. Thus, we propose a newly designed database that includes all the information from various public resources such as biological databases, virus taxonomy databanks, viral databases, and drug bank, integrated into this database, named as cytomegalovirus database (CMVdb). It features all the relevant data regarding the strains of CMV, genes, expressed proteins, the genomic sequence of CMV and drugs used in the treatment of cytomegalovirus infection. CMVdb has a unique feature of in-house data analysis, so all the data obtained from various resources are processed within the system. The user interface is more responsive because of the integrated platform that will highly facilitate the researchers. Based on CMVdb functionality and quality of the data, it will accelerate the research and development in the field of infectious diseases and immunology with a special focus on CMV. The obtained data would be useful in designing better therapeutic strategies and agents for the treatment of CMV infections. The proposed database (CMVdb) is freely accessible at http://shaktisahislab.com/include/CMV/ or http://weislab.com/WeiDOCK/include/content/CMV/.

Protection of Primary Dopaminergic Midbrain Neurons Through Impact of Small Molecules Using Virtual Screening of GPR139 Supported by Molecular Dynamic Simulation and Systems Biology.

INTRODUCTION: GPCR share a common structural feature, i.e., the presence of seven trans-membrane helices having three intracellular and three extracellular loops. The carboxyl terminal is intracellular whereas amino terminal is extracellular. Various conformational changes are observed in structure of GPCR during the binding with ligand, coupling with G protein and interaction with other proteins. In Rhodopsin class of GPCR the basic structure of GPCR is resolved by X-ray crystallography. Ligand acts as an extracellular stimulus for GPCRs to bring physiological changes in organisms. GPR139 has been found to have effective physiological role in primary dopaminergic midbrain neurons and in central nervous system. Recent reports suggested that the ligand of GPR139 protein inhibits the growth of primary dopaminergic midbrain neurons in central nervous system. These discoveries indicated the potential involvement and influence of GPR139 protein in central nervous system METHOD: Therefore, we used multi-approach analysis to investigate the role of GPR139 in the molecular mechanisms of central nervous system. In silico screening was performed to study compound 1 binding with GPR139 protein in their predicted three-dimensional structures. Compound 1 was subjected to molecular dynamics (MD) simulation and stability analysis. RESULTS: The results of MD analysis suggested that the loop region in GPR139 protein structure could affect its binding with drugs. Finally, we cross-validated the predicted compound 1 through systems biology approach. Our results suggested that GPR139 might play an important role in primary dopaminergic midbrain neurons therapy.

Invitro Evaluation of Torin2 and 2, 6-Dihydroxyacetophenone in Colorectal Cancer Therapy.

Colorectal cancer (CRC) is one of the most prevalent cancers diagnosed worldwide. Despite recent advances, resistance to cytotoxic and targeted therapy remains one of the greatest challenges in long-term management of colorectal cancer therapy. Recently established role of mTOR signaling in proliferation of CRC has incited for evaluation of mTOR kinase specific inhibitors in CRC therapy. Second generation mTOR kinase inhibitors including Torin2 has demonstrated efficient anticancer properties against variety of cancers and are in various stages of drug development. The time and financial constraints concomitant from discovery to development of efficient chemical inhibitors has redirected attention towards investigation of wide spread naturally occurring largely inexpensive compounds for their therapeutic potential. One such naturally occurring compound acetophenone derivative polyphenolic compound 2, 6-Dihydroxyacetophenone (DHAP) inhibits cell growth in different conditions. We investigated anticancer properties of both Torin2 and DHAP against colorectal cancer in HCT8 cell lines. Both Torin2 and DHAP inhibited growth of CRC cells at different concentrations by restricting multiple cellular functions e.g., cell cycle progression, cell migration and induced apoptosis. Treatment of HCT8 cells with natural compound DHAP resulted in reduced expression of mTOR pathway specific genes p70S6K1 and AKT1. In silico docking studies showed affinity of DHAP to mTOR kinase like Torin2. Taken together, our result vouches for role of Torin2 in CRC therapy and recommends DHAP an mTOR inhibitor, as a potential lead in the development of new therapeutic regimes against colorectal cancer.

Structure Based Virtual Screening Studies to Identify Novel Potential Compounds for GPR142 and Their Relative Dynamic Analysis for Study of Type 2 Diabetes.

GPR142 (G protein receptor 142) is a novel orphan GPCR (G protein coupled receptor) belonging to "Class A" of GPCR family and expressed in ß cells of pancreas. In this study, we reported the structure based virtual screening to identify the hit compounds which can be developed as leads for potential agonists. The results were validated through induced fit docking, pharmacophore modeling, and system biology approaches. Since, there is no solved crystal structure of GPR142, we attempted to predict the 3D structure followed by validation and then identification of active site using threading and ab initio methods. Also, structure based virtual screening was performed against a total of 1171519 compounds from different libraries and only top 20 best hit compounds were screened and analyzed. Moreover, the biochemical pathway of GPR142 complex with screened compound2 was also designed and compared with experimental data. Interestingly, compound2 showed an increase in insulin production via Gq mediated signaling pathway suggesting the possible role of novel GPR142 agonists in therapy against type 2 diabetes.

Insights into unbound-bound states of GPR142 receptor in a membrane-aqueous system using molecular dynamics simulations.

G protein coupled receptors (GPCRs) are source machinery in signal transduction pathways and being one of the major therapeutic targets play a significant in drug discovery. GPR142, an orphan GPCR, has been implicated in the regulation of insulin, thereby having a crucial role in Type II diabetes management. Deciphering of the structures of orphan, GPCRs (O-GPCRs) offer better prospects for advancements in research in ion translocation and transduction of extracellular signals. As the crystallographic structure of GPR142 is not available in PDB, therefore, threading and ab initio-based approaches were used for 3D modeling of GPR142. Molecular dynamic simulations (900 ns) were performed on the 3D model of GPR142 and complexes of GPR142 with top five hits, obtained through virtual screening, embedded in lipid bilayer with aqueous system using OPLS force field. Compound 1, 3, and 4 may act as scaffolds for designing potential lead agonists for GPR142. The finding of GPR142 MD simulation study provides more comprehensive representation of the functional properties. The concern for Type II diabetes is increasing worldwide and successful treatment of this disease demands novel drugs with better efficacy.

Screening and In Vitro Evaluation of Potential Plasmodium falciparum Leucyl Aminopeptidase Inhibitors.

BACKGROUND: Plasmodium falciparum leucyl aminopeptidase (PfA-M17) regulates the intracellular pool of amino acids required for the growth and development of parasites. Thus, PfA-M17 is a promising target for anti-malarial drug development. METHOD: In the present study, structure-based drug design was used to identify novel PfA-M17 inhibitors, which were subsequently validated by in vitro PfA-M17 and human LAP3 enzyme inhibition assay. A library of 3,147,882 compounds was screened using receptor-based virtual screening against the active site of PfA-M17, and three levels of accuracy were used: high-throughput virtual screening, gridbased ligand docking with energetics (Glide standard precision) and Glide extra precision. RESULTS: Seventeen screened compounds were selected and tested in the rPfA-M17 enzyme inhibition assay. Of these nine compounds were found to be effective inhibitors. To test the target activity, all nine PfA-M17 inhibitors were tested against rhLAP3, the human homolog of PfA-M17. One compound (compound 2) was found to be moderately effective against PfA-M17 (Ki = 287 µM) with limited inhibitory activity against hLAP3 (Ki of 4,464 µM). Subsequently, induced fit docking and pharmacophore modelling were used to further understand more precise ligand-protein interactions in the protein-inhibitor complexes. CONCLUSION: Among the 9 effective PfA-M17 inhibitors, 5 compounds were found effective in the P. falciparum schizont maturation inhibition (SMI) assay. A good correlation (r =0.83) was observed between the rPfA-M17 enzyme inhibition concentration and SMI assay.

Boolean network model for GPR142 against Type 2 diabetes and relative dynamic change ratio analysis using systems and biological circuits approach.

Systems biology addresses challenges in the analysis of genomics data, especially for complex genes and protein interactions using Meta data approach on various signaling pathways. In this paper, we report systems biology and biological circuits approach to construct pathway and identify early gene and protein interactions for predicting GPR142 responses in Type 2 diabetes. The information regarding genes, proteins and other molecules involved in Type 2 diabetes were retrieved from literature and kinetic simulation of GPR142 was carried out in order to determine the dynamic interactions. The major objective of this work was to design a GPR142 biochemical pathway using both systems biology as well as biological circuits synthetically. The term 'synthetically' refers to building biological circuits for cell signaling pathway especially for hormonal pathway disease. The focus of the paper is on logical components and logical circuits whereby using these applications users can create complex virtual circuits. Logic gates process represents only true or false and investigates whether biological regulatory circuits are active or inactive. The basic gates used are AND, NAND, OR, XOR and NOT gates and Integrated circuit composition of many such basic gates and some derived gates. Biological circuits may have a futuristic application in biomedical sciences which may involve placing a micro chip in human cells to modulate the down or up regulation of hormonal disease.

Modelling of human leucyl aminopeptidases for in silico off target binding analysis of potential Plasmodium falciparum leucine aminopeptidase (PfA-M17) specific inhibitors.

Malaria is one of the most widespread infectious diseases in the world. Emergence of multi-drug resistant Plasmodium strains makes it crucial to identify new classes of compounds for anti-malarial therapy. Novel anti-malarial compounds from natural sources (Gomphostema niveum) as well as synthetic chemicals (5-aminolevulinic acid) have been reported in recent patents. Plasmodium falciparum leucyl aminopeptidase (PfA-M17) is a validated target for antimalarial drug development. However, known aminopeptidase inhibitors beset with the problem of non-specificity. Therefore, 3D structural models of PfA-M17 human homologs, Leucine aminopeptidase3 (hLAP3) and probable leucine aminopeptidase (hNPEPL1) were predicted for molecular docking based screening of potential inhibitors for their off target activity. Comparison of IC50 and docking scores of highly active hLAP3 inhibitors shows good correlation (r(2)≈ 0.8). Further, docking analysis with potential PfA-M17 inhibitor Compound-X (identified through virtual screening) shows much higher binding affinity towards PfA-M17 (docking score -11.44) than hLAP3 (docking score -4.26) and hNPEPL1 (docking score -5.08). This lead compound, Compound-X can act as a scaffold for further increasing PfA-M17 binding affinity and hLAP3 and hNPEPL1 3D structure models will be useful for screening of PfA-M17 specific inhibitors.

Modeling of human M1 aminopeptidases for in silico screening of potential Plasmodium falciparum alanine aminopeptidase (PfA-M1) specific inhibitors.

Plasmodium falciparum alanine M1-aminopeptidase (PfA-M1) is a validated target for anti-malarial drug development. Presence of significant similarity between PfA-M1 and human M1-aminopeptidases, particularly within regions of enzyme active site leads to problem of non-specificity and off-target binding for known aminopeptidase inhibitors. Molecular docking based in silico screening approach for off-target binding has high potential but requires 3D-structure of all human M1-aminopeptidaes. Therefore, in the present study 3D structural models of seven human M1-aminopeptidases were developed. The robustness of docking parameters and quality of predicted human M1-aminopeptidases structural models was evaluated by stereochemical analysis and docking of their respective known inhibitors. The docking scores were in agreement with the inhibitory concentrations elucidated in enzyme assays of respective inhibitor enzyme combinations (r2≈0.70). Further docking analysis of fifteen potential PfA-M1 inhibitors (virtual screening identified) showed that three compounds had less docking affinity for human M1-aminopeptidases as compared to PfA-M1. These three identified potential lead compounds can be validated with enzyme assays and used as a scaffold for designing of new compounds with increased specificity towards PfA-M1.

Insights into the conformational perturbations of novel agonists with ß3-adrenergic receptor using molecular dynamics simulations.

Beta 3-adrenergic receptors (ß3-AR), belonging to the G-protein coupled receptor family, are known to be involved in important physiological functions as intestinal smooth muscle relaxation, glucose homeostasis etc. Detailed insight into the mechanistic mode of ß3-AR is not known. Molecular dynamic simulations (100 ns) were performed on the 3-D molecular model of ß3-AR and complexes of ß3-AR with potential agonists embedded in 2-dipalmitoyl-sn-phosphocholine (DPPC) bilayer-water system using OPLS (Optimized Potentials for Liquid Simulations) force field to gain structural insight into ß3-AR. The detailed structural analysis of the molecular dynamic trajectories reveal that the helical bundle conformations remain well preserved to maintain a conformation similar to the other X-ray solved G-protein coupled receptors, whereas significant flexibility is observed in intracellular and the extracellular loops region. The formation of extensive intra helical and water mediated H-bonds, and aromatic stacking interactions play a key role in stabilizing the transmembrane helical bundles. These interactions might be specific to the functional motifs such as D(E)RY, CWxP, S(N)LAxAD, SxxxS and NPxxY motifs which provide structural constraints on the ß3-AR. The compound 3, 4 and 6 are proposed to act as scaffolds for potential agonists for ß3-AR based on stereochemical and energetic considerations. In lieu of the lack of the crystal structure available, the findings of the simulation study provides more comprehensive picture of the functional properties of the ß3-AR.

Leishmania donovani pteridine reductase 1: comparative protein modeling and protein-ligand interaction studies of the leishmanicidal constituents isolated from the fruits of Piper longum.

Visceral leishmaniasis or kala-azar is caused by the dimorphic parasite Leishmania donovani in the Indian subcontinent. Treatment options for kala-azar are currently inadequate due to various limitations. Currently, drug discovery for leishmaniases is oriented towards rational drug design; the aim is to identify specific inhibitors that target particular metabolic activities as a possible means of controlling the parasites without affecting the host. Leishmania salvages pteridin from its host and reduces it using pteridine reductase 1 (PTR1, EC 1.5.1.33), which makes this reductase an excellent drug target. Recently, we identified six alkamides and one benzenoid compound from the n-hexane fraction of the fruit of Piper longum that possess potent leishmanicidal activity against promastigotes as well as axenic amastigotes. Based on a homology model derived for recombinant pteridine reductase isolated from a clinical isolate of L. donovani, we carried out molecular modeling and docking studies with these compounds to evaluate their binding affinity. A fairly good agreement between experimental data and the results of molecular modeling investigation of the bioactive and inactive compounds was observed. The amide group in the conjugated alkamides and the 3,4-methylenedioxystyrene moiety in the benzenoid compound acts as heads and the long aliphatic chain acts as a tail, thus playing important roles in the binding of the inhibitor to the appropriate position at the active site. The remarkably high activity of a component containing piperine and piperine isomers (3.36:1) as observed by our group prompted us to study the activities of all four isomers of piperine-piperine (2E,4E), isopiperine (2Z,4E), isochavicine (2E,4Z), and chavicine (2Z,4Z)-against LdPTR1. The maximum inhibitory effect was demonstrated by isochavicine. The identification of these predicted inhibitors of LdPTR1 allowed us to build up a stereoview of the structure of the binding site in relation to activity, affording significant information that should prove useful during the structure-based design of leishmanicidal drugs.

Identification of novel ß3-adrenoceptor agonists using energetic analysis, structure based pharmacophores and virtual screening.

ß3 Adrenergic receptor (ß3-AR), is a potential therapeutic target for the treatment of type II diabetes and obesity. We report the identification of novel compounds as ß3-AR agonists by integrating different approaches of energetic analysis, structure based pharmacophore designing and virtual screening. In a step wise filtering protocol, structure based virtual screening of 2, 33, 450 compounds was done. These molecules were docked into the active site of the receptor utilizing three levels of accuracy; ligands passing the HTVS (high throughput virtual screening) step were subsequently analyzed in Glide SP (Standard Precision) and finally in Glide XP (Extra Precision) to estimate the receptor ligand binding affinities. In the second step a total of 300 pharmacophore hypotheses were generated from a set of known and diverse ß3-AR agonists. The best hypothesis showed six features: three hydrogen bond acceptors, one positively charged group, and two aromatic rings. To cross validate, pharmacophore filtering was done on the set of shortlisted compounds from structure based VS (virtual screening). The different screening techniques employed were validated using enrichment factor calculations. The energetic based Pharmacophore performed fairly well at distinguishing active from the inactive compounds and yielded a greater diversity of active molecules whereas the number of actives retrieved in the case of structure based screening was the highest.

HER2+ breast cancer therapy: by CPP-ZFN mediated targeting of mTOR?

A significant fraction of HER2+ patients develop resistance to available therapies such as trastuzumab. The acquired resistance is primarily due to hyper activation of HER2 downstream PI3K/Akt/mTOR signalling pathway. Hence, identification of inhibitors of components of this pathway, particularly mTOR, is an area of intense investigation. Interestingly, mTOR specific inhibitors (rapamycin/rapalogs) have been tested and shown to potentiate the effect of HER2 inhibitors. However, the use of mTOR inhibitors will also be associated with the limitations inherently linked with extensive use of anticancer drugs e.g., toxicity and acquired drug resistance. Hereby, we hypothesize development of an alternative novel molecular therapeutic intervention based on cell penetrating peptide (CPP), a highly efficient carrier, conjugated to zinc finger nuclease (ZFN), a precise molecular scissor. The use of HER2 specific CPP conjugated to mTOR specific ZFN, will make the mTOR locus non-functional and inhibit the PI3K/Akt/mTOR pathway, essential for growth and proliferation of cancerous cells. With the availability of HER21 cancerous cell specific CPP and proved applications of ZFN in targeted genome engineering of over 11 species, the prospects of success of CPP-ZFN anti-cancer therapy are very high.

Modeling and simulation studies of human ß3 adrenergic receptor and its interactions with agonists.

ß3 adrenergic receptor (ß3AR) is known to mediate various pharmacological and physiological effects such as thermogenesis in brown adipocytes, lipolysis in white adipocytes, glucose homeostasis and intestinal smooth muscle relaxation. Several efforts have been made in this field to understand their function and regulation in different human tissues and they have emerged as potential attractive targets in drug discovery for the treatment of diabetes, depression, obesity etc. Although the crystal structures of Bovine Rhodopsin and ß2 adrenergic receptor have been resolved, to date there is no three dimensional structural information on ß3AR. Our aim in this study was to model 3D structure of ß3AR by various molecular modeling and simulation techniques. In this paper, we describe a refined predicted model of ß3AR using different algorithms for structure prediction. The structural refinement and minimization of the generated 3D model of ß3AR were done by Schrodinger suite 9.1. Docking studies of ß3AR model with the known agonists enabled us to identify specific residues, viz, Asp 117, Ser 208, Ser 209, Ser 212, Arg 315, Asn 332, within the ß3AR binding pocket, which might play an important role in ligand binding. Receptor ligand interaction studies clearly indicated that these five residues showed strong hydrogen bonding interactions with the ligands. The results have been correlated with the experimental data available. The predicted ligand binding interactions and the simulation studies validate the methods used to predict the 3D-structure.

In silico designing of insecticidal small interfering RNA (siRNA) for Helicoverpa armigera control.

Helicoverpa armigera, a polyphagous lepidopteron insect pest causes severe yield loss in cotton, legumes, tomato, okra and other crops. Application of chemical pesticides although effective, has human health and environmental safety concerns. Moreover, development of resistance against most of the available pesticides is compelling to look for alternative strategies. Adoption of Bt transgenic crops have resulted in reduction in pesticide consumption and increasing crop productivity. However, sustainability of Bt transgenic crops is threatened by the emergence of insect resistance. In the present study potential insecticidal siRNA were identified in six H. armigera horrhonal pathway genes. Out of over 2000 computationally identified siRNA, 16 most promising siRNA were selected that address the biosafety concerns and have high potential of targeted gene silencing. These siRNA will be useful for chemical synthesis, in insect feeding assays and knockdown the target H. armigera hormone biosynthesis, consequently obstructing the completion of insect life cycle. The siRNA have a great potential of deployment to control H. annrmigera alone as well as with Bt for insect resistance management.