Umashankar Vetrivel

Identification and Insilico Analysis of Retinoblastoma Serum microRNA Profile and Gene Targets Towards Prediction of Novel Serum Biomarkers.

Retinoblastoma (RB) is a malignant tumor of the retina seen in children, and potential non invasive biomarkers are in need for rapid diagnosis and for prognosticating the therapy. This study was undertaken to identify the differentially expressed miRNAs in the serum of children with RB in comparison with the normal age matched serum, to analyze its concurrence with the existing RB tumor miRNA profile, to identify its novel gene targets specific to RB, and to study the expression of a few of the identified oncogenic miRNAs in the advanced stage primary RB patients serum sample. MiRNA profiling was performed on 14 pooled serum from children with advanced RB and 14 normal age matched serum samples, wherein 21 miRNAs were found to be upregulated (fold change ≥ +2.0, P ≤ 0.05) and 24 to be downregulated (fold change ≤ –2.0, P ≤ 0.05). Furthermore, intersection of 59 significantly deregulated miRNAs identified from RB tumor profiles with that of miRNAs detected in serum profile revealed that 33 miRNAs had followed a similar deregulation pattern in RB serum. Later we validated a few of the miRNAs (miRNA 17-92) identified by microarray in the RB patient serum samples (n = 20) by using qRT-PCR. Expression of the oncogenic miRNAs, miR-17, miR-18a, and miR-20a by qRT-PCR was significant in the serum samples exploring the potential of serum miRNAs identification as noninvasive diagnosis. Moreover, from miRNA gene target prediction, key regulatory genes of cell proliferation, apoptosis, and positive and negative regulatory networks involved in RB progression were identified in the gene expression profile of RB tumors. Therefore, these identified miRNAs and their corresponding target genes could give insights on potential biomarkers and key events involved in the RB pathway.

A novel in silico approach to identify potential therapeutic targets in human bacterial pathogens.

In recent years, genome-sequencing projects of pathogens and humans have revolutionized microbial drug target identification. Of the several known genomic strategies, subtractive genomics has been successfully utilized for identifying microbial drug targets. The present work demonstrates a novel genomics approach in which codon adaptation index (CAI), a measure used to predict the translational efficiency of a gene based on synonymous codon usage, is coupled with subtractive genomics approach for mining potential drug targets. The strategy adopted is demonstrated using respiratory pathogens, namely, Streptococcus pneumoniae and Haemophilus influenzae as examples. Our approach identified 8 potent target genes (Streptococcus pneumoniae–2, H. influenzae–6), which are functionally significant and also play key role in host-pathogen interactions. This approach facilitates swift identification of potential drug targets, thereby enabling the search for new inhibitors. These results underscore the utility of CAI for enhanced in silico drug target identification.

Agonistic effect of polyunsaturated fatty acids (PUFAs) and its metabolites on brain-derived neurotrophic factor (BDNF) through molecular docking simulation

BackgroundBrain-derived neurotrophic factor (BDNF) is a potent neurotrophic factor that is implicated in the regulation of food intake and body weight. Polyunsaturated fatty acids (PUFAs) localised in cell membranes have been shown to alter the levels of BDNF in the brain, suggesting that PUFAs and BDNF could have physical interaction with each other. To decipher the molecular mechanism through which PUFAs modulates BDNF’s activity, molecular docking was performed for BDNF with PUFAs and its metabolites, with 4-Methyl Catechol as a control.ResultsInferring from molecular docking studies, lipoxin A4 (LXA4), and a known anti-inflammatory bioactive metabolite derived from PUFAs, with a binding energy of −3.98 Kcal/mol and dissociation constant of 1.2mM showed highest binding affinity for BDNF in comparison to other PUFAs and metabolites considered in the study. Further, the residues Lys 18, Thr 20, Ala 21, Val 22, Phe 46, Glu 48, Lys 50, Lys 58, Thr 75, Gln 77, Arg 97 and Ile 98 form hot point motif, which on interaction enhances BDNF’s function.ConclusionThese results suggest that PUFAs and their metabolites especially, LXA4, modulate insulin resistance by establishing a physical interaction with BDNF. Similar interaction(s) was noted between BDNF and resolvins and protectins but were of lesser intensity compared to LXA4.

In vitro and In silico studies on inhibitory effects of curcumin on multi drug resistance associated protein (MRP1) in retinoblastoma cells.

Multi Drug Resistance (MDR) is one of the major causes of chemotherapy failure in human malignancies. Curcumin, the active constituent of Curcuma longa is a proven anticancer agent potentially modulating the expression and function of these MDR proteins. In this study, we attempted to test curcumin for its potential to inhibit the expression and function of multidrug resistance associated protein 1 (MRP1) in retinoblastoma (RB) cell lines through western blot, RT-PCR and functional assays. In silico analysis were also performed to understand the molecular interactions conferred by curucmin on MRP1 in RB cells. Western blot and RTPCR analysis did not show any correlation of MRP1 expression with increase in concentration of curcumin. However, inhibitory effect of curcumin on MRP1 function was observed as a decrease in the efflux of fluorescent substrate. Moreover, Curcumin did not affect 8-azido-ATP-biotin binding to MRP1 and it also showed inhibition of ATP-hydrolysis stimulated by quercetin, which is indicative of curcumins interaction with the substrate binding site of MRP1. Furthermore, homology modelling and docking simulation studies of MRP1 also provided deeper insights into the molecular interactions, thereby inferring the potential binding mode of curcumin into the substrate binding site of MRP1.

Detection of novel coupled mutations in the katG gene (His276Met, Gln295His and Ser315Thr) in a multidrug-resistant Mycobacterium tuberculosis strain from Chennai, India, and insight into the molecular mechanism of isoniazid resistance using structural bioinformatics approaches

This study reports on the structural basis of drug resistance targeting the katG gene in a multidrug-resistant Mycobacterium tuberculosis (MDR-TB) strain with two novel mutations (His276Met and Gln295His) in addition to the most commonly reported mutation (Ser315Thr). A structural bioinformatics approach was used to predict the structure of the mutant KatG enzyme (MT). Subsequent molecular dynamics and docking studies were performed to explain the mechanism of isoniazid (INH) resistance. The results show significant conformational changes in the structure of MT leading to a change in INH binding residues at the active site, with a significant increase in the inhibition constant (Ki) of 5.67 μm in the mutant KatG-isoniazid complex (MT-INH) compared with the wild-type KatG-isoniazid complex (WT-INH). In the case of molecular dynamics studies, root mean square deviation (RMSD) analysis of the protein backbone in simulated biological conditions revealed an unstable trajectory with higher deviations in MT throughout the simulation process (1 ns). Moreover, root mean square fluctuation (RMSF) analysis revealed an overall increase in residual fluctuations in MT compared with the wild-type KatG enzyme (WT), whilst the INH binding residues of MT showed a decreased fluctuation that can be observed as peak deviations. Hence, the present study suggests that His276Met, Gln295His and Ser315Thr mutations targeting the katG gene result in decreased stability and flexibility of the protein at INH binding residues leading to impaired enzyme function.

Probing the intermolecular interactions of PPARγ-LBD with polyunsaturated fatty acids and their anti-inflammatory metabolites to infer most potential binding moieties

BackgroundPPARγ is an isoform of peroxisome proliferator-activated receptor (PPAR) belonging to a super family of nuclear receptors. PPARγ receptor is found to play a crucial role in the modulation of lipid and glucose homeostasis. Its commotion has been reported to play a significant role in a broad spectrum of diseases such as type 2 diabetes mellitus, inflammatory diseases, Alzheimer’s disease, and in some cancers. Hence, PPARγ is an important therapeutic target. Polyunsaturated fatty acids (PUFAs) and their metabolites (henceforth referred to as bioactive lipids) are known to function as agonists of PPARγ. However, agonistic binding modes and affinity of these ligands to PPARγ are yet to be deciphered.MethodsIn this study, we performed a comparative molecular docking, binding free energy calculation and molecular dynamics simulation to infer and rank bioactive lipids based on the binding affinities with the ligand binding domain (LBD) of PPARγ.ResultsThe results inferred affinity in the order of resolvin E1 > neuroprotectin D1 > hydroxy-linoleic acid > docosahexaenoic acid > lipoxin A4 > gamma-linolenic acid, arachidonic acid > alpha-linolenic acid > eicosapentaenoic acid > linoleic acid. Of all the bioactive lipids studied, resolvin E1, neuroprotectin D1 and hydroxy-linoleic acid showed significant affinity comparable to proven PPARγ agonist namely, rosiglitazone, in terms of Glide XP docking score, H-bond formation with the key residues, binding free energy and stable complex formation with LBD favouring co-activator binding, as inferred through Molecular Dynamics trajectory analysis.ConclusionHence, these three bioactive lipids (resolvin E1, neuroprotectin D1 and hydroxy-linoleic acid) may be favourably considered as ideal drug candidates in therapeutic modulation of clinical conditions such as type 2 DM, Alzheimer’s disease and other instances where PPARγ is a key player.

Virtual screening studies reveal linarin as a potential natural inhibitor targeting CDK4 in retinoblastoma

Objective: To find out whether linarin can be used as a potential natural inhibitor to target CDK4 in retinoblastoma using virtual screening studies. Materials and Methods: In this study, molecular modeling and protein structure optimization was performed for crystal structure of CDK4 (PDB id: 3G33), and was subjected to Molecular Dynamics (MD) simulation for 10 nanoseconds, as a preparatory process for docking. Furthermore, the stable conformation obtained in the MD simulation was utilized for virtual screening against the library of natural compounds in Indian Plant Anticancer Compounds Database (InPACdb) using AutoDock Vina. Finally, best docked ligands were revalidated individually through semi-flexible docking by AutoDock 4.0. Results: The CDK4 structure was stereochemically optimized to fix clashes and bad angles, which placed 96.4% residues in the core region of Ramachandran plot. The final structure of CDK4 that emerged after MD simulation was proven to be highly stable as per different validation tools. Virtual screening and docking was carried out for CDK4 against optimized ligands from InPACdb through AutoDock Vina. This inferred Linarin (Inpacdb AC.NO. acd0073) as a potential therapeutic agent with binding energy of -8.9 kJ/mol. Furthermore, it was also found to be valid as per AutoDock 4.0 semi-flexible docking procedure, with the binding energy of -8.18 kJ/mol and Ki value of 1.01 μM. Conclusion: The docking results indicate linarin, a flavonoid plant compound, as a potential inhibitor of CDK4 compared to some of the currently practiced anticancer drugs for retinoblastoma. This finding can be extended to experimental validation to assess the in vivo efficacy of the identified compound.

Modulation of multidrug resistance 1 expression and function in retinoblastoma cells by curcumin

Objective: To determine the possible interaction of curcumin with P-glycoprotein (P-gp) expression and function by in vitro and in silico studies. Materials and Methods: In this study, curcumin was compared for its potential to modulate the expression and function of P-gp in Y79 RB cells by western blot, RT-PCR (reverse transcription polymerase chain reaction) and functional assay. Further, in silico molecular modeling and docking simulations were performed to deduce the inhibitory binding mode of curcumin. Results: Western blot and RT-PCR analysis decreased the expression of P-gp in a dose-dependent manner. The effect of curcumin on P-gp function was demonstrated by Rhodamine 123 (Rh123) accumulation and efflux study. Curcumin increased the accumulation of Rh123 and decreased its efflux in retinoblastoma (RB) cells. In addition, curcumin inhibited verapamil stimulated ATPase activity and photoaffinity labeling study showed no effect on the binding of 8-azido-ATP-biotin, indicating its interaction at the substrate binding site. Moreover, molecular docking studies concurrently infer the binding of curcumin into the substrate binding site of P-gp with a binding energy of -7.66 kcal/mol. Conclusion: These findings indicate that curcumin suppresses the MDR1 expression and function, and therefore may be useful as modulators of multidrug resistance in RB tumor.

Inhibition of IKKβ by celastrol and its analogues – an in silico and in vitro approach

Abstract Context: Alzheimer’s disease (AD) is the most common form of dementia affecting the aged population and neuroinflammation is one of the most observed AD pathologies. NF-κB is the central regulator of inflammation and inhibitor κB kinase (IKK) is the converging point in NF-κB activation. Celastrol is a natural triterpene used as a treatment for inflammatory conditions. Objective: This study determines the neuroprotective and inhibitory effect of celastrol on amyloid beta1-42 (Aβ1-42) induced cytotoxicity and IKKβ activity, respectively. Materials and methods: Retinoic acid differentiated IMR-32 cells were treated with celastrol (1 μM) before treatment with Aβ1-42 (IC30 10 μM) for 24 h. The cytotoxicity and IKK phosphorylation were measured by MTT and western blotting analysis, respectively. We screened 36 celastrol analogues for the IKKβ inhibition by molecular docking and evaluated their drug like properties to delineate the neuroprotective effects. Results: Celastrol (1 μM) inhibited Aβ1-42 (10 μM) induced IκBα phosphorylation and protected IMR-32 cells from cell death. Celastrol and 25 analogues showed strong binding affinity with IKKβ as evidenced by strong hydrogen-bonding interactions with critical active site residues. All the 25 analogues displayed strong anti-inflammatory properties but only 11 analogues showed drug-likeness. Collectively, molecule 15 has highest binding affinity, CNS activity and more drug likeness than parent compound celastrol. Discussion and conclusion: The decreased expression of pIκBα in celastrol pretreated cells affirms the functional representation of inhibited IKKβ activity in these cells. The neuroprotective potentials of celastrol and its analogues may be related to IKK inhibition.

Multilevel Precision-Based Rational Design of Chemical Inhibitors Targeting the Hydrophobic Cleft of Toxoplasma gondii Apical Membrane Antigen 1 (AMA1)

Toxoplasma gondii is an intracellular Apicomplexan parasite and a causative agent of toxoplasmosis in human. It causes encephalitis, uveitis, chorioretinitis, and congenital infection. T. gondii invades the host cell by forming a moving junction (MJ) complex. This complex formation is initiated by intermolecular interactions between the two secretory parasitic proteins—namely, apical membrane antigen 1 (AMA1) and rhoptry neck protein 2 (RON2) and is critically essential for the host invasion process. By this study, we propose two potential leads, NSC95522 and NSC179676 that can efficiently target the AMA1 hydrophobic cleft, which is a hotspot for targeting MJ complex formation. The proposed leads are the result of an exhaustive conformational search-based virtual screen with multilevel precision scoring of the docking affinities. These two compounds surpassed all the precision levels of docking and also the stringent post docking and cumulative molecular dynamics evaluations. Moreover, the backbone flexibility of hotspot residues in the hydrophobic cleft, which has been previously reported to be essential for accommodative binding of RON2 to AMA1, was also highly perturbed by these compounds. Furthermore, binding free energy calculations of these two compounds also revealed a significant affinity to AMA1. Machine learning approaches also predicted these two compounds to possess more relevant activities. Hence, these two leads, NSC95522 and NSC179676, may prove to be potential inhibitors targeting AMA1-RON2 complex formation towards combating toxoplasmosis.