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Your search keyword '"Vankudavath, Raju Naik"' showing total 9 results
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9 results on '"Vankudavath, Raju Naik"'

2. Remdesivir (GS-5734) as a therapeutic option of 2019-nCOV main protease – in silico approach

Author

Giridhar Goudar, Boiroju Naveen Kumar, Manne Munikumar, Medithi Srujana, Pittla Naresh, Vankudavath Raju Naik, Rajkumar Hemalatha, and U.V. RamaKrishna

Subjects
0303 health sciences, 2019-20 coronavirus outbreak, Protease, biology, Sequence analysis, viruses, medicine.medical_treatment, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), In silico, 030303 biophysics, RNA virus, General Medicine, Computational biology, biology.organism_classification, medicine.disease_cause, Genome, 03 medical and health sciences, Structural Biology, medicine, Molecular Biology, Coronavirus
Abstract

2019 – Novel Coronavirus (2019-nCOV), enclosed large genome positive-sense RNA virus characterized by crown-like spikes that protrude from their surface, and have a distinctive replication strategy. The 2019-nCOV belongs to the Coronaviridae family, principally consists of virulent pathogens showing zoonotic property, has emerged as a pandemic outbreak with high mortality and high morbidity rate around the globe and no therapeutic vaccine or drugs against 2019-nCoV are discovered till now. In this study, in silico methods and algorithms were used for sequence, structure analysis and molecular docking on Mpro of 2019-nCOV. The co-crystal structure of 2019-nCOV protease, 6LU7 have ∼99% identity with SARS-CoV protease. The 6LU7 residues, Cys145 and His164 are playing a significant role in replication and are essential for the survival of 2019-nCOV. Alongside, 2019-nCOV Mpro sequence is non-homologous to human host-pathogen. Complete genome sequence analysis, structural and molecular docking results revealed that Remdesivir is having a better binding affinity with -8.2 kcal/mol than the rest of protease inhibitors, and peptide. Remdesivir is strongly forming h-bonds with crucial Mpro residues, Cys145, and His164. Further, MD simulation analysis also confirmed, that these residues are forming H-bond with Remdesivir during 100 ns simulations run and found stable (∼99%) by RMSD and RMSF. Thus, present in silico study at molecular approaches suggest that, Remdesivir is a potent therapeutic inhibitor against 2019-nCoV. Communicated by Ramaswamy H. Sarma

Published
2020

3. Remdesivir (GS-5734) as a therapeutic option of 2019-nCOV main protease

Author

Vankudavath Raju, Naik, Manne, Munikumar, Ungarala, Ramakrishna, Medithi, Srujana, Giridhar, Goudar, Pittla, Naresh, Boiroju Naveen, Kumar, and Rajkumar, Hemalatha

Subjects
Alanine, sequence analysis, SARS-CoV-2, Remdesivir, COVID-19, molecular docking, phylogeny, Adenosine Monophosphate, COVID-19 Drug Treatment, Molecular Docking Simulation, dynamics simulations, 2019-nCOV, Humans, Protease Inhibitors, Peptide Hydrolases, Research Article
Abstract

2019 – Novel Coronavirus (2019-nCOV), enclosed large genome positive-sense RNA virus characterized by crown-like spikes that protrude from their surface, and have a distinctive replication strategy. The 2019-nCOV belongs to the Coronaviridae family, principally consists of virulent pathogens showing zoonotic property, has emerged as a pandemic outbreak with high mortality and high morbidity rate around the globe and no therapeutic vaccine or drugs against 2019-nCoV are discovered till now. In this study, in silico methods and algorithms were used for sequence, structure analysis and molecular docking on Mpro of 2019-nCOV. The co-crystal structure of 2019-nCOV protease, 6LU7 have ∼99% identity with SARS-CoV protease. The 6LU7 residues, Cys145 and His164 are playing a significant role in replication and are essential for the survival of 2019-nCOV. Alongside, 2019-nCOV Mpro sequence is non-homologous to human host-pathogen. Complete genome sequence analysis, structural and molecular docking results revealed that Remdesivir is having a better binding affinity with -8.2 kcal/mol than the rest of protease inhibitors, and peptide. Remdesivir is strongly forming h-bonds with crucial Mpro residues, Cys145, and His164. Further, MD simulation analysis also confirmed, that these residues are forming H-bond with Remdesivir during 100 ns simulations run and found stable (∼99%) by RMSD and RMSF. Thus, present in silico study at molecular approaches suggest that, Remdesivir is a potent therapeutic inhibitor against 2019-nCoV. Communicated by Ramaswamy H. Sarma

Published
2020

5. Corrigendum to “Evaluation of bar, barnase, and barstar recombinant proteins expressed in genetically engineered Brassica juncea (Indian mustard) for potential risks of food allergy using bioinformatics and literature searches” [Food Chem. Toxicol. 83 (2015) 93–102]

Author

Siruguri, Vasanthi, primary, Bharatraj, Dinesh Kumar, additional, Vankudavath, Raju Naik, additional, Rao Mendu, Vishnu Vardhana, additional, Gupta, Vibha, additional, and Goodman, Richard E., additional

Published
2015
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7. Ellagic Acid Inhibits VEGF/VEGFR2, PI3K/Akt and MAPK Signaling Cascades in the Hamster Cheek Pouch Carcinogenesis Model

Author

Kowshik, Jaganathan, Giri, Hemant, Kishore, Tanagala Kranthi Kiran, Kesavan, Rushendhiran, Vankudavath, Raju Naik, Reddy, Geereddy Bhanuprakash, Dixit, Madhulika, and Nagini, Siddavaram

Abstract

Background: Blocking vascular endothelial growth factor (VEGF) mediated tumor angiogenesis by phytochemicals has emerged as an attractive strategy for cancer prevention and therapy. ; Methods: We investigated the anti-angiogenic effects of ellagic acid in a hamster model of oral oncogenesis by examining the transcript and protein expression of hypoxia-inducible factor-1alpha (HIF-1α), VEGF, VEGFR2, and the members of the PI3K/Akt and MAPK signaling cascades. Molecular docking studies and cell culture experiments with the endothelial cell line ECV304 were performed to delineate the mechanism by which ellagic acid regulates VEGF signaling. ; Results: We found that ellagic acid significantly inhibits HIF-1α-induced VEGF/VEGFR2 signalling in the hamster buccal pouch by abrogating PI3K/Akt and MAPK signaling via downregulation of PI3K, PDK-1, p-Aktser473, mTOR, p-ERK, and p-JNK. Ellagic acid was also found to reduce the expression of histone deacetylases that could inhibit neovascularization. Analysis of the mechanism revealed that ellagic acid inhibits hypoxia-induced angiogenesis via suppression of HDAC-6 in ECV304 cells. Furthermore, knockdown of endogenous HDAC6 via small interfering RNA abrogated hypoxia-induced expression of HIF-1α and VEGF and blocked Akt activation. Molecular docking studies confirmed interaction of ellagic acid with upstream kinases that regulate angiogenic signaling. ; Conclusions: Taken together, these findings demonstrate that the anti-angiogenic activity of ellagic acid may be mediated by abrogation of hypoxia driven PI3K/Akt/mTOR, MAPK and VEGF/VEGFR2 signaling pathways involving suppression of HDAC6 and HIF-1α responses. ; General Significance: Ellagic acid offers promise as a lead compound for anticancer therapeutics by virtue of its ability to inhibit key oncogenic signaling cascades and HDACs.

Published
2014

8. Identification of LOGP values and Electronegativities as structural insights to model inhibitory activity of HIV-1 capsid inhibitors - a SVM and MLR aided QSAR studies.

Author

Sharma N, Ethiraj KR, Yadav M, Nayarisseri S A, Chaurasiya M, Vankudavath RN, and Rao KR

Subjects
Cell Line, Humans, Inhibitory Concentration 50, Quantitative Structure-Activity Relationship, Capsid drug effects, HIV-1 drug effects
Abstract

Linear and non-linear QSAR studies have been performed in present investigation with multiple linear regressions (MLR) analysis and Support vector machine (SVM) using different kernels. Three relevant descriptors out of fifteen descriptors calculated are identified as LOGP values, G3e and Rte+. Their relationship with biological activity IC50 have provided structural insights in interpretation and serializing the results into a pragmatic approachable technique. QSAR models obtained show statistical fitness and good predictability. SVM using Gaussian kernel function was found more efficient in prediction of IC50 of training set of thirty small molecules HIV-1 capsid inhibitors. Y-scrambling, PRESS and test set were used as validation parameters. SVM was found superior to training set prediction and internal validations and found inferior to external test set (11 molecules) predictions. Wherein MLR analysis it was vice-versa. Mechanistic interpretation of selected descriptors from both the models actuates further research.

Published
2012

9. High-throughput phenotyping of plant populations using a personal digital assistant.

Author

Vankudavath RN, Bodanapu R, Sreelakshmi Y, and Sharma R

Subjects
Programming Languages, Statistics as Topic, Computers, Solanum lycopersicum anatomy & histology, Phenotype, Photography instrumentation
Abstract

During many biological experiments voluminous data is acquired, which can be best collected with -portable data acquisition devices and later analyzed with a personal computer (PC). Public domain software catering to data acquisition and analysis is currently limited. The necessity of phenotyping large plant populations led to the development of the application "PHENOME" to manage the data. PHENOME allows acquisition of phenotypic data using a personal digital assistant (PDA) with a built-in barcode scanner. The acquired data can be exported to a customized database on a PC for further analysis and cataloging. PHENOME can be used for a variety of applications, for example high-throughput phenotyping of a mutagenized or mapping population, or phenotyping of several individuals in one or more ecological niches.

Published
2012
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