Journal Articles
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Item A novel fibrinolytic serine metalloprotease from the marine Serratia marcescens subsp. sakuensis: Purification and characterization(Elsevier B.V., 2018) Krishnamurthy, A.; Belur, P.D.This study demonstrates the purification and characterization of a fibrinolytic serine metalloprotease from the marine Serratia marcescens subsp. sakuensis (KU296189.1). The purified enzyme (1033 U/mg) had a molecular weight of 43 KDa, with optimum pH and temperature being 7 and 55 °C. The in vitro half-life of the fibrinolytic enzyme at 37 °C was found to be 19 h. The kinetic constants, Km and Vmax of the purified enzyme determined using fibrin as substrate was 0.66 mg/mL and 158.73 U/mL. The Kcat and catalytic efficiency of the enzyme was found to be 12.21 min?1 and 18.32 mL/(mg min) respectively. The fibrinolytic enzyme did not show any proteolytic activity towards blood plasma proteins like haemoglobin, ?-globulins and transferrin. In vitro studies revealed that the fibrinolytic enzyme displayed 38% clot lysis for a period of 3 h which was higher than that displayed by streptokinase and heparin. A total of seven peptide sequences were obtained after the LC-MS/MS-TOF analysis, out of which only four sequences showed 67% homology with the sequences of the other proteases. All these results suggest its novelty and potential application in thrombolytic therapy. © 2018 Elsevier B.V.Item Computational analysis of therapeutic enzyme uricase from different source organisms(Bentham Science Publishers P.O. Box 294 Bussum 1400 AG, 2020) Nelapati, A.K.; JagadeeshBabu, J.Background: Hyperuricemia and gout are the conditions, which is a response of accumulation of uric acid in the blood and urine. Uric acid is the product of purine metabolic pathway in humans. Uricase is a therapeutic enzyme that can enzymatically reduces the concentration of uric acid in serum and urine into more a soluble allantoin. Uricases are widely available in several sources like bacteria, fungi, yeast, plants and animals. Objective: The present study is aimed at elucidating the structure and physiochemical properties of uricase by insilico analysis. Methods: A total number of sixty amino acid sequences of uricase belongs to different sources were obtained from NCBI and different analysis like Multiple Sequence Alignment (MSA), homology search, phylogenetic relation, motif search, domain architecture and physiochemical properties including pI, EC, Ai, Ii, and were performed. Results: Multiple sequence alignment of all the selected protein sequences has exhibited distinct difference between bacterial, fungal, plant and animal sources based on the position-specific existence of conserved amino acid residues. The maximum homology of all the selected protein sequences is between 51-388. In singular category, homology is between 16-337 for bacterial uricase, 14-339 for fungal uricase, 12-317 for plants uricase, and 37-361 for animals uricase. The phylogenetic tree constructed based on the amino acid sequences disclosed clusters indicating that uricase is from different source. The physiochemical features revealed that the uricase amino acid residues are in between 300-338 with a molecular weight as 33-39kDa and theoretical pI ranging from 4.95-8.88. The amino acid composition results showed that valine amino acid has a high average frequency of 8.79 percentage compared to different amino acids in all analyzed species. Conclusion: In the area of bioinformatics field, this work might be informative and a stepping-stone to other researchers to get an idea about the physicochemical features, evolutionary history and structural motifs of uricase that can be widely used in biotechnological and pharmaceutical industries. Therefore, the proposed in silico analysis can be considered for protein engineering work, as well as for gout therapy. © 2020 Bentham Science Publishers.Item Epitope-Based Potential Vaccine Candidate for Humoral and Cell-Mediated Immunity to Combat Severe Acute Respiratory Syndrome Coronavirus 2 Pandemic(American Chemical Society, 2020) Das, B.K.; Chakraborty, D.The emergence of severe acute respiratory syndrome from novel Coronavirus (SARS-CoV-2) has put an immense pressure worldwide where vaccination is believed to be an efficient way for developing hard immunity. Herein, we employ immunoinformatic tools to identify B-cell, T-cell epitopes associated with the spike protein of SARS-CoV-2, which is important for genome release. The results showed that the highly immunogenic epitopes located at the stalk part are mostly conserved compared to the receptor binding domain (RDB). Further, two vaccine candidates were computationally modeled from the linear B-cell, T-cell epitopes. Molecular docking reveals the crucial interactions of the vaccines with immune-receptors, and their stability is assessed by MD simulation studies. The chimeric vaccines showed remarkable binding affinity toward the immune cell receptors computed by the MM/PBSA method. van der Waals and electrostatic interactions are found to be the dominant factors for the stability of the complexes. The molecular-level interaction obtained from this study may provide deeper insight into the process of vaccine development against the pandemic of COVID-19. © 2020 American Chemical Society.Item In silico structural and functional analysis of bacillus uricases(Bentham Science Publishers, 2021) Nelapati, A.K.; Meena, S.; Singh, A.K.; Bhakta, N.; JagadeeshBabu, P.E.Background: Excluding humans, the peroxisomal uricase is responsible for the catabolism of uric acid into allantoin in many species like microorganisms, plants, and inverte-brates. Particularly in humans, the synthesis and excretion of uric acid are naturally balanced. When the uric acid concentration crosses 7 mg/dl, it results in conditions such as hyperuricemia and gout. Uricase is one of the potential sources for the reduction of uric acid in humans. Uricase is also widely used as a commercial diagnostic reagent in medical and clinical biochemistry to esti-mate the uric acid concentration in blood and other biological fluids. Computational approaches can be used for screening and investigation of uricase enzyme with desirable characteristics that can be employed in diverse industrial applications. Objectives: The present study deals with computational-based structural, functional, and phylogenetic analyses of uricase enzymes from various Bacillus species. Methods: Seventy uricase protein sequences from Bacillus species were selected for multiple sequence alignment, phylogenetic analysis, motif assessment, domain architecture examination, understanding of basic physicochemical properties and in silico identification of the composition of amino acids in uricase. Further, structural (secondary and tertiary structure prediction), and functional (CYS_REC, MOTIF scan, CD-search, STRING, SOSUI, and PeptideCutter) analyses of uric-ase were performed. Results: Bacillus simplex (WP_063232385.1) was chosen as the representative species of the Bacillus genera. The three-dimensional (3D) structure of B. simplex uricase was predicted and validated using QMEAN, RAMPAGE, ERRAT, Verify 3D and PROQ servers. The analysis revealed that the tertiary structure of the selected uricase has good quality and acceptability. Conclusion: Computational analysis of uricase from various Bacillus sources revealed that all the selected Bacillus uricases are active within acidic to a neutral environment, and thermally stable with a molecular weight ranging from 35.59-59.85kDa. The secondary structure analysis showed that all uricases are rich in alpha-helices and sheets. The CDD tool identified two conserved do-mains, one of which belongs to OHCU decarboxylase and another belongs to Uricase superfamily. The quality estimation of 3D modeled protein gave a high overall quality factor score of 94.64. Al-so, all Bacillus species of uricase enzyme and their corresponding genes showed a strong correlation from the phylogenetic comparison of the selected taxa. The present detailed computational investigation on the uricase protein could help in screening a suitable uricase producing microbe with desirable characteristics for industrial application. © 2021 Bentham Science Publishers.Item Enhanced protein structural class prediction using effective feature modeling and ensemble of classifiers(Institute of Electrical and Electronics Engineers Inc., 2021) Bankapur, S.; Patil, N.Protein Secondary Structural Class (PSSC) information is important in investigating further challenges of protein sequences like protein fold recognition, protein tertiary structure prediction, and analysis of protein functions for drug discovery. Identification of PSSC using biological methods is time-consuming and cost-intensive. Several computational models have been developed to predict the structural class; however, they lack in generalization of the model. Hence, predicting PSSC based on protein sequences is still proving to be an uphill task. In this article, we proposed an effective, novel and generalized prediction model consisting of a feature modeling and an ensemble of classifiers. The proposed feature modeling extracts discriminating information (features) by leveraging three techniques: (i) Embedding – features are extracted on the basis of spatial residue arrangements of the sequences using word embedding approaches; (ii) SkipXGram Bi-gram – various sets of skipped bi-gram features are extracted from the sequences; and (iii) General Statistical (GS) based features are extracted which covers the global information of structural sequences. The combined effective sets of features are trained and classified using an ensemble of three classifiers: Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting Machines (GBM). The proposed model when assessed on five benchmark datasets (high and low sequence similarity), viz. z277, z498, 25PDB, 1189, and FC699, reported an overall accuracy of 93.55, 97.58, 81.82, 81.11, and 93.93 percent respectively. The proposed model is further validated on a large-scale updated low similarity (?25%) dataset, where it achieved an overall accuracy of 81.11 percent. The proposed generalized model is robust and consistently outperformed several state-of-the-art models on all the five benchmark datasets. © 2021 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.Item Study of Correlated Motions to Detect the Conformational Transitions of the Intrinsically Disordered Sheep Prion Peptide(American Chemical Society, 2024) Chakraborty, D.; Singh, O.; Parameswaran, D.Intrinsically disordered proteins (IDPs) are known for their random structural changes throughout their sequence based on the environment. The mechanism underlying these structural changes is difficult to explain. All biological processes are known to follow the direction through which they act. A study of the correlated motion can help to understand the direction of the change. Herein, we introduced the multivariate statistical analysis (MSA) technique to study the correlated motion of the peptide. The correlated motion of the sheep prion peptide was studied with the change in the temperature and solvent. These techniques helped to identify the contributing residual motions that helped to form the different secondary structures of the protein and also the triggering factors that drive these sorts of residual motions. The structural details match the experimentally reported data. It was found that the direction of the change of the secondary structure for this peptide shifted from the C-terminal to the N-terminal with an increase in the temperature. It was found that the involvement of the hydrophobic residues present at the C-terminal and the middle residues (residues 12-17) is responsible for forming a β-sheet at the normal temperature. Hydration water was found to play an important role in this change. Insights gained from this study can be used to design strategies for desirable structural changes in the IDPs. © 2024 American Chemical Society.