In silico analysis of interaction pattern switching in ligand⋯receptor binding in Golgi α-mannosidase II induced by the protonated states of inhibitors

2017 ◽  
Vol 19 (19) ◽  
pp. 12527-12537 ◽  
Author(s):  
V. Sladek ◽  
J. Kóňa ◽  
H. Tokiwa
Keyword(s):  
Receptor Binding ◽  
In Silico ◽  
Active Sites ◽  
Biological Activities ◽  
In Silico Analysis ◽  
Interaction Pattern ◽  
Binding Modes ◽  
Silico Analysis

Different binding modes for charge-neutral and protonated inhibitor forms in Golgi α-mannosidase II active sites may influence their biological activities.

scholarly journals Prediction of Bioactive Peptides from Chlorella sorokiniana Proteins Using Proteomic Techniques in Combination with Bioinformatics Analyses

2019 ◽  
Vol 20 (7) ◽  
pp. 1786 ◽  
Author(s):  
Lhumen A. Tejano ◽  
Jose P. Peralta ◽  
Encarnacion Emilia S. Yap ◽  
Fenny Crista A. Panjaitan ◽  
Yu-Wei Chang
Keyword(s):  
In Silico ◽  
Bioactive Peptides ◽  
Biological Activities ◽  
Polyacrylamide Gel Electrophoresis ◽  
Sodium Dodecyl ◽  
In Silico Analysis ◽  
Chlorella Sorokiniana ◽  
Molecular Characteristics ◽  
Sds Page ◽  
Silico Analysis

Chlorella is one of the most nutritionally important microalgae with high protein content and can be a good source of potential bioactive peptides. In the current study, isolated proteins from Chlorella sorokiniana were subjected to in silico analysis to predict potential peptides with biological activities. Molecular characteristics of proteins were analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and proteomics techniques. A total of eight proteins were identified by proteomics techniques from 10 protein bands of the SDS-PAGE. The predictive result by BIOPEP’s profile of bioactive peptides tools suggested that proteins of C. sorokiniana have the highest number of dipeptidyl peptidase-IV (DPP IV) inhibitors, with high occurrence of other bioactive peptides such as angiotensin-I converting enzyme (ACE) inhibitor, glucose uptake stimulant, antioxidant, regulating, anti-amnestic and antithrombotic peptides. In silico analysis of enzymatic hydrolysis revealed that pepsin (pH > 2), bromelain and papain were proteases that can release relatively larger quantity of bioactive peptides. In addition, combinations of different enzymes in hydrolysis were observed to dispense higher numbers of bioactive peptides from proteins compared to using individual proteases. Results suggest the potential of protein isolated from C. sorokiniana could be a source of high value products with pharmaceutical and nutraceutical application potential.

scholarly journals Potential Biological Activities of Peptides Generated during Casein Proteolysis by Curly Kale (Brassica oleracea L. var. sabellica L.) Leaf Extract: An In Silico Preliminary Study

Foods ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 2877
Author(s):  
Magdalena Polak-Berecka ◽  
Magdalena Michalak-Tomczyk ◽  
Katarzyna Skrzypczak ◽  
Katarzyna Michalak ◽  
Kamila Rachwał ◽  
...  
Keyword(s):  
In Silico ◽  
Leaf Extract ◽  
Degradation Products ◽  
Biological Activities ◽  
Protein Profile ◽  
In Silico Analysis ◽  
Amino Acid Sequences ◽  
Casein Hydrolysis ◽  
Sds Page ◽  
Silico Analysis

This study is a brief report on the proteolytic activity of curly kale leaf extract against casein. Casein degradation products and an in silico analysis of the biological activity of the peptides obtained was performed. The efficiency of casein hydrolysis by curly kale extract was determined using SDS–PAGE and by peptide concentration determination. The pattern of the enzymatic activity was determined by MALDI–TOF MS analysis. The results showed that α- and β-casein were more resistant to curly kale extract hydrolysis, whereas κ-casein was absent in the protein profile after 8 h of proteolysis, and all casein fractions were completely hydrolyzed after 24 h of incubation. Based on sequence analysis, seven peptides were identified, with molecular mass in the range of 1151–3024 Da. All the peptides were products of β-casein hydrolysis. The identified amino acid sequences were analyzed in BIOPEP, MBPDB, and FeptideDB databases in order to detect the potential activities of the peptides. In silico analysis suggests that the β-casein-derived peptides possess sequences of peptides with ACE inhibitory, antioxidant, dipeptidyl peptidase IV inhibitory, antithrombotic, immunomodulatory, and antiamnesic bioactivity. Our study was first to evaluate the possibility of applying curly kale leaf extract to generate biopeptides through β-casein hydrolysis.

In-silico analysis of ligand-receptor binding patterns of α-MMC, TCS and MAP30 protein to LRP1 receptor

2020 ◽  
Vol 98 ◽  
pp. 107619
Author(s):  
Bin Liu ◽  
Zhonglin Zhang ◽  
Shiyong Lu ◽  
Qianchuan He ◽  
Nianhua Deng ◽  
...  
Keyword(s):  
Receptor Binding ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis

scholarly journals In Silico ADME, Metabolism Prediction and Hydrolysis Study of Melatonin Derivatives

2020 ◽  
Vol 13 ◽  
pp. 117864692097824
Author(s):  
Panyada Panyatip ◽  
Nadtanet Nunthaboot ◽  
Ploenthip Puthongking
Keyword(s):  
Oral Bioavailability ◽  
In Silico ◽  
Biological Activities ◽  
In Silico Analysis ◽  
Metabolism Rate ◽  
Amide Derivatives ◽  
Cns Drugs ◽  
Synthetic Derivatives ◽  
Silico Analysis ◽  
Pass Metabolism

Melatonin (MLT) is a well-known pineal hormone possessed with remarkable biological activities. However, its low oral bioavailability and high first-pass metabolism rate are important pharmacokinetics problems. Therefore, 5 MLT derivatives (1-5) were designed and synthesised in our group to solve these problems. In this work, in silico analysis of all synthetic derivatives for pharmacokinetic and drug-likeness parameters were predicted by SwissADME software. The results revealed that all derivatives (1-5) met the requirements for ideal oral bioavailability and CNS drugs. The molecular docking showed that the acetyl-MLT derivative (1) and the un-substitution at N1-position derivative 5 would be substrates of CYP1A2, while the lipophilic substituted N1-position derivatives 2-4 could not be metabolised by CYP1A2. Moreover, all N-amide derivatives (1-4) were hydrolysed and released less than 2.33% MLT after 4-hour incubation in 80% human plasma. It seemed that these derivatives preferred to behave like drugs rather than prodrugs of MLT. These findings confirmed that the addition of bulky groups at the N1-position of the MLT core could prolong the half-life, increase drug absorption and penetrate the blood brain barrier into the CNS.

scholarly journals IN-SILICO ANALYSIS

2016 ◽  
Vol 23 (02) ◽  
pp. 217-222
Author(s):  
Hammad Tufail Chaudhary ◽  
Shahida Hasnain
Keyword(s):  
Hydrogen Bonds ◽  
Active Site ◽  
In Silico ◽  
Active Sites ◽  
In Silico Analysis ◽  
Data Bank ◽  
Protein Data Bank Code ◽  
In Silico Study ◽  
Study Setting ◽  
Silico Analysis

ntroduction: Different pathogen reducing technologies are being implementedwhich includes S-303. CD-61 is important receptor for clotting. Pathogen reducing agents arebeing studied extensively to probe its effects. Objective: We conducted this study to reviewthe docking of S-303 at CD-61, to look into the effect of S-303 on function of platelets. StudyDesign: This was an observational study. Setting: In-silico study. Period: March 2015 toAugust 2015. Method: The study was carried out in-silico. PDB (Protein data bank) code ofTirofiban bound to CD-61 was 2vdm. CD-61 was docked with Tirofiban using online dockingtools i.e. Patchdock and Firedock. Then, S-303 and CD-61 were also docked. Best dockingposes to active sites of 2vdm were found. Interactions of ligands and CD-61 were obtained.Then comparison of Hydrogen Bonds, Hydrogen Bond Lengths, Hydrophobic bonds of 2vdmmolecule and best poses of docking results were done. Patchdock and Firdock results of bestposes were also analyzed using SPSS-16. Results: The Hydrogen bonds and Hydrogen bondlength and hydrophobic bonds of docking results were compared to 2vdm. 2 best poses wereobtained for docking of tirofiban to CD-61. No docking to active site was observed in Patchdockand firedock for S-303to CD-61. Conclusion: S-303 did not bind to the active site of CD-61. Wecan assume that S-303 doe

A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Gallbladder Carcinoma ◽  
In Silico ◽  
In Silico Analysis ◽  
Transcriptomic Profile ◽  
Silico Analysis

Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki
Keyword(s):  
Data Analysis ◽  
Virtual Screening ◽  
In Silico ◽  
Model Development ◽  
In Silico Analysis ◽  
Material Design ◽  
Efficient Solutions ◽  
Biological Data ◽  
Cost Efficient ◽  
Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

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