Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 3 de 3
Filter
Add more filters










Database
Language
Publication year range
1.
Comput Biol Chem ; 103: 107827, 2023 Apr.
Article in English | MEDLINE | ID: mdl-36805155

ABSTRACT

Computational designing of four different series (D-G) of thiazolidinone was done starting from different amines which was further condensed with various aldehydes. These underwent in silico molecular investigations for density functional theory (DFT), molecular docking, and absorption, distribution metabolism, excretion, and toxicity (ADMET) studies. The different electrochemical parameters of the compounds are predicted using quantum mechanical modeling approach with Gaussian. The docking software was used to dock the compounds against choosing PDB file for chickenpox, human immunodeficiency, hepatitis, and monkeypox virus as 1OSN, 1VZV, 6VLK, 1RTD, 3I7H, 3TYV, 4JU3, and 4QWO, respectively. The molecular interactions were visualized with discovery studio and maximum binding affinity was observed with D8 compounds against 4QWO (-13.383 kcal/mol) while for compound D5 against 1VZV which was -12.713 kcal/mol. Swiss ADME web tool was used to assess the drug-likeness of the designed compounds under consideration, and it is concluded that these molecules had a drug-like structure with almost zero violations.


Subject(s)
Chickenpox , Mpox (monkeypox) , Humans , Molecular Docking Simulation , Software , Hepatitis Viruses
2.
ChemistrySelect ; 7(36): e202201793, 2022 Sep 27.
Article in English | MEDLINE | ID: mdl-36249082

ABSTRACT

In silico studies in terms of density functional theory (DFT), molecular docking, and ADMET (absorption, distribution, metabolism, excretion and toxicity) were performed for 55 thiazolidinones compounds derived from different amines and aldehydes. DFT is a computational quantum mechanical modeling method used to predict the various properties of the compounds. Different parameters such as Electronegativity (x), Chemical Hardness (ŋ), Chemical Potential (µ), Ionization potential (IP), and Electron Affinity (EA), etc. were calculated by Koopmans theorem. The compounds were docked with Molecular Operating Environment (MOE) software using already reported PDB files of BChE, AChE, and α-glucosidase. To analyze the Spike Glycoprotein of SARS-Cov-2 and heterocyclic compounds, molecular interactions study was carried out between Spike Glycoprotein of SARS-Cov-2 (6VXX) and 55 synthetic heterocyclic compounds. It was performed by the utilization of PyRx Virtual Screening Tool and AutoDock Vina based virtual environment was used in PyRx. Maximum binding affinity was observed with compound A7 which was -8.7 kcal/mol and then with A5 which was -8.5 respectively. In the case of the AChE enzyme, B5 has a maximum docking score of -12.9027 kcal/mol while C7 depicted the maximum score for the BChE enzyme with a value of -8.6971 kcal/mol. The docking studies revealed that C6 compound has maximum binding capacity toward glucosidase (-14.8735 kcal/mol). ADMET properties of under consideration compounds were determined by Swiss online-based software which concluded that these molecules have a drug-like properties and having no violation.

3.
Environ Res ; 208: 112644, 2022 05 15.
Article in English | MEDLINE | ID: mdl-34979127

ABSTRACT

Surfactant stabilized Gold (Au) nanomaterials (NMs) have been documented extensively in recent years for numerous sensing applications in the academic literature. Despite the crucial role these surfactants play in the sensing applications, the comprehensive reviews that highlights the fundamentals associated with these assemblies and impact of these surfactants on the properties and sensing mechanisms are still quite scare. This review is an attempt in organizing the vast literature associated with this domain by providing critical insights into the fundamentals, preparation methodologies and sensing mechanisms of these surfactant stabilized Au NMs. For the simplification, the surfactants are divided into the typical and advanced surfactants and the Au NMs are classified into Au nanoparticles (NPs) and Au nanoclusters (NCs) depending upon the complexity in structure and size of the NMs respectively. The preparative methodologies are also elaborated for enhancing the understanding of the readers regarding such assemblies. The case studies regarding surfactant stabilized Au NMs were further divided into colorimetric sensors, surface plasmonic resonance (SPR) based sensors, luminescence-based sensors, and electrochemical/electrical sensors depending upon the property utilized by the sensor for the sensing of an analyte. Future perspectives are also discussed in detail for the researchers looking for further progress in that particular research domain.


Subject(s)
Metal Nanoparticles , Nanostructures , Colorimetry , Gold/chemistry , Metal Nanoparticles/chemistry , Nanostructures/chemistry , Surface-Active Agents
SELECTION OF CITATIONS
SEARCH DETAIL
...