scholarly journals Modeling with DFT and Chemical Descriptors Approach for the Development of Catalytic Alloys for PEMFCs

2019 ◽  
Author(s):  
Alejandro E. Pérez ◽  
Rafael Ribadeneira
Keyword(s):  
Chemical Descriptors

Reactivity of fullerenes. Quantum-chemical descriptors versus curvature

1995 ◽  
Vol 338 (1-3) ◽  
pp. 293-301 ◽  
Author(s):  
K. Choho ◽  
W. Langenaeker ◽  
G. Van De Woude ◽  
P. Geerlings
Keyword(s):  
Quantum Chemical ◽  
Quantum Chemical Descriptors ◽  
Chemical Descriptors

Structural, QSAR, machine learning and molecular docking studies of 5-thiophen-2-yl pyrazole derivatives as potent and selective cannabinoid-1 receptor antagonists

2021 ◽  
Author(s):  
Riad Hanachi ◽  
Ridha Ben Said ◽  
Hamza Allal ◽  
Seyfeddine Rahali ◽  
Mohammed A. M. Alkhalifah ◽  
...  
Keyword(s):  
Machine Learning ◽  
Biological Activity ◽  
Molecular Docking ◽  
Theoretical Analysis ◽  
Structural Study ◽  
Docking Studies ◽  
Pyrazole Derivatives ◽  
Molecular Docking Studies ◽  
Cannabinoid 1 Receptor ◽  
Chemical Descriptors

We performed a structural study followed by a theoretical analysis of the chemical descriptors and the biological activity of a series of 5-thiophen-2-yl pyrazole derivatives as potent and selective Cannabinoid-1...

New Chemical Descriptors Relevant for the Design of Biologically Active Peptides. A Multivariate Characterization of 87 Amino Acids

1998 ◽  
Vol 41 (14) ◽  
pp. 2481-2491 ◽  
Author(s):  
Maria Sandberg ◽  
Lennart Eriksson ◽  
Jörgen Jonsson ◽  
Michael Sjöström ◽  
Svante Wold
Keyword(s):  
Amino Acids ◽  
Biologically Active ◽  
Active Peptides ◽  
Biologically Active Peptides ◽  
Chemical Descriptors

scholarly journals A QUANTUM-CHEMICAL DESCRIPTORS OF CARBONIC ANHYDRASE CA(I) INHIBITION BY AROMATIC SULFONYL AMIDES

2020 ◽  
Vol 2 (29(56)) ◽  
pp. 27-30
Author(s):  
E.N. Krylov ◽  
L.V. Virzum ◽  
I.D. Kryukova
Keyword(s):  
Nitrogen Atom ◽  
Carbonic Anhydrase ◽  
Electrostatic Potential ◽  
Quantum Chemical ◽  
Molecular Electrostatic Potential ◽  
Quantum Chemical Descriptors ◽  
Carbonic Anhydrase Inhibition ◽  
Chemical Descriptors ◽  
Quantum Parameters

The quantum parameters of aromatic sulfonylamides are determined to describe their interaction with carbonic anhydrase at the theory level M06/6-311 ++G**(SMD). The molecular electrostatic potential on the nitrogen atom in sulfamides and Hirschfeld charge on this atom have been found to appear to be adequate and determinative descriptors of carbonic anhydrase inhibition.

Computational Intelligence Model of Orally Disintegrating Tablets: An Attempt to Explain Disintegration Process

2021 ◽  
Vol 11 (1) ◽  
pp. 24
Author(s):  
Jakub Szlęk ◽  
Adam Pacławski ◽  
Natalia Czub ◽  
Aleksander Mendyk
Keyword(s):  
Deep Learning ◽  
Computational Intelligence ◽  
Learning Model ◽  
Critical Parameters ◽  
Active Pharmaceutical Ingredients ◽  
Disintegration Process ◽  
Pharmaceutical Ingredients ◽  
Orally Disintegrating Tablets ◽  
Chemical Descriptors ◽  
Deep Learning Model

We obtained a curated database based on the database published elsewhere. Chemical descriptors were introduced as characteristics of active pharmaceutical ingredients (APIs). We used H2O AutoML platform in order to develop a Deep Learning model and SHAP method to explain its predictions. Obtained results were satisfactory with NRMSE of 8.1% and R2 of 0.84. Finally, we identified critical parameters affecting the process of disintegration of directly compressed ODTs.

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