Results 21 to 30 of about 4,458,384 (285)
, 2022 This document contains the supporting information published together with the article "Quantum Chemical Roots of Machine-Learning Molecular Similarity Descriptors" (J. Chem. Theory Comput., 2022, 18, 6670)
Gugler, Stefan, Reiher, Markus
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The Qsar Study of Azole Derivatives Using Molecular Descriptors for Quantum Molecular States.
Current health sciences journal, 2016 Azoles are the main antifungal agents currently used in systemic therapy and local mycoses. The class of azole derivatives has been studied using fingerprint descriptors based on electronegativity of the occupied molecular orbitals (OMO) and unoccupied molecular orbitals (UMO).
Amzoiu, M.O., Cristea, Oana Mariana
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International Journal of Electrochemical Science, 2011 QSAR studies on the inhibition corrosion efficiencies of twenty three organic compounds on steel surface in hydrochloric acid solutions using several physicochemical descriptors and investigation of the adsorption of these compounds on the steel surface ...
K.F. Khaled, N.S. Abdel-Shafi
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Molecular descriptors for corrosion inhibitors
, 2023 Molecular descriptors for 37 selected corrosion inhibitors. These descriptors cover quantum, topological, structural, bioavailability/pharmacokinetic (ADME), and physicochemical aspects, offering a multidimensional insight into the characteristics of the
BOUZIANI IDRISSI, M (via Mendeley Data) +1 more
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Molecular descriptors for corrosion ihibitors
, 2023 Molecular descriptors for 37 selected corrosion inhibitors. These descriptors cover quantum, topological, structural, bioavailability/pharmacokinetic (ADME), and physicochemical aspects, offering a multidimensional insight into the characteristics of the
BOUZIANI IDRISSI, M (via Mendeley Data)
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GUIDEMOL: a Python graphical user interface for molecular descriptors based on RDKit [PDF]
, 2023 GUIDEMOL is a Python computer program based on the RDKit software to process molecular structures and calculate molecular descriptors with a graphical user interface using the tkinter package.
Joao, Aires-de-Sousa
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Combining machine learning and quantum mechanics yields more
Journal of Computational Chemistry, 2021 AbstractMolecular interaction fields (MIFs), describing molecules in terms of their ability to interact with any chemical entity, are one of the most established and versatile concepts in drug discovery. Improvement of this molecular description is highly desirable for in silico drug discovery and medicinal chemistry applications.
Sara Tortorella +6 more
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Journal of Saudi Chemical Society, 2016 A quantitative structure–activity relationship (QSAR) was performed to analyze antimalarial activities of 68 urea derivatives using multiple linear regressions (MLR).
Abolghasem Beheshti +3 more
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Química Nova, 2010 In this work we show that structure-activity relationship studies are of great importance in modern chemistry and biochemistry. In order to obtain a significant correlation, it is crucial that appropriate descriptors be employed.
Agnaldo Arroio +2 more
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Quantum-Mechanical QSAR/QSPR Descriptors from Momentum-Space Wave Functions
, 2019 It is shown that quantum-mechanical descriptors obtained as parameters from the one-dimensional radial distribution function of electron momentum can be used to predict molecular activities or properties to a precision that compares favorably with the ...
Matthew J. Sykes (157946) +1 more
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