Results 11 to 20 of about 8,218,575 (213)

QSPR analysis of the drugs used to treat renal failure and its complications using degree and modified reverse degree indices [PDF]

Sci Rep
QSPR plays a crucial role in drug design by predicting the biological activity and the physico-chemical properties of compounds based on their molecular structures.
J. J. Jeni Godlin, S. Radha
semanticscholar   +3 more sources

Uses of degree-based topological indices in QSPR analysis of alkaloids with poisonous and healthful nature

Frontiers in Physics
In this article, a quantitative structure-property relationship is performed for the prediction of six physico-chemical properties of 16 alkaloid structures using three different types of degree-based topological indices.
Muhammad Waheed Rasheed, A. Mahboob, Iqra Hanif   +2 more
semanticscholar   +3 more sources

Prediction of the Extent of Blood–Brain Barrier Transport Using Machine Learning and Integration into the LeiCNS-PK3.0 Model [PDF]

Pharm Res
The unbound brain-to-plasma partition coefficient (Kp,uu,BBB) is an essential parameter for predicting central nervous system (CNS) drug disposition using physiologically-based pharmacokinetic (PBPK) modeling.
B. Gülave, Helle W. van den Maagdenberg, Luke van Boven, G. V. van Westen, E. D. de Lange, J. V. van Hasselt   +5 more
semanticscholar   +2 more sources

Predicting membrane protein localization by deep learning on structure and chemistry. [PDF]

Protein Sci
Abstract It has been known since at least the 1980's that the structure and chemistry of membranes and membrane proteins are matched. Exploiting this fact, a graph neural network model of proteins was trained on experimentally determined membrane protein structures to predict the native membrane environment of transmembrane domains from their structure.
Pokhrel B, Munley C, Pedraza M, Lyman E.
europepmc   +2 more sources

PHYSICO-CHEMICAL STUDIES OF A NEW COACERVATE SYSTEM.

, 1975
PHYSICO-CHEMICAL STUDIES OF A NEW COACERVATE ...
FUH-GUEY SHIEH. HWANG (7988900)
core   +6 more sources

Maxsmi: Maximizing molecular property prediction performance with confidence estimation using SMILES augmentation and deep learning

Artificial Intelligence in the Life Sciences, 2021
Accurate molecular property or activity prediction is one of the main goals in computer-aided drug design. Quantitative structure-activity relationship (QSAR) modeling and machine learning, more recently deep learning, have become an integral part of ...
Talia B. Kimber, Maxime Gagnebin, Andrea Volkamer   +2 more
doaj   +1 more source

PHYSICO-CHEMICAL CHARACTERISTICS OF ELECTROPHORETICALLY PURIFIED INFLUENZA VIRUS.

, 1953
PHYSICO-CHEMICAL CHARACTERISTICS OF ELECTROPHORETICALLY PURIFIED INFLUENZA ...
DONALD ZANE. SILVER (7978454)
core   +6 more sources

Group Contribution Revisited: The Enthalpy of Formation of Organic Compounds with “Chemical Accuracy” Part IV

Thermo, 2023
Group contribution (GC) methods to predict thermochemical properties are eminently important to process design. Following earlier work which presented a GC model in which, for the first time, chemical accuracy (1 kcal/mol or 4 kJ/mol) was accomplished ...
Robert J. Meier, Paul R. Rablen
doaj   +1 more source

Group Contribution Revisited: The Enthalpy of Formation of Organic Compounds with “Chemical Accuracy”

Engineering Proceedings, 2023
We established a group contribution (GC) parametrization for the heat of formation of organic molecules, but, and this is new, revealed chemical accuracy (1 kcal/mol). Compared to previous approaches which did not achieve this result, we succeeded by (i)
Robert J. Meier
doaj   +1 more source

Group Contribution Revisited: The Enthalpy of Formation of Organic Compounds with “Chemical Accuracy” Part III

AppliedChem, 2022
Group contribution (GC) methods to predict thermochemical properties are eminently important to process design. We report on a GC parametrization for the heat of formation of organic molecules exhibiting chemical accuracy, i.e., a maximum 1 kcal/mol (4.2
Robert J. Meier
doaj   +1 more source