A simple and novel method is proposed here for the first time to determine pK(a) values of chromogenic hydrophobic pH sensitive probes directly in nanospheres. pK(a) values can be obtained by measuring the pH response of the nanospheres (containing the probes and ion exchanger) followed by measuring the pH and Na(+) responses of the nanospheres (containing solvatochromic dyes and ion exchanger). The pK(a) values of four chromoionophores were successfully determined. This method is in principle also applicable to characterize colorimetric probes in other water immiscible nanomaterials.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1021/acs.analchem.5b04671 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Comprehensive Chemical Analysis of the Methyl 3-Nitrogen-2,3-Dideoxysaccharides Derivatives with d--Configuration: Synthesis, Reactivity of HIV-1 Reverse Transcriptase Inhibitors.
J Phys Chem B
January 2025
Intermolecular Interaction Laboratory, Department of Bioinorganic Chemistry, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland.
This study extends previous research, particularly focusing on patented scientific objects No. ID: PL 240 353 B1, investigating the physicochemical properties of the methyl 3-azido- and 3-amino-2,3-dideoxysaccharides with a nucleoside scaffold similar to 3'-azidothymidine (AZT). The study utilizes multiwavelength spectrophotometric and potentiometric methods to evaluate the ionization of the saccharide units in aqueous solutions.
View Article and Find Full Text PDFProtonation effects in protein-ligand complexes - a case study of endothiapepsin and pepstatin A with computational and experimental methods.
ChemMedChem
January 2025
Crystals First GmbH, -, GERMANY.
Protonation states serve as an essential molecular recognition motif for biological processes. Their correct consideration is key to successful drug design campaigns, since chemoinformatic tools usually deal with default protonation states of ligands and proteins and miss atypical protonation states. The protonation pattern for the Endothiapepsin/PepstatinA (EP/pepA) complex is investigated using different dry lab and wet lab techniques.
View Article and Find Full Text PDFExploring acidity-dependent PCET pathways in imino-bipyridyl cobalt complexes.
Dalton Trans
January 2025
Department of Chemistry, Gwangju Institute of Science and Technology, Gwangju 61005, Republic of Korea.
The electrochemical proton reactivity of transition metal complexes has received intensive attention in catalyst research. The proton-coupled electron transfer (PCET) process, influenced by the coordination geometry, determines the catalytic reaction mechanisms. Additionally, the p value of a proton source, as an external factor, plays a crucial role in regulating the proton transfer step.
View Article and Find Full Text PDFFilling the Gap in and Evaluation for Saturated Fluorine-Containing Derivatives With Machine Learning.
J Comput Chem
January 2025
Department of Organic Chemistry, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.
Lipophilicity and acidity/basicity are fundamental physical properties that profoundly affect the compound's pharmacological activity, bioavailability, metabolism, and toxicity. Predicting lipophilicity, measured by (1-octanol-water distribution coefficient logarithm), and acidity/basicity, measured by (negative of acid ionization constant logarithm), is essential for early drug discovery success. However, the limited availability of experimental data and poor accuracy of standard and assessment methods for saturated fluorine-containing derivatives pose a significant challenge to achieving satisfactory results for this compound class.
View Article and Find Full Text PDFInterpretable Deep-Learning p Prediction for Small Molecule Drugs via Atomic Sensitivity Analysis.
J Chem Inf Model
January 2025
Department of Chemical and Physical Biology, Vanderbilt University, Nashville, Tennessee 37232, United States.
Machine learning (ML) models now play a crucial role in predicting properties essential to drug development, such as a drug's logscale acid-dissociation constant (p). Despite recent architectural advances, these models often generalize poorly to novel compounds due to a scarcity of ground-truth data. Further, these models lack interpretability.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!