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Aqueous Solubility of Sodium and Chloride Salts of Glycine─"Uncommon" Common-Ion Effects of Self-Titrating Solids.
Mol Pharm
January 2025
Department of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, St. John's University, 8000 Utopia Parkway, Queens, New York 11439, United States.
Although glycine is the simplest of the amino acids, its solution and solid-state properties are far from straightforward. The aqueous solubility of glycine plays an important role in various applications, including nutrition, food products, biodegradable plastics, and drug development. There is evidence that glycine in subsaturated pH 3-8 solutions forms a dimer, as suggested by several techniques.
View Article and Find Full Text PDFEvaluation of Machine Learning/Molecular Mechanics End-State Corrections with Mechanical Embedding to Calculate Relative Protein-Ligand Binding Free Energies.
J Chem Theory Comput
January 2025
Exscientia, Schrödinger Building, Oxford Science Park, Oxford OX4 4GE, U.K.
The development of machine-learning (ML) potentials offers significant accuracy improvements compared to molecular mechanics (MM) because of the inclusion of quantum-mechanical effects in molecular interactions. However, ML simulations are several times more computationally demanding than MM simulations, so there is a trade-off between speed and accuracy. One possible compromise are hybrid machine learning/molecular mechanics (ML/MM) approaches with mechanical embedding that treat the intramolecular interactions of the ligand at the ML level and the protein-ligand interactions at the MM level.
View Article and Find Full Text PDFCurvature Dependence of Gravitational-Wave Tests of General Relativity.
Phys Rev Lett
December 2024
Center for Computational Astrophysics, Flatiron Institute, 162 5th Avenue, New York, New York 10010, USA.
High-energy extensions to general relativity modify the Einstein-Hilbert action with higher-order curvature corrections and theory-specific coupling constants. The order of these corrections imprints a universal curvature dependence on observations while the coupling constant controls the deviation strength. In this Letter, we leverage the theory-independent expectation that modifications to the action of a given order in spacetime curvature (Riemann tensor and contractions) lead to observational deviations that scale with the system length scale to a corresponding power.
View Article and Find Full Text PDFPM6-ML: The Synergy of Semiempirical Quantum Chemistry and Machine Learning Transformed into a Practical Computational Method.
J Chem Theory Comput
January 2025
Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, 160 00 Prague, Czech Republic.
Machine learning (ML) methods offer a promising route to the construction of universal molecular potentials with high accuracy and low computational cost. It is becoming evident that integrating physical principles into these models, or utilizing them in a Δ-ML scheme, significantly enhances their robustness and transferability. This paper introduces PM6-ML, a Δ-ML method that synergizes the semiempirical quantum-mechanical (SQM) method PM6 with a state-of-the-art ML potential applied as a universal correction.
View Article and Find Full Text PDFCorrection: The roles of 4f- and 5f-orbitals in bonding: a magnetochemical, crystal field, density functional theory, and multi-reference wavefunction study.
Dalton Trans
January 2025
Institute of Inorganic Chemistry, RWTH Aachen University, Aachen, Germany.
Correction for 'The roles of 4f- and 5f-orbitals in bonding: a magnetochemical, crystal field, density functional theory, and multi-reference wavefunction study' by W. W. Lukens , , 2016, , 11508-11521, https://doi.
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