Predicting aqueous solubility (log S), co-crystallization, and solvation dynamics remains one of the formidable bottlenecks in drug discovery, formulation engineering, and physical chemistry. Conventional approaches rely either on computationally expensive quantum mechanical methods (DFT/MD) or black-box machine learni...
Yoshihiro Honda· Zenodo (CERN European Organi...· 0 citations
Predicting aqueous solubility (log S), co-crystallization, and solvation dynamics remains one of the formidable bottlenecks in drug discovery, formulation engineering, and physical chemistry. Conventional approaches rely either on computationally expensive quantum mechanical methods (DFT/MD) or black-box machine learni...
Yoshihiro Honda· Zenodo (CERN European Organi...· 0 citations
Protein folding is traditionally described as a trajectory over a complex energy landscape governed by empirical physical forcefields (electrostatics, van der Waals, torsional potentials, and implicit/explicit solvent interactions). However, evaluating all atomic force interactions demands massive computational power,...
Yoshihiro Honda· Zenodo (CERN European Organi...· 0 citations
Protein folding is traditionally described as a trajectory over a complex energy landscape governed by empirical physical forcefields (electrostatics, van der Waals, torsional potentials, and implicit/explicit solvent interactions). However, evaluating all atomic force interactions demands massive computational power,...
Yoshihiro Honda· Zenodo (CERN European Organi...· 0 citations
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