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Yoshihiro Honda

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#graph neural networks Open access Sep 2026

Molecular Solubility, Hydration Shells, and Inverse Spectral Tomography via 3D Lone-Pair Fiedler Vector Optimization

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 · 0 citations
#graph neural networks Open access Sep 2026

Molecular Solubility, Hydration Shells, and Inverse Spectral Tomography via 3D Lone-Pair Fiedler Vector Optimization

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 · 0 citations
#protein folding Open access Sep 2026

Graph-Spectral Protein Folding: Simulating Peptide Self-Assembly via Laplacian Fiedler Vector Optimization

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 · 0 citations
#protein folding Open access Sep 2026

Graph-Spectral Protein Folding: Simulating Peptide Self-Assembly via Laplacian Fiedler Vector Optimization

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 · 0 citations

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