Although protein-RNA interactions are crucial for many biological processes, predicting their binding free energies (ΔG) is a challenging task due to limited available experimental data and the complexity of these interactions. To address this issue,...
CONTEXT: The extensive conformational space of flexible molecules poses a significant challenge for predicting chemical reactivity through quantum chemical methods. For curcumin, whose keto-enol tautomerization is crucial to its biological activity a...
The majority of machine learning scoring functions used in drug discovery for predicting protein-ligand binding poses and affinities have been trained on the PDBBind data set. However, it is unclear whether these new scoring functions are actually an...
ConspectusEnhanced-sampling techniques employed in free-energy calculations overcome the limitations of brute-force molecular dynamics (MD) and are widely used to interrogate complex biological and chemical systems at atomic resolution. Depending on ...
Journal of chemical information and modeling
Dec 19, 2025
Electrochemical carbon dioxide reduction (CORR) using electrocatalysts has gained attention for its potential to convert atmospheric CO into value-added chemicals. Recently, machine learning (ML) has emerged as a promising approach for catalyst devel...
Journal of computer-aided molecular design
Dec 19, 2025
Hit-to-lead (H2L) optimization is a critical stage in small-molecule drug discovery, where efficient exploration of chemical space is required to identify promising lead compounds. Conventional H2L workflows rely on iterative synthesis and experiment...
Journal of chemical information and modeling
Dec 15, 2025
Chemical reactions in solution are central to biological function, synthetic chemistry, and materials design. Accurate modeling of these systems is essential for obtaining mechanistic insights but remains computationally demanding. Hybrid machine-lea...
Journal of chemical information and modeling
Dec 13, 2025
Molecular dynamics (MD) simulations are powerful tools for studying biomolecular systems, but they are fundamentally limited by accessible time scales, making the study of rare events such as protein folding or ligand unbinding computationally challe...
Journal of chemical information and modeling
Dec 3, 2025
In this work, we present an open-access quantum-chemistry database of more than 14,500 API-like molecules and their degradation products, all optimized at the M06-2/6-31G(d) compound model. The data set delivers a comprehensive suite of thermochemica...
Journal of computer-aided molecular design
Nov 25, 2025
The pKa, also known as the logarithmic dissociation constant, is a crucial parameter that defines the ionization level of a molecule when it is in solution. It is essential for several physicochemical properties, including lipophilicity, solubility, ...
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