Journal of chemical information and modeling
40298943
Machine learning interatomic potentials (MLIPs) have emerged as powerful tools for investigating atomistic systems with high accuracy and a relatively low computational cost. However, a common and unaddressed challenge with many current neural networ...
Journal of chemical information and modeling
40143756
This paper reviews the recent and most impactful advancements in the application of artificial neural networks in modeling the properties of ionic liquids. As salts that are liquid at temperatures below 100 °C, ionic liquids possess unique properties...
Journal of chemical theory and computation
40091187
Tautomerization plays a critical role in chemical and biological processes, influencing molecular stability, reactivity, biological activity, and ADME-Tox properties. Many drug-like molecules exist in multiple tautomeric states in aqueous solution, c...
Physical chemistry chemical physics : PCCP
40072875
The phosphorylation of residue T177 produces a significant effect on the conformational dynamics of CDK6. Gaussian accelerated molecular dynamics (GaMD) simulations followed by deep learning (DL) are applied to explore the molecular mechanism of the ...
Journal of chemical theory and computation
40273117
Accurately modeling enzyme reactions through direct machine learning/molecular mechanics simulations remains challenging in describing the electrostatic coupling between the QM and MM subsystems. In this work, we proposed a reweighting ME (mechanic e...
Journal of chemical information and modeling
40234235
Accurate solubility prediction in supercritical carbon dioxide (scCO) is crucial for optimizing experimental design by eliminating unnecessary and costly trials at an early stage, thereby streamlining the workflow. A comprehensive solubility database...
Journal of chemical information and modeling
40196990
Accurate prediction of protein-ligand binding affinities is crucial in drug discovery, particularly during hit-to-lead and lead optimization phases, however, limitations in ligand force fields continue to impact prediction accuracy. In this work, we ...
With the rise of small interfering RNA (siRNA) as a therapeutic tool, effective siRNA design is crucial. Current methods often emphasize sequence-related features, overlooking structural information. To address this, we introduce ENsiRNA, a multimoda...
Journal of chemical information and modeling
40183476
Hydrolysis is a fundamental family of chemical reactions where water facilitates the cleavage of bonds. The process is ubiquitous in biological and chemical systems, owing to water's remarkable versatility as a solvent. However, accurately predicting...
RNA is a remarkably versatile molecule that has been engineered for applications in therapeutics, diagnostics, and in vivo information-processing systems. However, the complex relationship between the sequence, structure, and function of RNA often ne...