es1c02960_si_001.pdf (1 MB)
Download fileComprehensive Interrogation on Acetylcholinesterase Inhibition by Ionic Liquids Using Machine Learning and Molecular Modeling
journal contribution
posted on 12.10.2021, 16:07 authored by Jiachen Yan, Xiliang Yan, Song Hu, Hao Zhu, Bing YanQuantitative structure–activity
relationship (QSAR) modeling
can be used to predict the toxicity of ionic liquids (ILs), but most
QSAR models have been constructed by arbitrarily selecting one machine
learning method and ignored the overall interactions between ILs and
biological systems, such as proteins. In order to obtain more reliable
and interpretable QSAR models and reveal the related molecular mechanism,
we performed a systematic analysis of acetylcholinesterase (AChE)
inhibition by 153 ILs using machine learning and molecular modeling.
Our results showed that more reliable and stable QSAR models (R2 > 0.85 for both cross-validation and external
validation) were obtained by combining the results from multiple machine
learning approaches. In addition, molecular docking results revealed
that the cations and organic anions of ILs bound to specific amino
acid residues of AChE through noncovalent interactions such as π
interactions and hydrogen bonds. The calculation results of binding
free energy showed that an electrostatic interaction (ΔEele < −285 kJ/mol) was the main driving
force for the binding of ILs to AChE. The overall findings from this
investigation demonstrate that a systematic approach is much more
convincing. Future research in this direction will help design the
next generation of biosafe ILs.
History
Usage metrics
Read the peer-reviewed publication
Categories
Keywords
− 285 kjmain driving forcerelated molecular mechanismele </ sub2 </ supinterpretable qsar modelsr </qsar modelse </>< sup>< subπ interactionssystematic approachsystematic analysisoverall interactionsoverall findingsorganic anionsnoncovalent interactionsnext generationmolecular modelingionic liquidsinvestigation demonstratehydrogen bondshelp designfuture researchelectrostatic interactioncomprehensive interrogationbiological systems