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The anesthetic action of some polyhalogenated ethers-Monte Carlo method based QSAR study
Mlađan Golubović1, Milan Lazarević2, Dragan Zlatanović3
1Center for Anesthesiology and Reanimatology, Clinical Center Niš, Niš, Serbia.
Abstract:
Up to this date, there has been an ongoing debate about the mode of action of general anesthetics, which have postulated many biological sites as targets for their action. However, postoperative nausea and vomiting are common problems in which inhalational agents may have a role in their development. When a mode of action is unknown, QSAR modelling is essential in drug development. To investigate the aspects of their anesthetic, QSAR models based on the Monte Carlo method were developed for a set of polyhalogenated ethers. Until now, their anesthetic action has not been completely defined, although some hypotheses have been suggested. Therefore, a QSAR model should be developed on molecular fragments that contribute to anesthetic action. QSAR models were built on the basis of optimal molecular descriptors based on the SMILES notation and local graph invariants, whereas the Monte Carlo optimization method with three random splits into the training and test set was applied for model development. Different methods, including novel Index of ideality correlation, were applied for the determination of the robustness of the model and its predictive potential. The Monte Carlo optimization process was capable of being an efficient in silico tool for building up a robust model of good statistical quality. Molecular fragments which have both positive and negative influence on anesthetic action were determined. The presented study can be useful in the search for novel anesthetics.
Insights
Quantitative Structure-Activity Relationship (QSAR) models were developed to understand general anesthetic action. This research identified key molecular fragments influencing anesthetic effects, aiding the search for new anesthetic drugs.
Area of Science:
- Pharmacology
- Medicinal Chemistry
- Computational Chemistry
Background:
- The precise mechanism of action for general anesthetics remains debated, with multiple biological targets proposed.
- Postoperative nausea and vomiting are frequent complications potentially linked to inhalational anesthetic agents.
Purpose of the Study:
- To develop Quantitative Structure-Activity Relationship (QSAR) models for polyhalogenated ethers to elucidate their anesthetic properties.
- To identify specific molecular fragments contributing to anesthetic action, given the incomplete understanding of their mechanism.
Main Methods:
- QSAR models were constructed using optimal molecular descriptors derived from SMILES notation and local graph invariants.
- The Monte Carlo optimization method with random training/test set splits was employed for model development.
- Model robustness and predictive potential were assessed using various statistical methods, including the Index of ideality correlation.
Main Results:
- A robust QSAR model with good statistical quality was successfully developed using in silico methods.
- Specific molecular fragments were identified as having both positive and negative influences on anesthetic activity.
- The Monte Carlo optimization proved effective for building reliable predictive models.
Conclusions:
- The study provides valuable insights into the structure-activity relationships of general anesthetics.
- The identified molecular fragments can guide the design and discovery of novel anesthetic agents.
- QSAR modeling serves as an essential tool in drug development when mechanisms of action are not fully understood.
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