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CPP: Fachverband Chemische Physik und Polymerphysik

CPP 44: 2D Materials

CPP 44.3: Vortrag

Freitag, 21. März 2025, 12:00–12:15, H34

Towards the Computational Design of Molecular Olfactory Receptors for Digital Odor Detection — •Li Chen¹, Leonardo Medrano Sandonas¹, Arezoo Dianat¹, Nina Tverdokhleb¹, Rafael Gutierrez¹, Alexander Croy², and Gianaurelio Cuniberti¹ — ¹Institute for Materials Science and Max Bergmann Center for Biomaterials, TUD Dresden University of Technology, 01062 Dresden, Germany — ²Institute of Physical Chemistry, Friedrich Schiller University Jena

We present the MORE-Q dataset using quantum-mechanical (QM) simulations for dimer systems composed of body odor volatilome (BOV) and olfactory receptors. The dataset contains abundant QM properties of diverse BOV-receptor systems, both in the gas phase and when deposited on a graphene surface. After analyzing the property space spanned by MORE-Q, we observed flexibility when searching for a dimer configuration with a desired set of electronic binding features. To gain insights into the complex interplay between these sensing properties, an ensemble learning method (XGBoost) was constructed for the fast evaluation of BOV adsorption behavior using only the dimer configurations properties. The results show a significant increase in model performance by adding multiple conformers to the training procedure, and SHAP analysis identifies the most relevant descriptors for predicting the binding features. Our work provides valuable insights into the the sensing mechanism of BOV molecules and paves the way for the computational design of receptors with targeted sensitivity and selectivity.

Keywords: Olfactorial receptor; BOV; XGBoost; SHAP; DFT