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Artificial intelligence deciphers codes for color and odor perceptions based on large-scale chemoinformatic data.

Xiayin Zhang1, Kai Zhang1,2, Duoru Lin1

  • 1State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Xian Lie South Road 54#, Guangzhou 510060, China.

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|February 27, 2020
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Summary
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Artificial intelligence accurately predicts molecular color and odor using physicochemical features. This reveals a significant link between how molecules are perceived visually and olfactorily.

Keywords:
color perceptiondeep belief networkodor perceptionphysicochemical featuresrandom forest

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Area of Science:

  • Computational chemistry
  • Cheminformatics
  • Artificial intelligence

Background:

  • Color vision is crucial for organism-environment interaction, but its physicochemical basis and integration with other senses like odor remain unclear.
  • Understanding the molecular underpinnings of sensory perception is essential for biological and chemical sciences.

Purpose of the Study:

  • To develop an artificial intelligence (AI) platform for predicting molecular color and odor.
  • To investigate the physicochemical features that determine color and odor perception.
  • To explore the relationship between color and odor coding in molecules.

Main Methods:

  • Developed an AI platform utilizing random forest and deep belief network algorithms.
  • Trained algorithms on large datasets of physicochemical features for 1,267 color-related and 598 odor-related molecules.
  • Identified key physicochemical descriptors sufficient for accurate color (24 features) and odor (39 features) prediction.

Main Results:

  • Achieved high predictive accuracies for color (up to 100%) and odor (up to 94.75%) using AI models.
  • Demonstrated that a limited set of physicochemical features can accurately predict color and odor.
  • Predicted a positive correlation between molecular color-coding and odor-coding properties.

Conclusions:

  • AI models accurately predict the color and odor of diverse molecules based on their physicochemical properties.
  • Findings enhance understanding of the molecular basis of color vision and sensory integration.
  • Revealed a significant interrelationship between color and odor perceptions at the molecular level.