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Modeling Carbon Basicity.

Robert Fraczkiewicz1, Marvin Waldman1

  • 1Life Sciences, Simulations Plus, Inc., 42505 10th Street West, Lancaster, CA, 93534, USA.

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|March 20, 2025
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Summary
This summary is machine-generated.

This study introduces predictive models for calculating the aqueous ionization constants (pKa) of protonatable carbons in aromatic rings, a key factor in medicinal chemistry. These models identify basic carbons and their pKa values, enhancing chemical predictions.

Keywords:
carbon basicityionization constantmachine learningpKaprediction

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Area of Science:

  • Computational Chemistry
  • Medicinal Chemistry
  • Physical Organic Chemistry

Background:

  • Aromatic carbons can act as bases, accepting protons in aqueous solutions.
  • This basicity of carbon atoms is recognized in general chemistry but underutilized in medicinal chemistry.
  • Understanding carbon basicity is crucial for predicting the ionization behavior of organic molecules.

Purpose of the Study:

  • To develop predictive models for the aqueous ionization constants (pKa) of protonatable carbons in aromatic rings.
  • To identify the most basic carbon site within a given aromatic ring.
  • To calculate the microscopic pKa value associated with carbon protonation.

Main Methods:

  • Development of two distinct predictive models.
  • Model 1: Identifies the most basic carbon atom in an aromatic ring.
  • Model 2: Calculates the microscopic pKa value for the identified basic carbon.
  • Integration of these models into a comprehensive S+pKa prediction system.

Main Results:

  • Successful development of predictive models for carbon pKa in aromatic systems.
  • The models accurately identify basic carbon sites and quantify their protonation propensity.
  • The models are integrated into a global prediction tool considering all ionizable groups.

Conclusions:

  • The developed models provide valuable tools for predicting carbon basicity in aromatic compounds.
  • This work enhances the understanding and prediction of ionization constants, particularly for underappreciated carbon sites.
  • The integration into the S+pKa model offers a more complete assessment of molecular ionization.