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Cooperativity, absolute interaction, and algebraic optimization.

Nidhi Kaihnsa1, Yue Ren2, Mohab Safey El Din3

  • 1Division of Applied Mathematics, Brown University, 182 George Street, Providence, RI, 02912, USA.

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|September 24, 2020
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Summary
This summary is machine-generated.

This study introduces a new cooperativity measure for molecular binding, identifying the minimum interactions needed. This method, using algebraic optimization, helps analyze complex binding behaviors like those in hemoglobin.

Keywords:
90C2392C40

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Area of Science:

  • Biophysics
  • Biochemistry
  • Computational Biology

Background:

  • Understanding molecular binding cooperativity is crucial for biological processes.
  • Existing methods may not fully capture the complexity of binding curves.
  • Hemoglobin's oxygen binding serves as a key model system for studying cooperativity.

Purpose of the Study:

  • To develop a novel measure of cooperativity based on minimal required molecular interactions.
  • To solve the associated algebraic optimization problem using computational tools.
  • To analyze and compare binding behaviors of various hemoglobins.

Main Methods:

  • Defined a cooperativity measure based on minimal interaction for titration behavior.
  • Formulated and solved an algebraic optimization problem using the SCIP solver.
  • Computed minimal interactions and molecules for several binding polynomials.

Main Results:

  • Successfully computed minimal interactions and molecules for hemoglobin binding polynomials.
  • Compared the novel minimal interaction measure with the maximal slope of the Hill plot.
  • Identified similarities and discrepancies between the new measure and traditional methods.

Conclusions:

  • The proposed measure quantifies cooperativity effectively by focusing on minimal interactions.
  • SCIP provides a viable computational approach for solving the underlying optimization problem.
  • This method offers new insights into the shapes of molecular binding curves, particularly for hemoglobin.