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Conserved Binding Sites01:49

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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
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Long-Range Electrostatics in Serine Proteases: Machine Learning-Driven Reaction Sampling Yields Insights for Enzyme

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Computational enzyme design can be improved by understanding how distant charged residues affect enzyme activity. A new method reveals a negative charge significantly boosts catalytic efficiency, while a positive charge hinders it, offering insights for designing better biocatalysts.

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Area of Science:

  • Biochemistry and Molecular Biology
  • Computational Chemistry
  • Enzyme Engineering

Background:

  • Computational enzyme design aims to create novel enzymes but struggles to consistently achieve desired activity.
  • Natural enzymes utilize distant residues to optimize internal electrostatic fields for remarkable catalytic efficiency.
  • Current computational methods face limitations in isolating the electrostatic effects of charged residues.

Purpose of the Study:

  • To develop and apply a novel computational approach to isolate and quantify the influence of electrostatic fields on enzyme catalysis.
  • To investigate the specific contributions of charged residues, including those in the second-shell, to the catalytic efficiency of subtilisin.
  • To provide deeper insights into the role of electrostatic preorganization in enzyme evolution and function.

Main Methods:

  • Employed molecular modeling combined with AI-enhanced Quantum Mechanics/Molecular Mechanics (QM/MM) reaction sampling.
  • Applied the developed approach to a model serine protease, subtilisin.
  • Quantified the impact of specific charged residues on the activation energy barrier of the enzymatic reaction.

Main Results:

  • A negative charge located 8 Å from the catalytic site was found to be crucial for catalytic efficiency, reducing the activation barrier by over 2 kcal/mol.
  • A positive charge from a nearby residue was shown to oppose catalytic efficiency by increasing the activation barrier by 0.8 kcal/mol.
  • Demonstrated the significant, quantifiable impact of distant electrostatic interactions on enzyme performance.

Conclusions:

  • The study highlights the critical role of electrostatic preorganization, mediated by distant charged residues, in achieving high enzyme catalytic efficiency.
  • The developed computational approach effectively isolates electrostatic influences, offering a transferable method for studying enzyme evolution and engineering.
  • Findings suggest that targeted engineering of electrostatic fields holds significant potential for designing novel, highly efficient biocatalysts for industrial and clinical applications.