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SDRL: a sequence-dependent protein side-chain rotamer library.

Mohammad Taghizadeh1, Bahram Goliaei, Armin Madadkar-Sobhani

  • 1Laboratory of Biophysics and Molecular Biology, Institute of Biochemistry and Biophysics (IBB), Tehran University, P.O. Box 13145-1384, Tehran, Iran. goliaei@ibb.ut.ac.ir.

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This study introduces a novel sequence-dependent rotamer library (SDRL) for proteins, accounting for triplet sequence context. This new library improves the accuracy of predicting side-chain conformations in structural bioinformatics.

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Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Protein structure analysis

Background:

  • Protein side-chain rotamer libraries (RLs) are crucial in structural bioinformatics.
  • Existing RLs are categorized as backbone-independent, secondary-structure-dependent, or backbone-dependent.
  • Previous RLs overlooked the impact of sequence specificity on side-chain conformational preferences.

Purpose of the Study:

  • To develop a new class of rotamer libraries that incorporate sequence specificity.
  • To create a sequence-dependent rotamer library (SDRL) considering triplet sequence context.
  • To enhance the accuracy of predicting protein side-chain conformations.

Main Methods:

  • Considered 7200 unique triplet sequences for 18 natural amino acids as central residues.
  • Analyzed 2,364,541 instances from 11,546 PDB entries.
  • Developed a sequence-dependent rotamer library (SDRL) based on triplet sequence context.

Main Results:

  • Identified varying degrees of sequence dependency for different amino acid side-chain conformations.
  • Leu and Val showed minimal impact from adjacent residues.
  • Cys, Ile, Trp, His, Asp, Met, Glu, Gln, Arg, and Lys were highly dependent on adjacent residues.
  • Other residue types exhibited moderate dependence.

Conclusions:

  • The developed SDRL provides a more accurate representation of side-chain conformational preferences.
  • SDRLs can improve the performance of side-chain repacking algorithms in structural bioinformatics.
  • Sequence context is a significant factor in determining protein side-chain conformations.