Collect. Czech. Chem. Commun.
2011, 76, 605-618
https://doi.org/10.1135/cccc2011033
Published online 2011-04-29 13:20:07
How to fragment a polypeptide? An ab initio computational study of pair interactions between amino acids and ligand-amino acids in proteins
Vojtěch Klusáka, Petr Dobešb, Jiří Černýc and Jiří Vondrášeka,*
a Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, v.v.i., Flemingovo nám. 2, 166 10 Prague, Czech Republic
b University Hospital Brno, Department of Internal Medicine – Hematooncology, Jihlavská 20, 625 00 Brno, Czech Republic
c Institute of Biotechnology, Academy of Sciences of the Czech Republic, v.v.i., Vídeňská 1083, 142 20 Prague 4, Czech Republic
Abstract
To determine reasonably which amino acid side chain contributes significantly to the stability of a protein or to the stability of a protein–ligand complex is not a straightforward task. We suggest a partial but systematic solution of the problem by a specific fragmentation of a protein chain into blocks of single amino acid side chains with their corresponding backbone part. For such systems of building blocks, we have calculated the stabilisation/interaction energies by means of correlated ab initio calculations. We have shown that a reasonable way to treat an amino-acid residue composing the protein is to break the homonuclear C–C bond between the Cα atom and the C(O) carboxyl carbon. The reference data obtained by the RI-MP2 method with the cc-pVDZ basis set were compared with RIDFT, RIDFT augmented by the dispersion term, SCC-DFTB-D and Hartree–Fock calculations. The results clearly show the failure of those methods lacking an appropriate treatment of the correlation energy. The DFT methods augmented by the empirical dispersion term on the other hand describe the interaction in good agreement with the reference method.
Keywords: Pair interactions; Amino acids; Protein stabilisation; Peptides; Correlated ab initio methods; DFT; Protein–ligand interaction; Ab initio calculations; Ligand design; Protein engineering; Protein models.
References: 40 live references.
