ArticleJournal of molecular modeling2012
Theoretical prediction of the binding free energy for mutants of replication protein A.
Article in Journal of molecular modeling, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Accuracy Comparison of Generalized Born Models in the Calculation of Electrostatic Binding Free Energies.Journal of chemical theory and computation · 2018Article
- Effect of mutation at the interface of Trp-repressor dimeric protein: a steered molecular dynamics simulation.European biophysics journal : EBJ · 2013Article
- Locating a plausible binding site for an open-channel blocker, GlyH-101, in the pore of the cystic fibrosis transmembrane conductance regulator.Molecular pharmacology · 2012Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The replication protein A (RPA) is a heterotrimeric (70, 32, and 14 kDa subunits), single stranded DNA (ssDNA) binding protein required for pivotal functions in the cell metabolism, such as chromosomal replication, prevention of hairpin formation, DNA repair and recombination, and signaling after DNA damage. Studies based on deletions and mutations have identified the high affinity ssDNA binding domains in the 70 kDa subunit of RPA, regions A and B. Individually, the domain A and B have a low affinity for ssDNA, while tandems composed of AA, AB, BB, and BA sequences bind the ssDNA with moderate to high affinity. Single and double point mutations on polar residues in the binding domains leads to a reduction in affinity of RPA for ssDNA, in particular when two hydrophilic residues are involved. In view of these results, we performed a study based on molecular dynamics simulation aimed to reproduce the experimental change in binding free energy, ΔΔG, of RPA70 mutants to further elucidate the nature of the protein-ssDNA interaction. The MM-PB(GB)SA methods implemented in Amber10 and the code FoldX were used to estimate the binding free energy. The theoretical and experimental ΔΔG values correlate better when the results are obtained by MM-PBSA calculated on individual trajectories for each mutant. In these conditions, the correlation coefficient between experimental and theoretical ΔΔG reaches a value of 0.95 despite the overestimation of the energy change by one order of magnitude. The decomposition of the MM-GBSA energy per residue allows us to correlate the change of the affinity with the residue polarity and energy contribution to the binding. The method revealed reliable predictions of the change in the affinity in function of mutations, and can be used to identify new mutants with distinct binding properties.
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