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Monte carlo simulations of proteins at constant pH with generalized born solvent, flexible sidechains, and an effective dielectric boundary
- Source :
- Journal of Computational Chemistry, Journal of Computational Chemistry, Wiley, 2013, 34 (31), pp.2742-2756. ⟨10.1002/jcc.23450⟩
- Publication Year :
- 2013
- Publisher :
- Wiley, 2013.
-
Abstract
- International audience; Titratable residues determine the acid/base behavior of proteins, strongly influencing their function; in addition, proton binding is a valuable reporter on electrostatic interactions. We describe a method for pK(a) calculations, using constant-pH Monte Carlo (MC) simulations to explore the space of sidechain conformations and protonation states, with an efficient and accurate generalized Born model (GB) for the solvent effects. To overcome the many-body dependency of the GB model, we use a "Native Environment" approximation, whose accuracy is shown to be good. It allows the precalculation and storage of interactions between all sidechain pairs, a strategy borrowed from computational protein design, which makes the MC simulations themselves very fast. The method is tested for 12 proteins and 167 titratable sidechains. It gives an rms error of 1.1 pH units, similar to the trivial "Null" model. The only adjustable parameter is the protein dielectric constant. The best accuracy is achieved for values between 4 and 8, a range that is physically plausible for a protein interior. For sidechains with large pKa shifts, ≥2, the rms error is 1.6, compared to 2.5 with the Null model and 1.5 with the empirical PROPKA method.
- Subjects :
- Proton binding
Protein Conformation
Chemistry
Protein design
Monte Carlo method
Proteins
Boundary (topology)
Thermodynamics
General Chemistry
Hydrogen-Ion Concentration
Electrostatics
Computational Mathematics
Computational chemistry
Computer Simulation
[SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology
Solvent effects
Constant (mathematics)
Monte Carlo Method
Root-mean-square deviation
Subjects
Details
- ISSN :
- 01928651 and 1096987X
- Volume :
- 34
- Database :
- OpenAIRE
- Journal :
- Journal of Computational Chemistry
- Accession number :
- edsair.doi.dedup.....d5cd070b6d08df1549f889fdb348ec7d
- Full Text :
- https://doi.org/10.1002/jcc.23450