title: A self-consistent, microenvironment modulated screened coulomb potential approximation to calculate pH-dependent electrostatic effects in proteins.
abstract: An improved approach is presented for calculating pH-dependent electrostatic effects in proteins using sigmoidally screened Coulomb potentials (SCP). It is hypothesized that a key determinant of seemingly aberrant behavior in pKa shifts is due to the properties of the unique microenvironment around each residue. To help demonstrate this proposal, an approach is developed to characterize the microenvironments using the local hydrophobicity/hydrophilicity around each residue of the protein. The quantitative characterization of the microenvironments shows that the protein is a complex mosaic of differing dielectric regions that provides a physical basis for modifying the dielectric screening functions: in more hydrophobic microenvironments the screening decreases whereas the converse applies to more hydrophilic regions. The approach was applied to seven proteins providing more than 100 measured pKa values and yielded a root mean square deviation of 0.5 between calculated and experimental values. The incorporation of the local hydrophobicity characteristics into the algorithm allowed the resolution of some of the more intractable problems in the calculation of pKa. Thus, the divergent shifts of the pKa of Glu-35 and Asp-66 in hen egg white lysozyme, which are both about 90% buried, was correctly predicted. Mechanistically, the divergence occurs because Glu-35 is in a hydrophobic microenvironment, while Asp-66 is in a hydrophilic microenvironment. Furthermore, because the calculation of the microenvironmental effects takes very little CPU time, the computational speed of the SCP formulation is conserved. Finally, results from different crystal structures of a given protein were compared, and it is shown that the reliability of the calculated pKa values is sufficient to allow identification of conformations that may be more relevant for the solution structure.
authors.affiliation: Department of Physiology and Biophysics, Mount Sinai School of Medicine, CUNY, New York, New York 10029, USA. mehler@inka.mssm.edu
authors.forename: E L
authors.initials: EL
authors.lastname: Mehler
authors.forename: F
authors.initials: F
authors.lastname: Guarnieri
mesh_terms: D000465:Algorithms; D000818:Animals; D007611:Aprotinin / Q000737:chemistry; D001224:Aspartic Acid / Q000737:chemistry; D064026:Calbindins; D003198:Computer Simulation; D018698:Glutamic Acid / Q000737:chemistry; D016333:HIV Protease / Q000737:chemistry; D006863:Hydrogen-Ion Concentration; D009113:Muramidase / Q000737:chemistry; D009419:Nerve Tissue Proteins / Q000737:chemistry; D010059:Ovomucin / Q000737:chemistry; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012260:Ribonucleases / Q000737:chemistry; D064030:S100 Calcium Binding Protein G / Q000737:chemistry; D055672:Static Electricity
chemical_list: D064026:Calbindins; C029152:G-substrate; D009419:Nerve Tissue Proteins; D011506:Proteins; D064030:S100 Calcium Binding Protein G; D001224:Aspartic Acid; D010059:Ovomucin; D018698:Glutamic Acid; D007611:Aprotinin; D012260:Ribonucleases; D009113:Muramidase; D016333:HIV Protease