Effects of Acids, Bases, and Heteroatoms on Proximal Radial Distribution Functions for Proteins.

The proximal distribution of water around proteins is a convenient method of quantifying solvation. We consider the effect of charged and sulfur-containing amino acid side-chain atoms on the proximal radial distribution function (pRDF) of water molecules around proteins using side-chain analogs. The pRDF represents the relative probability of finding any solvent molecule at a distance from the closest or surface perpendicular protein atom. We consider the near-neighbor distribution. Previously, pRDFs were shown to be universal descriptors of the water molecules around C, N, and O atom types across hundreds of globular proteins. Using averaged pRDFs, a solvent density around any globular protein can be reconstructed with controllable relative error. Solvent reconstruction using the additional information from charged amino acid side-chain atom types from both small models and protein averages reveals the effects of surface charge distribution on solvent density and improves the reconstruction errors relative to simulation. Solvent density reconstructions from the small-molecule models are as effective and less computationally demanding than reconstructions from full macromolecular models in reproducing preferred hydration sites and solvent density fluctuations.

Solvation and cavity occupation in biomolecules.

BACKGROUND: Solvation density locations are important for protein dynamics and structure. Knowledge of the preferred hydration sites at biomolecular interfaces and those in the interior of cavities can enhance understanding of structure and function. While advanced X-ray diffraction methods can provide accurate atomic structures for proteins, that technique is challenged when it comes to providing accurate hydration structures, especially for interfacial and cavity bound solvent molecules. METHODS: Advances in integral equation theories which include more accurate methods for calculating the long-ranged Coulomb interaction contributions to the three-dimensional distribution functions make it possible to calculate angle dependent average solvent structure, accurately, around and inside irregular molecular conformations. The proximal radial distribution method provides another approximate method to determine average solvent structures for biomolecular systems based on a proximal or near neighbor solvent distribution that can be constructed from previously collected solvent distributions. These two approximate methods, along with all-atom molecular dynamics simulations are used to determine the solvent density inside the myoglobin heme cavity. DISCUSSION AND RESULTS: Myoglobin is a good test system for these methods because the cavities are many and one is large, tens of Å(3), but is shown to have only four hydration sites. These sites are not near neighbors which implies that the large cavity must have more than one way in and out. CONCLUSIONS: Our results show that main solvation sites are well reproduced by all three methods. The techniques also produce a clearly identifiable solvent pathway into the interior of the protein. GENERAL SIGNIFICANCE: The agreement between molecular dynamics and less computationally demanding approximate methods is encouraging. This article is part of a Special Issue entitled Recent developments of molecular dynamics.

Toward accurate prediction of pKa values for internal protein residues: the importance of conformational relaxation and desolvation energy.

Proton uptake or release controls many important biological processes, such as energy transduction, virus replication, and catalysis. Accurate pK(a) prediction informs about proton pathways, thereby revealing detailed acid-base mechanisms. Physics-based methods in the framework of molecular dynamics simulations not only offer pK(a) predictions but also inform about the physical origins of pK(a) shifts and provide details of ionization-induced conformational relaxation and large-scale transitions. One such method is the recently developed continuous constant pH molecular dynamics (CPHMD) method, which has been shown to be an accurate and robust pK(a) prediction tool for naturally occurring titratable residues. To further examine the accuracy and limitations of CPHMD, we blindly predicted the pK(a) values for 87 titratable residues introduced in various hydrophobic regions of staphylococcal nuclease and variants. The predictions gave a root-mean-square deviation of 1.69 pK units from experiment, and there were only two pK(a)'s with errors greater than 3.5 pK units. Analysis of the conformational fluctuation of titrating side-chains in the context of the errors of calculated pK(a) values indicate that explicit treatment of conformational flexibility and the associated dielectric relaxation gives CPHMD a distinct advantage. Analysis of the sources of errors suggests that more accurate pK(a) predictions can be obtained for the most deeply buried residues by improving the accuracy in calculating desolvation energies. Furthermore, it is found that the generalized Born implicit-solvent model underlying the current CPHMD implementation slightly distorts the local conformational environment such that the inclusion of an explicit-solvent representation may offer improvement of accuracy.