Absolute free energies of hydration (ΔGhyd) for more than 500 neutral and charged compounds have been computed, using Poisson-Boltzmann (PB) and Generalized Born (GB) continuum methods plus a solvent-accessible surface area (SA) term, to evaluate the accuracy of eight simple point-charge models used in molecular modeling. The goal is to develop improved procedures and protocols for protein-ligand binding calculations and virtual screening (docking). The best overall PBSA and GBSA results, in comparison with experimental ΔGhyd values for small molecules, were obtained using MSK, RESP, or ChelpG charges obtained from ab initio calculations using 6-31G* wave functions. Correlations using semiempirical (AM1BCC, AM1CM2, and PM3CM2) or empirical (Gasteiger-Marsili and MMFF94) methods yielded mixed results, particularly for charged compounds. For neutral compounds, the AM1BCC method yielded the best agreement with experimental results. In all cases, the PBSA and GBSA results are highly correlated (overall r(2) = 0.94), which highlights the fact that various partial charge models influence the final results much more than which continuum method is used to compute hydration free energies. Overall improved agreement with experimental results was demonstrated using atom-based constants in place of a single surface area term. Sets of optimized SA constants, suitable for use with a given charge model, were derived by fitting to the difference in experimental free energies and polar continuum results. The use of optimized atom-based SA constants for the computation of ΔGhyd can fine-tune already reasonable agreement with experimental results, ameliorate gross deficiencies in any particular charge model, account for nonoptimal radii, or correct for systematic errors.

Intramolecular cross-linking coupled with mass spectrometric identification of cross-linked amino acids is a rapid method for elucidating low-resolution protein tertiary structures or fold families. However, previous cross-linking studies on model proteins, such as cytochrome c and ribonuclease A, identified a limited number of peptide cross-links that are biased toward only a few of the potentially reactive lysine residues. Here, we report an approach to improve the diversity of intramolecular protein cross-linking starting with a systematic quantitation of the reactivity of lysine residues of a model protein, bovine cytochrome c. Relative lysine reactivities among the 18 lysine residues of cytochrome c were determined by the ratio of d0 and acetyl-d3 groups at each lysine after partial acetylation with sulfosuccinimidyl acetate followed by denaturation and quantitative acetylation of remaining unmodified lysines with acetic-d6 anhydride. These lysine reactivities were then compared with theoretically derived pKa and relative solvent accessibility surface values. To ascertain if partial N-acetylation of the most reactive lysine residues prior to cross-linking can redirect and increase the observable Lys-Lys cross-links, partially acetylated bovine cytochrome c was cross-linked with the amine-specific, bis-functional reagent, bis(sulfosuccinimidyl)suberate. After proteolysis and mass spectrometry analysis, partial acetylation was shown to significantly increase the number of observable peptides containing Lys-Lys cross-links, shifting the pattern from the most reactive lysine residues to less reactive ones. More importantly, these additional cross-linked peptides contained novel Lys-Lys cross-link information not seen in the non-acetylated protein and provided additional distance constraints that were consistent with the crystal structure and facilitated the identification of the proper protein fold.

For a completely enumerated set of conformers of a macromolecule or for exhaustive lattice walks of model polymers it is straightforward to use Shannon information theory to deduce the information content of the ensemble. It is also practicable to develop numerical measures of the information content of sets of exact distance constraints applied to specific conformational ensembles. We examine the effects of experimental uncertainties by considering "noisy" constraints. The introduction of noise requires additional assumptions about noise distribution and conformational clustering protocols that make the problem of measuring information content more complex. We make use of a standard concept in communication theory, the "noise sphere," to link uncertainty in measurements to information loss. Most of our numerical results are derived from two-dimensional lattice ensembles. Expressing results in terms of information per degree of freedom removes almost all of the chain length dependence. We also explore off-lattice polyalanine chains that yield surprisingly similar results.

In this article, we explore the information content of molecular force-field calculations. We make use of exhaustive lattice models of molecular conformations and reduced alphabet sequences to determine the relative resolving power of pairwise interaction-based force fields. We find that sequence-specific interactions that operate over longer distances offer greater amounts of information than nearest-neighbor or non-sequence-specific interactions. In a companion article in this issue, we explored the information content of sequence alignment procedures and the calculation of gap penalties. Both articles have implications for protein and nucleic-acid computations.

We are interested in applying the principles of information theory to structural biology calculations. In this article, we explore the information content of an important computational procedure: sequence alignment. Using a reference state developed from exhaustive sequences, we measure alignment statistics and evaluate gap penalties based on first-principle considerations and gap distributions. We show that there are different gap penalties for different alphabet sizes and that the gap penalties can depend on the length of the sequences being aligned. In a companion article, we examine the information content of molecular force fields.

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