Proteins have evolved to use water to help guide folding. A physically motivated, nonpairwise-additive model of water-mediated interactions added to a protein structure prediction Hamiltonian yields marked improvement in the quality of structure prediction for larger proteins. Free energy profile analysis suggests that long-range water-mediated potentials guide folding and smooth the underlying folding funnel. Analyzing simulation trajectories gives direct evidence that water-mediated interactions facilitate native-like packing of supersecondary structural elements. Long-range pairing of hydrophilic groups is an integral part of protein architecture. Specific water-mediated interactions are a universal feature of biomolecular recognition landscapes in both folding and binding. W ater is intimately involved in protein folding (1-4). That proteins denature both on heating and cooling strongly implicates the involvement of water degrees of freedom. Kauzmann (5) correctly inferred from thermodynamics the hydrophobic layering characteristic of protein structure before protein structures were determined crystallographically. The kinetics of water exclusion is often considered in discussing mechanisms of protein folding, but again it is the avoidance of water in the final folded structure that is emphasized (1). Hydrophobicity patterns have long been a dominant consideration in predicting protein structure by using sequence data (6) and are basic in synthetic protein design (7). Nevertheless, the structured character of water has not been a paramount factor in most existing algorithms for structure prediction (8). These usually rely on effective pair potentials (9) or buried surface area terms to account for the free energy of burying hydrophobic residues (10).In this article, we hypothesize that specific water-mediated interactions help guide the folding process even before native contacts form. Using this idea we develop a bioinformatic, nonpairwise-additive interaction model accounting for water and show that it greatly improves the efficiency and accuracy of structure prediction for ␣-helical proteins. Analysis of folding trajectories with this potential strongly implicates the guiding role of long-range water-mediated interactions. Interestingly, we find here that long-range hydrophilic interactions, as distinct from hydrophobic interactions, also take center stage.The bioinformatic route to water-mediated potentials is difficult in several ways (for more directly physical approaches see ref. 11). Although bound water is visible in structures, localizing waters is more difficult than localizing main-chain atoms. Monomeric protein structures also have relatively few visible watermediated interactions. Our path to a water-mediated potential started with an energy landscape analysis of protein-protein interactions and a bioinformatic survey of interfaces in dimer structures (12, 13). We found that the often-used contact potentials (9) worked well to describe hydrophobic binding interfaces; however, hydrophilic interf...

The energy landscape picture of protein folding and binding is employed to optimize a number of pair potentials for direct and water-mediated interactions in protein complex interfaces. We find that water-mediated interactions greatly complement direct interactions in discriminating against various types of trap interactions that model those present in the cell. We highlight the context dependent nature of knowledge-based binding potentials, as contrasted with the situation for autonomous folding. By performing a Principal Component Analysis (PCA) of the corresponding interaction matrixes, we rationalize the strength of the recognition signal for each combination of the contact type and reference trap states using the differential in the idealized "canonical" amino acid compositions of native and trap layers. The comparison of direct and water-mediated contact potential matrixes emphasizes the importance of partial solvation in stabilizing charged groups in the protein interfaces. Specific water-mediated interresidue interactions are expected to influence significantly the kinetics as well as thermodynamics of protein association.

The use of ligand binding thermodynamics has been proposed as a potential success factor to accelerate drug discovery. However, despite the intuitive appeal of optimizing binding enthalpy, a number of factors complicate routine use of thermodynamic data. On a macroscopic level, a range of experimental parameters including temperature and buffer choice significantly influence the observed thermodynamic signatures. On a microscopic level, solute effects, structural flexibility, and cooperativity lead to nonlinear changes in enthalpy. This multifactorial character hides essential enthalpy contributions of intermolecular contacts, making them experimentally nonobservable. In this perspective, we present three case studies, reflect on some key factors affecting thermodynamic signatures, and investigate their relation to the hydrophobic effect, enthalpy-entropy compensation, lipophilic ligand efficiency, and promiscuity. The studies highlight that enthalpy and entropy cannot be used as direct end points but can together with calculations increase our understanding of ligand binding and identify interesting outliers that do not behave as expected.

Valproic acid is a short branched fatty acid used as an anticonvulsant drug whose therapeutic action has been proposed to arise from membrane-disordering properties. Static and kinetic properties of valproic acid interacting with fully hydrated dipalmitoyl phosphatidylcholine lipid bilayers are studied using molecular-dynamics simulations. We calculate spatially resolved free energy profiles and local diffusion coefficients using the distance between the bilayer and valproic acid respective centers-of-mass along the bilayer normal as reaction coordinate. To investigate the pH dependence, we calculate profiles for the neutral valproic acid as well as its water-soluble anionic conjugate base valproate. The local diffusion constants for valproate/valproic acid along the bilayer normal are found to be approximately 10(-6) to 10(-5) cm2 s(-1). Assuming protonation of valproic acid upon association with--or insertion into--the lipid bilayer, we calculate the permeation coefficient to be approximately 2.0 10(-3) cm s(-1), consistent with recent experimental estimates of fast fatty acid transport. The ability of the lipid bilayer to sustain local defects such as water intrusions stresses the importance of going beyond mean field and taking into account correlation effects in theoretical descriptions of bilayer translocation processes.