Biomolecular Hydration and Interactions

The last two decades have seen an incredible revolution in structural biology: Over 90,000 protein structures have now been solved at atomic resolution. Translating this wealth of static structural information into a molecular-level understanding of their biological functions - and their impact on dynamic intracellular processes - represents a grand challenge in molecular biology, with direct implications on our understanding of human health and disease. Progress in this area hinges on our ability to understand, predict, and manipulate the interactions of various proteins, given their precise structure: Out of the menagerie of molecules that a protein encounters in the cellular milieu -- ligands, peptide fragments, nucleic acids, membranes, and other proteins -- which will it interact favorably with, how strong will the interaction be, and what are the strategies for modulating the interaction strength?

Based on recent work in our group and those of others, we hypothesize that one of the biggest challenges in accurately predicting protein interactions is precisely accounting for the role of water. Water is a key player in every biochemical interaction: Every biomolecular binding process requires replacing water-surface interactions with direct protein-protein interactions. While the direct interactions are straightforward to estimate, the protein-water interactions are difficult to quantify because proteins have incredibly complex surfaces that disrupt the inherent structure of water (strong hydrogen bonds) in countless different ways. Any hope to accurately account for the strength of water-protein interactions would require considering not only on the chemistry of the underlying protein surface, but also the precise topography.

Using principles of liquid state theory in conjunction with novel simulation techniques in explicit solvent, we are developing a computational and theoretical framework that rigorously quantifies protein-water interactions. We are applying insights from these calculations to predict the protein intermolecular interactions.

Computational Material Design

By understanding the molecular underpinnings of solvation (of water and other liquids) adjacent to complex nanoscopic surfaces, that is, surfaces with nanoscopic pattern and/or texture, our goal is to inform the design of the next generation of advanced materials.

One example is the design of robust superhydrophobic surfaces (left). Surface texture can transform hydrophobic surfaces into "superhydrophobic" surfaces, endowed with properties like water-repellency, self-cleaning, and fouling resistance. However, superhydrophobicity is fragile, and depends on water being excluded from the surface texture. Thus, fully realizing its promise requires an understanding of the underpinnings of wetting-dewetting transitions on nanotextured surfaces.

Other examples of interest to our group include the design of superhydrophilic surfaces with superior protein non-fouling properties (center), nanoparticle membranes for desalination (right), and polymer electrolytes for batteries.

Understanding Hydrophobic Effects

The aversion of oil and water towards each other is something we have all experienced. The hydrophobic effect, the driving force that causes oil and water to phase separate, also drives important molecular level phenomena: protein folding/misfolding, interactions, and aggregation, formation of micelles and membranes, and colloidal self-assembly. However, the hydrophobicity of nano-scaled surfaces is intimately dependent on the local chemical environment, or context. This context-dependence of hydrophobicity makes accurately estimating surface-water interactions incredibly challenging.

By understanding some of the basic signatures of hydrophobicity, we can begin to unravel the mysteries surrounding some of the more puzzling processes in biology and chemistry. For instance, the strength of hydrophobic interactions increases with temperature; and this (perhaps non-intuitive) result provides a basis for observed cold-denaturation of proteins. In more recent work, it was shown that hydrophobic assembly is enhanced near extended hydrophobic surfaces - explaining, for instance, why amyloid fibril formation is facilitated by the presence of hydrophobic surfaces.

All of the questions we grapple with share a common theme: They require molecular-level understanding of hydrophobicity and the hydrophobic effect A (very non-exhaustive) list of questions includes: How can we quantitatively define and characterize the hydrophobicity of a complex nano-scale surfaces - such as that of a protein? How does surface topography, ruggedness, and curvature affect its hydrophobicity? What are the pathways to dewetting in hydrophobic environments? What role does the flexibility/rigidity of a surface play in determining its hydrophobicity?

Developing Novel Simulation Techniques and Theoretical Models

Our tool for tackling these challenges is a combination of explicit-solvent molecular dynamics simulations with the aid of enhanced sampling techniques. We make extensive use of configurational and path sampling techniques, and when necessary, develop new simulations techniques. We also develop highly efficient coarse-grained theoretical models to study phenomena characterized by large length scales and/or long time scales.

One of the fundamental tools in our lab for characterizing water's interactions and behavior the INDUS (INDirect Umbrella Sampling) method. INDUS has been applied extensively to characterize the density fluctuations and statistical thermodynamics of water in the bulk and near the interfaces of surfaces.

We make extensive use of INDUS to perturb water density near surfaces (e.g. proteins or engineered nano-structures). The response of water to perturbations provides a wealth of information about the underyling context-dependent hydrophobicity of the surface.