Interdisciplinary PhD in Structural and Computational Biology and Quantitative Biosciences

Reid C. Van Lehn

Conway Assistant Professor, Department of Chemical and Biological Engineering Lab Website 263-9487

3012 Engineering Hall
1415 Engineering Drive
Madison, WI 53706-1607


B.S., Massachusetts Institute of Technology
Ph.D., Massachusetts Institute of Technology
Postdoctoral, California Institute of Technology

Biomolecular simulation; nano-bio interactions; complex bio interfaces; cotranslational protein synthesis; biomembranes

Research in the Van Lehn group is thematically organized around the goal of relating molecular properties to macroscopic function by employing a variety of simulation techniques to interrogate behavior at multiple length and time scales. We focus on multicomponent systems with spatially varying interfacial properties, studying both synthetic (e.g., nanoparticles, surfactants, and peptides) and biological (e.g., proteins, lipid bilayers, and biopolymers) soft material systems. Current areas of research are detailed below.

Solvent-Mediated Interactions in Complex Environments

In liquid solutions, solutes can experience solvent-mediated interactions that arise solely from the collective behavior of the surrounding solvent molecules, rather than from noncovalent interactions between the solutes themselves. For example, the exclusion of water molecules from nonpolar interfaces leads to a water-mediated attractive interaction (i.e., the hydrophobic effect). In solutions with multiple solvent species, preferential interactions can also drive solute partitioning into nanoscale domains that are enriched in one of the solvent species. Similarly, materials embedded within a lipid bilayer can interact by mechanically deforming the surrounding lipid matrix. We develop simulation methods to understand how solvent-mediated interactions can direct molecular assembly or association in these complex solvent environments, and apply this insight to design stimuli-responsive materials and optimize solvent compositions for liquid-phase reactions.

Materials Design Using Simulation-Derived Molecular Descriptors

An outstanding challenge – and opportunity – for soft materials design is the large set of parameters that can be manipulated synthetically. For example, peptides can incorporate an enormous number of amino-acid residue combinations, while nanomaterials can be synthesized with different surface compositions, sizes, and shapes. Macroscopic behavior is highly sensitive to these parameters; for example, the cellular uptake of nanoparticles depends strongly on surface charge and size. Developing design rules for these systems is challenging given the difficulty in experimentally screening material compositions or accurately modeling long-timescale biological processes. We instead use simulations to compute molecular descriptors that are incorporated into quantitative structure-property relationship models to predict experimental observables, enabling the high-throughput screening and optimization of materials properties for applications in drug delivery and catalysis.

Interactions at Heterogeneous Interfaces

Many soft materials present surfaces that vary in polarity, charge, and composition over nanometer length scales. These spatial heterogeneities can lead to interfacial properties that differ significantly from the properties of homogeneous materials, and intermolecular interactions with heterogeneous interfaces are often non-additive and poorly understood. We use atomistic simulations, in conjunction with advanced sampling techniques, to study the physicochemical properties of multicomponent, heterogeneous interfaces. We focus on understanding the effect of nanoscale variations in interfacial chemical properties (e.g., due to patterns of polar and nonpolar moieties) and physical properties (e.g., due to differences in curvature or molecular order). The resulting structure-property relationships can inform the creation of materials for sensing and targeting applications, including nanomaterials that bind to specific small molecules and peptides that target components of bacterial membranes.

Multiscale Modeling of Amphiphilic Assemblies

Lipids, surfactants, and other amphiphiles can self-assemble into soft nanostructures, such as the lipid bilayer that represents the primary component of the cell membrane. Both the physical and chemical properties of these assemblies can dictate interfacial processes: for example, the hydrophobic core of the lipid bilayer inhibits the passive diffusion of polar molecules, but mechanical perturbations to its structure can dramatically increase bilayer permeability. We develop and apply multiscale simulations and enhanced sampling techniques to understand how the chemical and physical properties of amphiphiles affect their self-assembly, interactions with synthetic materials, and structural response to external perturbations. The insight obtained from these simulations can guide the design of drug delivery vehicles that efficiently bypass cell membranes, engineered membrane proteins that respond to changes in lipid bilayer composition, and materials that co-assemble with natural amphiphiles.

Areas of Expertise

  • Biotechnology
  • Computational Biology & Bioinformatics
  • Membrane & Cellular Biophysics