Computer Simulation of Self-Assembling Macromolecules

<strong>Joint Seminar of the SCIS and SPS ---------------------------------------------</strong> Title:<strong> Computer Simulation of Self-Assembling Macromolecules</strong> Speaker:<strong> Michael L. Klein (FRS)</strong> (Temple University, Philadelphia) Date: <strong>January 13, 2015 (Tuesday)</strong> <strong>Abstract : </strong>In the early 1920's, physicists were struggling with the consequences of the birth of quantum mechanics, and quantum chemistry did not exist as a discipline. It is not surprising therefore that there was some confusion among chemists as to the nature of the chemical bond. One of the consequences of this lack of understanding of the fundamentals of molecular structure and bonding was that initially there was little appreciation for the notion that high molecular weight "macromolecules", really were manifestations of covalent-linked monomeric entities as opposed to simple "aggregates" of monomers. Nowadays we take for granted that both synthetic and natural polymers really are macromolecules. In the decades since Hermann Staudinger's 1953 Nobel Prize, driven in part by the immense technological importance of macromolecules in consumer products and advanced materials, a deep understanding has emerged of the phenomenon of macromolecular "aggregation" that underpins the field of supramolecular chemistry, championed by ]ean-Marie Lehn. Biology is rife with examples of the latter, which provides inspiration for novel materials development based on either the spontaneous or directed selfassembly of macromolecules. 1953 was important not only because of the Staudinger Nobel Prize, but also because it was the year that the structure of the macromolecule DNA was reported by ]ames Watson and Francis Crick. Yet another important milestone was recorded in 1953, namely the first published use of a computer to carry out a simulation of liquid, albeit a liquid composed of Argon atoms. This seminal work, which was carried out on the famous MANIAC machine at Los Alamos National Laboratory, by Nick Metropolis and collaborators, was never honored with a Nobel Prize, but nonetheless had an enormous impact across the whole breadth of the physical and life sciences. Indeed, it is inconceivable today that one would attempt a research program dealing with either natural or synthetic macromolecules without the aid of computer simulation as a complement to their design, synthesis, and characterization. My lecture deals with the use of large-scale computer simulation techniques to investigate the self-assembly of modest sized natural and synthetic macromolecules. Over the 60 years since the invention of this methodology, computers have evolved enormously along with concomitant algorithm development such that today computer simulation is capable of being a true partner to experiments. Amphiphilic polymers have the ability to self-assemble into supramolecular structures of remarkable complexity. To understand the formation of such structures, knowing the chemical structure of the macromolecules involved is necessary, but not sufficient. The reason has a relatively simple chemical origin: with the exception of a polymer's chemical bonds, the cohesive forces between its atoms are often outmatched by those between its atoms and those of another macromolecule. More often than not, a direct simulation is the only efficient route to model the self-assembly of amphiphilic polymers into the plethora of novel structures. Historically, computational molecular scientists have used many methods to investigate the structures and thermodynamics of polymer assemblies. In recent years, molecular dynamics (MD) simulations withempirical potential energy functions ("potentials"] have become, arguably, the preferred approach towards this goal.Aside from defining the thermodynamic coupling between the microscopic model and the macroscopic environment, and choosing suitable potentials, MD simulations feature little or no approximation in describing the real motions of polymers during their self-assembly. Therefore, self-assembly into an organized phase, or transformations between - different phases, can be predicted with surprising accuracy.