The computational study of molecular processes in nature, such as polymer dynamics or aggregation, are for the most part still out of reach for conventional simulation methods such as Molecular Dynamics or Monte Carlo. Here we present a fragmentation engine designed to handle in principle any molecular architecture. The methodology is based on the well-known notion that atomic groups in molecules can be lumped into single particles, or �beads� [1]. This so-called �coarse-graining� allows for (much) larger length and time scales that can typically be attained by conventional simulation methods.The problem of fragmenting an atomistally detailed molecule is transformed to a global minimization problem. A scoring function determines how good or bad a given fragmentation is. Then the algorithm is reduced to finding the global minimum of the scoring function. The global minimization is performed by a Monte Carlo evolution where the lowest scoring fragmentation is stored [3]. This typically succeeds finding the global minimum for a given molecular architecture within a reasonable amount of time.From a fundamental chemical informatics point of view, it is interesting to note that that we can represent a collection of different molecules by a much smaller set of distinct fragments, and that the frequency distribution of fragments follows Heap's power law. Extrapolation indicates that one could fragment the entire PubChem database into a mere few thousands distinct fragments. The great practical advantage is that in this way, by pre-parameterization, one can in principle speed up molecular affinity calculations of thermodynamic accuracy by many orders of magnitude, while still maintaining chemical specificity.So far we have successfully applied the fragment-based computational approach to molecular systems and architectures found in the chemical [3], oil [4] and pharmaceutical industry. The method has been refined and validated against industrially relevant data. Here we will demonstrate the versatility of the methodology by applying it to the biopolymer lignin. First we discuss the problem of generating atomic structures of lignin oligomers from 2D NMR data, followed by a description of the actual fragmentation to coarse-grained lignin models. We finally discuss the application of these coarse-grained lignin models by performing simulations to study the phase behavior in aqueous solution.1. See: Carbone, P.; Karimi-Varzaneh, H. A.; M�ller-Plathe, F. Faraday Discuss. 2010, 144, 25�42, and references therein.2. Fraaije, J. G. E. M., Nath, S. K., van Male, J., Becherer, P., Klein Wolterink, J., Handgraaf, J.-W., Case F., Tanase,, C. Serral Graci�, R., Culgi Manual version 8.0, www.culgi.com (2013) (ISBN: 978-90-817846-0-3).3. Handgraaf, J.-W.; Serral Graci�, R.; Nath, S. K.; Chen Z.; Chou, S.-H.; Ross, R. B.; Schultz, N. E.; Fraaije, J. G. M. E., Macromolecules 2011, 44, 1053-1061.4. Fraaije, J. G. E. M.; Tandon, K.; Jain, S.; Handgraaf, J.-W.; Buijse, M., Langmuir 2013, 29, 2136-2151.

Fragment-based computational approach to study the phase behavior of biopolymers

248th National Meeting (2014)

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