A number of lower organisms (bacteria, fungi, and parasites) produce glycoconjugates that contain furanose rings. Of particular interest to our group are cell wall polysaccharides from mycobacteria, including the human pathogen, Mycobacterium tuberculosis, which contain a large number of arabinofuranose resides. As part of a larger project on the conformational analysis of these molecules, we report here molecular dynamics simulations on methyl α-D-arabinofuranoside (1) using the AMBER force field and the GLYCAM carbohydrate parameter set. We initially studied the ability of this method to predict rotamer populations about the hydroxymethyl group (C4-C5) bond. Importantly, we show that simulation times of up to 200 ns are required in order to obtain convergence of the rotamer populations for this ring system. We also propose a new charge derivation approach that accounts for the flexibility of the furanoside ring by taking an average of the charges from a large number of conformers across the psuedorotational itinerary. The approach yields rotamer populations that are in good agreement with available NMR data and, in addition, provides insight into the nature of the puckering angle and amplitude in 1.

Summary: Participating as the Cornell-Gdansk group, we have used our physics-based coarsegrained UNited RESidue (UNRES) force field to predict protein structure in the 11th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP11). Our methodology involved extensive multiplexed replica exchange simulations of the target proteins with a recently improved UNRES force field to provide better reproductions of the local structures of polypeptide chains. All simulations were started from fully extended polypeptide chains, and no external information was included in the simulation process except for weak restraints on secondary structure to enable us to finish each prediction within the allowed 3-week time window. Because of simplified UNRES representation of polypeptide chains, use of enhanced sampling methods, code optimization and parallelization and sufficient computational resources, we were able to treat, for the first time, all 55 human prediction targets with sizes from 44 to 595 amino acid residues, the average size being 251 residues. Complete structures of six singledomain proteins were predicted accurately, with the highest accuracy being attained for the T0769, for which the CaRMSD was 3.8 Å for 97 residues of the experimental structure. Correct structures were also predicted for 13 domains of multi-domain proteins with accuracy comparable to that of the best template-based modeling methods. With further improvements of the UNRES force field that are now underway, our physics-based coarse-grained approach to protein-structure prediction will eventually reach global prediction capacity and, consequently, reliability in simulating protein structure and dynamics that are important in biochemical processes. Availability and Implementation: Freely available on the web at

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