Development and testing of new force fields for molecular dynamics simulations

Recent progress in modeling of protein folding in Dr. Shaw laboratory has been achieved only after some improvements of potentials of covalent forces, taken from the standard AMBER force field; and still, the force field used is not quite satisfactory to reproduce folded structures of some larger proteins, having significant, about 5A, RMS deviation between the computed and experimentally determined 3D structures. The objective of this research is to develop and test new polarizable atomic force fields (FFs) for "in-vacuum" and "in-water" non-bonded interactions based on AMBER ff99SBILDN force fields, improved by inclusion of new terms. FFs parameter optimization will be done using our set of molecular crystals with crystallographic data from the Cambridge Structural Database and sublimation/solvation thermodynamics characteristics from various sources

Prediction of peptide and protein propensity for amyloid formation

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔGº values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation

How Can Ice Emerge at 0 °C?

The classical nucleation theory shows that bulk water freezing does not occur at temperatures above ≈ −30 °C, and that at higher temperatures ice nucleation requires the presence of some ice-binding surfaces. The temperature and rate of ice nucleation depend on the size and level of complementarity between the atomic structure of these surfaces and various H-bond-rich/depleted crystal planes. In our experiments, the ice nucleation temperature was within a range from −8 °C to −15 °C for buffer and water in plastic test tubes. Upon the addition of ice-initiating substances (i.e., conventional AgI or CuO investigated here), ice appeared in a range from −3 °C to −7 °C, and in the presence of the ice-nucleating bacterium Pseudomonas syringae from −1 °C to −2 °C. The addition of an antifreeze protein inhibited the action of the tested ice-initiating agents