We describe a fast and accurate protocol, LoopBuilder, for the prediction of loop conformations in proteins. The procedure includes extensive sampling of backbone conformations, side chain addition, the use of a statistical potential to select a subset of these conformations, and, finally, an energy minimization and ranking with an all-atom force field. We find that the Direct Tweak algorithm used in the previously developed LOOPY program is successful in generating an ensemble of conformations that on average are closer to the native conformation than those generated by other methods. An important feature of Direct Tweak is that it checks for interactions between the loop and the rest of the protein during the loop closure process. DFIRE is found to be a particularly effective statistical potential that can bias conformation space toward conformations that are close to the native structure. Its application as a filter prior to a full molecular mechanics energy minimization both improves prediction accuracy and offers a significant savings in computer time. Final scoring is based on the OPLS/SBG-NP force field implemented in the PLOP program. The approach is also shown to be quite successful in predicting loop conformations for cases where the native side chain conformations are assumed to be unknown, suggesting that it will prove effective in real homology modeling applications. Proteins 2008. © 2007 Wiley-Liss, Inc.

We present an adaptive sampling method for computing free energies, radial distribution functions, and potentials of mean force. The method is characterized by simplicity and accuracy, with the added advantage that the data are obtained in terms of quasicontinuous functions. The method is illustrated and tested with simulations on a high density fluid, including a stringent consistency test involving an unusual thermodynamic cycle that highlights its advantages.

Gene regulatory networks that control the terminally differentiated state of a cell are, by and large, only superficially understood. In a mutant screen aimed at identifying regulators of gene batteries that define the differentiated state of two left/right asymmetric C. elegans gustatory neurons, ASEL and ASER, we have isolated a mutant, fozi-1, with a novel mixed-fate phenotype, characterized by de-repression of ASEL fate in ASER. fozi-1 codes for a protein that functions in the nucleus of ASER to inhibit the expression of the LIM homeobox gene lim-6, neuropeptide-encoding genes and putative chemoreceptors of the GCY gene family. The FOZI-1 protein displays a highly unusual domain architecture, that combines two functionally essential C2H2 zinc-finger domains, which are probably involved in transcriptional regulation, with a formin homology 2 (FH2) domain, normally found only in cytosolic regulators of the actin cytoskeleton. We demonstrate that the FH2 domain of FOZI-1 has lost its actin polymerization function but maintains its phylogenetically ancient ability to homodimerize. fozi-1 genetically interacts with several transcription factors and micro RNAs in the context of specific regulatory network motifs. These network motifs endow the system with properties that provide insights into how cells adopt their stable terminally differentiated states.