AB Initio Protein Tertiary Structure Prediction: Comparative-Genetic Algorithm with Graph Theoretical Methods

During the period from September 1, 1998 until September 1, 2000 I was awarded a Sloan/DOE postdoctoral fellowship to work in collaboration with Professor John Moult at the Center for Advanced Research in Biotechnology (CARB). Our research project, ''Ab Initio Protein Tertiary Structure Prediction and a Comparative Genetic algorithm'', yielded promising initial results. In short, the project is designed to predict the native fold, or native tertiary structure, of a given protein by inputting only the primary sequence of the protein (one or three letter code). The algorithm is based on a general learning, or evolutionary algorithm and is called Genetic Algorithm (GAS). In our particular application of GAS, we search for native folds, or lowest energy structures, using two different descriptions for the interactions of the atoms and residues in a given protein sequence. One potential energy function is based on a free energy description, while the other function is a threading potential derived by Moult and Samudrala. This modified genetic algorithm was loosely termed a Comparative Genetic Algorithm and was designed to search for native folded structures on both potential energy surfaces, simultaneously. We tested the algorithm on a series of peptides ranging from 11 to 15 residues in length, which are thought to be independent folding units and thereby will fold to native structures independent of the larger protein environment. Our initial results indicated a modest increase in accuracy, as compared to a standard Genetic Algorithm. We are now in the process of improving the algorithm to increase the sensitivity to other inputs, such as secondary structure requirements. The project did not involve additional students and as of yet, the work has not been published

Systems Biology Knowledgebase for a New Era in Biology A Genomics:GTL Report from the May 2008 Workshop

Biology has entered a systems-science era with the goal to establish a predictive understanding of the mechanisms of cellular function and the interactions of biological systems with their environment and with each other. Vast amounts of data on the composition, physiology, and function of complex biological systems and their natural environments are emerging from new analytical technologies. Effectively exploiting these data requires developing a new generation of capabilities for analyzing and managing the information. By revealing the core principles and processes conserved in collective genomes across all biology and by enabling insights into the interplay between an organism's genotype and its environment, systems biology will allow scientific breakthroughs in our ability to project behaviors of natural systems and to manipulate and engineer managed systems. These breakthroughs will benefit Department of Energy (DOE) missions in energy security, climate protection, and environmental remediation

CW THZ SPECTROSCOPY OF SMALL PEPTIDES

Author Institution: National Institute of Standards and Technology, Gaithersburg MD 20899 USA; Dept. of Chemistry and Biochemistry, University of Maryland, Baltimore, MD 21250; National Institute of Standards and Technology, Gaithersburg MD 20899 USACW THz spectroscopy has been used to investigate the lowest frequency vibrational modes of small peptides. Due to their non-local character, these large amplitude modes are remarkably sensitive to intermolecular hydrogen bonding. THz spectra obtained from 2 \wn to 100 \wn, for three different crystalline forms of alanine tripeptide at 4.2 K were all quite different. These three forms included one parallel and two anti-parallel beta sheet structures. The latter two forms differ only in the presence and absence of water molecules that bridge and cross link the sheets. Despite the weak nature of the water hydrogen bonds, the THz spectra for the hydrated and dehydrated antiparallel structures of trialanine are drastically different, while spectra observed for the two forms in the mid-infrared region were indistinguishable. Together with data obtained at intermediate hydration levels, these results provide insight into the nature and scope of forces fields necessary to model these low energy interactions. Spectral predictions obtained for crystal-like structures using the CHARMM force field and for various dimer forms from density functional theory will be discussed

'Omics data sharing

Development of high-throughput genomic and postgenomic technologies has caused a change in approaches to data handling and processing (1). One biological sample might be used to generate many kinds of “big” data in parallel, such as genome sequence (genomics), patterns of gene and protein expression (transcriptomics and proteomics), and metabolite concentrations and fluxes (metabolomics). Extensive computer manipulations are required for even basic analyses of such data; the challenges mount further when two or more studies' outputs must be compared or integrated