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Elijah Roberts

Publications and source records attributed to Elijah Roberts.

2 recordsLinked to original sources

Cytochrome c(2) Exit Strategy: Dissociation Studies and Evolutionary Implications.

Small, water-soluble, type c cytochromes form a transient network connecting major bioenergetic membrane protein complexes in both photosynthesis and respiration. In the photosynthesis cycle of Rhodobacter sphaeroides, cytochrome c2 (cyt c2) docks to the reaction center (RC), undergoes electron transfer, and exits for the cytochrome bc1 complex. Translations of cyt c2 about the RC-cyt c2 docking interface and surrounding membrane reveal possible exit pathways. A pathway at a minimal elevation allowed by the architecture of the RC is analyzed using both an all-atom steered molecular dynamics simulation of the RC-cyt c2 complex and a bioinformatic analysis of the structures and sequences of cyt c. The structure-based phylogenetic analysis allows for the identification of structural elements that have evolved to satisfy the requirements of having multiple functional partners. The patterns of evolutionary variation obtained from the phylogenetic analysis of both docking partners of cyt c2 reveal conservation of key residues involved in the interaction interfaces that would be candidates for further experimental studies. Additionally, using the molecular mechanics Poisson-Boltzmann surface area method we calculate that the binding free energy of reduced cyt c2 to the RC is nearly 6 kcal/mol more favorable than with oxidized cyt c2. The redox-dependent variations lead to changes in structural flexibility, behavior of the interfacial water molecules, and eventually changes in the binding free energy of the complex.

Amino Acid Sequence↗

MultiSeq: unifying sequence and structure data for evolutionary analysis.

BACKGROUND: Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes. RESULTS: Here we present MultiSeq, a unified bioinformatics analysis environment that allows one to organize, display, align and analyze both sequence and structure data for proteins and nucleic acids. While special emphasis is placed on analyzing the data within the framework of evolutionary biology, the environment is also flexible enough to accommodate other usage patterns. The evolutionary approach is supported by the use of predefined metadata, adherence to standard ontological mappings, and the ability for the user to adjust these classifications using an electronic notebook. MultiSeq contains a new algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. The method, based on the multidimensional QR factorization of multiple sequence and structure alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. CONCLUSION: MultiSeq is a major extension of the Multiple Alignment tool that is provided as part of VMD, a structural visualization program for analyzing molecular dynamics simulations. Both are freely distributed by the NIH Resource for Macromolecular Modeling and Bioinformatics and MultiSeq is included with VMD starting with version 1.8.5. The MultiSeq website has details on how to download and use the software: http://www.scs.uiuc.edu/~schulten/multiseq/

Algorithms↗