Dataset Information

Fold versus sequence effects on the driving force for protein-mediated electron transfer.

ABSTRACT: Electron transport chains composed of electron transfer reactions mainly between proteins provide fast efficient flow of energy in a variety of metabolic pathways. Reduction potentials are essential characteristics of the proteins because they determine the driving forces for the electron transfers. As both polar and charged groups from the backbone and side chains define the electrostatic environment, both the fold and the sequence will contribute. However, although the role of a specific sequence may be determined by experimental mutagenesis studies of reduction potentials, understanding the role of the fold by experiment is much more difficult. Here, continuum electrostatics and density functional theory calculations are used to analyze reduction potentials in [4Fe-4S] proteins. A key feature is that multiple homologous proteins in three different folds are compared: six high potential iron-sulfur proteins, four bacterial ferredoxins, and four nitrogenase iron proteins. Calculated absolute reduction potentials are shown to be in quantitative agreement with electrochemical reduction potentials. Calculations further demonstrate that the contribution of the backbone is larger than that of the side chains and is consistent for homologous proteins but differs for nonhomologous proteins, indicating that the fold is the major protein factor determining the reduction potential, whereas the specific amino acid sequence tunes the reduction potential for a given fold. Moreover, the fold contribution is determined mainly by the proximity of the redox site to the protein surface and the orientation of the dipoles of backbone near the redox site.

SUBMITTER: Perrin BS

PROVIDER: S-EPMC2927784 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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Fold versus sequence effects on the driving force for protein-mediated electron transfer.

Perrin Bradley Scott BS Ichiye Toshiko T

Proteins 20101001 13

Electron transport chains composed of electron transfer reactions mainly between proteins provide fast efficient flow of energy in a variety of metabolic pathways. Reduction potentials are essential characteristics of the proteins because they determine the driving forces for the electron transfers. As both polar and charged groups from the backbone and side chains define the electrostatic environment, both the fold and the sequence will contribute. However, although the role of a specific seque ...[more]

PMID: 20635418

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Project description:BackgroundSequence matching is extremely important for applications throughout biology, particularly for discovering information such as functional and evolutionary relationships, and also for discriminating between unimportant and disease mutants. At present the functions of a large fraction of genes are unknown; improvements in sequence matching will improve gene annotations. Universal amino acid substitution matrices such as Blosum62 are used to measure sequence similarities and to identify distant homologues, regardless of the structure class. However, such single matrices do not take into account important structural information evident within the different topologies of proteins and treats substitutions within all protein folds identically. Others have suggested that the use of structural information can lead to significant improvements in sequence matching but this has not yet been very effective. Here we develop novel substitution matrices that include not only general sequence information but also have a topology specific component that is unique for each CATH topology. This novel feature of using a combination of sequence and structure information for each protein topology significantly improves the sequence matching scores for the sequence pairs tested. We have used a novel multi-structure alignment method for each homology level of CATH in order to extract topological information.ResultsWe obtain statistically significant improved sequence matching scores for 73 % of the alpha helical test cases. On average, 61 % of the test cases showed improvements in homology detection when structure information was incorporated into the substitution matrices. On average z-scores for homology detection are improved by more than 54 % for all cases, and some individual cases have z-scores more than twice those obtained using generic matrices. Our topology specific similarity matrices also outperform other traditional similarity matrices and single matrix based structure methods. When default amino acid substitution matrix in the Psi-blast algorithm is replaced by our structure-based matrices, the structure matching is significantly improved over conventional Psi-blast. It also outperforms results obtained for the corresponding HMM profiles generated for each topology.ConclusionsWe show that by incorporating topology-specific structure information in addition to sequence information into specific amino acid substitution matrices, the sequence matching scores and homology detection are significantly improved. Our topology specific similarity matrices outperform other traditional similarity matrices, single matrix based structure methods, also show improvement over conventional Psi-blast and HMM profile based methods in sequence matching. The results support the discriminatory ability of the new amino acid similarity matrices to distinguish between distant homologs and structurally dissimilar pairs.

Dataset Information

Fold versus sequence effects on the driving force for protein-mediated electron transfer.

Publications

Fold versus sequence effects on the driving force for protein-mediated electron transfer.

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