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Four distances between pairs of amino acids provide a precise description of their interaction.

ABSTRACT: The three-dimensional structures of proteins are stabilized by the interactions between amino acid residues. Here we report a method where four distances are calculated between any two side chains to provide an exact spatial definition of their bonds. The data were binned into a four-dimensional grid and compared to a random model, from which the preference for specific four-distances was calculated. A clear relation between the quality of the experimental data and the tightness of the distance distribution was observed, with crystal structure data providing far tighter distance distributions than NMR data. Since the four-distance data have higher information content than classical bond descriptions, we were able to identify many unique inter-residue features not found previously in proteins. For example, we found that the side chains of Arg, Glu, Val and Leu are not symmetrical in respect to the interactions of their head groups. The described method may be developed into a function, which computationally models accurately protein structures.

SUBMITTER: Cohen M

PROVIDER: S-EPMC2715887 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature

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Four distances between pairs of amino acids provide a precise description of their interaction.

Cohen Mati M Potapov Vladimir V Schreiber Gideon G

PLoS computational biology 20090814 8

The three-dimensional structures of proteins are stabilized by the interactions between amino acid residues. Here we report a method where four distances are calculated between any two side chains to provide an exact spatial definition of their bonds. The data were binned into a four-dimensional grid and compared to a random model, from which the preference for specific four-distances was calculated. A clear relation between the quality of the experimental data and the tightness of the distance ...[more]

PMID: 19680437

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Project description:BackgroundWell-performing automated protein function recognition approaches usually comprise several complementary techniques. Beside constructing better consensus, their predictive power can be improved by either adding or refining independent modules that explore orthogonal features of proteins. In this work, we demonstrated how the exploration of global atomic distributions can be used to indicate functionally important residues.ResultsUsing a set of carefully selected globular proteins, we parametrized continuous probability density functions describing preferred central distances of individual protein atoms. Relative preferred burials were estimated using mixture models of radial density functions dependent on the amino acid composition of a protein under consideration. The unexpectedness of extraordinary locations of atoms was evaluated in the information-theoretic manner and used directly for the identification of key amino acids. In the validation study, we tested capabilities of a tool built upon our approach, called SurpResi, by searching for binding sites interacting with ligands. The tool indicated multiple candidate sites achieving success rates comparable to several geometric methods. We also showed that the unexpectedness is a property of regions involved in protein-protein interactions, and thus can be used for the ranking of protein docking predictions. The computational approach implemented in this work is freely available via a Web interface at http://www.bioinformatics.org/surpresi.ConclusionsProbabilistic analysis of atomic central distances in globular proteins is capable of capturing distinct orientational preferences of amino acids as resulting from different sizes, charges and hydrophobic characters of their side chains. When idealized spatial preferences can be inferred from the sole amino acid composition of a protein, residues located in hydrophobically unfavorable environments can be easily detected. Such residues turn out to be often directly involved in binding ligands or interfacing with other proteins.

Project description:Protein-DNA interactions facilitate the fundamental functions of living cells and are universal in all living organisms. Several investigations have been carried out, essentially identifying pairs of interactions between the amino acid residues in proteins and the bases in DNA. In the present study, we have detected the recognition motifs that may constitute a cluster of spatially interacting residues in proteins, which interact with the bases of DNA. Graph spectral algorithm has been used to detect side chain clusters comprising Arg, Lys, Asn, Gln and aromatic residues from proteins interacting with DNA. We find that the interaction of proteins with DNA is through clusters in about half of the proteins in the dataset and through individual residues in the rest. Furthermore, inspection of the clusters has revealed additional interactions in a few cases, which have not been reported earlier. The geometry of the interaction between the DNA base and the protein residue is quantified by the distance d and the angle theta. These parameters have been identified for the cation-pi/H-bond stair motif that was reported earlier. Among the Arg, Lys, Asn and Gln residues, the range of (d, theta) values of the interacting Arg clearly falls into the cation-pi and the hydrogen bond interactions of the 'cation-pi/H-bond' stair motif. Analysis of the cluster composition reveals that the Arg residue is predominant than the Lys, Asn and Gln residues. The clusters are classified into Type I and Type II based on the presence or absence of aromatic residues (Phe, Tyr) in them. Residue conservation in these clusters has been examined. Apart from the conserved residues identified previously, a few more residues mainly Phe, Tyr and Arg have also been identified as conserved and interactive with the DNA. Interestingly, a few residues that are parts of interacting clusters and do not interact directly with the DNA have also been conserved. This emphasizes the importance of recognizing the protein side chain cluster motifs interacting with the DNA, which could serve as signatures of protein-DNA recognition in the families of DNA binding proteins.

Project description:BackgroundRibosomal protein L30 belongs to the L7Ae family of RNA-binding proteins, which recognize diverse targets. L30 binds to kink-turn motifs in the 28S ribosomal RNA, L30 pre-mRNA, and mature L30 mRNA. L30 has a noncanonical function as a component of the UGA recoding machinery that incorporates selenocysteine (Sec) into selenoproteins during translation. L30 binds to a putative kink-turn motif in the Sec Insertion Sequence (SECIS) element in the 3' UTR of mammalian selenoprotein mRNAs. The SECIS also interacts with SECIS-binding protein 2 (SBP2), an essential factor for Sec incorporation. Previous studies showed that L30 and SBP2 compete for binding to the SECIS in vitro. The SBP2:SECIS interaction has been characterized but much less is known about how L30 recognizes the SECIS.ResultsHere we use enzymatic RNA footprinting to define the L30 binding site on the SECIS. Like SBP2, L30 protects nucleotides in the 5' side of the internal loop, the 5' side of the lower helix, and the SECIS core, including the GA tandem base pairs that are predicted to form a kink-turn. However, L30 has additional determinants for binding as it also protects nucleotides in the 3' side of the internal loop, which are not protected by SBP2. In support of the competitive binding model, we found that purified L30 repressed UGA recoding in an in vitro translation system, and that this inhibition was rescued by SBP2. To define the amino acid requirements for SECIS-binding, site-specific mutations in L30 were generated based on published structural studies of this protein in a complex with its canonical target, the L30 pre-mRNA. We identified point mutations that selectively inhibited binding of L30 to the SECIS, to the L30 pre-mRNA, or both RNAs, suggesting that there are subtle differences in how L30 interacts with the two targets.ConclusionsThis study establishes that L30 and SBP2 bind to overlapping but non-identical sites on the SECIS. The amino acid requirements for the interaction of L30 with the SECIS differ from those that mediate binding to the L30 pre-mRNA. Our results provide insight into how L7Ae family members recognize their cognate RNAs.

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Four distances between pairs of amino acids provide a precise description of their interaction.

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Four distances between pairs of amino acids provide a precise description of their interaction.

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