Amino/aromatic interactions

Mitchell, John B. O.; Nandi, C. Lilian; Ali, Shamimara; McDonald, Ian K.; Thornton, Janet; Price, Sarah L.; Singh, Juswinder

doi:10.1038/366413a0

Cited by 59 publications

(42 citation statements)

References 7 publications

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“…Amino-interactions, where an amino side-chain stack on top of an aromatic group, have been shown to be favored in protein-protein interactions and in protein-base interactions (40,43,44). Gln 218, for example, presents a similar structure to the RecQ arginine in the hexameric ATPase P4 of dsRNA bacteriophage phi12 (45).…”

Section: Resultsmentioning

confidence: 99%

A binding mechanism in protein–nucleotide interactions: Implication for U1A RNA binding

Guallar

Borrelli

2005

Proc. Natl. Acad. Sci. U.S.A.

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We present a close electronic view of the protein-base interface for the N-terminal domain of the human protein U1A. Combining accurate mixed quantum mechanics͞molecular mechanics techniques and protein structure prediction methods, we provide a detailed electronic structure description of the protein-RNA stacking interactions. Our analysis indicates the evolution of the protein structure optimizing the interaction between Asp-92 and the RNA bases. The results show a direct coupling of the C-terminal tail and Asp-92, providing a direct rationalization of the experimentally determined role of the C-terminal domain in RNA binding. Here, we propose a mechanism where a protein side chain, with a delocalized electronic pi system, assists in the nucleotide binding. The binding mechanism involves a short-range interaction of the side chain with the nucleotide base and an electronic long-range interaction through a sandwich-stacking motif. The structural motif of the binding mechanism is observed in similar protein-RNA interactions and in various protein-ATP-binding sites.ATP binding ͉ quantum mechanics͞molecular mechanics ͉ stacking ͉ aromatic T he mechanisms of protein-nucleotide association constitute a central intermolecular interaction. Such mechanisms, for example, regulate DNA, RNA, and NTP recognition and binding. As pointed out recently by Williamson (1), there is a large complexity of induced fit processes, requiring conformational change in the proteins, in the ligands, or in both. These dynamical processes, responsible for the induced affinity and specificity, are far from being understood. A common feature in ssDNA, RNA, and NTP binding is the direct interaction of the protein with the nucleotides' bases. Recent structural analyses have underlined the main features involved in these protein-base interactions (2, 3). These studies revealed the importance of van der Waal interactions, aromatic stacking interactions in particular, in the stabilization of the protein-base interaction.The ribonucleoprotein domain, also known as the RNAbinding domain or the RNA-recognition motif, binds RNA by using extensive interactions through its characteristic fourstranded ␤-sheet structure (Fig. 1). Among the members of this motif, the N-terminal domain of the human protein U1A is the most studied (4-29). The isolated domain binds to a short RNA hairpin with high affinity and specificity. The importance of stacking interactions in RNA binding is confirmed by the aromatic nature of three of the most highly conserved residues in the RNA-recognition motif (30). Baranger and coworkers (11) recently obtained 5.5 kcal͞mol destabilization of the protein-RNA complex when mutating Phe-56 to alanine. Subsequent studies by the same group indicated that stacking (hydrophobic) interactions are able to compensate for the loss of hydrogenbonding-capable functional groups in the RNA bases (5). Recent kinetic data by Laird-Offringa and coworkers (6) supported a rapid initial association based on electrostatic interactions, followed by a subs...

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Section: Resultsmentioning

confidence: 99%

A binding mechanism in protein–nucleotide interactions: Implication for U1A RNA binding

Guallar

Borrelli

2005

Proc. Natl. Acad. Sci. U.S.A.

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“…Table 2 summarize the counts for each dihedral category, 00 < a < 300, 300 < a < 600, and 600 < a < 900. Blundell et al (16) and Mitchell et al (19) emphasize their nonrandom nature relative to aromatic-aromatic and cationic-aromatic planar dispositions. We highlight (large boldface numbers) and venture some interpretations on the statistics of Table 2.…”

Section: In Rpmentioning

confidence: 99%

“…The dihedral angles between interacting phenylalanine side-chain rings in globular proteins showed an approximate random distribution (15,16). In contrast, aromatic rings tend to approach the planar guanidinium group of arginine in a parallel stacking fashion, where the line connecting the centers of the planar sections is approximately orthogonal to each plane (19). Amide group-phenyl planar arrangements strive to be parallel, but the nitrogen atom of the amide group is located at or beyond the ring edge (2).…”

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confidence: 99%

Geometry of interplanar residue contacts in protein structures.

Brocchieri

Karlin

1994

Proc. Natl. Acad. Sci. U.S.A.

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The relative spatial d tin of interns side-chain planar groups (aromatic, u niin, amide, carboxyl, imidaole) is analyzed for 186 non-homologous wellresolved protein structures. The dihedral angle of amide or carboxyl planar groups with other planar groups accords with a random distribution of planes. By contrast, the dihedral angle ofthe planes between close aromatic rings or ofthe hie ring Interacting with aromatic residues is gnlcany nandom, showing an approximately uniform distribution. Our results indicate that edge-to-edge and edge-to-center spatial dsoions of residue planar sections are prevalent, while c pte s ig configurations are uncommon. The hypothesis that eleo atic forces are a major determinant of the geometry of interactions between side-chain planar groups is dis s.

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“…There have been numerous studies of specialized protein structural features that have been performed over a large set of structures (such as sulfuraromatic interactions (Reid et al, 1985), amino-aromatic interactions (Mitchell et al, 1994), ion pairs (Barlow & Thornton, 1986), distribution of charge (Barlow & Thornton, 1986), distribution of hydropathy (Korn & Burnett, 1991), anion-ligand interactions (Chakrabarti, 1990a(Chakrabarti, , 1990b(Chakrabarti, , 1993(Chakrabarti, , 1994, patterns of hydration (Roe & Teeter, 1993), protein side-chain interactions (Singh & Thornton [1992] and others). For each of these studies, a standard coordinate system (or frame of reference) was chosen in order to provide the most useful perspective on the data.…”

mentioning

confidence: 99%

Characterizing the microenvironment surrounding protein sites

1995

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Sites are microenvironments within a biomolecular structure, distinguished by their structural or functional role. A site can be defined by a three-dimensional location and a local neighborhood around this location in which the structure or function exists. We have developed a computer system to facilitate structural analysis (both qualitative and quantitative) of biomolecular sites. Our system automatically examines the spatial distributions of biophysical and biochemical properties, and reports those regions within a site where the distribution of these properties differs significantly from control nonsites. The properties range from simple atom-based characteristics such as charge to polypeptide-based characteristics such as type of secondary structure. Our analysis of sites uses nonsites as controls, providing a baseline for the quantitative assessment of the significance of the features that are uncovered. In this paper, we use radial distributions of properties to study three well-known sites (the binding sites for calcium, the milieu of disulfide bridges, and the serine protease active site). We demonstrate that the system automatically finds many of the previously described features of these sites and augments these features with some new details. In some cases, we cannot confirm the statistical significance of previously reported features. Our results demonstrate that analysis of protein structure is sensitive to assumptions about background distributions, and that these distributions should be considered explicitly during structural analyses.Keywords: biophysical properties; calcium binding; computational biology; disulfide bridges; microenvironment; protein structure analysis; serine proteases; software Central to molecular biology is the determination of macromolecular structure and the analysis of how structural elements produce an observed function. The principles by which structure relates to function have been elucidated in a piecemeal fashion, from work on single structures or small classes of structures. Computational assistance has come primarily in the form of graphical methods for scientific visualization and from special purpose programs for analyzing individual biophysical properties (such as solvent accessibility or electrostatic fields). Unfortunately, studying structures individually entails a risk of missing important relationships that would be revealed by pooling relevant data. The expected surfeit of protein structures provides an opportunity to develop tools for automatically examining biological structures and producing useful representations of the key biophysical and biochemical features. The utility of a general purpose system for producing these representations would extend from medical/pharmaceutical applications (model-based drug design, comparing pharmacological Reprint requests to: Russ B. Altman, Section on Medical Informatics, Stanford University School of Medicine, MSOB X-215, Stanford, California 94305-5479; e-mail: altman@camis.stanford.edu. activities) to ind...

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Amino/aromatic interactions

Cited by 59 publications

References 7 publications

A binding mechanism in protein–nucleotide interactions: Implication for U1A RNA binding

A binding mechanism in protein–nucleotide interactions: Implication for U1A RNA binding

Geometry of interplanar residue contacts in protein structures.

Characterizing the microenvironment surrounding protein sites

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