Interhelical angle and distance preferences in globular proteins. 2004

Sangyoon Lee, and Gregory S Chirikjian
Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA.

Orientational preferences between interacting helices within globular proteins have been studied extensively over the years. A number of classical structural models such as "knobs into holes" and "ridges into grooves" were developed decades ago to explain perceived preferences in interhelical angle distributions. In contrast, relatively recent works have examined statistical biases in angular distributions which result from spherical geometric effects. Those works have concluded that the predictions of classical models are due in large part to these biases. In this article we perform an analysis on the largest set of helix-helix interactions within high-resolution structures of nonhomologous proteins studied to date. We examine the interhelical angle distribution as a function of spatial distance between helix pairs. We show that previous efforts to normalize angle distribution data did not include two important effects: 1), helices can interact with each other in three distinct ways which we refer to as "line-on-line," "endpoint-to-line," and "endpoint-to-endpoint," and each of these interactions has its own geometric effects which must be included in the proper normalization of data; and 2), all normalizations that depend on geometric parameters such as interhelical angle must occur before the data is binned to avoid artifacts of bin size from biasing the conclusions. Taking these two points into account, we find that there are very pronounced preferences for helices to interact at angles of approximately +/-160 and +/-20 degrees in the line-on-line case. This pattern persists when the closest alpha-carbons in the helices vary from 4 to 12 A. The endpoint-to-line and endpoint-to-endpoint cases also exhibit distinct preferences when the data is normalized properly. Analysis of the local structural interactions which give rise to these preferences has not been studied here and is left for future work.

UI MeSH Term Description Entries
D008958 Models, Molecular Models used experimentally or theoretically to study molecular shape, electronic properties, or interactions; includes analogous molecules, computer-generated graphics, and mechanical structures. Molecular Models,Model, Molecular,Molecular Model
D011487 Protein Conformation The characteristic 3-dimensional shape of a protein, including the secondary, supersecondary (motifs), tertiary (domains) and quaternary structure of the peptide chain. PROTEIN STRUCTURE, QUATERNARY describes the conformation assumed by multimeric proteins (aggregates of more than one polypeptide chain). Conformation, Protein,Conformations, Protein,Protein Conformations
D011506 Proteins Linear POLYPEPTIDES that are synthesized on RIBOSOMES and may be further modified, crosslinked, cleaved, or assembled into complex proteins with several subunits. The specific sequence of AMINO ACIDS determines the shape the polypeptide will take, during PROTEIN FOLDING, and the function of the protein. Gene Products, Protein,Gene Proteins,Protein,Protein Gene Products,Proteins, Gene
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D017433 Protein Structure, Secondary The level of protein structure in which regular hydrogen-bond interactions within contiguous stretches of polypeptide chain give rise to ALPHA-HELICES; BETA-STRANDS (which align to form BETA-SHEETS), or other types of coils. This is the first folding level of protein conformation. Secondary Protein Structure,Protein Structures, Secondary,Secondary Protein Structures,Structure, Secondary Protein,Structures, Secondary Protein
D017510 Protein Folding Processes involved in the formation of TERTIARY PROTEIN STRUCTURE. Protein Folding, Globular,Folding, Globular Protein,Folding, Protein,Foldings, Globular Protein,Foldings, Protein,Globular Protein Folding,Globular Protein Foldings,Protein Foldings,Protein Foldings, Globular
D030562 Databases, Protein Databases containing information about PROTEINS such as AMINO ACID SEQUENCE; PROTEIN CONFORMATION; and other properties. Amino Acid Sequence Databases,Databases, Amino Acid Sequence,Protein Databases,Protein Sequence Databases,SWISS-PROT,Protein Structure Databases,SwissProt,Database, Protein,Database, Protein Sequence,Database, Protein Structure,Databases, Protein Sequence,Databases, Protein Structure,Protein Database,Protein Sequence Database,Protein Structure Database,SWISS PROT,Sequence Database, Protein,Sequence Databases, Protein,Structure Database, Protein,Structure Databases, Protein

Related Publications

Sangyoon Lee, and Gregory S Chirikjian
December 1994, Journal of biomolecular structure & dynamics,
Sangyoon Lee, and Gregory S Chirikjian
October 1978, Biochemistry,
Sangyoon Lee, and Gregory S Chirikjian
January 1976, Doklady Akademii nauk SSSR,
Sangyoon Lee, and Gregory S Chirikjian
June 2004, Proteins,
Sangyoon Lee, and Gregory S Chirikjian
May 1995, Protein science : a publication of the Protein Society,
Sangyoon Lee, and Gregory S Chirikjian
February 2014, Biophysical journal,
Sangyoon Lee, and Gregory S Chirikjian
January 1998, Biofizika,
Sangyoon Lee, and Gregory S Chirikjian
March 2003, Journal of molecular biology,
Sangyoon Lee, and Gregory S Chirikjian
March 2004, FEBS letters,
Copied contents to your clipboard!