1 4 Fe b 20 05 Recoverable One-dimensional Encoding of Protein Three-dimensional Structures

Protein one-dimensional (1D) structures such as secondary structure and contact number provide intuitive pictures to understand how the native three-dimensional (3D) structure of a protein is encoded in the amino acid sequence. However, it has not been clear whether a given set of 1D structures contains sufficient information for recovering the underlying 3D structure. Here we show that the 3D structure of a protein can be recovered from a set of three types of 1D structures, namely, secondary structure, contact number and residue-wise contact order which is introduced here for the first time. Using simulated annealing molecular dynamics simulations, the structures satisfying the given native 1D structural restraints were sought for 16 proteins of various structural classes and of sizes ranging from 56 to 146 residues. By selecting the structures best satisfying the restraints, all the proteins showed a coordinate RMS deviation of less than 4Å from the native structure, and for most of them, the deviation was even less than 2Å. The present result opens a new possibility to protein structure prediction and our understanding of the sequence-structure relationship.

[1]  Akira R. Kinjo,et al.  Predicting secondary structures, contact numbers, and residue-wise contact orders of native protein structures from amino acid sequences using critical random networks , 2005, Biophysics.

[2]  D. Baker,et al.  Contact order, transition state placement and the refolding rates of single domain proteins. , 1998, Journal of molecular biology.

[3]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[4]  W. Kabsch,et al.  Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features , 1983, Biopolymers.

[5]  M Vendruscolo,et al.  Recovery of protein structure from contact maps. , 1997, Folding & design.

[6]  D. Landau,et al.  Efficient, multiple-range random walk algorithm to calculate the density of states. , 2000, Physical review letters.

[7]  M Vendruscolo,et al.  Statistical properties of contact vectors. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[8]  Timothy F. Havel.  An evaluation of computational strategies for use in the determination of protein structure from distance constraints obtained by nuclear magnetic resonance. , 1991, Progress in biophysics and molecular biology.

[9]  Michele Vendruscolo,et al.  Reconstruction of protein structures from a vectorial representation. , 2004, Physical review letters.

[10]  P. Kraulis.  A program to produce both detailed and schematic plots of protein structures , 1991 .

[11]  H Nakamura,et al.  Intrinsic nature of the three-dimensional structure of proteins as determined by distance geometry with good sampling properties , 1993, Journal of biomolecular NMR.

[12]  K. Nishikawa,et al.  Predicting absolute contact numbers of native protein structure from amino acid sequence , 2004, Proteins.

[13]  Burkhard Rost,et al.  Prediction in 1D: secondary structure, membrane helices, and accessibility. , 2003, Methods of biochemical analysis.

[14]  P. Kollman,et al.  An all atom force field for simulations of proteins and nucleic acids , 1986, Journal of computational chemistry.

[15]  Akira R. Kinjo,et al.  Predicting Residue-wise Contact Orders of Native Protein Structure from Amino Acid Sequence , 2005 .