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HAAD: A quick algorithm for accurate prediction of hydrogen atoms in protein structures.

Li Y, Roy A, Zhang Y - PLoS ONE (2009)

Bottom Line: Compared with the widely used programs CHARMM and REDUCE, HAAD has a significantly higher accuracy, with the average RMSD of the predicted hydrogen atoms to the X-ray and neutron diffraction structures decreased by 26% and 11%, respectively.The average CPU cost by HAAD is 18 and 8 times lower than that of CHARMM and REDUCE, respectively.The significant advantage of HAAD in both the accuracy and the speed of the hydrogen additions should make HAAD a useful tool for the detailed study of protein structure and function.

View Article: PubMed Central - PubMed

Affiliation: Center for Bioinformatics and Department of Molecular Bioscience, University of Kansas, Lawrence, Kansas, USA.

ABSTRACT
Hydrogen constitutes nearly half of all atoms in proteins and their positions are essential for analyzing hydrogen-bonding interactions and refining atomic-level structures. However, most protein structures determined by experiments or computer prediction lack hydrogen coordinates. We present a new algorithm, HAAD, to predict the positions of hydrogen atoms based on the positions of heavy atoms. The algorithm is built on the basic rules of orbital hybridization followed by the optimization of steric repulsion and electrostatic interactions. We tested the algorithm using three independent data sets: ultra-high-resolution X-ray structures, structures determined by neutron diffraction, and NOE proton-proton distances. Compared with the widely used programs CHARMM and REDUCE, HAAD has a significantly higher accuracy, with the average RMSD of the predicted hydrogen atoms to the X-ray and neutron diffraction structures decreased by 26% and 11%, respectively. Furthermore, hydrogen atoms placed by HAAD have more matches with the NOE restraints and fewer clashes with heavy atoms. The average CPU cost by HAAD is 18 and 8 times lower than that of CHARMM and REDUCE, respectively. The significant advantage of HAAD in both the accuracy and the speed of the hydrogen additions should make HAAD a useful tool for the detailed study of protein structure and function. Both an executable and the source code of HAAD are freely available at http://zhang.bioinformatics.ku.edu/HAAD.

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The average number of atom clashes made by hydrogen atoms in various categories, in models of 37 protein structures.The dashed line marks the boundary between X-ray (left) and neutron diffraction structures (right).
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pone-0006701-g004: The average number of atom clashes made by hydrogen atoms in various categories, in models of 37 protein structures.The dashed line marks the boundary between X-ray (left) and neutron diffraction structures (right).

Mentions: The number of atomic clashes between the predicted H-atoms and other atoms for all the 37 high resolution structures are shown in Fig. 4 and the average values are summarized in Table 5. Some of the structures solved by neutron diffraction have an Npolar equal to 0 because no polar H-atom is compared in these structures. On average, for all the H-atoms, the experimental structures have the lowest average number of atomic clashes, i.e. Nall = 1.48. The number of clashing atoms in structures generated by HAAD is 2% higher than that in the experimental structures, but 5% lower than that in models from HBUILD and 6% lower than that in models from REDUCE.


HAAD: A quick algorithm for accurate prediction of hydrogen atoms in protein structures.

Li Y, Roy A, Zhang Y - PLoS ONE (2009)

The average number of atom clashes made by hydrogen atoms in various categories, in models of 37 protein structures.The dashed line marks the boundary between X-ray (left) and neutron diffraction structures (right).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2724740&req=5

pone-0006701-g004: The average number of atom clashes made by hydrogen atoms in various categories, in models of 37 protein structures.The dashed line marks the boundary between X-ray (left) and neutron diffraction structures (right).
Mentions: The number of atomic clashes between the predicted H-atoms and other atoms for all the 37 high resolution structures are shown in Fig. 4 and the average values are summarized in Table 5. Some of the structures solved by neutron diffraction have an Npolar equal to 0 because no polar H-atom is compared in these structures. On average, for all the H-atoms, the experimental structures have the lowest average number of atomic clashes, i.e. Nall = 1.48. The number of clashing atoms in structures generated by HAAD is 2% higher than that in the experimental structures, but 5% lower than that in models from HBUILD and 6% lower than that in models from REDUCE.

Bottom Line: Compared with the widely used programs CHARMM and REDUCE, HAAD has a significantly higher accuracy, with the average RMSD of the predicted hydrogen atoms to the X-ray and neutron diffraction structures decreased by 26% and 11%, respectively.The average CPU cost by HAAD is 18 and 8 times lower than that of CHARMM and REDUCE, respectively.The significant advantage of HAAD in both the accuracy and the speed of the hydrogen additions should make HAAD a useful tool for the detailed study of protein structure and function.

View Article: PubMed Central - PubMed

Affiliation: Center for Bioinformatics and Department of Molecular Bioscience, University of Kansas, Lawrence, Kansas, USA.

ABSTRACT
Hydrogen constitutes nearly half of all atoms in proteins and their positions are essential for analyzing hydrogen-bonding interactions and refining atomic-level structures. However, most protein structures determined by experiments or computer prediction lack hydrogen coordinates. We present a new algorithm, HAAD, to predict the positions of hydrogen atoms based on the positions of heavy atoms. The algorithm is built on the basic rules of orbital hybridization followed by the optimization of steric repulsion and electrostatic interactions. We tested the algorithm using three independent data sets: ultra-high-resolution X-ray structures, structures determined by neutron diffraction, and NOE proton-proton distances. Compared with the widely used programs CHARMM and REDUCE, HAAD has a significantly higher accuracy, with the average RMSD of the predicted hydrogen atoms to the X-ray and neutron diffraction structures decreased by 26% and 11%, respectively. Furthermore, hydrogen atoms placed by HAAD have more matches with the NOE restraints and fewer clashes with heavy atoms. The average CPU cost by HAAD is 18 and 8 times lower than that of CHARMM and REDUCE, respectively. The significant advantage of HAAD in both the accuracy and the speed of the hydrogen additions should make HAAD a useful tool for the detailed study of protein structure and function. Both an executable and the source code of HAAD are freely available at http://zhang.bioinformatics.ku.edu/HAAD.

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