Bioinformatics Advance Access originally published online on January 25, 2005
Bioinformatics 2005 21(9):2110-2111; doi:10.1093/bioinformatics/bti276
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PERMOL: restraint-based protein homology modeling using DYANA or CNS
Institut für Biophysik und physikalische Biochemie, Universität Regensburg D-93040 Regensburg, Germany
*To whom correspondence should be addressed.
 |
Abstract |
|---|
 TOP Abstract INTRODUCTIONPROGRAM OVERVIEWPROGRAM DESCRIPTIONDISCUSSIONREFERENCES |
|---|
Summary: PERMOL is a new restraint-based program for homology modeling of proteins. Restraints are generated from the information contained in structures of homologous template proteins. Employing the restraints generated by PERMOL, three-dimensional structures are obtained using MD programs such as DYANA or CNS. In contrast to other programs PERMOL is mainly based on the use of dihedral angle information which is optimally suited to preserve the local secondary structure. The global arrangement of these elements is then facilitated by a small number of distance restraints. Using PERMOL homology, models of high quality are obtained. A key advantage of the proposed method is its flexibility, which allows the inclusion of data from other sources, such as experimental restraints and the use of modern molecular dynamics programs to calculate structures.
Availability: The software and a detailed manual are available free of charge (http://www.biologie.uni-regensburg.de/Biophysik/Kalbitzer/permol/permol.html)
Contact: hans-robert.kalbitzer{at}biologie.uni-regensburg.de
|
INTRODUCTION |
|---|
|
TOPAbstractINTRODUCTIONPROGRAM OVERVIEWPROGRAM DESCRIPTIONDISCUSSIONREFERENCES |
|---|
As significant advances in gene sequencing have been achieved in recent years, the gap between known sequences and protein structures is ever widening. While from 1999 to 2003 the number of sequences in the GenBank database (http://www.ncbi.nlm.nih.gov/Genbank) increased by a factor of 6.4, during the same time the number of structures stored in the Protein Data Bank (http://www.rcsb.org/pdb) rose only by a factor of 2.4. Clearly, experimental techniques for structure determination, notably X-ray crystallography and NMR spectroscopy, alone are not sufficient to fill this gap. In principle, computational approaches could be used to determine protein structures at a much faster pace. Noting that the ensemble of protein structures stored in the PDB only shows a remarkably limited number of different folds (SCOP database, http://www.scop.berkeley.edu), strategies based on homology modeling seem particularly rewarding.
Here, we present the program PERMOL which can be employed to generate protein homology models using restraint molecular dynamics (MD) simulation programs.
|
PROGRAM OVERVIEW |
|---|
|
TOPAbstractINTRODUCTIONPROGRAM OVERVIEWPROGRAM DESCRIPTIONDISCUSSIONREFERENCES |
|---|
Homology modeling with PERMOL is accomplished in several stages. Initial sequence alignment between the target sequence and the homologous template proteins is carried out with CLUSTAL_X (Thompson et al., 1997). In several modules, the PERMOL software evaluates the three-dimensional structures of the template proteins and derives different types of spatial restraints such as averaged dihedral angle restraints for use with the MD programs DYANA (Güntert et al., 1997) and CNS (Brünger et al., 1998), both of which are routinely used for structure determination by NMR spectroscopy. Simulated annealing runs yield an ensemble of homology structures. PERMOL is written in Perl/Tk (http://www.perl.org) and has been tested on Unix (IRIX), Suse Linux and various Windows systems (98, 2000 and XP).
|
PROGRAM DESCRIPTION |
|---|
|
TOPAbstractINTRODUCTIONPROGRAM OVERVIEWPROGRAM DESCRIPTIONDISCUSSIONREFERENCES |
|---|
As input, PERMOL takes one or several protein structures in the PDB format and a text file containing the sequence of the target protein in one-letter code. Using CLUSTAL_X the sequences of the homologous template proteins are aligned to the target sequence. The resulting alignment is imported by PERMOL. Within three separate program modules different kinds of restraints are generated from the spatial information contained in the template structures: dihedral angles, interatomic distances and hydrogen bonds are automatically translated into restraints for MD runs. A graphical user interface shows the aligned sequences with the individual residues colored depending on their degree of sequence conservation. Restraints are generated only for the residues which have been selected before. Amino acids can be selected or deselected either individually or as a class based on their degree of sequence conservation. After appropriate selection, the template structures are evaluated and spatial properties, e.g. dihedral angles, are computed. Finally, from these data restraints are generated. Several options are available that control how the spatial information is translated into restraints. For example, the restraint for a specific dihedral angle can be defined as the mean value observed in the template structures for this angle plus/minus the corresponding standard deviation. The individual restraints are weighted relative to each other according to the degree of homology of the amino acid residues involved. Output files can be created for use with either DYANA or CNS. Standard simulated annealing protocols in torsion angle space are used to calculate an ensemble of structures. From these the best in terms of the MD target function are selected as the homology model of the target protein.
|
DISCUSSION |
|---|
|
TOPAbstractINTRODUCTIONPROGRAM OVERVIEWPROGRAM DESCRIPTIONDISCUSSIONREFERENCES |
|---|
As an example we used PERMOL along with DYANA to calculate a homology structure for the HPr protein from Escherichia coli. Comparison with the experimentally determined X-ray structure (Jia et al., 1993) yielded a value of 0.15 nm for the root mean square deviation of the backbone atom positions in the two structures. PERMOL was also successfully tested on the ligand-binding domain of human nuclear receptor PPAR
(Uppenberg et al., 1998). A related approach for homology modeling was published by Sali and Blundell (1993). In their program MODELLER spatial restraints are expressed as so-called probability density functions that are derived from structural features observed in homologous proteins. In some respects the PERMOL approach is also related to the program for fold prediction of helical proteins recently published by Zhang et al. (2002). Here, however, restraints are not derived from template proteins but are predicted based on primary and secondary structure of the target protein. Other previously published programs utilizing restrained molecular dynamics simulations include, for example, the programs by Kolinski et al. (2001) and Brocklehurst and Perham (1993). The high quality of the homology models we generated demonstrates that MD programs used for NMR structure determination can also be employed for the purpose of homology modeling. Using the graphical user interface of PERMOL, full control over which restraints enter the modeling process is retained. As the created restraint files are text files, they can be easily edited and joined with data from other sources. Thus we believe that PERMOL could also be particularly useful in the context of NMR structure determination. Homology models could help in the process of resonance and NOE cross-peak assignment, as well as in the analysis of residual dipolar couplings. The modeled structures can be validated by comparison with experimental data. Further, incomplete experimental data could be combined with spatial restraints derived from template proteins to yield reasonable structures. Recently, PERMOL has been successfully employed for the determination of the solution structure of a mutant form of HPr from Staphylococcus carnosus (Möglich et al., 2004). A modified version ofPERMOL has also been incorporated into the NMR program suite AUREMOL (Gronwald and Kalbitzer, 2004).
|
Acknowledgments |
|---|
The authors thank Dr R. Döker and Dr W. Kremer for helpful discussions. Financial support by the European Union is gratefully acknowledged.
Received on September 14, 2004; revised on January 13, 2005; accepted on January 13, 2005
|
REFERENCES |
|---|
|
TOPAbstractINTRODUCTIONPROGRAM OVERVIEWPROGRAM DESCRIPTIONDISCUSSIONREFERENCES |
|---|
Brocklehurst, S.M. and Perham, R.N. (1993) Prediction of the three-dimensional structures of the biotinylated domain from yeast pyruvate carboxylase and of the lipoylated H-protein from the pea leaf glycine cleavage system: a new automated method for the prediction of protein tertiary structure. Prot. Sci., 2, 626–639[Web of Science][Medline].
Brünger, A.T., Adams, P.D., Clore, G.M., DeLano, W.L., Gros, P., Grossekunstleve, R.W., Jiang, J.S., Kuszewski, J., Nilges, M., Pannu, N.S., et al. (1998) Crystallography & NMR system: a new software suite for macromolecular structure determination. Acta Cryst., D54, 905–921.
Gronwald, W. and Kalbitzer, H.R. (2004) Automated structure determination of proteins by NMR spectroscopy. Prog. NMR Spectrosc., 44, 33–96.
Güntert, P., Mumenthaler, C., Wüthrich, K. (1997) Torsion angle dynamics for NMR structure calculation with the new program DYANA. J. Mol. Biol., 273, 283–298[CrossRef][Web of Science][Medline].
Jia, Z., Quail, J.W., Waygood, E.B., Delbaere, L.T. (1993) The 2.0-A resolution structure of Escherichia coli histidine-containing phosphocarrier protein HPr. A redetermination. J. Biol. Chem., 268, 22490–22501
Kolinski, A., Betancourt, M.R., Kihara, D., Rotkiewicz, P., Skolnick, J. (2001) Generalized comparitive modeling (GENECOMP): a combination of sequence comparison, threading, and lattice modeling for protein structure prediction and refinement. Proteins, 44, 133–149[CrossRef][Web of Science][Medline].
Möglich, A., Koch, B., Hengstenberg, W., Brunner, E., Gronwald, W., Kalbitzer, H.R. (2004) Solution Structure of the Active-Centre Mutant Ile14Ala of the Histidine-Containing Phosphocarrier Protein (HPr) from Staphylococcus Carnosus. Eur. J. Biochem., 271, 4815–4824[Web of Science][Medline].
Sali, A. and Blundell, T.L. (1993) Comparitive protein modelling by satisfaction of spatial restraints. J. Mol. Biol., 234, 779–815[CrossRef][Web of Science][Medline].
Thompson, J.D., Gibson, T.J., Plewniak, F., Jeanmougin, F., Higgins, D.G. (1997) The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res., 25, 4876–4882
Uppenberg, J., Svensson, C., Jaki, M., Bertilsson, G., Jendeberg, L., Berkenstam, A. (1998) Crystal structure of the ligand binding domain of the human nuclear receptor PPAR. J. Biol. Chem, 273, 31108–31112
Zhang, C., Hou, J., Kim, S.-H. (2002) Fold prediction of helical proteins using torsion angle dynamics and predicted restraints. Proc. Natl Acad. Sci. USA, 99, 3581–3585
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  H. R. A. Jonker, S. Ilin, S. K. Grimm, J. Wohnert, and H. Schwalbe L11 domain rearrangement upon binding to RNA and thiostrepton studied by NMR spectroscopy Nucleic Acids Res., January 28, 2007; 35(2): 441 - 454. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||