MODELLER

Last updated
Modeller
Original author(s) Andrej Sali
Developer(s) University of California, San Francisco, Accelrys
Initial release1989;35 years ago (1989)
Stable release
10.3 / July 13, 2022;23 months ago (2022-07-13) [1]
Operating system Unix, Linux, macOS, Windows
Platform x86, x86-64
Available inEnglish
Type homology modeling of proteins
License Proprietary: academic nonprofit freeware, commercial software
Website www.salilab.org/modeller/

Modeller, often stylized as MODELLER, is a computer program used for homology modeling to produce models of protein tertiary structures and quaternary structures (rarer). [2] [3] It implements a method inspired by nuclear magnetic resonance spectroscopy of proteins (protein NMR), termed satisfaction of spatial restraints , by which a set of geometrical criteria are used to create a probability density function for the location of each atom in the protein. The method relies on an input sequence alignment between the target amino acid sequence to be modeled and a template protein which structure has been solved.

Contents

The program also incorporates limited functions for ab initio structure prediction of loop regions of proteins, which are often highly variable even among homologous proteins and thus difficult to predict by homology modeling.

Modeller was originally written and is currently maintained by Andrej Sali at the University of California, San Francisco. [4] It runs on the operating systems Unix, Linux, macOS, and Windows. It is freeware for academic use. Graphical user interfaces (GUIs) and commercial versions are distributed by Accelrys. The ModWeb comparative protein structure modeling webserver is based on Modeller and other tools for automatic protein structure modeling, with an option to deposit the resulting models into ModBase. Due to Modeller's popularity, several third party GUIs for MODELLER are available:

See also

Related Research Articles

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Protein secondary structure is the local spatial conformation of the polypeptide backbone excluding the side chains. The two most common secondary structural elements are alpha helices and beta sheets, though beta turns and omega loops occur as well. Secondary structure elements typically spontaneously form as an intermediate before the protein folds into its three dimensional tertiary structure.

<span class="mw-page-title-main">Protein structure prediction</span> Type of biological prediction

Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure. Structure prediction is different from the inverse problem of protein design. Protein structure prediction is one of the most important goals pursued by computational biology; it is important in medicine and biotechnology.

<span class="mw-page-title-main">Structural bioinformatics</span> Bioinformatics subfield

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<span class="mw-page-title-main">PyMOL</span> Biology structure visualization software

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<span class="mw-page-title-main">Avogadro (software)</span>

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FoldX is a protein design algorithm that uses an empirical force field. It can determine the energetic effect of point mutations as well as the interaction energy of protein complexes. FoldX can mutate protein and DNA side chains using a probability-based rotamer library, while exploring alternative conformations of the surrounding side chains.

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ModBase is a database of annotated comparative protein structure models, containing models for more than 3.8 million unique protein sequences. Models are created by the comparative modeling pipeline ModPipe which relies on the MODELLER program.

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<span class="mw-page-title-main">Backbone-dependent rotamer library</span> Collection of data on conformations of a given proteins amino acid side chains

In biochemistry, a backbone-dependent rotamer library provides the frequencies, mean dihedral angles, and standard deviations of the discrete conformations of the amino acid side chains in proteins as a function of the backbone dihedral angles φ and ψ of the Ramachandran map. By contrast, backbone-independent rotamer libraries express the frequencies and mean dihedral angles for all side chains in proteins, regardless of the backbone conformation of each residue type. Backbone-dependent rotamer libraries have been shown to have significant advantages over backbone-independent rotamer libraries, principally when used as an energy term, by speeding up search times of side-chain packing algorithms used in protein structure prediction and protein design.

References

  1. "MODELLER News". salilab.org. Retrieved 2022-11-02.
  2. Fiser A, Sali A (2003). "Modeller: Generation and Refinement of Homology-Based Protein Structure Models". Macromolecular Crystallography, Part D. Methods in Enzymology. Vol. 374. pp. 461–91. doi:10.1016/S0076-6879(03)74020-8. ISBN   9780121827779. PMID   14696385.
  3. Martí-Renom MA, Stuart AC, Fiser A, Sánchez R, Melo F, Sali A (2000). "Comparative protein structure modeling of genes and genomes". Annu Rev Biophys Biomol Struct. 29: 291–325. doi:10.1146/annurev.biophys.29.1.291. PMID   10940251.
  4. Sali A, Blundell TL (December 1993). "Comparative protein modelling by satisfaction of spatial restraints". J. Mol. Biol. 234 (3): 779–815. doi:10.1006/jmbi.1993.1626. PMID   8254673.
  5. Kuntal, B. K., Aparoy, P., & Reddanna, P. (2010). EasyModeller: A graphical interface to MODELLER. BMC research notes, 3(1), 1.
  6. Janson G, Zhang C, Prado MG, Paiardini A (2017). "PyMod 2.0: improvements in protein sequence-structure analysis and homology modeling within PyMOL". Bioinformatics. 33 (3): 444–446. doi: 10.1093/bioinformatics/btw638 . PMID   28158668.
  7. Bramucci E, Paiardini A, Bossa F, Pascarella S (2012). "PyMod: sequence similarity searches, multiple sequence-structure alignments, and homology modeling within PyMOL". BMC Bioinformatics. 13 (Suppl 4): S2. doi: 10.1186/1471-2105-13-S4-S2 . PMC   3303726 . PMID   22536966.
  8. Parida BK, Panda PK, Misra N, Mishra BK (2015). "MaxMod: a hidden Markov model based novel interface to MODELLER for improved prediction of protein 3D models". Journal of Molecular Modeling. 21 (2): 1–10. doi:10.1007/s00894-014-2563-3. PMID   25636267. S2CID   30626573.