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| MODELLER | |
|---|---|
| Name | MODELLER |
| Developer | Salvador Sali / UNC |
| Released | 1989 |
| Latest release | 10.6 |
| Programming language | Python, Fortran |
| Operating system | Unix, Linux, macOS, Windows |
| License | Proprietary academic |
MODELLER
MODELLER is a widely used computational tool for comparative protein structure modeling created to generate three-dimensional models of proteins from their amino acid sequences and known homologous structures. It is commonly employed in structural biology, bioinformatics, and drug discovery workflows to predict protein conformations, assist in homology modeling, and support integrative modelling efforts across experimental platforms.
MODELLER performs comparative modeling by satisfaction of spatial restraints derived from known template structures such as those deposited in the Protein Data Bank or reported in literature by groups at institutions like European Molecular Biology Laboratory and RCSB PDB. The program integrates scripting via Python (programming language) and numerical routines historically implemented in Fortran (programming language), enabling users from labs at University of California, San Francisco, Stanford University, and Harvard University to incorporate MODELLER into pipelines that also use tools from European Bioinformatics Institute, National Center for Biotechnology Information, and vendors like Schrödinger (company). MODELLER has influenced methods referenced by research from laboratories at Massachusetts Institute of Technology and clinical research centers such as Mayo Clinic.
MODELLER was principally developed by Salvador Sali while affiliated with the University of California, San Francisco and later distributed via collaborations with groups at the Salk Institute and the Scripps Research Institute. Early versions built upon algorithms introduced in the late 1980s and 1990s, contemporaneous with structural studies led at facilities like Brookhaven National Laboratory and Argonne National Laboratory. Successive releases incorporated community feedback from users at institutions including Max Planck Society, Cold Spring Harbor Laboratory, and universities across Europe such as University of Oxford and University of Cambridge. MODELLER’s evolution paralleled growth in databases like UniProt and initiatives such as the Human Genome Project.
MODELLER’s core methodology relies on alignment-based spatial restraint generation and optimization using techniques related to comparative modeling frameworks described by groups at European Molecular Biology Laboratory and computational laboratories at University of California, San Diego. It uses statistical potentials and probability density functions similar in spirit to energy functions developed in computational chemistry groups at Dow Chemical Company and algorithmic advances from researchers at IBM Research. Conformational sampling is guided by restrained optimization procedures that draw on numerical methods taught at institutions such as Massachusetts Institute of Technology and algorithmic work from Bell Labs. MODELLER accommodates multiple template alignments generated by alignment programs from projects at European Bioinformatics Institute, EMBL-EBI, and software developed by researchers at Tokyo Institute of Technology.
MODELLER supports automated model building, loop refinement, and modeling of multi-chain complexes, enabling integration with refinement tools used by groups at Lawrence Berkeley National Laboratory and visualization systems developed by teams at University of California, San Diego and Johns Hopkins University. It offers a programmable Python (programming language) interface compatible with pipelines at bioinformatics centers like Broad Institute and resources provided by National Institutes of Health. Capabilities include handling of custom restraints introduced in structural studies from laboratories at University of Washington and compatibility with validation metrics utilized by reviewers at journals such as Nature, Science (journal), and Cell (journal). MODELLER can be combined with docking suites produced by companies like AutoDock (Scripps Research) and molecular dynamics packages originating from researchers at University of Illinois Urbana-Champaign.
MODELLER is applied in structure prediction projects undertaken by consortia such as CASP and in applied research at pharmaceutical companies like Pfizer, Novartis, and GlaxoSmithKline. Academic groups at Yale University and University of Toronto use it for modeling enzyme active sites in studies linked to discoveries reported in Proceedings of the National Academy of Sciences. MODELLER supports integrative structural biology efforts combining cryo-EM maps from facilities like European Synchrotron Radiation Facility and crystallography datasets produced at synchrotrons including Diamond Light Source. It is used in antigen modeling in immunology research at centers such as Pasteur Institute and in metabolic enzyme modeling at institutes like Max Delbrück Center.
Validation of MODELLER-generated models commonly employs assessment tools developed by groups at Uppsala University, University of Basel, and the Swiss Institute of Bioinformatics as well as metrics popularized in community benchmarks such as CASP and structural assessments by EMDataBank. Comparative studies conducted at universities like Columbia University and research centers including Dana-Farber Cancer Institute evaluate accuracy relative to experimental structures from the Protein Data Bank and against alternative modeling systems from companies like Rosetta Commons and research groups at Weizmann Institute of Science. Performance varies with template quality as noted in publications from Johns Hopkins University and computational centers such as Purdue University.
MODELLER is distributed under an academic license maintained by the developers and is available to researchers at academic institutions like University of California, Berkeley, Princeton University, and Imperial College London. Commercial entities including biotechnology firms at Cambridge, MA may obtain separate licensing arrangements. Binary builds and source distributions have been provided for operating systems used in high-performance computing centers such as Oak Ridge National Laboratory and cloud platforms utilized by organizations like Amazon Web Services.
Category:Bioinformatics software