Name
Abstract | ||
|---|---|---|
Computational methods for protein structure modelling are routinely used to complement experimental structure determination, thus they help to address a broad spectrum of scientific questions in biomedical research. The most accurate methods today are based on homology modelling, i.e. detecting a homologue to the desired target sequence that can be used as a template for modelling. Here we present a versatile open source homology modelling toolbox as foundation for flexible and computationally efficient modelling workflows. ProMod3 is a fully scriptable software platform that can perform all steps required to generate a protein model by homology. Its modular design aims at fast prototyping of novel algorithms and implementing flexible modelling pipelines. Common modelling tasks, such as loop modelling, sidechain modelling or generating a full protein model by homology, are provided as production ready pipelines, forming the starting point for own developments and enhancements. ProMod3 is the central software component of the widely used SWISS-MODEL web-server.Author summaryKnowledge of a protein's structure permits key insights in its molecular function and supports scientists in the design of targeted and efficient experiments. However, experimental structure determination is a limiting factor and, as a consequence, the number of entries in the Protein Data Bank (PDB) is orders of magnitude lower than the number of known protein sequences. Computational modelling methods can be used to bridge this gap by complementing experimental structure determination. In particular, homology modelling (aka comparative or template-based modelling) approaches which interpolate structural information from homologous structures can provide protein models of sufficiently high accuracy to guide structure based research. In this manuscript we describe ProMod3 which is a modular software package targeted at modelling protein structures by homology. ProMod3 empowers the widely used SWISS-MODEL webserver and already served millions of protein structure models to the scientific community. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1371/journal.pcbi.1008667 | PLOS COMPUTATIONAL BIOLOGY |
DocType | Volume | Issue |
Journal | 17 | 1 |
ISSN | Citations | PageRank |
1553-734X | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gabriel Studer | 1 | 0 | 0.34 |
| Gerardo Tauriello | 2 | 3 | 0.76 |
| Stefan Bienert | 3 | 74 | 4.56 |
| Marco Biasini | 4 | 59 | 4.95 |
| Niklaus Johner | 5 | 1 | 1.64 |
| Torsten Schwede | 6 | 3 | 1.09 |