ISAMBARD
ISAMBARD enables parametric structural analysis, model building, and rational design of biomolecules to generate and explore de novo protein folds and backbone conformations.
Key Features:
- Structural analysis and model building: Supports parametric model building and structural analysis of biomolecules.
- Parametric modeling and backbone variability: Generalizes parametric modeling tools to introduce controlled backbone variability and generate novel backbone conformations and entire folds.
- Geometric description independent of experimental data: Describes proteins' overall shapes geometrically without reliance on experimentally determined structures.
- De novo protein-fold exploration: Enables creation of de novo protein structures and access to unexplored regions of protein-fold space.
- Computational scalability: Designed to handle large-scale computations for extensive biomolecular modeling tasks.
- Modular architecture: Provides a modular design that allows customization and extension of computational functionalities.
Scientific Applications:
- Biomolecular design: Designing new proteins with desired structures and functions to support applications such as drug discovery and therapeutic development.
- Biotechnology: Engineering biomolecules with enhanced properties or novel functionalities for biotechnological applications.
- Synthetic biology: Designing custom protein structures to perform specific tasks within engineered biological systems.
Methodology:
Employs a geometric approach and a generalization of parametric modeling tools to describe overall protein shape independent of experimental structures, enabling controlled backbone variability and generation of de novo folds.
Topics
Details
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Mac
- Programming Languages:
- Python
- Added:
- 6/12/2018
- Last Updated:
- 11/25/2024
Operations
Publications
Wood CW, Heal JW, Thomson AR, Bartlett GJ, Ibarra AÁ, Brady RL, Sessions RB, Woolfson DN. ISAMBARD: an open-source computational environment for biomolecular analysis, modelling and design. Bioinformatics. 2017;33(19):3043-3050. doi:10.1093/bioinformatics/btx352. PMID:28582565. PMCID:PMC5870769.
PMID: 28582565
PMCID: PMC5870769
Funding: - Biotechnology and Biological Sciences Research Council: BB/J008990/1
- European Research Council: 340764