ArticleBioinformatics (Oxford, England)2017
ISAMBARD: an open-source computational environment for biomolecular analysis, modelling and design.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
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- Tuning ProteinMPNN to reduce protein visibility via MHC Class I through direct preference optimization.Protein engineering, design & selection : PEDS · 2025Article
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- TIMED-Design: flexible and accessible protein sequence design with convolutional neural networks.Protein engineering, design & selection : PEDS · 2024Article
- Computational Protein Design - Where it goes?Current medicinal chemistry · 2024Review
- An expandable, modular de novo protein platform for precision redox engineering.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Rational Design of Phosphorylation-Responsive Coiled Coil-Peptide Assemblies.ACS synthetic biology · 2023Article
- PDBench: evaluating computational methods for protein-sequence design.Bioinformatics (Oxford, England) · 2023Article
- Protein Design: From the Aspect of Water Solubility and Stability.Chemical reviews · 2022Review
- Metal ion-regulated assembly of designed modular protein cages.Science advances · 2022Article
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Authors and funding
8 authors.
Funding
Abstract
motivationThe rational design of biomolecules is becoming a reality. However, further computational tools are needed to facilitate and accelerate this, and to make it accessible to more users.
resultsHere we introduce ISAMBARD, a tool for structural analysis, model building and rational design of biomolecules. ISAMBARD is open-source, modular, computationally scalable and intuitive to use. These features allow non-experts to explore biomolecular design in silico. ISAMBARD addresses a standing issue in protein design, namely, how to introduce backbone variability in a controlled manner. This is achieved through the generalization of tools for parametric modelling, describing the overall shape of proteins geometrically, and without input from experimentally determined structures. This will allow backbone conformations for entire folds and assemblies not observed in nature to be generated de novo, that is, to access the 'dark matter of protein-fold space'. We anticipate that ISAMBARD will find broad applications in biomolecular design, biotechnology and synthetic biology. AVAILABILITY AND IMPLEMENTATION: A current stable build can be downloaded from the python package index (https://pypi.python.org/pypi/isambard/) with development builds available on GitHub (https://github.com/woolfson-group/) along with documentation, tutorial material and all the scripts used to generate the data described in this paper. CONTACT: d.n.woolfson@bristol.ac.uk or chris.wood@bristol.ac.uk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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