ISAMBARD: an Open-source Computational Environment for Biomolecular Analysis, Modelling and Design

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2017 Jun 6

PMID 28582565

Citations 21

Authors

Christopher W Wood

Jack W Heal

Andrew R Thomson

Gail J Bartlett

Amaurys A Ibarra

R Leo Brady

Richard B Sessions

Derek N Woolfson

Affiliations

Soon will be listed here.

Abstract

Motivation: The 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.

Results: Here 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.

Citing Articles

CCfrag: scanning folding potential of coiled-coil fragments with AlphaFold.

Martinez-Goikoetxea M Bioinform Adv. 2024; 5(1):vbae195.

PMID: 39735573 PMC: 11676326. DOI: 10.1093/bioadv/vbae195.

Applicability of AlphaFold2 in the modeling of dimeric, trimeric, and tetrameric coiled-coil domains.

Madaj R, Martinez-Goikoetxea M, Kaminski K, Ludwiczak J, Dunin-Horkawicz S Protein Sci. 2024; 34(1):e5244.

PMID: 39688306 PMC: 11651203. DOI: 10.1002/pro.5244.

AI Prediction of Structural Stability of Nanoproteins Based on Structures and Residue Properties by Mean Pooled Dual Graph Convolutional Network.

Li D, Zhu Y, Zhang W, Liu J, Yang X, Liu Z Interdiscip Sci. 2024; 17(1):101-113.

PMID: 39367992 DOI: 10.1007/s12539-024-00662-7.

TIMED-Design: flexible and accessible protein sequence design with convolutional neural networks.

Castorina L, Unal S, Subr K, Wood C Protein Eng Des Sel. 2024; 37.

PMID: 38288671 PMC: 10939383. DOI: 10.1093/protein/gzae002.

An expandable, modular de novo protein platform for precision redox engineering.

Hutchins G, Noble C, Bunzel H, Williams C, Dubiel P, Yadav S Proc Natl Acad Sci U S A. 2023; 120(31):e2306046120.

PMID: 37487099 PMC: 10400981. DOI: 10.1073/pnas.2306046120.

References

Das R, Baker D . Macromolecular modeling with rosetta. Annu Rev Biochem. 2008; 77:363-82. DOI: 10.1146/annurev.biochem.77.062906.171838. View

Brunette T, Parmeggiani F, Huang P, Bhabha G, Ekiert D, Tsutakawa S . Exploring the repeat protein universe through computational protein design. Nature. 2015; 528(7583):580-4. PMC: 4845728. DOI: 10.1038/nature16162. View

Wood C, Bruning M, Ibarra A, Bartlett G, Thomson A, Sessions R . CCBuilder: an interactive web-based tool for building, designing and assessing coiled-coil protein assemblies. Bioinformatics. 2014; 30(21):3029-35. PMC: 4201159. DOI: 10.1093/bioinformatics/btu502. View

Chaudhury S, Lyskov S, Gray J . PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta. Bioinformatics. 2010; 26(5):689-91. PMC: 2828115. DOI: 10.1093/bioinformatics/btq007. View

McIntosh-Smith S, Price J, Sessions R, Ibarra A . High performance virtual drug screening on many-core processors. Int J High Perform Comput Appl. 2015; 29(2):119-134. PMC: 4425459. DOI: 10.1177/1094342014528252. View

Lupas A, Gruber M . The structure of alpha-helical coiled coils. Adv Protein Chem. 2005; 70:37-78. DOI: 10.1016/S0065-3233(05)70003-6. View

Shoulders M, Raines R . Collagen structure and stability. Annu Rev Biochem. 2009; 78:929-58. PMC: 2846778. DOI: 10.1146/annurev.biochem.77.032207.120833. View

Offer G, Hicks M, Woolfson D . Generalized Crick equations for modeling noncanonical coiled coils. J Struct Biol. 2002; 137(1-2):41-53. DOI: 10.1006/jsbi.2002.4448. View

MacDonald J, Freemont P . Computational protein design with backbone plasticity. Biochem Soc Trans. 2016; 44(5):1523-1529. PMC: 5264498. DOI: 10.1042/BST20160155. View

10.

Dahiyat B, Mayo S . De novo protein design: fully automated sequence selection. Science. 1997; 278(5335):82-7. DOI: 10.1126/science.278.5335.82. View

11.

Huang P, Oberdorfer G, Xu C, Pei X, Nannenga B, Rogers J . High thermodynamic stability of parametrically designed helical bundles. Science. 2014; 346(6208):481-485. PMC: 4612401. DOI: 10.1126/science.1257481. View

12.

Taylor W, Chelliah V, Hollup S, MacDonald J, Jonassen I . Probing the "dark matter" of protein fold space. Structure. 2009; 17(9):1244-52. DOI: 10.1016/j.str.2009.07.012. View

13.

Parmeggiani F, Huang P, Vorobiev S, Xiao R, Park K, Caprari S . A general computational approach for repeat protein design. J Mol Biol. 2014; 427(2):563-75. PMC: 4303030. DOI: 10.1016/j.jmb.2014.11.005. View

14.

Harbury P, Kim P, Alber T . Crystal structure of an isoleucine-zipper trimer. Nature. 1994; 371(6492):80-3. DOI: 10.1038/371080a0. View

15.

Harbury P, Zhang T, Kim P, Alber T . A switch between two-, three-, and four-stranded coiled coils in GCN4 leucine zipper mutants. Science. 1993; 262(5138):1401-7. DOI: 10.1126/science.8248779. View

16.

Boersma Y, Pluckthun A . DARPins and other repeat protein scaffolds: advances in engineering and applications. Curr Opin Biotechnol. 2011; 22(6):849-57. DOI: 10.1016/j.copbio.2011.06.004. View

17.

Eastman P, Friedrichs M, Chodera J, Radmer R, Bruns C, Ku J . OpenMM 4: A Reusable, Extensible, Hardware Independent Library for High Performance Molecular Simulation. J Chem Theory Comput. 2013; 9(1):461-469. PMC: 3539733. DOI: 10.1021/ct300857j. View

18.

Jacobs T, Williams B, Williams T, Xu X, Eletsky A, Federizon J . Design of structurally distinct proteins using strategies inspired by evolution. Science. 2016; 352(6286):687-90. PMC: 4934125. DOI: 10.1126/science.aad8036. View

19.

de Bakker P, DePristo M, Burke D, Blundell T . Ab initio construction of polypeptide fragments: Accuracy of loop decoy discrimination by an all-atom statistical potential and the AMBER force field with the Generalized Born solvation model. Proteins. 2003; 51(1):21-40. DOI: 10.1002/prot.10235. View

20.

Doyle L, Hallinan J, Bolduc J, Parmeggiani F, Baker D, Stoddard B . Rational design of α-helical tandem repeat proteins with closed architectures. Nature. 2015; 528(7583):585-8. PMC: 4727831. DOI: 10.1038/nature16191. View