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isambard

Intelligent System for Analysis, Model Building And Rational Design of biomolecules.

https://github.com/isambard-uob/isambard

Science Score: 23.0%

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    2 of 5 committers (40.0%) from academic institutions
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    Low similarity (12.8%) to scientific vocabulary

Keywords

bioinformatics computational-biology parametric-modelling python structural-biology university-of-bristol
Last synced: 6 months ago · JSON representation

Repository

Intelligent System for Analysis, Model Building And Rational Design of biomolecules.

Basic Info
Statistics
  • Stars: 25
  • Watchers: 1
  • Forks: 6
  • Open Issues: 9
  • Releases: 0
Topics
bioinformatics computational-biology parametric-modelling python structural-biology university-of-bristol
Created almost 8 years ago · Last pushed almost 5 years ago
Metadata Files
Readme Contributing License Code of conduct

README.md

ISAMBARD

Intelligent System for Analysis, Model Building And Rational Design.

CircleCI Python Version MIT licensed

ISAMBARD is a Python-based framework for structural analysis and rational design of biomolecules, with a particular focus on parametric modelling of proteins. It is developed and maintained by members of the Woolfson group, University of Bristol.

Citing ISAMBARD

Any publication arising from use of the ISAMBARD software package should cite the following reference:

Wood CW et al (2017) ISAMBARD: an open-source computational environment for biomolecular analysis, modelling and design. Bioinformatics, 33, 3043-50

Installation

ISAMBARD can be installed straight from PyPI using pip:

pip install isambard Or if you want to try an experimental build (you'll need a C compiler), download from GitHub either by downloading the zipped file or cloning, then navigate to the ISAMBARD folder and type:

pip install .

External Programs

If you want to add side chains to your designs, you need to have Scwrl4 installed and available on your system path.

Upgrading to ISAMBARD 2

If you were already using ISAMBARD prior to the 2.0.0 release, here's a handy guide on the differences between version 1 and 2.

Quick Start

Note
If you're not sure what parametric modelling of proteins is, have a play with CCBuilder 2.0.

Let's build a coiled-coil dimer with typical parameters:

```Python import isambard.specifications as specifications import isambard.modelling as modelling import isambard.optimisation

mydimer = specifications.CoiledCoil.fromparameters(2, 28, 5, 225, 283) dimersequences = [ 'EIAALKQEIAALKKENAALKWEIAALKQ', 'EIAALKQEIAALKKENAALKWEIAALKQ' ] mydimer = modelling.packsidechainsscwrl(mydimer, dimersequences) print(mydimer.pdb)

OUT:

HEADER ISAMBARD Model

ATOM 1 N GLU A 1 -5.364 -1.566 -0.689 1.00 0.00 N

ATOM 2 CA GLU A 1 -4.483 -2.220 0.308 1.00 0.00 C

ATOM 3 C GLU A 1 -3.886 -1.143 1.216 1.00 0.00 C

ATOM 4 O GLU A 1 -3.740 -1.337 2.425 1.00 0.00 O

ATOM 5 CB GLU A 1 -3.389 -3.028 -0.392 1.00 0.00 C

...

```

Don't know what your parameters might be? Let's optimise them then!

```Python import budeff import isambard.optimisation.evooptimizers as evopts from isambard.optimisation.evo_optimizers import Parameter

specification = specifications.CoiledCoil.from_parameters sequences = [ 'EIAALKQEIAALKKENAALKWEIAALKQ', 'EIAALKQEIAALKKENAALKWEIAALKQ' ] parameters = [ Parameter.static('Oligomeric State', 2), Parameter.static('Helix Length', 28), Parameter.dynamic('Radius', 5.0, 1.0), Parameter.dynamic('Pitch', 200, 60), Parameter.dynamic('PhiCA', 283, 27), # 283 is equivalent a g position ]

def getbufftotalenergy(ampalobject): return budeff.getinternalenergy(ampalobject).totalenergy

optga = evopts.GA(specification, sequences, parameters, getbufftotalenergy) optga.run_opt(100, 5, cores=8)

OUT:

gen evals avg std min max

0 61 -820.401 42.0119 -908.875 -750.001

1 59 -859.86 31.4194 -950.15 -807.265

2 60 -887.028 23.8683 -951.153 -847.346

3 70 -907.257 15.9615 -952.863 -882.028

4 81 -922.522 14.6206 -972.335 -903.444

Evaluated 431 models in total in 0:00:29.523487

Best fitness is (-972.3348571854714,)

Best parameters are [2, 28, 4.678360526981807, 151.35365923229745, 277.2061538048508]

optimizedmodel = optga.best_model ```

This quick example of parametric modelling with ISAMBARD, the next thing to do is take a look at the docs from tutorials on the tools available, or just take a look through the code base and hack around. Feel free to contact us through email or the issues if you get stuck.

Release Notes

v2.3.1

  • Fixes a minor bug in the DSSP output parsing code

v2.3.0

  • Introduces functionality to calculate the packing density (measured as the atomic contact number) of all non-hydrogen atoms in a Polymer / Assembly object.

v2.2.0

  • Adds pacc module for parametric analysis of coiled coils.

Owner

  • Name: ISAMBARD
  • Login: isambard-uob
  • Kind: organization

Repositories associated with the ISAMBARD biomolecular modelling package.

GitHub Events

Total
  • Watch event: 5
Last Year
  • Watch event: 5

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 418
  • Total Committers: 5
  • Avg Commits per committer: 83.6
  • Development Distribution Score (DDS): 0.112
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Chris Wells Wood c****q@g****m 371
Jack Heal j****l@b****k 34
Ajasja Ljubetic a****c@g****m 9
kls93 k****y@g****m 3
Gail Bartlett c****b@b****k 1
Committer Domains (Top 20 + Academic)
bristol.ac.uk: 2

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 14
  • Total pull requests: 7
  • Average time to close issues: 19 days
  • Average time to close pull requests: 2 days
  • Total issue authors: 9
  • Total pull request authors: 3
  • Average comments per issue: 2.57
  • Average comments per pull request: 1.29
  • Merged pull requests: 6
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • ajasja (4)
  • broncio123 (2)
  • ChrisWellsWood (2)
  • universvm (1)
  • eric-jm-lang (1)
  • wdawson14 (1)
  • xiaotianzhou1982 (1)
  • jmrussell (1)
  • FengChunsong666 (1)
Pull Request Authors
  • ChrisWellsWood (4)
  • ajasja (2)
  • kls93 (1)
Top Labels
Issue Labels
enhancement (4) good first issue (1) help wanted (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 42 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 2
  • Total versions: 3
  • Total maintainers: 3
pypi.org: isambard

A package for biomolecular analysis, modelling and design

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 2
  • Downloads: 42 Last month
Rankings
Dependent packages count: 10.1%
Dependent repos count: 11.5%
Forks count: 13.3%
Stargazers count: 14.0%
Average: 16.6%
Downloads: 33.8%
Maintainers (3)
ChrisWellsWood kathryn_shelley prasun30
Last synced: 6 months ago

Dependencies

setup.py pypi
  • Cython *
  • ampal *
  • budeff *
  • deap *
  • matplotlib *
  • numpy *