castp-Script/CITATION.cff at main · athulvis/castp-Script · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: 'CASTpFoldpy : Commandline tool to access CASTpFold server'
message: >-
  If you are using this tool for your research purpose.
  Please cite the original CASTpFold paper along with this
  software -
  Ye, B., Tian, W., Wang, B., and Liang, J.
  (2024). CASTpFold: Computed Atlas of Surface Topography of
  the universe of protein Folds. Nucleic Acids Research,
  52(W1), W194–W199. https://doi.org/10.1093/nar/gkae415.
type: software
authors:
  - given-names: Athul R T
    affiliation: Sahya Digital Conservation Foundation
    orcid: 'https://orcid.org/0000-0001-5565-7470'
identifiers:
  - type: doi
    value: 10.5281/zenodo.17292401
repository-code: 'https://github.com/athulvis/castp-Script'
abstract: >-
  CASTpFoldpy is an automated Python-based commandline tool
  designed to streamline the submission and retrieval of
  protein structure analyses from the CASTpFold server.
  CASTpFold is a widely used web server that identifies and
  quantifies protein surface pockets, cavities and channels
  using the alpha shape method providing key structural
  insights for functional and drug design studies. However,
  the manual submission of structures and downloading of
  results can be time-consuming for large-scale analyses.

  The CASTpFoldpy script automates the entire CASTpFold
  workflow: it uploads user-provided protein structures in
  PDB format, retrieves the assigned job ID, downloads the
  processed results automatically and extracts the output
  files in the working directory. Tool computes the grid box
  dimensions (X, Y, Z) in a text file, by averaging the
  atomic coordinates of residues within the selected pocket,
  a feature particularly useful for active site prediction.

  This automation enables seamless high-throughput protein
  pocket analysis, reduces manual intervention and ensures
  reproducible structural annotation pipelines integrating
  CASTpFold results with downstream visualization and
  computational workflows.
commit: GPL
version: '3.0'