Skip to main content

ConPhar

Project description

Concensus Pharmacophore

Description | Requirements | Installation | Tutorials | Citation | License | Information | Disclaimer

DOI

Description

A consensus pharmacophore is a set of properties shared by several active molecules that bind to the same target. It is composed of geometric elements such as points, spheres, vectors, or planes that represent different types of features such as hydrophobic regions, hydrogen bond donors or acceptors, aromatic rings, or positive or negative charges. It can be used to represent the fundamental properties of a molecular interaction and to direct the development of new compounds with comparable or improved activity.

The consensus pharmacophore as Ligand-based method for examining the chemical structures of known active compounds in order to determine the common features that account for their activity. Using the three-dimensional structure of the target protein and its bound ligands, it can provide information about the interaction site and extract the key features required for binding.

A consensus pharmacophore can also be used to identify new potential ligands that match the features of the target and are likely to bind to it. This technique is known as pharmacophore matching, and it is useful for identifying drug targets and performing virtual screening.

This library was developed to generate concensus pharmacophores from large datasets of ligands and ligand-protein complexes.

Question about usage or troubleshooting? Please leave a comment in the discussion section of this repo

Requirements

ConPhar is reliant on a variety of academic software:

Installation

pip install conphar

Tutorials

Ligand-Receptor pharmacophores

Generate Consensus Pharmacophore

Citation

If you use this software or its results in your research, publication, or project, please cite it as follows:

ConPhar: Tool for generation and analysis of concensus pharmacophore: DOI: 10.5281/zenodo.8276506

If you use pharmer for your work you must cite:

Koes, D.R., & Camacho, C.J. (2011). Pharmer: Efficient and Exact Pharmacophore Search. Journal of chemical information and modeling, 51 6, 1307-14 .

If you use Pharmit in your work you must cite:

Sunseri, J., & Koes, D.R. (2016). Pharmit: interactive exploration of chemical space. Nucleic Acids Research, 44, W442 - W448.

License

This tool is under MIT license, see the LICENSE file for details.

Information

  • This library works with pharmacophores generated with pharmer and/or pharmit. An executable version of pharmit is included in this library but works only for linux.

Users can generate their pharmacophores and use this library for analysis. Check tutorials for more information.

Disclaimer

This software is still under development and may contain bugs or errors. The developers do not guarantee the accuracy, completeness, or reliability of the software or its results. Use it at your own risk and discretion. The software is provided "as is" without any warranty of any kind, either express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose, and non-infringement. The developers are not liable for any damages, losses, or costs arising from the use of the software or its results.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

conphar-0.1.2.tar.gz (3.9 MB view details)

Uploaded Source

Built Distribution

conphar-0.1.2-py3-none-any.whl (3.9 MB view details)

Uploaded Python 3

File details

Details for the file conphar-0.1.2.tar.gz.

File metadata

  • Download URL: conphar-0.1.2.tar.gz
  • Upload date:
  • Size: 3.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.2

File hashes

Hashes for conphar-0.1.2.tar.gz
Algorithm Hash digest
SHA256 e1c8a1a23b4fa64481a7c6c15811a0f26ff2cc4669f38e97a5d78695f93af305
MD5 9c17db1a610dc40dccf666659cfa2896
BLAKE2b-256 1f79ed96c77954d4a7db79f1bb9b579e5e223bd4d1331204ddeac483df7e82a8

See more details on using hashes here.

File details

Details for the file conphar-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: conphar-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 3.9 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.2

File hashes

Hashes for conphar-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 3c6b62f554ea02510bd88b81f6dc17d1a075c8e6d78f03185eccafa5eb2063d3
MD5 8d97d8d4248ddc976087739a5941883c
BLAKE2b-256 6d92f6d08ccff73334ad0b73dcc79d2447ce256f6a9c78e326f5787518d1d5ce

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page