ConfID

Conformational generation is a recurrent challenge in early phases of drug design, mostly due to the task of making sense between the number of conformers generated and their relevance for biological purposes.

In this sense, ConfID, a Python-based computational tool, was designed to identify and characterize conformational populations of drug-like molecules sampled through molecular dynamics simulations.

By using molecular dynamics (MD) simulations (and assuming accurate parameters are used), ConfID can identify all conformational populations sampled in the presence of solvent and quantify their relative abundance, while harnessing the benefits of MD and calculating time-dependent properties of each conformational population identified.

To contact us, please drop an email to bigrisci@inf.ufrgs.br and mdpoleto@vt.edu.

It is a Python-based computational tool designed to identify and characterize conformational populations of small molecules sampled through molecular dynamics simulations.

ConfID was developed by:

Bruno I. Grisci - PhD student (Institute of Informatics - UFRGS)
Marcelo D. Polêto - Postdoctoral Associate (Biochemistry Department - VirginiaTech)
Marcio Dorn - Associate Professor (Institute of Informatics - UFRGS)
Hugo Verli - Associate Professor (Center of Biotechnology - UFRGS)

Genetic algorithms and knowledge-based approaches have been employed to study molecular flexibility. However, these methods are usually based on crystallographic information, and their calculations are made in vacuum or with implicit solvent and do not take into account the influence of explicit solvent molecules on conformational preferences.

By using structural information gathered from MD simulations (and assuming accurate parameters are used), ConfID can identify all conformational populations of drug-like molecules sampled in the presence of solvent and quantify their relative abundance, while harnessing the benefits of MD and calculating time-dependent properties of each conformational population.

a) Two analogue ligands in water

Do you have any questions? Take a look at our FAQ.

There are some papers already using ConfID! These are some:

If you use ConfID in a scientific publication, we would appreciate citations to the following paper:

BibTeX

@article{10.1093/bioinformatics/btaa130,
    author = {Polêto, M D and Grisci, B I and Dorn, M and Verli, H},
    title = "ConfID: an analytical method for conformational characterization of small molecules using molecular dynamics trajectories",
    journal = {Bioinformatics},
    year = {2020},
    month = {02},
    issn = {1367-4803},
    doi = {10.1093/bioinformatics/btaa130},
    url = {https://doi.org/10.1093/bioinformatics/btaa130},
    note = {btaa130},
    eprint = {https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btaa130/32677172/btaa130.pdf},
}