Literature DB >> 21335612

fconv: Format conversion, manipulation and feature computation of molecular data.

Gerd Neudert1, Gerhard Klebe.   

Abstract

UNLABELLED: fconv is a program intended for parsing and manipulating multiple aspects and properties of molecular data. Up to now, it has been developed and extensively tested for 3 years. It has become a very robust and comprehensive tool involved in a broad range of computational workflows that are currently applied in our drug design environment. Typical tasks are as follows: conversion and error correction of formats such as PDB(QT), MOL2, SDF, DLG and CIF; extracting ligands from PDB as MOL2; automatic or ligand-based cavity detection; rmsd calculation and clustering; substructure searches; alignment and structural superposition; building of crystal packings; adding hydrogens; calculation of various properties like the number of rotatable bonds; molecular weights or vdW volumes. The atom type classification is based on a consistent assignment of internal atom types, which are by far more differentiated compared with e.g. Sybyl atom types. Apart from the predefined mapping of these types onto Sybyl types, the user is able to assign own mappings by providing modified template files, thus allowing for tailor-made atom type sets. AVAILABILITY: fconv is free software available under GNU General Public License. C++ sources and precompiled executables for LINUX/UNIX, Mac OS and Windows, as well as tutorials are available on http://www.agklebe.de.

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Year:  2011        PMID: 21335612     DOI: 10.1093/bioinformatics/btr055

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  14 in total

1.  Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation.

Authors:  Sergei Grudinin; Maria Kadukova; Andreas Eisenbarth; Simon Marillet; Frédéric Cazals
Journal:  J Comput Aided Mol Des       Date:  2016-10-07       Impact factor: 3.686

2.  When theory meets experiment: the PD-1 challenge.

Authors:  Marawan Ahmed; Khaled Barakat
Journal:  J Mol Model       Date:  2017-10-10       Impact factor: 1.810

3.  Convex-PL: a novel knowledge-based potential for protein-ligand interactions deduced from structural databases using convex optimization.

Authors:  Maria Kadukova; Sergei Grudinin
Journal:  J Comput Aided Mol Des       Date:  2017-09-18       Impact factor: 3.686

4.  Structural Basis of Substrate Recognition and Covalent Inhibition of Cdu1 from Chlamydia trachomatis.

Authors:  Yesid A Ramirez; Thomas B Adler; Eva Altmann; Theresa Klemm; Christian Tiesmeyer; Florian Sauer; Stefan G Kathman; Alexander V Statsyuk; Christoph Sotriffer; Caroline Kisker
Journal:  ChemMedChem       Date:  2018-09-06       Impact factor: 3.466

5.  Identification of potential trypanothione reductase inhibitors among commercially available β-carboline derivatives using chemical space, lead-like and drug-like filters, pharmacophore models and molecular docking.

Authors:  Jorge Rodríguez-Becerra; Lizethly Cáceres-Jensen; José Hernández-Ramos; Lorena Barrientos
Journal:  Mol Divers       Date:  2017-06-27       Impact factor: 2.943

6.  Using diverse potentials and scoring functions for the development of improved machine-learned models for protein-ligand affinity and docking pose prediction.

Authors:  Omar N A Demerdash
Journal:  J Comput Aided Mol Des       Date:  2021-10-28       Impact factor: 3.686

7.  Novel type II fatty acid biosynthesis (FAS II) inhibitors as multistage antimalarial agents.

Authors:  Florian C Schrader; Serghei Glinca; Julia M Sattler; Hans-Martin Dahse; Gustavo A Afanador; Sean T Prigge; Michael Lanzer; Ann-Kristin Mueller; Gerhard Klebe; Martin Schlitzer
Journal:  ChemMedChem       Date:  2013-01-22       Impact factor: 3.466

8.  Rational design of broad spectrum antibacterial activity based on a clinically relevant enoyl-acyl carrier protein (ACP) reductase inhibitor.

Authors:  Johannes Schiebel; Andrew Chang; Sonam Shah; Yang Lu; Li Liu; Pan Pan; Maria W Hirschbeck; Mona Tareilus; Sandra Eltschkner; Weixuan Yu; Jason E Cummings; Susan E Knudson; Gopal R Bommineni; Stephen G Walker; Richard A Slayden; Christoph A Sotriffer; Peter J Tonge; Caroline Kisker
Journal:  J Biol Chem       Date:  2014-04-16       Impact factor: 5.157

9.  Slow-Onset Inhibition of Mycobacterium tuberculosis InhA: Revealing Molecular Determinants of Residence Time by MD Simulations.

Authors:  Benjamin Merget; Christoph A Sotriffer
Journal:  PLoS One       Date:  2015-05-21       Impact factor: 3.240

10.  Electrostatic similarities between protein and small molecule ligands facilitate the design of protein-protein interaction inhibitors.

Authors:  Arnout Voet; Francois Berenger; Kam Y J Zhang
Journal:  PLoS One       Date:  2013-10-10       Impact factor: 3.240

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