Literature DB >> 8060670

A novel computational tool for automated structure-based drug design.

H J Böhm1.   

Abstract

The computer program LUDI for automated structure-based drug design is described. The program constructs possible new ligands for a given protein of known three-dimensional structure. This novel approach is based upon rules about energetically favourable non-bonded contact geometries between functional groups of the protein and the ligand which are derived from a statistical analysis of crystal packings of organic molecules. In a first step small fragments are docked into the protein binding site in such a way that hydrogen bonds and ionic interactions can be formed with the protein and hydrophobic pockets are filled with lipophilic groups of the ligand. The program can then append further fragments onto a previously positioned fragment or onto an already existing ligand (e.g., a lead structure that one seeks to improve). It is also possible to link several fragments together by bridge fragments to form a complete molecule. All putative ligands retrieved or constructed by LUDI are scored. We use a simple scoring function that was fitted to experimentally determined binding constants of protein-ligand complexes. LUDI is a very fast program with typical execution times of 1-5 min on a work station and is therefore suitable for interactive usage.

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Year:  1993        PMID: 8060670     DOI: 10.1002/jmr.300060305

Source DB:  PubMed          Journal:  J Mol Recognit        ISSN: 0952-3499            Impact factor:   2.137


  7 in total

1.  Computer-aided design and activity prediction of leucine aminopeptidase inhibitors.

Authors:  J Grembecka; W A Sokalski; P Kafarski
Journal:  J Comput Aided Mol Des       Date:  2000-08       Impact factor: 3.686

2.  The concept of template-based de novo design from drug-derived molecular fragments and its application to TAR RNA.

Authors:  Andreas Schüller; Marcel Suhartono; Uli Fechner; Yusuf Tanrikulu; Sven Breitung; Ute Scheffer; Michael W Göbel; Gisbert Schneider
Journal:  J Comput Aided Mol Des       Date:  2007-12-07       Impact factor: 3.686

3.  CONFIRM: connecting fragments found in receptor molecules.

Authors:  David C Thompson; R Aldrin Denny; Ramaswamy Nilakantan; Christine Humblet; Diane Joseph-McCarthy; Eric Feyfant
Journal:  J Comput Aided Mol Des       Date:  2008-07-09       Impact factor: 3.686

4.  Potential drug-like inhibitors of Group 1 influenza neuraminidase identified through computer-aided drug design.

Authors:  Jacob D Durrant; J Andrew McCammon
Journal:  Comput Biol Chem       Date:  2010-04-03       Impact factor: 2.877

5.  Pyrone-based inhibitors of metalloproteinase types 2 and 3 may work as conformation-selective inhibitors.

Authors:  Jacob D Durrant; César A F de Oliveira; J Andrew McCammon
Journal:  Chem Biol Drug Des       Date:  2011-06-20       Impact factor: 2.817

Review 6.  Machine Learning and Computational Chemistry for the Endocannabinoid System.

Authors:  Kenneth Atz; Wolfgang Guba; Uwe Grether; Gisbert Schneider
Journal:  Methods Mol Biol       Date:  2023

Review 7.  Protein-Ligand Docking in the Machine-Learning Era.

Authors:  Chao Yang; Eric Anthony Chen; Yingkai Zhang
Journal:  Molecules       Date:  2022-07-18       Impact factor: 4.927

  7 in total

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