Literature DB >> 18064402

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

Andreas Schüller1, Marcel Suhartono, Uli Fechner, Yusuf Tanrikulu, Sven Breitung, Ute Scheffer, Michael W Göbel, Gisbert Schneider.   

Abstract

Principles of fragment-based molecular design are presented and discussed in the context of de novo drug design. The underlying idea is to dissect known drug molecules in fragments by straightforward pseudo-retro-synthesis. The resulting building blocks are then used for automated assembly of new molecules. A particular question has been whether this approach is actually able to perform scaffold-hopping. A prospective case study illustrates the usefulness of fragment-based de novo design for finding new scaffolds. We were able to identify a novel ligand disrupting the interaction between the Tat peptide and TAR RNA, which is part of the human immunodeficiency virus (HIV-1) mRNA. Using a single template structure (acetylpromazine) as reference molecule and a topological pharmacophore descriptor (CATS), new chemotypes were automatically generated by our de novo design software Flux. Flux features an evolutionary algorithm for fragment-based compound assembly and optimization. Pharmacophore superimposition and docking into the target RNA suggest perfect matching between the template molecule and the designed compound. Chemical synthesis was straightforward, and bioactivity of the designed molecule was confirmed in a FRET assay. This study demonstrates the practicability of de novo design to generating RNA ligands containing novel molecular scaffolds.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 18064402     DOI: 10.1007/s10822-007-9157-4

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  54 in total

1.  A graph-based genetic algorithm and its application to the multiobjective evolution of median molecules.

Authors:  Nathan Brown; Ben McKay; François Gilardoni; Johann Gasteiger
Journal:  J Chem Inf Comput Sci       Date:  2004 May-Jun

Review 2.  Navigating chemical space for biology and medicine.

Authors:  Christopher Lipinski; Andrew Hopkins
Journal:  Nature       Date:  2004-12-16       Impact factor: 49.962

3.  New inhibitors of the Tat-TAR RNA interaction found with a "fuzzy" pharmacophore model.

Authors:  Steffen Renner; Verena Ludwig; Oliver Boden; Ute Scheffer; Michael Göbel; Gisbert Schneider
Journal:  Chembiochem       Date:  2005-06       Impact factor: 3.164

Review 4.  Computer-based de novo design of drug-like molecules.

Authors:  Gisbert Schneider; Uli Fechner
Journal:  Nat Rev Drug Discov       Date:  2005-08       Impact factor: 84.694

5.  Flux (2): comparison of molecular mutation and crossover operators for ligand-based de novo design.

Authors:  Uli Fechner; Gisbert Schneider
Journal:  J Chem Inf Model       Date:  2007-02-23       Impact factor: 4.956

6.  Identification of common functional configurations among molecules.

Authors:  D Barnum; J Greene; A Smellie; P Sprague
Journal:  J Chem Inf Comput Sci       Date:  1996 May-Jun

7.  Evaluation of a method for controlling molecular scaffold diversity in de novo ligand design.

Authors:  N P Todorov; P M Dean
Journal:  J Comput Aided Mol Des       Date:  1997-03       Impact factor: 3.686

8.  BUILDER v.2: improving the chemistry of a de novo design strategy.

Authors:  D C Roe; I D Kuntz
Journal:  J Comput Aided Mol Des       Date:  1995-06       Impact factor: 3.686

9.  Artificial neural networks and simulated molecular evolution are potential tools for sequence-oriented protein design.

Authors:  G Schneider; J Schuchhardt; P Wrede
Journal:  Comput Appl Biosci       Date:  1994-12

10.  Automated molecular design: a new fragment-joining algorithm.

Authors:  A R Leach; S R Kilvington
Journal:  J Comput Aided Mol Des       Date:  1994-06       Impact factor: 3.686

View more
  3 in total

1.  Designing the molecular future.

Authors:  Gisbert Schneider
Journal:  J Comput Aided Mol Des       Date:  2011-11-30       Impact factor: 3.686

Review 2.  Advances in de Novo Drug Design: From Conventional to Machine Learning Methods.

Authors:  Varnavas D Mouchlis; Antreas Afantitis; Angela Serra; Michele Fratello; Anastasios G Papadiamantis; Vassilis Aidinis; Iseult Lynch; Dario Greco; Georgia Melagraki
Journal:  Int J Mol Sci       Date:  2021-02-07       Impact factor: 5.923

3.  Strategies to Block HIV Transcription: Focus on Small Molecule Tat Inhibitors.

Authors:  Guillaume Mousseau; Susana Valente
Journal:  Biology (Basel)       Date:  2012-11-19
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.