Literature DB >> 24451634

De novo design - hop(p)ing against hope.

Gisbert Schneider.   

Abstract

Current trends in computational de novo design provide a fresh approach to 'scaffold-hopping' in drug discovery. The methodological repertoire is no longer limited to receptor-based methods, but specifically ligand-based techniques that consider multiple properties in parallel, including the synthetic feasibility of the computer-generated molecules and their polypharmacology, provide innovative ideas for the discovery of new chemical entities. The concept of fragment-based and virtual reaction-driven design enables rapid compound optimization from scratch with a manageable complexity of the search. Starting from known drugs as a reference, such algorithms suggest drug-like molecules with motivated scaffold variations, and advanced mathematical models of structure-activity landscapes and multi-objective design techniques have created new opportunities for hit and lead finding.

Mesh:

Substances:

Year:  2013        PMID: 24451634     DOI: 10.1016/j.ddtec.2012.06.001

Source DB:  PubMed          Journal:  Drug Discov Today Technol        ISSN: 1740-6749


  7 in total

1.  Molecular Scaffold Hopping via Holistic Molecular Representation.

Authors:  Francesca Grisoni; Gisbert Schneider
Journal:  Methods Mol Biol       Date:  2021

2.  Identifying the macromolecular targets of de novo-designed chemical entities through self-organizing map consensus.

Authors:  Daniel Reker; Tiago Rodrigues; Petra Schneider; Gisbert Schneider
Journal:  Proc Natl Acad Sci U S A       Date:  2014-03-03       Impact factor: 11.205

3.  Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets.

Authors:  William J Allen; Brian C Fochtman; Trent E Balius; Robert C Rizzo
Journal:  J Comput Chem       Date:  2017-09-22       Impact factor: 3.376

4.  Chemically Advanced Template Search (CATS) for Scaffold-Hopping and Prospective Target Prediction for 'Orphan' Molecules.

Authors:  Michael Reutlinger; Christian P Koch; Daniel Reker; Nickolay Todoroff; Petra Schneider; Tiago Rodrigues; Gisbert Schneider
Journal:  Mol Inform       Date:  2013-02-07       Impact factor: 3.353

5.  Designed Spiroketal Protein Modulation.

Authors:  Marcel Scheepstra; Sebastian A Andrei; M Yagiz Unver; Anna K H Hirsch; Seppe Leysen; Christian Ottmann; Luc Brunsveld; Lech-Gustav Milroy
Journal:  Angew Chem Int Ed Engl       Date:  2017-04-13       Impact factor: 15.336

Review 6.  Computer-aided drug discovery.

Authors:  Jürgen Bajorath
Journal:  F1000Res       Date:  2015-08-26

7.  Network-based piecewise linear regression for QSAR modelling.

Authors:  Jonathan Cardoso-Silva; Lazaros G Papageorgiou; Sophia Tsoka
Journal:  J Comput Aided Mol Des       Date:  2019-10-18       Impact factor: 3.686

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.