Literature DB >> 8768903

Current computational tools for de novo ligand design.

H J Böhm1.   

Abstract

Several new algorithms have been proposed recently for computational de novo ligand design. Empirical scoring functions are now available to prioritize the suggested structures. The first successful applications have been reported.

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Year:  1996        PMID： 8768903     DOI： 10.1016/s0958-1669(96)80120-0

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN： 0958-1669            Impact factor:   9.740


  7 in total

1.  Comparative molecular field analysis and energy interaction studies of thrombin-inhibitor complexes.

Authors:  R Bursi; P D Grootenhuis
Journal:  J Comput Aided Mol Des       Date:  1999-05       Impact factor: 3.686

2.  Further development and validation of empirical scoring functions for structure-based binding affinity prediction.

Authors:  Renxiao Wang; Luhua Lai; Shaomeng Wang
Journal:  J Comput Aided Mol Des       Date:  2002-01       Impact factor: 3.686

3.  Designing the molecular future.

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

4.  Targeting imidazoline site on monoamine oxidase B through molecular docking simulations.

Authors:  Fernanda Pretto Moraes; Walter Filgueira de Azevedo
Journal:  J Mol Model       Date:  2012-03-17       Impact factor: 1.810

5.  An automated method for predicting the positions of hydrogen-bonding atoms in binding sites.

Authors:  J E Mills; T D Perkins; P M Dean
Journal:  J Comput Aided Mol Des       Date:  1997-05       Impact factor: 3.686

6.  Minimal pharmacophoric elements and fragment hopping, an approach directed at molecular diversity and isozyme selectivity. Design of selective neuronal nitric oxide synthase inhibitors.

Authors:  Haitao Ji; Benjamin Z Stanton; Jotaro Igarashi; Huiying Li; Pavel Martásek; Linda J Roman; Thomas L Poulos; Richard B Silverman
Journal:  J Am Chem Soc       Date:  2008-03-06       Impact factor: 15.419

Review 7.  Computer-Aided Drug Discovery in Plant Pathology.

Authors:  Gnanendra Shanmugam; Junhyun Jeon
Journal:  Plant Pathol J       Date:  2017-12-01       Impact factor: 1.795
  7 in total

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