Literature DB >> 8749844

An automated method for dynamic ligand design.

A Miranker1, M Karplus.   

Abstract

An automated method for the dynamic ligand design (DLD) for a binding site of known structure is described. The method can be used for the creation of de novo ligands and for the modification of existing ligands. The binding site is saturated with atoms (sp3 carbon atoms in the present implementation) that form molecules under the influence of a potential function that joins atoms to each other with the correct stereochemistry. The resulting molecules are linked to precomputed functional group minimum energy positions in the binding site. The generalized potential function allows atoms to sample a continuous parameter space that includes the Cartesian coordinates and their occupancy and type, e.g., the method allows change of an sp3 carbon into an sp2 carbon or oxygen. A parameter space formulated in this way can then be sampled and optimized by a variety of methods. In this work, molecules are generated by use of a Monte Carlo simulated annealing algorithm. The DLD method is illustrated by its application to the binding site of FK506 binding protein (FKBP), an immunophilin. De novo ligands are designed and modification of the immunosuppressant drug FK506 are suggested. The results demonstrate that the dynamic ligand design approach can automatically construct ligands which complement both the shape and charge distribution of the binding site.

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Year:  1995        PMID: 8749844     DOI: 10.1002/prot.340230403

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  21 in total

1.  Computational design of D-peptide inhibitors of hepatitis delta antigen dimerization.

Authors:  C D Elkin; H J Zuccola; J M Hogle; D Joseph-McCarthy
Journal:  J Comput Aided Mol Des       Date:  2000-11       Impact factor: 3.686

2.  Design of dimerization inhibitors of HIV-1 aspartic proteinase: a computer-based combinatorial approach.

Authors:  A Caflisch; H J Schramm; M Karplus
Journal:  J Comput Aided Mol Des       Date:  2000-02       Impact factor: 3.686

3.  Evaluation of designed ligands by a multiple screening method: application to glycogen phosphorylase inhibitors constructed with a variety of approaches.

Authors:  S S So; M Karplus
Journal:  J Comput Aided Mol Des       Date:  2001-07       Impact factor: 3.686

4.  Functional group placement in protein binding sites: a comparison of GRID and MCSS.

Authors:  R Bitetti-Putzer; D Joseph-McCarthy; J M Hogle; M Karplus
Journal:  J Comput Aided Mol Des       Date:  2001-10       Impact factor: 3.686

5.  A genetic algorithm for structure-based de novo design.

Authors:  S C Pegg; J J Haresco; I D Kuntz
Journal:  J Comput Aided Mol Des       Date:  2001-10       Impact factor: 3.686

6.  Protein-ligand binding free energy estimation using molecular mechanics and continuum electrostatics. Application to HIV-1 protease inhibitors.

Authors:  V Zoete; O Michielin; M Karplus
Journal:  J Comput Aided Mol Des       Date:  2003-12       Impact factor: 3.686

7.  Gaussian mapping of chemical fragments in ligand binding sites.

Authors:  Kun Wang; Marta Murcia; Pere Constans; Carlos Pérez; Angel R Ortiz
Journal:  J Comput Aided Mol Des       Date:  2004-02       Impact factor: 3.686

8.  Locating binding poses in protein-ligand systems using reconnaissance metadynamics.

Authors:  Pär Söderhjelm; Gareth A Tribello; Michele Parrinello
Journal:  Proc Natl Acad Sci U S A       Date:  2012-03-21       Impact factor: 11.205

9.  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

10.  Ligand design by a combinatorial approach based on modeling and experiment: application to HLA-DR4.

Authors:  Erik Evensen; Diane Joseph-McCarthy; Gregory A Weiss; Stuart L Schreiber; Martin Karplus
Journal:  J Comput Aided Mol Des       Date:  2007-07-27       Impact factor: 3.686

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