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1.
Molecules ; 26(18)2021 Sep 15.
Article in English | MEDLINE | ID: mdl-34577064

ABSTRACT

Rapid in silico selection of target focused libraries from commercial repositories is an attractive and cost-effective approach in early drug discovery. If structures of active compounds are available, rapid 2D similarity search can be performed on multimillion compounds' databases. This approach can be combined with physico-chemical parameter and diversity filtering, bioisosteric replacements, and fragment-based approaches for performing a first round biological screening. Our objectives were to investigate the combination of 2D similarity search with various 3D ligand and structure-based methods for hit expansion and validation, in order to increase the hit rate and novelty. In the present account, six case studies are described and the efficiency of mixing is evaluated. While sequentially combined 2D/3D similarity approach increases the hit rate significantly, sequential combination of 2D similarity with pharmacophore model or 3D docking enriched the resulting focused library with novel chemotypes. Parallel integrated approaches allowed the comparison of the various 2D and 3D methods and revealed that 2D similarity-based and 3D ligand and structure-based techniques are often complementary, and their combinations represent a powerful synergy. Finally, the lessons we learnt including the advantages and pitfalls of the described approaches are discussed.


Subject(s)
Drug Discovery/methods , Molecular Docking Simulation/methods , Small Molecule Libraries/chemistry , Databases, Chemical , Humans , Quantitative Structure-Activity Relationship , Sequence Analysis, Protein/methods , Small Molecule Libraries/pharmacology
2.
Mol Divers ; 21(1): 175-186, 2017 Feb.
Article in English | MEDLINE | ID: mdl-28070724

ABSTRACT

A glutaminyl cyclase (QC) fragment library was in silico selected by disconnection of the structure of known QC inhibitors and by lead-like 2D virtual screening of the same set. The resulting fragment library (204 compounds) was acquired from commercial suppliers and pre-screened by differential scanning fluorimetry followed by functional in vitro assays. In this way, 10 fragment hits were identified ([Formula: see text]5 % hit rate, best inhibitory activity: 16 [Formula: see text]). The in vitro hits were then docked to the active site of QC, and the best scoring compounds were analyzed for binding interactions. Two fragments bound to different regions in a complementary manner, and thus, linking those fragments offered a rational strategy to generate novel QC inhibitors. Based on the structure of the virtual linked fragment, a 77-membered QC target focused library was selected from vendor databases and docked to the active site of QC. A PubChem search confirmed that the best scoring analogues are novel, potential QC inhibitors.


Subject(s)
Aminoacyltransferases/antagonists & inhibitors , Computer Simulation , Enzyme Inhibitors/pharmacology , Small Molecule Libraries/pharmacology , Aminoacyltransferases/chemistry , Aminoacyltransferases/metabolism , Catalytic Domain , Drug Design , Drug Evaluation, Preclinical , Enzyme Inhibitors/chemistry , Enzyme Inhibitors/metabolism , Molecular Docking Simulation , Protein Conformation , Small Molecule Libraries/chemistry , Small Molecule Libraries/metabolism , Structure-Activity Relationship
3.
Molecules ; 19(6): 7008-39, 2014 May 28.
Article in English | MEDLINE | ID: mdl-24879613

ABSTRACT

Rapid in silico selection of target focused libraries from commercial repositories is an attractive and cost effective approach. If structures of active compounds are available rapid 2D similarity search can be performed on multimillion compound databases but the generated library requires further focusing by various 2D/3D chemoinformatics tools. We report here a combination of the 2D approach with a ligand-based 3D method (Screen3D) which applies flexible matching to align reference and target compounds in a dynamic manner and thus to assess their structural and conformational similarity. In the first case study we compared the 2D and 3D similarity scores on an existing dataset derived from the biological evaluation of a PDE5 focused library. Based on the obtained similarity metrices a fusion score was proposed. The fusion score was applied to refine the 2D similarity search in a second case study where we aimed at selecting and evaluating a PDE4B focused library. The application of this fused 2D/3D similarity measure led to an increase of the hit rate from 8.5% (1st round, 47% inhibition at 10 µM) to 28.5% (2nd round at 50% inhibition at 10 µM) and the best two hits had 53 nM inhibitory activities.


Subject(s)
Phosphodiesterase 4 Inhibitors , Phosphodiesterase 5 Inhibitors , Drug Evaluation, Preclinical , Molecular Structure , Structure-Activity Relationship
4.
Chem Biol Drug Des ; 86(4): 864-80, 2015 Oct.
Article in English | MEDLINE | ID: mdl-25823681

ABSTRACT

Rapid in silico selection of target-focused libraries from commercial repositories is an attractive and cost-effective approach. If structures of active compounds are available, rapid 2D similarity search can be performed on multimillion compound databases, but the generated library requires further focusing. We report here a combination of the 2D approach with pharmacophore matching which was used for selecting 5-HT6 antagonists. In the first screening round, 12 compounds showed >85% antagonist efficacy of the 91 screened. For the second-round (hit validation) screening phase, pharmacophore models were built, applied, and compared with the routine 2D similarity search. Three pharmacophore models were created based on the structure of the reference compounds and the first-round hit compounds. The pharmacophore search resulted in a high hit rate (40%) and led to novel chemotypes, while 2D similarity search had slightly better hit rate (51%), but lacking the novelty. To demonstrate the power of the virtual screening cascade, ligand efficiency indices were also calculated and their steady improvement was confirmed.


Subject(s)
Drug Discovery , Receptors, Serotonin/metabolism , Serotonin Antagonists/chemistry , Serotonin Antagonists/pharmacology , Small Molecule Libraries/chemistry , Small Molecule Libraries/pharmacology , Databases, Pharmaceutical , Drug Discovery/methods , Humans , Ligands , Models, Molecular
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