Literature DB >> 31260165

Fragment- and negative image-based screening of phosphodiesterase 10A inhibitors.

Elmeri M Jokinen1, Pekka A Postila2, Mira Ahinko2, Sanna Niinivehmas1, Olli T Pentikäinen1,2,3.   

Abstract

A novel virtual screening methodology called fragment- and negative image-based (F-NiB) screening is introduced and tested experimentally using phosphodiesterase 10A (PDE10A) as a case study. Potent PDE10A-specific small-molecule inhibitors are actively sought after for their antipsychotic and neuroprotective effects. The F-NiB combines features from both fragment-based drug discovery and negative image-based (NIB) screening methodologies to facilitate rational drug discovery. The selected structural parts of protein-bound ligand(s) are seamlessly combined with the negative image of the target's ligand-binding cavity. This cavity- and fragment-based hybrid model, namely its shape and electrostatics, is used directly in the rigid docking of ab initio generated ligand 3D conformers. In total, 14 compounds were acquired using the F-NiB methodology, 3D quantitative structure-activity relationship modeling, and pharmacophore modeling. Three of the small molecules inhibited PDE10A at ~27 to ~67 μM range in a radiometric assay. In a larger context, the study shows that the F-NiB provides a flexible way to incorporate small-molecule fragments into the drug discovery.
© 2019 John Wiley & Sons A/S.

Entities:  

Keywords:  Huntington's disease; Parkinson's disease; fragment- and negative image-based (F-NiB) screening; fragment-based drug discovery; negative image-based; phosphodiesterase 10A; radiometric activity assay; schizophrenia; structure-based virtual screening; virtual screening

Year:  2019        PMID: 31260165     DOI: 10.1111/cbdd.13584

Source DB:  PubMed          Journal:  Chem Biol Drug Des        ISSN: 1747-0277            Impact factor:   2.817


  6 in total

1.  Screening of Natural Products Targeting SARS-CoV-2-ACE2 Receptor Interface - A MixMD Based HTVS Pipeline.

Authors:  Krishnasamy Gopinath; Elmeri M Jokinen; Sami T Kurkinen; Olli T Pentikäinen
Journal:  Front Chem       Date:  2020-11-19       Impact factor: 5.221

2.  Detection of Binding Sites on SARS-CoV-2 Spike Protein Receptor-Binding Domain by Molecular Dynamics Simulations in Mixed Solvents.

Authors:  Elmeri M Jokinen; Krishnasamy Gopinath; Sami T Kurkinen; Olli T Pentikainen
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2021-08-06       Impact factor: 3.702

3.  Identification of bio-active food compounds as potential SARS-CoV-2 PLpro inhibitors-modulators via negative image-based screening and computational simulations.

Authors:  Shovonlal Bhowmick; Nora Abdullah AlFaris; Jozaa Zaidan ALTamimi; Zeid A ALOthman; Pritee Chunarkar Patil; Tahany Saleh Aldayel; Saikh Mohammad Wabaidur; Achintya Saha
Journal:  Comput Biol Med       Date:  2022-04-01       Impact factor: 6.698

4.  Ligand-Enhanced Negative Images Optimized for Docking Rescoring.

Authors:  Sami T Kurkinen; Jukka V Lehtonen; Olli T Pentikäinen; Pekka A Postila
Journal:  Int J Mol Sci       Date:  2022-07-17       Impact factor: 6.208

5.  Identification of Novel Ribonucleotide Reductase Inhibitors for Therapeutic Application in Bile Tract Cancer: An Advanced Pharmacoinformatics Study.

Authors:  Md Ataul Islam; Mayuri Makarand Barshetty; Sridhar Srinivasan; Dawood Babu Dudekula; V P Subramanyam Rallabandi; Sameer Mohammed; Sathishkumar Natarajan; Junhyung Park
Journal:  Biomolecules       Date:  2022-09-10

6.  Identification of Potential Cytochrome P450 3A5 Inhibitors: An Extensive Virtual Screening through Molecular Docking, Negative Image-Based Screening, Machine Learning and Molecular Dynamics Simulation Studies.

Authors:  Md Ataul Islam; Dawood Babu Dudekula; V P Subramanyam Rallabandi; Sridhar Srinivasan; Sathishkumar Natarajan; Hoyong Chung; Junhyung Park
Journal:  Int J Mol Sci       Date:  2022-08-19       Impact factor: 6.208

  6 in total

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