Cited by 137Computational Drug Discovery MethodsReceptor Mechanisms and SignalingProtein Interaction Studies and Fluorescence Analysis

Development of proteo-chemometrics: a novel technology for the analysis of drug-receptor interactions

Lapinsh, Maris, Prusis, Peteris, Gutcaits, Alexandrs, Lundstedt, Torbjörn, Wikberg, Jarl E.S.·2001·Biochimica et Biophysica Acta (BBA) - General Subjects

Abstract

A novel method for the analysis of drug receptor interactions has been developed and used to explore mechanisms involved in the binding of 4-piperidyl oxazole antagonists to alpha1a-, alpha1b- and alpha1d-adrenoceptors. The method exploits affinity data for a series of organic chemical compounds binding to wild-type and artificially mutated receptors. The receptor sequences and compounds are assigned predictor variables that are correlated to the measured pharmacological activities using partial least-squares projections to latent structures. The predictor variables consist of one descriptor block derived from the chemical properties of the receptors' primary amino acid sequences and another descriptor block derived from the chemical properties of the organic compounds. The cross-terms generated from the two descriptor blocks are also derived. Using this approach, very sturdy models were generated describing the interactions of the chemical compounds with the receptors. Models are useful to predict binding affinity and receptor subtype selectivity of compounds prior to their synthesis, and may find use in rational drug design. Moreover, models also give quantitative information about the interactions of the amino acids of the receptors with the ligands, thereby giving an insight into the molecular mechanisms involved in ligand binding.

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Crossref · 10.1016/s0304-4165(00)00187-2

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14 of 14 references verified0 citation errors · 0 not checkable

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  • PCM was used to predict ligand interactions with wild-type and mutated α-adrenoceptors, demonstrating superior predictivity compared to conventional QSAR methods.

    “For instance, this approach was used to predict ligand interactions with wild-type and mutated α-adrenoceptors where it has demonstrated superior predictivity in comparison with conventional QSAR methods.118”

    From QSAR without borders (2020) · cites this paper as [118]

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Authors
Lapinsh, M., Prusis, P., Gutcaits, A., Lundstedt, T., & Wikberg, J. E. S.
Affiliations
Uppsala University (SE)
Corresponding author
Wikberg, Jarl E.S.
Venue
Biochimica et Biophysica Acta (BBA) - General Subjects
Publisher
Elsevier BV
Published
2001-02
Volume
1525
Issue
1-2
Pages
180-190
ISSN
0304-4165 (ISSN-L)
OpenAlex
W2106440817
Cited by
134
References
15
Citations by year
2026: 3 · 2025: 2 · 2024: 4 · 2023: 5 · 2022: 3 · 2021: 6 · 2020: 13 · 2019: 5 · 2018: 9 · 2017: 4 · 2016: 11 · 2015: 4 · 2014: 6 · 2013: 7 · 2012: 3
FWCI
4.33
Type
journal article
Language
en
Open access
closed
Locations
  • Biochimica et Biophysica Acta (BBA) - General Subjects (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Interaction Studies and Fluorescence Analysis
Keywords
drug-receptor interactions, alpha1-adrenoceptors, receptor subtype selectivity, binding affinity prediction, ligand binding mechanism, rational drug design, receptor mutations
MeSH terms
Adrenergic alpha-Antagonists, Pharmaceutical Preparations, Humans, Ligands, Models, Biological, Oxazoles, Pharmacology, Receptors, Drug, Recombinant Fusion Proteins, Drug Design, Point Mutation, Receptors, Adrenergic, alpha-1, Quantitative Structure-Activity Relationship, In Vitro Techniques

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