<i>In silico</i> identification of novel 5-HT<sub>2A</sub> antagonists supported with ligand- and target-based drug design methodologies

Radan, Milica; Antonijević, Mirjana; Djikić, Teodora; Nikolic, Katarina

doi:10.1080/07391102.2020.1738961

Cited by 13 publications

(4 citation statements)

References 66 publications

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“…Similar to VS, QSAR studies are a valuable tool for ligand-based hit compound optimization. This approach has been employed in radiotracer development for multiple targets, including dopamine receptors [ 135 , 136 , 137 , 138 , 139 , 140 ], serotonin receptors [ 141 ], sigma receptors [ 142 , 143 ], beta-amyloid fibrils [ 4 , 144 , 145 ], and cancer-related kinases or receptors [ 146 , 147 , 148 , 149 ]. A QSAR model that is built to investigate ligand fragments that contribute to the binding affinities for multiple proteins, such as target and off-target proteins, can be used to predict the binding affinity for a protein of interest as well as selectivity versus off-target binding.…”

Section: Hit Compound Optimizationmentioning

confidence: 99%

Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development

et al. 2023

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The use of computer-aided drug design (CADD) for the identification of lead compounds in radiotracer development is steadily increasing. Traditional CADD methods, such as structure-based and ligand-based virtual screening and optimization, have been successfully utilized in many drug discovery programs and are highlighted throughout this review. First, we discuss the use of virtual screening for hit identification at the beginning of drug discovery programs. This is followed by an analysis of how the hits derived from virtual screening can be filtered and culled to highly probable candidates to test in in vitro assays. We then illustrate how CADD can be used to optimize the potency of experimentally validated hit compounds from virtual screening for use in positron emission tomography (PET). Finally, we conclude with a survey of the newest techniques in CADD employing machine learning (ML).

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Section: Hit Compound Optimizationmentioning

confidence: 99%

Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development

et al. 2023

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“…Previously published CoMFA/CoMSIA LB 3-D QSAR models based on dibenzazecines [80], 3-aminoethyl-1-tetralones, piperazines, benzothiazepines, pyrrolobenzazepines [81], and arylpiperazines [82], as well as the LB GRID/GOLPE models of (aminoalkyl)benzo and heterocycloalkanones [83], were also more accurate in predicting the potencies of compounds occupying the hydrophobic pocket. On the other hand, within the molecular docking-based SB GRID/GOLPE 3-D QSAR models generated on either butyrophenones [84], or lozapine, ziprasidone, and ChEMBL-listed analogues [84], the quality of the alignment within either the orthosteric area, the hydrophobic pocket, or both, was, as here, evaluated using the highest q 2 [63,85]. However, the universal SB 3-D QSAR model(s) defining the agonism/antagonism on the entire 5-HT 2A R active site remains to be generated, perhaps after increasing the number of K i -associated co-crystallized 5-HT 2A R compounds to a minimum of 15 (and thus updating Table 1), using either Open3DQSAR [77], 3-D_QSAutogrid/R [78], or Py_CoMFA [31,86].…”

Section: Molecular Determinants For Scsmentioning

confidence: 99%

Molecular Docking Assessment of Cathinones as 5-HT2AR Ligands: Developing of Predictive Structure-Based Bioactive Conformations and Three-Dimensional Structure-Activity Relationships Models for Future Recognition of Abuse Drugs

Tomašević,

Vujović,

Kostić

et al. 2023

Molecules

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Commercially available cathinones are drugs of long-term abuse drugs whose pharmacology is fairly well understood. While their psychedelic effects are associated with 5-HT2AR, the enclosed study summarizes efforts to shed light on the pharmacodynamic profiles, not yet known at the receptor level, using molecular docking and three-dimensional quantitative structure–activity relationship (3-D QSAR) studies. The bioactive conformations of cathinones were modeled by AutoDock Vina and were used to build structure-based (SB) 3-D QSAR models using the Open3DQSAR engine. Graphical inspection of the results led to the depiction of a 3-D structure analysis-activity relationship (SAR) scheme that could be used as a guideline for molecular determinants by which any untested cathinone molecule can be predicted as a potential 5-HT2AR binder prior to experimental evaluation. The obtained models, which showed a good agreement with the chemical properties of co-crystallized 5-HT2AR ligands, proved to be valuable for future virtual screening campaigns to recognize unused cathinones and similar compounds, such as 5-HT2AR ligands, minimizing both time and financial resources for the characterization of their psychedelic effects.

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“…In a recent investigation, Radan et al integrated a number of CADD methods, including MD simulation, molecular docking, and 3D-QSAR modelling in order to analyse the 3D-structure of the pharmacophore and binding kinetics of structurally different 5-HT2A receptor antagonists (98). Based on chemical structures, dataset compounds were separated into three clusters representing dibenzodiazepine, 1,2-benzoisothiazole and sulfonylpyridine derivatives.…”

Section: Successful Application Of Cadd Approaches In the Discovery Of Aminergic Gpcr Ligands For Treatment Of Neuropsychiatric Disordersmentioning

confidence: 99%

Current computer-aided drug design methodologies in discovery of novel drug candidates for neuropsychiatric and inflammatory diseases

Radan¹,

Bošković²,

Dobričić³

et al. 2021

Arhiv za farmaciju

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Drug discovery and development is a very challenging, expensive and time-consuming process. Impressive technological advances in computer sciences and molecular biology have made it possible to use computer-aided drug design (CADD) methods in various stages of the drug discovery and development pipeline. Nowadays, CADD presents an efficacious and indispensable tool, widely used in medicinal chemistry, to lead rational drug design and synthesis of novel compounds. In this article, an overview of commonly used CADD approaches from hit identification to lead optimization was presented. Moreover, different aspects of design of multitarget ligands for neuropsychiatric and anti-inflammatory diseases were summarized. Apparently, designing multi-target directed ligands for treatment of various complex diseases may offer better efficacy, and fewer side effects. Antipsychotics that act through aminergic G protein-coupled receptors (GPCRs), especially Dopamine D2 and serotonin 5-HT2A receptors, are the best option for treatment of various symptoms associated with neuropsychiatric disorders. Furthermore, multi-target directed cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) inhibitors are also a successful approach to aid the discovery of new anti-inflammatory drugs with fewer side effects. Overall, employing CADD approaches in the process of rational drug design provides a great opportunity for future development, allowing rapid identification of compounds with the optimal polypharmacological profile.

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In silico identification of novel 5-HT_2A antagonists supported with ligand- and target-based drug design methodologies

Cited by 13 publications

References 66 publications

Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development

Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development

Molecular Docking Assessment of Cathinones as 5-HT2AR Ligands: Developing of Predictive Structure-Based Bioactive Conformations and Three-Dimensional Structure-Activity Relationships Models for Future Recognition of Abuse Drugs

Current computer-aided drug design methodologies in discovery of novel drug candidates for neuropsychiatric and inflammatory diseases

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In silico identification of novel 5-HT2A antagonists supported with ligand- and target-based drug design methodologies

Cited by 13 publications

References 66 publications

Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development

Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development

Molecular Docking Assessment of Cathinones as 5-HT2AR Ligands: Developing of Predictive Structure-Based Bioactive Conformations and Three-Dimensional Structure-Activity Relationships Models for Future Recognition of Abuse Drugs

Current computer-aided drug design methodologies in discovery of novel drug candidates for neuropsychiatric and inflammatory diseases

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In silico identification of novel 5-HT_2A antagonists supported with ligand- and target-based drug design methodologies