Identification of Novel Histamine H4 Ligands by Virtual Screening on Molecular Dynamics Ensembles

Kiss, Robert S.; Jójárt, Balázs; Schmidt, Éva; Kiss, Béla; Keserü, György M.

doi:10.1002/minf.201300072

Cited by 7 publications

(7 citation statements)

References 16 publications

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“…Our group also reported a retrospective and prospective screening study using snapshots from a previously described MD simulation of H4R built on the bovine rhodopsin structure [45]. Ensemble docking on selected snapshots that demonstrated highest enrichment factors in the retrospective analysis was used to identify new H4 ligands.…”

Section: H4 Receptormentioning

confidence: 99%

Structure-based discovery and binding site analysis of histamine receptor ligands

Kingsford-Adaboh

Keserü

2016

Expert Opinion on Drug Discovery

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Introduction: Application of structure-based drug discovery in histamine receptor projects was previously hampered by the lack of experimental structures. The publication of the first X-ray structure of the histamine H1 receptor has been followed by several successful virtual screens and binding site analysis studies of H1-antihistamines. This structure together with several other recently solved aminergic G-protein coupled receptors (GPCRs) enabled the development of more realistic homology models for H2, H3 and H4 receptors. Areas covered: In this paper, we review the development of histamine receptors models and their application on drug discovery. Expert opinion: In our opinion, the application of atomistic histamine receptor models played a significant role in understanding key ligand-receptor interactions as well as in the discovery of novel chemical starting points. The recently solved H1 receptor structure is a major milestone in structure-based drug discovery, however our analysis also demonstrate that for building H3 and H4 receptor homology models other GPCRs may be more suitable as a template. For these receptors we envisage that the development of higher quality homology models will significantly contribute to the discovery and optimization of novel H3 and H4 ligands.

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Section: H4 Receptormentioning

confidence: 99%

Structure-based discovery and binding site analysis of histamine receptor ligands

Kingsford-Adaboh

Keserü

2016

Expert Opinion on Drug Discovery

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“…Kiss et al identified novel histamine H 4 R ligands through the ensemble docking based on homology model conformers obtained from MD simulations. Such representative hH 4 R conformers were found to be more suitable for the identification of H 4 R antagonists than the initial homology models [25]. It was also found that X-ray and homology model structures may be complementary, or at least able to sample different protein conformations leading to non-overlapping hits and can provide important starting points for fragment-based lead discovery for other GPCRs [6].…”

Section: Ligands Targeting H 4 R and Their Interactionsmentioning

confidence: 96%

“…The multitarget-directed ligands with H 3 R antagonistic activity coupled with the ability to inhibit acetyl/butyrylcholinesterases and monoamine oxidases A/B, potentially suitable for the treatment of Alzheimer's or Parkinson's disease, were studied by Bautista-Aguilera et al [78]. All the studied compounds revealed an interesting neuroprotection profile against oligomycin A, okadaic acid (as a model of the hyperphosphorylation of tau), and βamyloid peptide Aβ [25][26][27][28][29][30][31][32][33][34][35] . Of all ligands the non-imidazole ligand, contilisant, had the best properties.…”

Section: Multi-target H 3 R Ligandsmentioning

confidence: 99%

“…Recent investigations on the role of HRs in (patho)physiology and the use of receptor antagonists in in vivo disease models reveal a vast potential of histamine receptors in the treatment of e.g., allergic inflammation, neuropathic pain, and cancer [13][14][15][16][17][18][19][20][21]. The search for new and potent HR antagonists contributes to a steadily increasing number of potent and structurally diverse compounds [6,[22][23][24][25][26][27][28]. Furthermore, development of ligands that are able to bind to two or more HR subtypes offers another opportunity to achieve a synergistic clinical effect mostly for allergic inflammations and neuropsychiatric disorders [29][30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

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Molecular Modeling of Histamine Receptors—Recent Advances in Drug Discovery

Mehta

Filipek

2021

Molecules

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The recent developments of fast reliable docking, virtual screening and other algorithms gave rise to discovery of many novel ligands of histamine receptors that could be used for treatment of allergic inflammatory disorders, central nervous system pathologies, pain, cancer and obesity. Furthermore, the pharmacological profiles of ligands clearly indicate that these receptors may be considered as targets not only for selective but also for multi-target drugs that could be used for treatment of complex disorders such as Alzheimer’s disease. Therefore, analysis of protein-ligand recognition in the binding site of histamine receptors and also other molecular targets has become a valuable tool in drug design toolkit. This review covers the period 2014–2020 in the field of theoretical investigations of histamine receptors mostly based on molecular modeling as well as the experimental characterization of novel ligands of these receptors.

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“…Virtual screening (VS) is an applicable strategy, which is used to differentiate molecules based on a desired property and can be useful for the identification of novel potential leads . Virtual screening as a rapid and economic approach has been extensively used in medicinal chemistry area . It can be divided into two wide classes: structure‐based and ligand‐based.…”

Section: Introductionmentioning

confidence: 99%

Anti‐HIV‐1 Activity Prediction of Novel Gp41 Inhibitors Using Structure‐Based Virtual Screening and Molecular Dynamics Simulation

Sepehri

Saghaie

Fassihi

2016

Molecular Informatics

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The fusion of viral and host cell membranes is mediated using gp41 subunit of the human immunodeficiency virus type 1 (HIV-1) envelope glycoprotein. As the HIV-1 enters the host cells, the two helical regions (HR1 and HR2) in the ectodomain of gp41 form a six-helix bundle, which carries the target and viral cell membranes to close proximity. Steps of this process serve as attractive targets for developing HIV-1 fusion inhibitors. Identification of some novel HIV fusion inhibitors with the goal of blocking the formation of the six-helix bundle was accomplished by computer-aided drug design techniques. A virtual screening strategy was employed to recognize small molecules presumably able to bind the gp41 at the internal interface of the NHR helices at the core native viral six-helix. This study was carried out in two stages. In the first stage, a library of more than seven thousand compounds was collected from ZINC, PubChem and BindingDB databases and protein data bank. Key contacts of known inhibitors with gp41 binding site residues were considered as the collecting criteria. In the second stage series of filtering processes were performed on this library in subsequent steps to find the potential gp41 inhibitors. The filtering criteria included pharmacokinetic and ADMET properties as well as in silico anti-HIV-1 prediction. Molecular docking simulation was carried out to identify interactions of the filtered molecules with the key residues in the gp41 binding site. Finally, molecular dynamics simulation indicates the superior inhibitory ability of three selected compounds over the known gp41inhibitor, NB-64.

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Identification of Novel Histamine H4 Ligands by Virtual Screening on Molecular Dynamics Ensembles

Cited by 7 publications

References 16 publications

Structure-based discovery and binding site analysis of histamine receptor ligands

Structure-based discovery and binding site analysis of histamine receptor ligands

Molecular Modeling of Histamine Receptors—Recent Advances in Drug Discovery

Anti‐HIV‐1 Activity Prediction of Novel Gp41 Inhibitors Using Structure‐Based Virtual Screening and Molecular Dynamics Simulation

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