Toward the Digitalization of Olfaction

Pizio, Antonella Di; Behr, Jürgen; Krautwurst, Dietmar

doi:10.1016/b978-0-12-809324-5.24147-3

Cited by 8 publications

(15 citation statements)

References 180 publications

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“…Hence, strategies aiming at enhancing the sampling of the conformational space of the receptor-ligand complex have been applied to overcome this limitation. These include flexible docking approaches and experimental data-driven model refinement (Di Pizio et al 2017 ; Nowak et al 2018 ; Bushdid et al 2018 ; Bushdid et al 2019 ; Di Pizio et al 2020a , b ), as well as molecular dynamics (MD) simulations (Gelis et al 2012 ; Charlier et al 2012 ; Charlier et al 2013 ; Topin et al 2014 ; Marchiori et al 2013 ; Sandal et al 2015 ; Li et al 2016 ; Fierro et al 2017 ; Ahmed et al 2018 ; Fierro et al 2019 ; Alfonso-Prieto et al 2019a , 2019b ; Haag et al, 2020 ; Schneider et al 2020 ).…”

Section: Computational Structural Methodsmentioning

confidence: 99%

“…Taken together, this suggests that bitter taste and odor molecules may be potential drug candidates (Di Pizio et al 2019 ). A few computational molecular modeling studies have been carried out to explore the pharmacological potential of TAS2Rs and ORs (Tong et al 2017 ; Nowak et al 2018 ; Di Pizio et al 2020a , b ). Besides generating structural models of the receptor/ligand pairs already known (Levit et al 2014 ; Tong et al 2017 ; Nowak et al 2018 ), computational approaches can also be used to design chemical modifications to improve ligand-receptor affinity and other drug-like properties (Di Pizio et al 2020a , b ).…”

Section: Computational Structural Methodsmentioning

confidence: 99%

“…A few computational molecular modeling studies have been carried out to explore the pharmacological potential of TAS2Rs and ORs (Tong et al 2017 ; Nowak et al 2018 ; Di Pizio et al 2020a , b ). Besides generating structural models of the receptor/ligand pairs already known (Levit et al 2014 ; Tong et al 2017 ; Nowak et al 2018 ), computational approaches can also be used to design chemical modifications to improve ligand-receptor affinity and other drug-like properties (Di Pizio et al 2020a , b ). For instance, TAS2R14 has been recently studied as potential drug target against respiratory infections (Di Pizio et al 2020a , b ) due to its association with innate immune responses (Hariri et al 2017 ) and its ability to bind clinical drugs that taste bitter, such as flufenamic acid (Levit et al 2014 ; Behrens et al 2018a , b ).…”

Section: Computational Structural Methodsmentioning

confidence: 99%

“…Besides generating structural models of the receptor/ligand pairs already known (Levit et al 2014 ; Tong et al 2017 ; Nowak et al 2018 ), computational approaches can also be used to design chemical modifications to improve ligand-receptor affinity and other drug-like properties (Di Pizio et al 2020a , b ). For instance, TAS2R14 has been recently studied as potential drug target against respiratory infections (Di Pizio et al 2020a , b ) due to its association with innate immune responses (Hariri et al 2017 ) and its ability to bind clinical drugs that taste bitter, such as flufenamic acid (Levit et al 2014 ; Behrens et al 2018a , b ). By integrating experimental mutagenesis data, homology modeling and molecular docking, an initial structural model of TAS2R14 in complex with flufenamic acid was generated (Levit et al 2014 ; Nowak et al 2018 ).…”

Section: Computational Structural Methodsmentioning

confidence: 99%

“…These ligands, as well as additional analogs designed using medicinal chemistry concepts, were synthesized and subsequently tested with in vitro functional assays, resulting in the identification of new TAS2R14 agonists with nanomolar potency. Moreover, these experimental data were further used to refine the initial TAS2R14 model and obtain a better molecular description of the ligand binding modes (Di Pizio et al 2020a , b ). Altogether, this success story shows the potential of integrated experimental-computational approaches for ligand design for TAS2Rs and eventually ORs and opens the way to exploit the largely untapped pharmacological potential of these chemosensory receptors.…”

Section: Computational Structural Methodsmentioning

confidence: 99%

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Bitter Taste and Olfactory Receptors: Beyond Chemical Sensing in the Tongue and the Nose

Alfonso‐Prieto

2021

J Membrane Biol

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The Up-and-Coming-Scientist section of the current issue of the Journal of Membrane Biology features the invited essay by Dr. Mercedes Alfonso-Prieto, Assistant Professor at the Forschungszentrum Jülich (FZJ), Germany, and the Heinrich-Heine University Düsseldorf, Vogt Institute for Brain Research. Dr. Alfonso-Prieto completed her doctoral degree in chemistry at the Barcelona Science Park, Spain, in 2009, pursued post-doctoral research in computational molecular sciences at Temple University, USA, and then, as a Marie Curie post-doctoral fellow at the University of Barcelona, worked on computations of enzyme reactions and modeling of photoswitchable ligands targeting neuronal receptors. In 2016, she joined the Institute for Advanced Science and the Institute for Computational Biomedicine at the FZJ, where she pursues research on modeling and simulation of chemical senses. The invited essay by Dr. Alfonso-Prieto discusses state-of-the-art modeling of molecular receptors involved in chemical sensing – the senses of taste and smell. These receptors, and computational methods to study them, are the focus of Dr. Alfonso-Prieto’s research. Recently, Dr. Alfonso-Prieto and colleagues have presented a new methodology to predict ligand binding poses for GPCRs, and extensive computations that deciphered the ligand selectivity determinants of bitter taste receptors. These developments inform our current understanding of how taste occurs at the molecular level. Graphic Abstract

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Section: Computational Structural Methodsmentioning

confidence: 99%

Section: Computational Structural Methodsmentioning

confidence: 99%

Section: Computational Structural Methodsmentioning

confidence: 99%

Section: Computational Structural Methodsmentioning

confidence: 99%

Section: Computational Structural Methodsmentioning

confidence: 99%

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Bitter Taste and Olfactory Receptors: Beyond Chemical Sensing in the Tongue and the Nose

Alfonso‐Prieto

2021

J Membrane Biol

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Welches analytische Potenzial steckt darin?

2022

Lebensmittelchemie

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Modeling the Orthosteric Binding Site of the G Protein-Coupled Odorant Receptor OR5K1

Nicoli

Haag

Marcinek

et al. 2023

J. Chem. Inf. Model.

Self Cite

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With approximately 400 encoding genes in humans, odorant receptors (ORs) are the largest subfamily of class A G protein-coupled receptors (GPCRs). Despite its high relevance and representation, the odorant-GPCRome is structurally poorly characterized: no experimental structures are available, and the low sequence identity of ORs to experimentally solved GPCRs is a significant challenge for their modeling. Moreover, the receptive range of most ORs is unknown. The odorant receptor OR5K1 was recently and comprehensively characterized in terms of cognate agonists. Here, we report two additional agonists and functional data of the most potent compound on two mutants, L104 3.32 and L255 6.51 . Experimental data was used to guide the investigation of the binding modes of OR5K1 ligands into the orthosteric binding site using structural information from AI-driven modeling, as recently released in the AlphaFold Protein Structure Database, and from homology modeling. Induced-fit docking simulations were used to sample the binding site conformational space for ensemble docking. Mutagenesis data guided side chain residue sampling and model selection. We obtained models that could better rationalize the different activity of active (agonist) versus inactive molecules with respect to starting models and also capture differences in activity related to minor structural differences. Therefore, we provide a model refinement protocol that can be applied to model the orthosteric binding site of ORs as well as that of GPCRs with low sequence identity to available templates.

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Toward the Digitalization of Olfaction

Cited by 8 publications

References 180 publications

Bitter Taste and Olfactory Receptors: Beyond Chemical Sensing in the Tongue and the Nose

Bitter Taste and Olfactory Receptors: Beyond Chemical Sensing in the Tongue and the Nose

Welches analytische Potenzial steckt darin?

Modeling the Orthosteric Binding Site of the G Protein-Coupled Odorant Receptor OR5K1

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