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Blanes-Mira C, Fernández-Aguado P, de Andrés-López J, Fernández-Carvajal A, Ferrer-Montiel A, Fernández-Ballester G. Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening. Molecules 2022; 28:molecules28010175. [PMID: 36615367 PMCID: PMC9821981 DOI: 10.3390/molecules28010175] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 12/19/2022] [Accepted: 12/21/2022] [Indexed: 12/28/2022] Open
Abstract
The rapid advances of 3D techniques for the structural determination of proteins and the development of numerous computational methods and strategies have led to identifying highly active compounds in computer drug design. Molecular docking is a method widely used in high-throughput virtual screening campaigns to filter potential ligands targeted to proteins. A great variety of docking programs are currently available, which differ in the algorithms and approaches used to predict the binding mode and the affinity of the ligand. All programs heavily rely on scoring functions to accurately predict ligand binding affinity, and despite differences in performance, none of these docking programs is preferable to the others. To overcome this problem, consensus scoring methods improve the outcome of virtual screening by averaging the rank or score of individual molecules obtained from different docking programs. The successful application of consensus docking in high-throughput virtual screening highlights the need to optimize the predictive power of molecular docking methods.
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Veríssimo GC, Serafim MSM, Kronenberger T, Ferreira RS, Honorio KM, Maltarollo VG. Designing drugs when there is low data availability: one-shot learning and other approaches to face the issues of a long-term concern. Expert Opin Drug Discov 2022; 17:929-947. [PMID: 35983695 DOI: 10.1080/17460441.2022.2114451] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Modern drug discovery generally is accessed by useful information from previous large databases or uncovering novel data. The lack of biological and/or chemical data tends to slow the development of scientific research and innovation. Here, approaches that may help provide solutions to generate or obtain enough relevant data or improve/accelerate existing methods within the last five years were reviewed. AREAS COVERED One-shot learning (OSL) approaches, structural modeling, molecular docking, scoring function space (SFS), molecular dynamics (MD), and quantum mechanics (QM) may be used to amplify the amount of available data to drug design and discovery campaigns, presenting methods, their perspectives, and discussions to be employed in the near future. EXPERT OPINION Recent works have successfully used these techniques to solve a range of issues in the face of data scarcity, including complex problems such as the challenging scenario of drug design aimed at intrinsically disordered proteins and the evaluation of potential adverse effects in a clinical scenario. These examples show that it is possible to improve and kickstart research from scarce available data to design and discover new potential drugs.
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Affiliation(s)
- Gabriel C Veríssimo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Mateus Sá M Serafim
- Departamento de Microbiologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Thales Kronenberger
- Department of Medical Oncology and Pneumology, Internal Medicine VIII, University Hospital of Tübingen, Tübingen, Germany.,School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Rafaela S Ferreira
- Departamento de Bioquímica e Imunologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Kathia M Honorio
- Escola de Artes, Ciências e Humanidades, Universidade de São Paulo (USP), São Paulo, Brazil.,Centro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André, Brazil
| | - Vinícius G Maltarollo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
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Krishna Deepak RNV, Verma RK, Hartono YD, Yew WS, Fan H. Recent Advances in Structure, Function, and Pharmacology of Class A Lipid GPCRs: Opportunities and Challenges for Drug Discovery. Pharmaceuticals (Basel) 2021; 15:12. [PMID: 35056070 PMCID: PMC8779880 DOI: 10.3390/ph15010012] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/17/2021] [Accepted: 12/17/2021] [Indexed: 01/01/2023] Open
Abstract
Great progress has been made over the past decade in understanding the structural, functional, and pharmacological diversity of lipid GPCRs. From the first determination of the crystal structure of bovine rhodopsin in 2000, much progress has been made in the field of GPCR structural biology. The extraordinary progress in structural biology and pharmacology of GPCRs, coupled with rapid advances in computational approaches to study receptor dynamics and receptor-ligand interactions, has broadened our comprehension of the structural and functional facets of the receptor family members and has helped usher in a modern age of structure-based drug design and development. First, we provide a primer on lipid mediators and lipid GPCRs and their role in physiology and diseases as well as their value as drug targets. Second, we summarize the current advancements in the understanding of structural features of lipid GPCRs, such as the structural variation of their extracellular domains, diversity of their orthosteric and allosteric ligand binding sites, and molecular mechanisms of ligand binding. Third, we close by collating the emerging paradigms and opportunities in targeting lipid GPCRs, including a brief discussion on current strategies, challenges, and the future outlook.
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Affiliation(s)
- R. N. V. Krishna Deepak
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, Matrix #07-01, Singapore 138671, Singapore; (R.K.V.); (Y.D.H.)
| | - Ravi Kumar Verma
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, Matrix #07-01, Singapore 138671, Singapore; (R.K.V.); (Y.D.H.)
| | - Yossa Dwi Hartono
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, Matrix #07-01, Singapore 138671, Singapore; (R.K.V.); (Y.D.H.)
- Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, 14 Medical Drive, Singapore 117599, Singapore;
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore
| | - Wen Shan Yew
- Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, 14 Medical Drive, Singapore 117599, Singapore;
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore
| | - Hao Fan
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, Matrix #07-01, Singapore 138671, Singapore; (R.K.V.); (Y.D.H.)
- Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, 14 Medical Drive, Singapore 117599, Singapore;
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Ballante F, Kooistra AJ, Kampen S, de Graaf C, Carlsson J. Structure-Based Virtual Screening for Ligands of G Protein-Coupled Receptors: What Can Molecular Docking Do for You? Pharmacol Rev 2021; 73:527-565. [PMID: 34907092 DOI: 10.1124/pharmrev.120.000246] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome and are important therapeutic targets. During the last decade, the number of atomic-resolution structures of GPCRs has increased rapidly, providing insights into drug binding at the molecular level. These breakthroughs have created excitement regarding the potential of using structural information in ligand design and initiated a new era of rational drug discovery for GPCRs. The molecular docking method is now widely applied to model the three-dimensional structures of GPCR-ligand complexes and screen for chemical probes in large compound libraries. In this review article, we first summarize the current structural coverage of the GPCR superfamily and the understanding of receptor-ligand interactions at atomic resolution. We then present the general workflow of structure-based virtual screening and strategies to discover GPCR ligands in chemical libraries. We assess the state of the art of this research field by summarizing prospective applications of virtual screening based on experimental structures. Strategies to identify compounds with specific efficacy and selectivity profiles are discussed, illustrating the opportunities and limitations of the molecular docking method. Our overview shows that structure-based virtual screening can discover novel leads and will be essential in pursuing the next generation of GPCR drugs. SIGNIFICANCE STATEMENT: Extraordinary advances in the structural biology of G protein-coupled receptors have revealed the molecular details of ligand recognition by this large family of therapeutic targets, providing novel avenues for rational drug design. Structure-based docking is an efficient computational approach to identify novel chemical probes from large compound libraries, which has the potential to accelerate the development of drug candidates.
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Affiliation(s)
- Flavio Ballante
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Albert J Kooistra
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Stefanie Kampen
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Chris de Graaf
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Jens Carlsson
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
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Jabeen A, de March CA, Matsunami H, Ranganathan S. Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors. Int J Mol Sci 2021; 22:ijms222111546. [PMID: 34768977 PMCID: PMC8583936 DOI: 10.3390/ijms222111546] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 10/21/2021] [Accepted: 10/22/2021] [Indexed: 12/29/2022] Open
Abstract
Olfactory receptors (ORs) constitute the largest superfamily of G protein-coupled receptors (GPCRs). ORs are involved in sensing odorants as well as in other ectopic roles in non-nasal tissues. Matching of an enormous number of the olfactory stimulation repertoire to its counterpart OR through machine learning (ML) will enable understanding of olfactory system, receptor characterization, and exploitation of their therapeutic potential. In the current study, we have selected two broadly tuned ectopic human OR proteins, OR1A1 and OR2W1, for expanding their known chemical space by using molecular descriptors. We present a scheme for selecting the optimal features required to train an ML-based model, based on which we selected the random forest (RF) as the best performer. High activity agonist prediction involved screening five databases comprising ~23 M compounds, using the trained RF classifier. To evaluate the effectiveness of the machine learning based virtual screening and check receptor binding site compatibility, we used docking of the top target ligands to carefully develop receptor model structures. Finally, experimental validation of selected compounds with significant docking scores through in vitro assays revealed two high activity novel agonists for OR1A1 and one for OR2W1.
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Affiliation(s)
- Amara Jabeen
- Applied BioSciences, Macquarie University, Sydney, NSW 2109, Australia;
| | - Claire A. de March
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA;
| | - Hiroaki Matsunami
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, USA;
- Department of Neurobiology, Duke Institute for Brain Sciences, Duke University, Durham, NC 27710, USA
- Correspondence: (H.M.); (S.R.)
| | - Shoba Ranganathan
- Applied BioSciences, Macquarie University, Sydney, NSW 2109, Australia;
- Correspondence: (H.M.); (S.R.)
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6
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Vidad AR, Macaspac S, Ng HL. Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation. PeerJ 2021; 9:e12219. [PMID: 34631323 PMCID: PMC8475542 DOI: 10.7717/peerj.12219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 09/06/2021] [Indexed: 11/20/2022] Open
Abstract
GPCRs (G-protein coupled receptors) are the largest family of drug targets and share a conserved structure. Binding sites are unknown for many important GPCR ligands due to the difficulties of GPCR recombinant expression, biochemistry, and crystallography. We describe our approach, ConDockSite, for predicting ligand binding sites in class A GPCRs using combined information from surface conservation and docking, starting from crystal structures or homology models. We demonstrate the effectiveness of ConDockSite on crystallized class A GPCRs such as the beta2 adrenergic and A2A adenosine receptors. We also demonstrate that ConDockSite successfully predicts ligand binding sites from high-quality homology models. Finally, we apply ConDockSite to predict the ligand binding sites on a structurally uncharacterized GPCR, GPER, the G-protein coupled estrogen receptor. Most of the sites predicted by ConDockSite match those found in other independent modeling studies. ConDockSite predicts that four ligands bind to a common location on GPER at a site deep in the receptor cleft. Incorporating sequence conservation information in ConDockSite overcomes errors introduced from physics-based scoring functions and homology modeling.
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Affiliation(s)
- Ashley Ryan Vidad
- Department of Chemistry, University of Hawaii at Manoa, Honolulu, Hawaii, United States of America
| | - Stephen Macaspac
- Department of Chemistry, University of Hawaii at Manoa, Honolulu, Hawaii, United States of America
| | - Ho Leung Ng
- Department of Biochemistry and Molecular Biophysics, Kansas State University, Manhattan, Kansas, United States of America
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Bhunia SS, Saxena AK. Efficiency of Homology Modeling Assisted Molecular Docking in G-protein Coupled Receptors. Curr Top Med Chem 2021; 21:269-294. [PMID: 32901584 DOI: 10.2174/1568026620666200908165250] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 08/20/2020] [Accepted: 09/01/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Molecular docking is in regular practice to assess ligand affinity on a target protein crystal structure. In the absence of protein crystal structure, the homology modeling or comparative modeling is the best alternative to elucidate the relationship details between a ligand and protein at the molecular level. The development of accurate homology modeling (HM) and its integration with molecular docking (MD) is essential for successful, rational drug discovery. OBJECTIVE The G-protein coupled receptors (GPCRs) are attractive therapeutic targets due to their immense role in human pharmacology. The GPCRs are membrane-bound proteins with the complex constitution, and the understanding of their activation and inactivation mechanisms is quite challenging. Over the past decade, there has been a rapid expansion in the number of solved G-protein-coupled receptor (GPCR) crystal structures; however, the majority of the GPCR structures remain unsolved. In this context, HM guided MD has been widely used for structure-based drug design (SBDD) of GPCRs. METHODS The focus of this review is on the recent (i) developments on HM supported GPCR drug discovery in the absence of GPCR crystal structures and (ii) application of HM in understanding the ligand interactions at the binding site, virtual screening, determining receptor subtype selectivity and receptor behaviour in comparison with GPCR crystal structures. RESULTS The HM in GPCRs has been extremely challenging due to the scarcity in template structures. In such a scenario, it is difficult to get accurate HM that can facilitate understanding of the ligand-receptor interactions. This problem has been alleviated to some extent by developing refined HM based on incorporating active /inactive ligand information and inducing protein flexibility. In some cases, HM proteins were found to outscore crystal structures. CONCLUSION The developments in HM have been highly operative to gain insights about the ligand interaction at the binding site and receptor functioning at the molecular level. Thus, HM guided molecular docking may be useful for rational drug discovery for the GPCRs mediated diseases.
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Affiliation(s)
- Shome S Bhunia
- Global Institute of Pharmaceutical Education and Research, Kashipur, Uttarakhand, India
| | - Anil K Saxena
- Division of Medicinal and Process Chemistry, CSIR-CDRI, Lucknow 226031, India
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8
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Jaladanki CK, He Y, Zhao LN, Maurer-Stroh S, Loo LH, Song H, Fan H. Virtual screening of potentially endocrine-disrupting chemicals against nuclear receptors and its application to identify PPARγ-bound fatty acids. Arch Toxicol 2020; 95:355-374. [PMID: 32909075 PMCID: PMC7811525 DOI: 10.1007/s00204-020-02897-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 08/27/2020] [Indexed: 12/17/2022]
Abstract
Nuclear receptors (NRs) are key regulators of energy homeostasis, body development, and sexual reproduction. Xenobiotics binding to NRs may disrupt natural hormonal systems and induce undesired adverse effects in the body. However, many chemicals of concerns have limited or no experimental data on their potential or lack-of-potential endocrine-disrupting effects. Here, we propose a virtual screening method based on molecular docking for predicting potential endocrine-disrupting chemicals (EDCs) that bind to NRs. For 12 NRs, we systematically analyzed how multiple crystal structures can be used to distinguish actives and inactives found in previous high-throughput experiments. Our method is based on (i) consensus docking scores from multiple structures at a single functional state (agonist-bound or antagonist-bound), (ii) multiple functional states (agonist-bound and antagonist-bound), and (iii) multiple pockets (orthosteric site and alternative sites) of these NRs. We found that the consensus enrichment from multiple structures is better than or comparable to the best enrichment from a single structure. The discriminating power of this consensus strategy was further enhanced by a chemical similarity-weighted scoring scheme, yielding better or comparable enrichment for all studied NRs. Applying this optimized method, we screened 252 fatty acids against peroxisome proliferator-activated receptor gamma (PPARγ) and successfully identified 3 previously unknown fatty acids with Kd = 100-250 μM including two furan fatty acids: furannonanoic acid (FNA) and furanundecanoic acid (FUA), and one cyclopropane fatty acid: phytomonic acid (PTA). These results suggested that the proposed method can be used to rapidly screen and prioritize potential EDCs for further experimental evaluations.
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Affiliation(s)
- Chaitanya K Jaladanki
- Bioinformatics Institute (BII), Agency for Science, Technology, and Research (A*STAR), 30 Biopolis Street, Matrix No. 07-01, Singapore, 138671, Singapore
- Toxicity Mode-of-Action Discovery (ToxMAD) Platform, Innovations in Food and Chemical Safety Programme, Agency for Science, Technology, and Research (A*STAR), Singapore, 138671, Singapore
| | - Yang He
- Institute of Molecular and Cell Biology, 61 Biopolis Drive, Singapore, 138673, Singapore
| | - Li Na Zhao
- Bioinformatics Institute (BII), Agency for Science, Technology, and Research (A*STAR), 30 Biopolis Street, Matrix No. 07-01, Singapore, 138671, Singapore
| | - Sebastian Maurer-Stroh
- Bioinformatics Institute (BII), Agency for Science, Technology, and Research (A*STAR), 30 Biopolis Street, Matrix No. 07-01, Singapore, 138671, Singapore
- Toxicity Mode-of-Action Discovery (ToxMAD) Platform, Innovations in Food and Chemical Safety Programme, Agency for Science, Technology, and Research (A*STAR), Singapore, 138671, Singapore
| | - Lit-Hsin Loo
- Bioinformatics Institute (BII), Agency for Science, Technology, and Research (A*STAR), 30 Biopolis Street, Matrix No. 07-01, Singapore, 138671, Singapore
- Toxicity Mode-of-Action Discovery (ToxMAD) Platform, Innovations in Food and Chemical Safety Programme, Agency for Science, Technology, and Research (A*STAR), Singapore, 138671, Singapore
| | - Haiwei Song
- Institute of Molecular and Cell Biology, 61 Biopolis Drive, Singapore, 138673, Singapore.
| | - Hao Fan
- Bioinformatics Institute (BII), Agency for Science, Technology, and Research (A*STAR), 30 Biopolis Street, Matrix No. 07-01, Singapore, 138671, Singapore.
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Structure-based screening for discovery of sweet compounds. Food Chem 2020; 315:126286. [DOI: 10.1016/j.foodchem.2020.126286] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 01/10/2020] [Accepted: 01/21/2020] [Indexed: 02/06/2023]
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Jaiteh M, Rodríguez-Espigares I, Selent J, Carlsson J. Performance of virtual screening against GPCR homology models: Impact of template selection and treatment of binding site plasticity. PLoS Comput Biol 2020; 16:e1007680. [PMID: 32168319 PMCID: PMC7135368 DOI: 10.1371/journal.pcbi.1007680] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 04/06/2020] [Accepted: 01/23/2020] [Indexed: 12/15/2022] Open
Abstract
Rational drug design for G protein-coupled receptors (GPCRs) is limited by the small number of available atomic resolution structures. We assessed the use of homology modeling to predict the structures of two therapeutically relevant GPCRs and strategies to improve the performance of virtual screening against modeled binding sites. Homology models of the D2 dopamine (D2R) and serotonin 5-HT2A receptors (5-HT2AR) were generated based on crystal structures of 16 different GPCRs. Comparison of the homology models to D2R and 5-HT2AR crystal structures showed that accurate predictions could be obtained, but not necessarily using the most closely related template. Assessment of virtual screening performance was based on molecular docking of ligands and decoys. The results demonstrated that several templates and multiple models based on each of these must be evaluated to identify the optimal binding site structure. Models based on aminergic GPCRs showed substantial ligand enrichment and there was a trend toward improved virtual screening performance with increasing binding site accuracy. The best models even yielded ligand enrichment comparable to or better than that of the D2R and 5-HT2AR crystal structures. Methods to consider binding site plasticity were explored to further improve predictions. Molecular docking to ensembles of structures did not outperform the best individual binding site models, but could increase the diversity of hits from virtual screens and be advantageous for GPCR targets with few known ligands. Molecular dynamics refinement resulted in moderate improvements of structural accuracy and the virtual screening performance of snapshots was either comparable to or worse than that of the raw homology models. These results provide guidelines for successful application of structure-based ligand discovery using GPCR homology models.
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Affiliation(s)
- Mariama Jaiteh
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Ismael Rodríguez-Espigares
- Research Programme on Biomedical Informatics (GRIB), Department of Experimental and Health Sciences of Pompeu Fabra University (UPF), Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Jana Selent
- Research Programme on Biomedical Informatics (GRIB), Department of Experimental and Health Sciences of Pompeu Fabra University (UPF), Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Jens Carlsson
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
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Abstract
Asthma is a heterogeneous inflammatory disease of the airways that is associated with airway hyperresponsiveness and airflow limitation. Although asthma was once simply categorized as atopic or nonatopic, emerging analyses over the last few decades have revealed a variety of asthma endotypes that are attributed to numerous pathophysiological mechanisms. The classification of asthma by endotype is primarily routed in different profiles of airway inflammation that contribute to bronchoconstriction. Many asthma therapeutics target G protein-coupled receptors (GPCRs), which either enhance bronchodilation or prevent bronchoconstriction. Short-acting and long-acting β 2-agonists are widely used bronchodilators that signal through the activation of the β 2-adrenergic receptor. Short-acting and long-acting antagonists of muscarinic acetylcholine receptors are used to reduce bronchoconstriction by blocking the action of acetylcholine. Leukotriene antagonists that block the signaling of cysteinyl leukotriene receptor 1 are used as an add-on therapy to reduce bronchoconstriction and inflammation induced by cysteinyl leukotrienes. A number of GPCR-targeting asthma drug candidates are also in different stages of development. Among them, antagonists of prostaglandin D2 receptor 2 have advanced into phase III clinical trials. Others, including antagonists of the adenosine A2B receptor and the histamine H4 receptor, are in early stages of clinical investigation. In the past decade, significant research advancements in pharmacology, cell biology, structural biology, and molecular physiology have greatly deepened our understanding of the therapeutic roles of GPCRs in asthma and drug action on these GPCRs. This review summarizes our current understanding of GPCR signaling and pharmacology in the context of asthma treatment. SIGNIFICANCE STATEMENT: Although current treatment methods for asthma are effective for a majority of asthma patients, there are still a large number of patients with poorly controlled asthma who may experience asthma exacerbations. This review summarizes current asthma treatment methods and our understanding of signaling and pharmacology of G protein-coupled receptors (GPCRs) in asthma therapy, and discusses controversies regarding the use of GPCR drugs and new opportunities in developing GPCR-targeting therapeutics for the treatment of asthma.
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Affiliation(s)
- Stacy Gelhaus Wendell
- Department of Pharmacology and Chemical Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania (S.G.W., C.Z.); Bioinformatics Institute, Agency for Science, Technology, and Research, Singapore (H.F.); and Department of Biological Sciences, National University of Singapore, and Center for Computational Biology, DUKE-NUS Medical School, Singapore (H.F.)
| | - Hao Fan
- Department of Pharmacology and Chemical Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania (S.G.W., C.Z.); Bioinformatics Institute, Agency for Science, Technology, and Research, Singapore (H.F.); and Department of Biological Sciences, National University of Singapore, and Center for Computational Biology, DUKE-NUS Medical School, Singapore (H.F.)
| | - Cheng Zhang
- Department of Pharmacology and Chemical Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania (S.G.W., C.Z.); Bioinformatics Institute, Agency for Science, Technology, and Research, Singapore (H.F.); and Department of Biological Sciences, National University of Singapore, and Center for Computational Biology, DUKE-NUS Medical School, Singapore (H.F.)
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12
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Woo JA, Castaño M, Goss A, Kim D, Lewandowski EM, Chen Y, Liggett SB. Differential long-term regulation of TAS2R14 by structurally distinct agonists. FASEB J 2019; 33:12213-12225. [PMID: 31430434 DOI: 10.1096/fj.201802627rr] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Bitter taste receptor-14 (TAS2R14) is a GPCR also expressed on human airway smooth muscle cells, which signals to intracellular [Ca2+], resulting in relaxation of the airway, and is a novel target for bronchodilators. Here, we examine long-term, agonist-promoted down-regulation of TAS2R14 expression because tachyphylaxis would be an undesirable therapeutic characteristic. Five TAS2R structurally distinct full agonists were studied to ascertain biasing away from down-regulation. Agonist exposure for 18 h caused minimal desensitization by diphenhydramine (DPD) compared with ∼50% desensitization with all other agonists. Agonists evoked β-arrestin recruitment to TAS2R14, which was not seen with a phosphoacceptor-deficient mutant, TAS2R14-10A. All agonists except for DPD also caused subsequent TAS2R14 internalization and trafficking via early and late endosomes to down-regulation. TAS2R14-10A failed to undergo these events with any agonist. Molecular docking showed that DPD has specific interactions deep within a binding pocket that are not observed with the other agonists, which may lock the receptor in a conformation that does not internalize and therefore does not undergo down-regulation. Thus, TAS2R14 is subject to β-arrestin-mediated internalization and subsequent down-regulation with chronic exposure to most agonists. However, by manipulating the agonist structure, biasing toward G-protein coupling but away from long-term down-regulation can be achieved.-Woo, J. A., Castaño, M., Goss, A., Kim, D., Lewandowski, E. M., Chen, Y., Liggett, S. B. Differential long-term regulation of TAS2R14 by structurally distinct agonists.
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Affiliation(s)
- Jung A Woo
- Department of Molecular Pharmacology and Physiology, University of South Florida Morsani College of Medicine, Tampa, Florida, USA
| | - Maria Castaño
- Department of Medicine, University of South Florida Morsani College of Medicine, Tampa, Florida, USA
| | - Ashley Goss
- Department of Medicine, University of South Florida Morsani College of Medicine, Tampa, Florida, USA
| | - Donghwa Kim
- Department of Medicine, University of South Florida Morsani College of Medicine, Tampa, Florida, USA
| | - Eric M Lewandowski
- Department of Molecular Medicine, University of South Florida Morsani College of Medicine, Tampa, Florida, USA
| | - Yu Chen
- Department of Molecular Medicine, University of South Florida Morsani College of Medicine, Tampa, Florida, USA
| | - Stephen B Liggett
- Department of Molecular Pharmacology and Physiology, University of South Florida Morsani College of Medicine, Tampa, Florida, USA.,Department of Medicine, University of South Florida Morsani College of Medicine, Tampa, Florida, USA
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Latek D, Rutkowska E, Niewieczerzal S, Cielecka-Piontek J. Drug-induced diabetes type 2: In silico study involving class B GPCRs. PLoS One 2019; 14:e0208892. [PMID: 30650080 PMCID: PMC6334951 DOI: 10.1371/journal.pone.0208892] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Accepted: 11/27/2018] [Indexed: 01/10/2023] Open
Abstract
A disturbance of glucose homeostasis leading to type 2 diabetes mellitus (T2DM) is one of the severe side effects that may occur during a prolonged use of many drugs currently available on the market. In this manuscript we describe the most common cases of drug-induced T2DM, discuss available pharmacotherapies and propose new ones. Among various pharmacotherapies of T2DM, incretin therapies have recently focused attention due to the newly determined crystal structure of incretin hormone receptor GLP1R. Incretin hormone receptors: GLP1R and GIPR together with the glucagon receptor GCGR regulate food intake and insulin and glucose secretion. Our study showed that incretin hormone receptors, named also gut hormone receptors as they are expressed in the gastrointestinal tract, could potentially act as unintended targets (off-targets) for orally administrated drugs. Such off-target interactions, depending on their effect on the receptor (stimulation or inhibition), could be beneficial, like in the case of incretin mimetics, or unwanted if they cause, e.g., decreased insulin secretion. In this in silico study we examined which well-known pharmaceuticals could potentially interact with gut hormone receptors in the off-target way. We observed that drugs with the strongest binding affinity for gut hormone receptors were also reported in the medical information resources as the least disturbing the glucose homeostasis among all drugs in their class. We suggested that those strongly binding molecules could potentially stimulate GIPR and GLP1R and/or inhibit GCGR which could lead to increased insulin secretion and decreased hepatic glucose production. Such positive effect on the glucose homeostasis could compensate for other, adverse effects of pharmacotherapy which lead to drug-induced T2DM. In addition, we also described several top hits as potential substitutes of peptidic incretin mimetics which were discovered in the drug repositioning screen using gut hormone receptors structures against the ZINC15 compounds subset.
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Affiliation(s)
- Dorota Latek
- Faculty of Chemistry, University of Warsaw, Warsaw, Poland
| | | | | | - Judyta Cielecka-Piontek
- Department of Pharmacognosy, Faculty of Pharmacy, Poznan University of Medical Sciences, Poznan, Poland
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