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Carpenter KA, Altman RB. Databases of ligand-binding pockets and protein-ligand interactions. Comput Struct Biotechnol J 2024; 23:1320-1338. [PMID: 38585646 PMCID: PMC10997877 DOI: 10.1016/j.csbj.2024.03.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 03/16/2024] [Accepted: 03/17/2024] [Indexed: 04/09/2024] Open
Abstract
Many research groups and institutions have created a variety of databases curating experimental and predicted data related to protein-ligand binding. The landscape of available databases is dynamic, with new databases emerging and established databases becoming defunct. Here, we review the current state of databases that contain binding pockets and protein-ligand binding interactions. We have compiled a list of such databases, fifty-three of which are currently available for use. We discuss variation in how binding pockets are defined and summarize pocket-finding methods. We organize the fifty-three databases into subgroups based on goals and contents, and describe standard use cases. We also illustrate that pockets within the same protein are characterized differently across different databases. Finally, we assess critical issues of sustainability, accessibility and redundancy.
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Affiliation(s)
- Kristy A. Carpenter
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Russ B. Altman
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
- Department of Medicine, Stanford University, Stanford, CA 94305, USA
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Thompson MD, Reiner-Link D, Berghella A, Rana BK, Rovati GE, Capra V, Gorvin CM, Hauser AS. G protein-coupled receptor (GPCR) pharmacogenomics. Crit Rev Clin Lab Sci 2024:1-44. [PMID: 39119983 DOI: 10.1080/10408363.2024.2358304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/03/2023] [Accepted: 05/18/2024] [Indexed: 08/10/2024]
Abstract
The field of pharmacogenetics, the investigation of the influence of one or more sequence variants on drug response phenotypes, is a special case of pharmacogenomics, a discipline that takes a genome-wide approach. Massively parallel, next generation sequencing (NGS), has allowed pharmacogenetics to be subsumed by pharmacogenomics with respect to the identification of variants associated with responders and non-responders, optimal drug response, and adverse drug reactions. A plethora of rare and common naturally-occurring GPCR variants must be considered in the context of signals from across the genome. Many fundamentals of pharmacogenetics were established for G protein-coupled receptor (GPCR) genes because they are primary targets for a large number of therapeutic drugs. Functional studies, demonstrating likely-pathogenic and pathogenic GPCR variants, have been integral to establishing models used for in silico analysis. Variants in GPCR genes include both coding and non-coding single nucleotide variants and insertion or deletions (indels) that affect cell surface expression (trafficking, dimerization, and desensitization/downregulation), ligand binding and G protein coupling, and variants that result in alternate splicing encoding isoforms/variable expression. As the breadth of data on the GPCR genome increases, we may expect an increase in the use of drug labels that note variants that significantly impact the clinical use of GPCR-targeting agents. We discuss the implications of GPCR pharmacogenomic data derived from the genomes available from individuals who have been well-phenotyped for receptor structure and function and receptor-ligand interactions, and the potential benefits to patients of optimized drug selection. Examples discussed include the renin-angiotensin system in SARS-CoV-2 (COVID-19) infection, the probable role of chemokine receptors in the cytokine storm, and potential protease activating receptor (PAR) interventions. Resources dedicated to GPCRs, including publicly available computational tools, are also discussed.
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Affiliation(s)
- Miles D Thompson
- Krembil Brain Institute, Toronto Western Hospital, Toronto, Ontario, Canada
| | - David Reiner-Link
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Alessandro Berghella
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Brinda K Rana
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - G Enrico Rovati
- Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy
| | - Valerie Capra
- Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy
| | - Caroline M Gorvin
- Institute of Metabolism and Systems Research (IMSR), University of Birmingham, Birmingham, United Kingdom
| | - Alexander S Hauser
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Ung CY, Correia C, Billadeau DD, Zhu S, Li H. Manifold epigenetics: A conceptual model that guides engineering strategies to improve whole-body regenerative health. Front Cell Dev Biol 2023; 11:1122422. [PMID: 36866271 PMCID: PMC9971008 DOI: 10.3389/fcell.2023.1122422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 01/30/2023] [Indexed: 02/16/2023] Open
Abstract
Despite the promising advances in regenerative medicine, there is a critical need for improved therapies. For example, delaying aging and improving healthspan is an imminent societal challenge. Our ability to identify biological cues as well as communications between cells and organs are keys to enhance regenerative health and improve patient care. Epigenetics represents one of the major biological mechanisms involving in tissue regeneration, and therefore can be viewed as a systemic (body-wide) control. However, how epigenetic regulations concertedly lead to the development of biological memories at the whole-body level remains unclear. Here, we review the evolving definitions of epigenetics and identify missing links. We then propose our Manifold Epigenetic Model (MEMo) as a conceptual framework to explain how epigenetic memory arises and discuss what strategies can be applied to manipulate the body-wide memory. In summary we provide a conceptual roadmap for the development of new engineering approaches to improve regenerative health.
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Affiliation(s)
- Choong Yong Ung
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States
| | - Cristina Correia
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States
| | | | - Shizhen Zhu
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, United States
| | - Hu Li
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States
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Pawar G, Madden JC, Ebbrell D, Firman JW, Cronin MTD. In Silico Toxicology Data Resources to Support Read-Across and (Q)SAR. Front Pharmacol 2019; 10:561. [PMID: 31244651 PMCID: PMC6580867 DOI: 10.3389/fphar.2019.00561] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Accepted: 05/03/2019] [Indexed: 12/14/2022] Open
Abstract
A plethora of databases exist online that can assist in in silico chemical or drug safety assessment. However, a systematic review and grouping of databases, based on purpose and information content, consolidated in a single source, has been lacking. To resolve this issue, this review provides a comprehensive listing of the key in silico data resources relevant to: chemical identity and properties, drug action, toxicology (including nano-material toxicity), exposure, omics, pathways, Absorption, Distribution, Metabolism and Elimination (ADME) properties, clinical trials, pharmacovigilance, patents-related databases, biological (genes, enzymes, proteins, other macromolecules etc.) databases, protein-protein interactions (PPIs), environmental exposure related, and finally databases relating to animal alternatives in support of 3Rs policies. More than nine hundred databases were identified and reviewed against criteria relating to accessibility, data coverage, interoperability or application programming interface (API), appropriate identifiers, types of in vitro, in vivo,-clinical or other data recorded and suitability for modelling, read-across, or similarity searching. This review also specifically addresses the need for solutions for mapping and integration of databases into a common platform for better translatability of preclinical data to clinical data.
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Affiliation(s)
| | | | | | | | - Mark T. D. Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, United Kingdom
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Thompson MD, Capra V, Clunes MT, Rovati GE, Stankova J, Maj MC, Duffy DL. Cysteinyl Leukotrienes Pathway Genes, Atopic Asthma and Drug Response: From Population Isolates to Large Genome-Wide Association Studies. Front Pharmacol 2016; 7:299. [PMID: 27990118 PMCID: PMC5131607 DOI: 10.3389/fphar.2016.00299] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2015] [Accepted: 08/24/2016] [Indexed: 02/05/2023] Open
Abstract
Genetic variants associated with asthma pathogenesis and altered response to drug therapy are discussed. Many studies implicate polymorphisms in genes encoding the enzymes responsible for leukotriene synthesis and intracellular signaling through activation of seven transmembrane domain receptors, such as the cysteinyl leukotriene 1 (CYSLTR1) and 2 (CYSLTR2) receptors. The leukotrienes are polyunsaturated lipoxygenated eicosatetraenoic acids that exhibit a wide range of pharmacological and physiological actions. Of the three enzymes involved in the formation of the leukotrienes, arachidonate 5 lipoxygenase 5 (ALOX5), leukotriene C4 synthase (LTC4S), and leukotriene hydrolase (LTA4H) are all polymorphic. These polymorphisms often result in variable production of the CysLTs (LTC4, LTD4, and LTE4) and LTB4. Variable number tandem repeat sequences located in the Sp1-binding motif within the promotor region of the ALOX5 gene are associated with leukotriene burden and bronchoconstriction independent of asthma risk. A 444A > C SNP polymorphism in the LTC4S gene, encoding an enzyme required for the formation of a glutathione adduct at the C-6 position of the arachidonic acid backbone, is associated with severe asthma and altered response to the CYSLTR1 receptor antagonist zafirlukast. Genetic variability in the CysLT pathway may contribute additively or synergistically to altered drug responses. The 601 A > G variant of the CYSLTR2 gene, encoding the Met201Val CYSLTR2 receptor variant, is associated with atopic asthma in the general European population, where it is present at a frequency of ∼2.6%. The variant was originally found in the founder population of Tristan da Cunha, a remote island in the South Atlantic, in which the prevalence of atopy is approximately 45% and the prevalence of asthma is 36%. In vitro work showed that the atopy-associated Met201Val variant was inactivating with respect to ligand binding, Ca2+ flux and inositol phosphate generation. In addition, the CYSLTR1 gene, located at Xq13-21.1, has been associated with atopic asthma. The activating Gly300Ser CYSLTR1 variant is discussed. In addition to genetic loci, risk for asthma may be influenced by environmental factors such as smoking. The contribution of CysLT pathway gene sequence variants to atopic asthma is discussed in the context of other genes and environmental influences known to influence asthma.
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Affiliation(s)
- Miles D Thompson
- Biochemical Genetics and Metabolomics Laboratory, Department of Pediatrics, University of California, San Diego, La JollaCA, USA; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ONCanada
| | - Valerie Capra
- Department of Health Sciences, San Paolo Hospital, Università degli Studi di Milano Milano, Italy
| | - Mark T Clunes
- Department of Physiology/Neuroscience, School of Medicine, Saint George's University Saint George's, Grenada
| | - G E Rovati
- Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano Milano, Italy
| | - Jana Stankova
- Division of Immunology and Allergy, Department of Pediatrics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke QC, Canada
| | - Mary C Maj
- Department of Biochemistry, School of Medicine, Saint George's University Saint George's, Grenada
| | - David L Duffy
- QIMR Berghofer Medical Research Institute, Herston QLD, Australia
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Groh KJ, Carvalho RN, Chipman JK, Denslow ND, Halder M, Murphy CA, Roelofs D, Rolaki A, Schirmer K, Watanabe KH. Development and application of the adverse outcome pathway framework for understanding and predicting chronic toxicity: I. Challenges and research needs in ecotoxicology. CHEMOSPHERE 2015; 120:764-77. [PMID: 25439131 DOI: 10.1016/j.chemosphere.2014.09.068] [Citation(s) in RCA: 116] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2014] [Revised: 09/11/2014] [Accepted: 09/19/2014] [Indexed: 05/02/2023]
Abstract
To elucidate the effects of chemicals on populations of different species in the environment, efficient testing and modeling approaches are needed that consider multiple stressors and allow reliable extrapolation of responses across species. An adverse outcome pathway (AOP) is a concept that provides a framework for organizing knowledge about the progression of toxicity events across scales of biological organization that lead to adverse outcomes relevant for risk assessment. In this paper, we focus on exploring how the AOP concept can be used to guide research aimed at improving both our understanding of chronic toxicity, including delayed toxicity as well as epigenetic and transgenerational effects of chemicals, and our ability to predict adverse outcomes. A better understanding of the influence of subtle toxicity on individual and population fitness would support a broader integration of sublethal endpoints into risk assessment frameworks. Detailed mechanistic knowledge would facilitate the development of alternative testing methods as well as help prioritize higher tier toxicity testing. We argue that targeted development of AOPs supports both of these aspects by promoting the elucidation of molecular mechanisms and their contribution to relevant toxicity outcomes across biological scales. We further discuss information requirements and challenges in application of AOPs for chemical- and site-specific risk assessment and for extrapolation across species. We provide recommendations for potential extension of the AOP framework to incorporate information on exposure, toxicokinetics and situation-specific ecological contexts, and discuss common interfaces that can be employed to couple AOPs with computational modeling approaches and with evolutionary life history theory. The extended AOP framework can serve as a venue for integration of knowledge derived from various sources, including empirical data as well as molecular, quantitative and evolutionary-based models describing species responses to toxicants. This will allow a more efficient application of AOP knowledge for quantitative chemical- and site-specific risk assessment as well as for extrapolation across species in the future.
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Affiliation(s)
- Ksenia J Groh
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland; ETH Zürich, Department of Chemistry and Applied Biosciences, 8093 Zürich, Switzerland.
| | - Raquel N Carvalho
- European Commission, Joint Research Centre, Institute for Environment and Sustainability, Water Resources Unit, 21027 Ispra, Italy
| | | | - Nancy D Denslow
- University of Florida, Department of Physiological Sciences, Center for Environmental and Human Toxicology and Genetics Institute, 32611 Gainesville, FL, USA
| | - Marlies Halder
- European Commission, Joint Research Centre, Institute for Health and Consumer Protection, Systems Toxicology Unit, 21027 Ispra, Italy
| | - Cheryl A Murphy
- Michigan State University, Fisheries and Wildlife, Lyman Briggs College, 48824 East Lansing, MI, USA
| | - Dick Roelofs
- VU University, Institute of Ecological Science, 1081 HV Amsterdam, The Netherlands
| | - Alexandra Rolaki
- European Commission, Joint Research Centre, Institute for Health and Consumer Protection, Systems Toxicology Unit, 21027 Ispra, Italy
| | - Kristin Schirmer
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland; ETH Zürich, Department of Environmental Systems Science, 8092 Zürich, Switzerland; EPF Lausanne, School of Architecture, Civil and Environmental Engineering, 1015 Lausanne, Switzerland
| | - Karen H Watanabe
- Oregon Health & Science University, Institute of Environmental Health, Division of Environmental and Biomolecular Systems, 97239-3098 Portland, OR, USA
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Thompson MD, Cole DEC, Capra V, Siminovitch KA, Rovati GE, Burnham WM, Rana BK. Pharmacogenetics of the G protein-coupled receptors. Methods Mol Biol 2014; 1175:189-242. [PMID: 25150871 DOI: 10.1007/978-1-4939-0956-8_9] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Pharmacogenetics investigates the influence of genetic variants on physiological phenotypes related to drug response and disease, while pharmacogenomics takes a genome-wide approach to advancing this knowledge. Both play an important role in identifying responders and nonresponders to medication, avoiding adverse drug reactions, and optimizing drug dose for the individual. G protein-coupled receptors (GPCRs) are the primary target of therapeutic drugs and have been the focus of these studies. With the advance of genomic technologies, there has been a substantial increase in the inventory of naturally occurring rare and common GPCR variants. These variants include single-nucleotide polymorphisms and insertion or deletions that have potential to alter GPCR expression of function. In vivo and in vitro studies have determined functional roles for many GPCR variants, but genetic association studies that define the physiological impact of the majority of these common variants are still limited. Despite the breadth of pharmacogenetic data available, GPCR variants have not been included in drug labeling and are only occasionally considered in optimizing clinical use of GPCR-targeted agents. In this chapter, pharmacogenetic and genomic studies on GPCR variants are reviewed with respect to a subset of GPCR systems, including the adrenergic, calcium sensing, cysteinyl leukotriene, cannabinoid CB1 and CB2 receptors, and the de-orphanized receptors such as GPR55. The nature of the disruption to receptor function is discussed with respect to regulation of gene expression, expression on the cell surface (affected by receptor trafficking, dimerization, desensitization/downregulation), or perturbation of receptor function (altered ligand binding, G protein coupling, constitutive activity). The large body of experimental data generated on structure and function relationships and receptor-ligand interactions are being harnessed for the in silico functional prediction of naturally occurring GPCR variants. We provide information on online resources dedicated to GPCRs and present applications of publically available computational tools for pharmacogenetic studies of GPCRs. As the breadth of GPCR pharmacogenomic data becomes clearer, the opportunity for routine assessment of GPCR variants to predict disease risk, drug response, and potential adverse drug effects will become possible.
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Affiliation(s)
- Miles D Thompson
- Department of Pharmacology and Toxicology, Faculty of Medicine, University of Toronto, 1 King's College Circle, Toronto, ON, Canada, M5S 1A8,
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