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Waman VP, Ashford P, Lam SD, Sen N, Abbasian M, Woodridge L, Goldtzvik Y, Bordin N, Wu J, Sillitoe I, Orengo CA. Predicting human and viral protein variants affecting COVID-19 susceptibility and repurposing therapeutics. Sci Rep 2024; 14:14208. [PMID: 38902252 PMCID: PMC11190248 DOI: 10.1038/s41598-024-61541-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 05/07/2024] [Indexed: 06/22/2024] Open
Abstract
The COVID-19 disease is an ongoing global health concern. Although vaccination provides some protection, people are still susceptible to re-infection. Ostensibly, certain populations or clinical groups may be more vulnerable. Factors causing these differences are unclear and whilst socioeconomic and cultural differences are likely to be important, human genetic factors could influence susceptibility. Experimental studies indicate SARS-CoV-2 uses innate immune suppression as a strategy to speed-up entry and replication into the host cell. Therefore, it is necessary to understand the impact of variants in immunity-associated human proteins on susceptibility to COVID-19. In this work, we analysed missense coding variants in several SARS-CoV-2 proteins and their human protein interactors that could enhance binding affinity to SARS-CoV-2. We curated a dataset of 19 SARS-CoV-2: human protein 3D-complexes, from the experimentally determined structures in the Protein Data Bank and models built using AlphaFold2-multimer, and analysed the impact of missense variants occurring in the protein-protein interface region. We analysed 468 missense variants from human proteins and 212 variants from SARS-CoV-2 proteins and computationally predicted their impacts on binding affinities for the human viral protein complexes. We predicted a total of 26 affinity-enhancing variants from 13 human proteins implicated in increased binding affinity to SARS-CoV-2. These include key-immunity associated genes (TOMM70, ISG15, IFIH1, IFIT2, RPS3, PALS1, NUP98, AXL, ARF6, TRIMM, TRIM25) as well as important spike receptors (KREMEN1, AXL and ACE2). We report both common (e.g., Y13N in IFIH1) and rare variants in these proteins and discuss their likely structural and functional impact, using information on known and predicted functional sites. Potential mechanisms associated with immune suppression implicated by these variants are discussed. Occurrence of certain predicted affinity-enhancing variants should be monitored as they could lead to increased susceptibility and reduced immune response to SARS-CoV-2 infection in individuals/populations carrying them. Our analyses aid in understanding the potential impact of genetic variation in immunity-associated proteins on COVID-19 susceptibility and help guide drug-repurposing strategies.
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Affiliation(s)
- Vaishali P Waman
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Paul Ashford
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Su Datt Lam
- Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia
| | - Neeladri Sen
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Mahnaz Abbasian
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Laurel Woodridge
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Yonathan Goldtzvik
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Nicola Bordin
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Jiaxin Wu
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Ian Sillitoe
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Christine A Orengo
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK.
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Gracia J, Perumal D, Dhandapani P, Ragunathan P. Systematic identification and repurposing of FDA-approved drugs as antibacterial agents against Streptococcus pyogenes: In silico and in vitro studies. Int J Biol Macromol 2024; 257:128667. [PMID: 38101681 DOI: 10.1016/j.ijbiomac.2023.128667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 10/31/2023] [Accepted: 12/06/2023] [Indexed: 12/17/2023]
Abstract
Streptococcus pyogenes (Group A Streptococcus - GAS) is a human pathogen causing wide range of infections and toxin-mediated diseases in human beings of all age groups with fatality of 10-30 %. The limited success of antibiotics and the non-availability of vaccines makes GAS a global burden. The multi-subunit RNA polymerase (RNAP) is a validated bacterial therapeutic target as it is involved in transcription and can arrest growth. Of the five subunits of this enzyme complex, the β-subunit (RpoC) has attracted specific attention as a drug target, particularly in the switch region. Here we attempt to repurpose non-antimicrobial drugs to act as RpoC inhibitors against S. pyogenes. In this study, 1826 FDA approved drugs have been identified through high-throughput virtual screening. Free Energy Perturbation (FEP) based binding free energy calculations have been performed at the final step of the virtual screening funnel to ensure high accuracy in silico results. Three compounds identified have been tested for susceptibility of S. pyogenes MTCC 442 strain and two antibiotic-resistant clinical isolates of S. pyogenes using microdilution assay. Among the three, two drugs Amlodipine Besylate (Amd) and Ranitidine hydrochloride (Rnt) have shown inhibition against all the tested strains and its mechanism of interaction with RpoC has been studied. The docked complexes were analyzed to understand the binding mode of the drugs to the target. Classical Molecular Dynamics studies for RpoC-Rnt complex and the two stable conformations of RpoC-Amd complex was carried out. Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Radius of Gyration (RoG) and Solvent Accessible Surface Area (SASA) of the complexes were plotted and studied. The thermodynamic parameters of protein-drug were experimentally determined using Isothermal Titration Calorimetry (ITC). Infrared spectroscopic studies and Fluorescence quenching studies provided insights into the secondary structural changes in RpoC on binding to the drugs.
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Affiliation(s)
- Judith Gracia
- Centre for Advanced Studies in Crystallography and Biophysics, University of Madras, Guindy, India
| | - Damodharan Perumal
- Department of Microbiology, Dr. ALMPG IBMS, University of Madras, Taramani, India
| | - Prabu Dhandapani
- Department of Microbiology, Dr. ALMPG IBMS, University of Madras, Taramani, India
| | - Preethi Ragunathan
- Centre for Advanced Studies in Crystallography and Biophysics, University of Madras, Guindy, India.
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Zhang T, Huang S, Wang M, Yang N, Zhu H. Integrated untargeted and targeted proteomics to unveil plasma prognostic markers for patients with acute paraquat poisoning: A pilot study. Food Chem Toxicol 2023; 182:114187. [PMID: 37967786 DOI: 10.1016/j.fct.2023.114187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 11/05/2023] [Accepted: 11/08/2023] [Indexed: 11/17/2023]
Abstract
Paraquat (PQ) is a widely used but strongly toxic herbicide, which can induce multiple organ failure. The overall survival rate of the poisoned patients was only 54.4% due to lack of specific antidotes. Besides, the definite pathogenic mechanism of PQ is still not fully understood. In this pilot study, untargeted and targeted proteomics were integrated to explore the expression characteristics of plasma protein in PQ poisoned patients, and identify the differentially expressed proteins between survivors and non-survivors. A total of 494 plasma proteins were detected, and of which 47 were upregulated and 44 were downregulated in PQ poisoned patients compared to healthy controls. Among them, five differential plasma proteins (S100A9, S100A8, MB, ACTB and RAB11FIP3) were further validated by multiple reaction monitoring (MRM)-based targeted proteomic approach, and three of them (S100A9, S100A8 and ACTB) were confirmed to be correlated with PQ poisoning. Meanwhile, 84 dysregulated plasma proteins were identified in non-survivors compared with survivors. Moreover, targeted proteomic and ROC analysis suggested that ACTB had a good performance in predicting the prognosis of PQ poisoned patients. These findings highlighted the value of label-free and mass spectrometry-based proteomics in screening prognostic biomarkers of PQ poisoning and studying the mechanism of PQ toxicity.
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Affiliation(s)
- Tianqi Zhang
- Department of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China; Nanjing Medical Center for Clinical Pharmacy, Nanjing, 210008, China
| | - Siqi Huang
- Department of Pharmacy, Nanjing Drum Tower Hospital, Clinical College of Nanjing University of Chinese Medicine, Nanjing, 210008, China
| | - Min Wang
- Department of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China; Nanjing Medical Center for Clinical Pharmacy, Nanjing, 210008, China
| | - Na Yang
- Department of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China; Nanjing Medical Center for Clinical Pharmacy, Nanjing, 210008, China.
| | - Huaijun Zhu
- Department of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China; Nanjing Medical Center for Clinical Pharmacy, Nanjing, 210008, China.
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Hoch M, Smita S, Cesnulevicius K, Schultz M, Lescheid D, Wolkenhauer O, Gupta S. Network analyses reveal new insights into the effect of multicomponent Tr14 compared to single-component diclofenac in an acute inflammation model. J Inflamm (Lond) 2023; 20:12. [PMID: 36973809 PMCID: PMC10044762 DOI: 10.1186/s12950-023-00335-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 02/21/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND Modifying the acute inflammatory response has wide clinical benefits. Current options include non-steroidal anti-inflammatory drugs (NSAIDs) and therapies that may resolve inflammation. Acute inflammation involves multiple cell types and various processes. We, therefore, investigated whether an immunomodulatory drug that acts simultaneously at multiple sites shows greater potential to resolve acute inflammation more effectively and with fewer side effects than a common anti-inflammatory drug developed as a small molecule for a single target. In this work, we used time-series gene expression profiles from a wound healing mouse model to compare the effects of Traumeel (Tr14), a multicomponent natural product, to diclofenac, a single component NSAID on inflammation resolution. RESULTS We advance previous studies by mapping the data onto the "Atlas of Inflammation Resolution", followed by in silico simulations and network analysis. We found that Tr14 acts primarily on the late phase of acute inflammation (during resolution) compared to diclofenac, which suppresses acute inflammation immediately after injury. CONCLUSIONS Our results provide new insights how network pharmacology of multicomponent drugs may support inflammation resolution in inflammatory conditions.
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Affiliation(s)
- Matti Hoch
- Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, 18055, Germany
| | - Suchi Smita
- Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, 18055, Germany
| | | | | | | | - Olaf Wolkenhauer
- Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, 18055, Germany
- Leibniz-Institute for Food Systems Biology at the Technical University of Munich, Freising, 85354, Germany
- Stellenbosch Institute of Advanced Study, Wallenberg Research Centre, Stellenbosch University, Stellenbosch, 7602, South Africa
| | - Shailendra Gupta
- Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, 18055, Germany.
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Adeyelu T, Bordin N, Waman VP, Sadlej M, Sillitoe I, Moya-Garcia AA, Orengo CA. KinFams: De-Novo Classification of Protein Kinases Using CATH Functional Units. Biomolecules 2023; 13:277. [PMID: 36830646 PMCID: PMC9953599 DOI: 10.3390/biom13020277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 01/24/2023] [Accepted: 01/26/2023] [Indexed: 02/05/2023] Open
Abstract
Protein kinases are important targets for treating human disorders, and they are the second most targeted families after G-protein coupled receptors. Several resources provide classification of kinases into evolutionary families (based on sequence homology); however, very few systematically classify functional families (FunFams) comprising evolutionary relatives that share similar functional properties. We have developed the FunFam-MARC (Multidomain ARchitecture-based Clustering) protocol, which uses multi-domain architectures of protein kinases and specificity-determining residues for functional family classification. FunFam-MARC predicts 2210 kinase functional families (KinFams), which have increased functional coherence, in terms of EC annotations, compared to the widely used KinBase classification. Our protocol provides a comprehensive classification for kinase sequences from >10,000 organisms. We associate human KinFams with diseases and drugs and identify 28 druggable human KinFams, i.e., enriched in clinically approved drugs. Since relatives in the same druggable KinFam tend to be structurally conserved, including the drug-binding site, these KinFams may be valuable for shortlisting therapeutic targets. Information on the human KinFams and associated 3D structures from AlphaFold2 are provided via our CATH FTP website and Zenodo. This gives the domain structure representative of each KinFam together with information on any drug compounds available. For 32% of the KinFams, we provide information on highly conserved residue sites that may be associated with specificity.
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Affiliation(s)
- Tolulope Adeyelu
- Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK
- Department of Comparative Biomedical Science, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Nicola Bordin
- Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK
| | - Vaishali P. Waman
- Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK
| | - Marta Sadlej
- Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK
| | - Ian Sillitoe
- Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK
| | - Aurelio A. Moya-Garcia
- Departamento de Biología Molecular y Bioquímica, Universidad de Málaga, 29071 Málaga, Spain
- Laboratorio de Biología Molecular del Cáncer, Centro de Investigaciones Médico-Sanitarias (CIMES), Universidad de Málaga, 29071 Málaga, Spain
| | - Christine A. Orengo
- Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK
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Toikumo S, Xu H, Gelernter J, Kember RL, Kranzler HR. Integrating human brain proteomic data with genome-wide association study findings identifies novel brain proteins in substance use traits. Neuropsychopharmacology 2022; 47:2292-2299. [PMID: 35941285 PMCID: PMC9630289 DOI: 10.1038/s41386-022-01406-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 06/13/2022] [Accepted: 07/16/2022] [Indexed: 11/09/2022]
Abstract
Despite the identification of a growing number of genetic risk loci for substance use traits (SUTs), the impact of these loci on protein abundance and the potential utility of relevant proteins as therapeutic targets are unknown. We conducted a proteome-wide association study (PWAS) in which we integrated human brain proteomes from discovery (Banner; N = 152) and validation (ROSMAP; N = 376) datasets with genome-wide association study (GWAS) summary statistics for 4 SUTs. The 4 samples comprised GWAS of European-ancestry individuals for smoking initiation [Smk] (N = 1,232,091), alcohol use disorder [AUD] (N = 313,959), cannabis use disorder [CUD] (N = 384,032), and opioid use disorder [OUD] (N = 302,585). We conducted transcriptome-wide association studies (TWAS) with human brain transcriptomic data to examine the overlap of genetic effects at the proteomic and transcriptomic levels and characterize significant genes through conditional, colocalization, and fine-mapping analyses. We identified 27 genes (Smk = 21, AUD = 3, CUD = 2, OUD = 1) that were significantly associated with cis-regulated brain protein abundance. Of these, 7 showed evidence for causality (Smk: NT5C2, GMPPB, NQO1, RHOT2, SRR and ACTR1B; and AUD: CTNND1). Cis-regulated transcript levels for 8 genes (Smk = 6, CUD = 1, OUD = 1) were associated with SUTs, indicating that genetic loci could confer risk for these SUTs by modulating both gene expression and proteomic abundance. Functional studies of the high-confidence risk proteins identified here are needed to determine whether they are modifiable targets and useful in developing medications and biomarkers for these SUTs.
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Affiliation(s)
- Sylvanus Toikumo
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
| | - Heng Xu
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Rachel L Kember
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA.
| | - Henry R Kranzler
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA.
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Identification of New Toxicity Mechanisms in Drug-Induced Liver Injury through Systems Pharmacology. Genes (Basel) 2022; 13:genes13071292. [PMID: 35886075 PMCID: PMC9315637 DOI: 10.3390/genes13071292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/19/2022] [Accepted: 07/19/2022] [Indexed: 02/05/2023] Open
Abstract
Among adverse drug reactions, drug-induced liver injury presents particular challenges because of its complexity, and the underlying mechanisms are still not completely characterized. Our knowledge of the topic is limited and based on the assumption that a drug acts on one molecular target. We have leveraged drug polypharmacology, i.e., the ability of a drug to bind multiple targets and thus perturb several biological processes, to develop a systems pharmacology platform that integrates all drug–target interactions. Our analysis sheds light on the molecular mechanisms of drugs involved in drug-induced liver injury and provides new hypotheses to study this phenomenon.
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Porphyromonas gingivalis resistance and virulence: An integrated functional network analysis. Gene 2022; 839:146734. [PMID: 35835406 DOI: 10.1016/j.gene.2022.146734] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 06/23/2022] [Accepted: 07/08/2022] [Indexed: 11/23/2022]
Abstract
BACKGROUND The gram-negative bacteria Porphyromonas gingivalis (PG) is the most prevalent cause of periodontal diseases and multidrug-resistant (MDR) infections. Periodontitis and MDR infections are severe due to PG's ability to efflux antimicrobial and virulence factors. This gives rise to colonisation, biofilm development, evasion, and modulation of the host defence system. Despite extensive studies on the MDR efflux pump in other pathogens, little is known about the efflux pump and its association with the virulence factor in PG. Prolonged infection of PG leads to complete loss of teeth and other systemic diseases. This necessitates the development of new therapeutic interventions to prevent and control MDR. OBJECTIVE The study aims to identify the most indispensable proteins that regulate both resistance and virulence in PG, which could therefore be used as a target to fight against the MDR threat to antibiotics. METHODS We have adopted a hierarchical network-based approach to construct a protein interaction network. Firstly, individual networks of four major efflux pump proteins and two virulence regulatory proteins were constructed, followed by integrating them into one. The relationship between proteins was investigated using a combination of centrality scores, k-core network decomposition, and functional annotation, to computationally identify the indispensable proteins. RESULTS Our study identified four topologically significant genes, PG_0538, PG_0539, PG_0285, and PG_1797, as potential pharmacological targets. PG_0539 and PG_1797 were identified to have significant associations between the efflux pump and virulence genes. This type of underpinning research may help in narrowing the drug spectrum used for treating periodontal diseases, and may also be exploited to look into antibiotic resistance and pathogenicity in bacteria other than PG.
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Mass Spectrometric Behavior and Molecular Mechanisms of Fermented Deoxyanthocyanidins to Alleviate Ulcerative Colitis Based on Network Pharmacology. Int J Anal Chem 2022; 2022:9293208. [PMID: 35356765 PMCID: PMC8960007 DOI: 10.1155/2022/9293208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 03/07/2022] [Indexed: 11/17/2022] Open
Abstract
Aims. Ulcerative colitis (UC) is a type of chronic idiopathic inflammatory bowel disease with a multifactorial pathogenesis and limited treatment options. The aim of the present study is to investigate the hydrogen deuterium exchange mass spectrometry (HDX-MS) behaviors of fermented deoxyanthocyanidins and their molecular mechanisms to alleviate UC by using quantum chemistry and network pharmacology. Methods. Tandem MS indicated at least two fragmentation pathways through which deuterated vinylphenol-deoxyanthocyanidins could generate different product ions. Quantum calculations were conducted to determine the transition states of the relevant molecules and analyze their optimized configuration, vibrational characteristics, intrinsic reaction coordinates, and corresponding energies. The potential targets of deoxyanthocyanidins in UC were screened from a public database. The R package was used for Gene Ontology (GO) and KEGG pathway analyses, and the protein–protein interactions (PPIs) of the targets were assessed using Search Tool for the Retrieval of Interacting Genes (STRING). Finally, molecular docking was implemented to analyze the binding energies and action modes of the target compounds through the online tool CB-Dock. Results. Quantum calculations indicated two potential fragmentation pathways involving the six-membered ring and dihydrogen cooperative transfer reactions of the vinylphenol-deoxyanthocyanidins. A total of 146 and 57 intersecting targets of natural and fermented deoxyanthocyanidins were separately screened out from the UC database and significant overlaps in GO terms and KEGG pathways were noted. Three shared hub targets (i.e., PTGS2, ESR1, and EGFR) were selected from the two PPI networks by STRING. Molecular docking results showed that all deoxyanthocyanidins have a good binding potential with the hub target proteins and that fermented deoxyanthocyanidins have lower binding energies and more stable conformations compared with natural ones. Conclusions. Deoxyanthocyanidins may provide anti-inflammatory, antioxidative, and immune system regulatory effects to suppress UC progression. It is proposed for the first time that fermentation of deoxyanthocyanidins can help adjust the structure of the intestinal microbiota and increase the biological activity of the natural compounds against UC. Furthermore, HDX-MS is a helpful strategy to analyze deoxyanthocyanidin metabolites with unknown structures.
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Exploiting protein family and protein network data to identify novel drug targets for bladder cancer. Oncotarget 2022; 13:105-117. [PMID: 35035776 PMCID: PMC8758182 DOI: 10.18632/oncotarget.28175] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 12/08/2021] [Indexed: 12/11/2022] Open
Abstract
Bladder cancer remains one of the most common forms of cancer and yet there are limited small molecule targeted therapies. Here, we present a computational platform to identify new potential targets for bladder cancer therapy. Our method initially exploited a set of known driver genes for bladder cancer combined with predicted bladder cancer genes from mutationally enriched protein domain families. We enriched this initial set of genes using protein network data to identify a comprehensive set of 323 putative bladder cancer targets. Pathway and cancer hallmarks analyses highlighted putative mechanisms in agreement with those previously reported for this cancer and revealed protein network modules highly enriched in potential drivers likely to be good targets for targeted therapies. 21 of our potential drug targets are targeted by FDA approved drugs for other diseases — some of them are known drivers or are already being targeted for bladder cancer (FGFR3, ERBB3, HDAC3, EGFR). A further 4 potential drug targets were identified by inheriting drug mappings across our in-house CATH domain functional families (FunFams). Our FunFam data also allowed us to identify drug targets in families that are less prone to side effects i.e., where structurally similar protein domain relatives are less dispersed across the human protein network. We provide information on our novel potential cancer driver genes, together with information on pathways, network modules and hallmarks associated with the predicted and known bladder cancer drivers and we highlight those drivers we predict to be likely drug targets.
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Polypharmacology: The science of multi-targeting molecules. Pharmacol Res 2022; 176:106055. [PMID: 34990865 DOI: 10.1016/j.phrs.2021.106055] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 12/23/2021] [Accepted: 12/31/2021] [Indexed: 12/28/2022]
Abstract
Polypharmacology is a concept where a molecule can interact with two or more targets simultaneously. It offers many advantages as compared to the conventional single-targeting molecules. A multi-targeting drug is much more efficacious due to its cumulative efficacy at all of its individual targets making it much more effective in complex and multifactorial diseases like cancer, where multiple proteins and pathways are involved in the onset and development of the disease. For a molecule to be polypharmacologic in nature, it needs to possess promiscuity which is the ability to interact with multiple targets; and at the same time avoid binding to antitargets which would otherwise result in off-target adverse effects. There are certain structural features and physicochemical properties which when present would help researchers to predict if the designed molecule would possess promiscuity or not. Promiscuity can also be identified via advanced state-of-the-art computational methods. In this review, we also elaborate on the methods by which one can intentionally incorporate promiscuity in their molecules and make them polypharmacologic. The polypharmacology paradigm of "one drug-multiple targets" has numerous applications especially in drug repurposing where an already established drug is redeveloped for a new indication. Though designing a polypharmacological drug is much more difficult than designing a single-targeting drug, with the current technologies and information regarding different diseases and chemical functional groups, it is plausible for researchers to intentionally design a polypharmacological drug and unlock its advantages.
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Viacava Follis A. Centrality of drug targets in protein networks. BMC Bioinformatics 2021; 22:527. [PMID: 34715787 PMCID: PMC8555226 DOI: 10.1186/s12859-021-04342-x] [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: 05/27/2021] [Accepted: 08/23/2021] [Indexed: 01/13/2023] Open
Abstract
Background In the pharmaceutical industry, competing for few validated drug targets there is a drive to identify new ways of therapeutic intervention. Here, we attempted to define guidelines to evaluate a target’s ‘fitness’ based on its node characteristics within annotated protein functional networks to complement contingent therapeutic hypotheses. Results We observed that targets of approved, selective small molecule drugs exhibit high node centrality within protein networks relative to a broader set of investigational targets spanning various development stages. Targets of approved drugs also exhibit higher centrality than other proteins within their respective functional class. These findings expand on previous reports of drug targets’ network centrality by suggesting some centrality metrics such as low topological coefficient as inherent characteristics of a ‘good’ target, relative to other exploratory targets and regardless of its functional class. These centrality metrics could thus be indicators of an individual protein’s ‘fitness’ as potential drug target. Correlations between protein nodes’ network centrality and number of associated publications underscored the possibility of knowledge bias as an inherent limitation to such predictions. Conclusions Despite some entanglement with knowledge bias, like structure-oriented ‘druggability’ assessments of new protein targets, centrality metrics could assist early pharmaceutical discovery teams in evaluating potential targets with limited experimental proof of concept and help allocate resources for an effective drug discovery pipeline. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-021-04342-x.
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Affiliation(s)
- Ariele Viacava Follis
- EMD Serono Research and Development Inc., 45A Middlesex Turnpike, Billerica, MA, 01821, USA.
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Patton EE, Zon LI, Langenau DM. Zebrafish disease models in drug discovery: from preclinical modelling to clinical trials. Nat Rev Drug Discov 2021; 20:611-628. [PMID: 34117457 PMCID: PMC9210578 DOI: 10.1038/s41573-021-00210-8] [Citation(s) in RCA: 171] [Impact Index Per Article: 57.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/12/2021] [Indexed: 02/03/2023]
Abstract
Numerous drug treatments that have recently entered the clinic or clinical trials have their genesis in zebrafish. Zebrafish are well established for their contribution to developmental biology and have now emerged as a powerful preclinical model for human disease, as their disease characteristics, aetiology and progression, and molecular mechanisms are clinically relevant and highly conserved. Zebrafish respond to small molecules and drug treatments at physiologically relevant dose ranges and, when combined with cell-specific or tissue-specific reporters and gene editing technologies, drug activity can be studied at single-cell resolution within the complexity of a whole animal, across tissues and over an extended timescale. These features enable high-throughput and high-content phenotypic drug screening, repurposing of available drugs for personalized and compassionate use, and even the development of new drug classes. Often, drugs and drug leads explored in zebrafish have an inter-organ mechanism of action and would otherwise not be identified through targeted screening approaches. Here, we discuss how zebrafish is an important model for drug discovery, the process of how these discoveries emerge and future opportunities for maximizing zebrafish potential in medical discoveries.
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Affiliation(s)
- E Elizabeth Patton
- MRC Human Genetics Unit and Cancer Research UK Edinburgh Centre, MRC Institute of Genetics and Cancer, Western General Hospital Campus, University of Edinburgh, Edinburgh, UK.
| | - Leonard I Zon
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Howard Hughes Medical Institute, Harvard Medical School; Harvard Stem Cell Institute, Stem Cell and Regenerative Biology Department, Harvard University, Boston, MA, USA.
| | - David M Langenau
- Department of Pathology, Massachusetts General Research Institute, Boston, MA, USA.
- Center of Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA.
- Harvard Stem Cell Institute, Harvard University, Boston, MA, USA.
- Center of Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA.
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14
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Wingo TS, Liu Y, Gerasimov ES, Gockley J, Logsdon BA, Duong DM, Dammer EB, Lori A, Kim PJ, Ressler KJ, Beach TG, Reiman EM, Epstein MP, De Jager PL, Lah JJ, Bennett DA, Seyfried NT, Levey AI, Wingo AP. Brain proteome-wide association study implicates novel proteins in depression pathogenesis. Nat Neurosci 2021; 24:810-817. [PMID: 33846625 PMCID: PMC8530461 DOI: 10.1038/s41593-021-00832-6] [Citation(s) in RCA: 75] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 03/04/2021] [Indexed: 02/01/2023]
Abstract
Depression is a common condition, but current treatments are only effective in a subset of individuals. To identify new treatment targets, we integrated depression genome-wide association study (GWAS) results (N = 500,199) with human brain proteomes (N = 376) to perform a proteome-wide association study of depression followed by Mendelian randomization. We identified 19 genes that were consistent with being causal in depression, acting via their respective cis-regulated brain protein abundance. We replicated nine of these genes using an independent depression GWAS (N = 307,353) and another human brain proteomic dataset (N = 152). Eleven of the 19 genes also had cis-regulated mRNA levels that were associated with depression, based on integration of the depression GWAS with human brain transcriptomes (N = 888). Meta-analysis of the discovery and replication proteome-wide association study analyses identified 25 brain proteins consistent with being causal in depression, 20 of which were not previously implicated in depression by GWAS. Together, these findings provide promising brain protein targets for further mechanistic and therapeutic studies.
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Affiliation(s)
- Thomas S Wingo
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA.
| | - Yue Liu
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | | | | | | | - Duc M Duong
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Eric B Dammer
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Adriana Lori
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA
| | - Paul J Kim
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA
| | | | | | - Eric M Reiman
- Banner Alzheimer's Institute, Arizona State University and University of Arizona, Phoenix, AZ, USA
| | - Michael P Epstein
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, USA
| | - James J Lah
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Nicholas T Seyfried
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Allan I Levey
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Aliza P Wingo
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA.
- Division of Mental Health, Atlanta VA Medical Center, Decatur, GA, USA.
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15
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Alsayed SSR, Lun S, Bailey AW, Suri A, Huang CC, Mocerino M, Payne A, Sredni ST, Bishai WR, Gunosewoyo H. Design, synthesis and evaluation of novel indole-2-carboxamides for growth inhibition of Mycobacterium tuberculosis and paediatric brain tumour cells. RSC Adv 2021; 11:15497-15511. [PMID: 35481189 PMCID: PMC9029315 DOI: 10.1039/d0ra10728j] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 04/10/2021] [Indexed: 12/17/2022] Open
Abstract
The omnipresent threat of tuberculosis (TB) and the scant treatment options thereof necessitate the development of new antitubercular agents, preferably working via a novel mechanism of action distinct from the current drugs. Various studies identified the mycobacterial membrane protein large 3 transporter (MmpL3) as the target of several classes of compounds, including the indole-2-caboxamides. Herein, several indoleamide analogues were rationally designed, synthesised, and evaluated for their antitubercular and antitumour activities. Compound 8g displayed the highest activity (MIC = 0.32 μM) against the drug-sensitive (DS) Mycobacterium tuberculosis (M. tb) H37Rv strain. This compound also exhibited high selective activity towards M. tb over mammalian cells [IC50 (Vero cells) = 40.9 μM, SI = 128], suggesting its minimal cytotoxicity. In addition, when docked into the MmpL3 active site, 8g adopted a binding profile similar to the indoleamide ligand ICA38. A related compound 8f showed dual antitubercular (MIC = 0.62 μM) and cytotoxic activities against paediatric glioblastoma multiforme (GBM) cell line KNS42 [IC50 (viability) = 0.84 μM]. Compound 8f also showed poor cytotoxic activity against healthy Vero cells (IC50 = 39.9 μM). Compounds 9a and 15, which were inactive against M. tb, showed potent cytotoxic (IC50 = 8.25 and 5.04 μM, respectively) and antiproliferative activities (IC50 = 9.85 and 6.62 μM, respectively) against KNS42 cells. Transcriptional analysis of KNS42 cells treated with compound 15 revealed a significant downregulation in the expression of the carbonic anhydrase 9 (CA9) and the spleen tyrosine kinase (SYK) genes. The expression levels of these genes in GBM tumours were previously shown to contribute to tumour progression, suggesting their involvement in our observed antitumour activities. Compounds 9a and 15 were selected for further evaluations against three different paediatric brain tumour cell lines (BT12, BT16 and DAOY) and non-neoplastic human fibroblast cells HFF1. Compound 9a showed remarkable cytotoxic (IC50 = 0.89 and 1.81 μM, respectively) and antiproliferative activities (IC50 = 7.44 and 6.06 μM, respectively) against the two tested atypical teratoid/rhabdoid tumour (AT/RT) cells BT12 and BT16. Interestingly, compound 9a was not cytotoxic when tested against non-neoplastic HFF1 cells [IC50 (viability) = 119 μM]. This suggests that an indoleamide scaffold can be fine-tuned to confer a set of derivatives with selective antitubercular and/or antitumour activities. In this study, we demonstrated that an indoleamide scaffold can be fine-tuned to confer a set of derivatives with selective antitubercular and/or antitumour activities.![]()
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Affiliation(s)
- Shahinda S R Alsayed
- Curtin Medical School, Faculty of Health Sciences, Curtin University Bentley Perth WA 6102 Australia
| | - Shichun Lun
- Center for Tuberculosis Research, Department of Medicine, Division of Infectious Disease, Johns Hopkins School of Medicine 1550, Orleans Street Baltimore Maryland 21231-1044 USA
| | - Anders W Bailey
- Division of Pediatric Neurosurgery, Ann and Robert H. Lurie Children's Hospital of Chicago Chicago IL 60611 USA
| | - Amreena Suri
- Division of Pediatric Neurosurgery, Ann and Robert H. Lurie Children's Hospital of Chicago Chicago IL 60611 USA
| | - Chiang-Ching Huang
- Department of Biostatistics, Zilber School of Public Health, University of Wisconsin Milwaukee WI 53205 USA
| | - Mauro Mocerino
- School of Molecular and Life Sciences, Curtin University Perth WA 6102 Australia
| | - Alan Payne
- School of Molecular and Life Sciences, Curtin University Perth WA 6102 Australia
| | - Simone Treiger Sredni
- Division of Pediatric Neurosurgery, Ann and Robert H. Lurie Children's Hospital of Chicago Chicago IL 60611 USA.,Department of Surgery, Northwestern University, Feinberg School of Medicine Chicago IL 60611 USA
| | - William R Bishai
- Center for Tuberculosis Research, Department of Medicine, Division of Infectious Disease, Johns Hopkins School of Medicine 1550, Orleans Street Baltimore Maryland 21231-1044 USA .,Howard Hughes Medical Institute 4000 Jones Bridge Road Chevy Chase Maryland 20815-6789 USA
| | - Hendra Gunosewoyo
- Curtin Medical School, Faculty of Health Sciences, Curtin University Bentley Perth WA 6102 Australia
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16
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Assessing Protein Function Through Structural Similarities with CATH. Methods Mol Biol 2021. [PMID: 32006277 DOI: 10.1007/978-1-0716-0270-6_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
The functional diversity of proteins is closely related to their differences in sequence and structure. Despite variations in functional sites, global structural similarity is a valuable source of information when assessing potential functional similarities between proteins. The CATH database contains a well-established hierarchical classification of more than 430,000 protein domain structures and nearly 95 million protein domain sequences, with integrated functional annotations for each represented family. The present chapter provides an overview of the main features of CATH with emphasis on exploiting structural similarities to obtain functional information for proteins.
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17
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González-Durruthy M, Concu R, Vendrame LFO, Zanella I, Ruso JM, Cordeiro MNDS. Targeting Beta-Blocker Drug-Drug Interactions with Fibrinogen Blood Plasma Protein: A Computational and Experimental Study. Molecules 2020; 25:molecules25225425. [PMID: 33228181 PMCID: PMC7699576 DOI: 10.3390/molecules25225425] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 11/16/2020] [Accepted: 11/17/2020] [Indexed: 12/05/2022] Open
Abstract
In this work, one of the most prevalent polypharmacology drug–drug interaction events that occurs between two widely used beta-blocker drugs—i.e., acebutolol and propranolol—with the most abundant blood plasma fibrinogen protein was evaluated. Towards that end, molecular docking and Density Functional Theory (DFT) calculations were used as complementary tools. A fibrinogen crystallographic validation for the three best ranked binding-sites shows 100% of conformationally favored residues with total absence of restricted flexibility. From those three sites, results on both the binding-site druggability and ligand transport analysis-based free energy trajectories pointed out the most preferred biophysical environment site for drug–drug interactions. Furthermore, the total affinity for the stabilization of the drug–drug complexes was mostly influenced by steric energy contributions, based mainly on multiple hydrophobic contacts with critical residues (THR22: P and SER50: Q) in such best-ranked site. Additionally, the DFT calculations revealed that the beta-blocker drug–drug complexes have a spontaneous thermodynamic stabilization following the same affinity order obtained in the docking simulations, without covalent-bond formation between both interacting beta-blockers in the best-ranked site. Lastly, experimental ultrasound density and velocity measurements were performed and allowed us to validate and corroborate the computational obtained results.
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Affiliation(s)
- Michael González-Durruthy
- LAQV-REQUIMTE, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal;
- Soft Matter and Molecular Biophysics Group, Department of Applied Physics, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain;
- Correspondence: (M.G.-D.); (M.N.D.S.C.); Tel.: +351-220402502 (M.N.D.S.C.)
| | - Riccardo Concu
- LAQV-REQUIMTE, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal;
| | - Laura F. Osmari Vendrame
- Post-Graduate Program in Nanoscience, Franciscana University (UFN), Santa Maria 97010-032, RS, Brazil; (L.F.O.V.); (I.Z.)
| | - Ivana Zanella
- Post-Graduate Program in Nanoscience, Franciscana University (UFN), Santa Maria 97010-032, RS, Brazil; (L.F.O.V.); (I.Z.)
| | - Juan M. Ruso
- Soft Matter and Molecular Biophysics Group, Department of Applied Physics, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain;
| | - M. Natália D. S. Cordeiro
- LAQV-REQUIMTE, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal;
- Correspondence: (M.G.-D.); (M.N.D.S.C.); Tel.: +351-220402502 (M.N.D.S.C.)
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18
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Prasher P, Sharma M, Singh SP, Rawat DS. Barbiturate derivatives for managing multifaceted oncogenic pathways: A mini review. Drug Dev Res 2020; 82:364-373. [PMID: 33210368 DOI: 10.1002/ddr.21761] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 10/31/2020] [Accepted: 11/09/2020] [Indexed: 12/12/2022]
Abstract
Development and progression of metastasis comprises synchronized erroneous expressions of several composite pathways, which are difficult to manage simultaneously with the representative anticancer molecules. The emergence of the drug resistance and the complex interplay between these pathways further potentiates cancer related complexities. Barbiturates and their derivatives present a commendable anticancer profile by attenuating the cancer manifesting metabolic and enzymatic pathways including, but not limited to matrix metalloproteinases, xanthine oxidase, amino peptidases, histone deacetylases, and Ras/mitogen-activated protein kinase. The derivatization and conjugation of barbiturates with pharmacophores delivers a suitable hybrid profile in containing the anomalous expression of these pathways. The present report presents a succinct collation of the barbiturates and their derivatives in managing the various cancer causing pathways.
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Affiliation(s)
- Parteek Prasher
- UGC Sponsored Centre for Advanced Studies, Department of Chemistry, Guru Nanak Dev University, Amritsar, India.,Department of Chemistry, University of Petroleum & Energy Studies, Dehradun, India
| | - Mousmee Sharma
- UGC Sponsored Centre for Advanced Studies, Department of Chemistry, Guru Nanak Dev University, Amritsar, India.,Department of Chemistry, Uttaranchal University, Dehradun, India
| | - Samarth P Singh
- Department of Chemistry, University of Petroleum & Energy Studies, Dehradun, India
| | - Devendra S Rawat
- Department of Chemistry, University of Petroleum & Energy Studies, Dehradun, India
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19
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Exploration in the Mechanism of Kaempferol for the Treatment of Gastric Cancer Based on Network Pharmacology. BIOMED RESEARCH INTERNATIONAL 2020; 2020:5891016. [PMID: 33145355 PMCID: PMC7596434 DOI: 10.1155/2020/5891016] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 09/07/2020] [Accepted: 10/09/2020] [Indexed: 12/11/2022]
Abstract
Background Kaempferol is a natural polyphenol in lots of Chinese herbs, which has shown promising treatment for gastric cancer (GC). However, the molecular mechanisms of its action have not been systematically revealed yet. In this work, a network pharmacology approach was used to elucidate the potential mechanisms of kaempferol in the treatment of GC. Methods The kaempferol was input into the PharmMapper and SwissTargetPrediction database to get its targets, and the targets of GC were obtained by retrieving the Online Mendelian Inheritance in Man (OMIM) database, MalaCards database, Therapeutic Target Database (TTD), and Coolgen database. The molecular docking was performed to assess the interactions between kaempferol and these targets. Next, the overlap targets of kaempferol and GC were identified for GO and KEGG enrichment analyses. Afterward, a protein-protein interaction (PPI) network was constructed to get the hub targets, and the expression and overall survival analysis of the hub target were investigated. Finally, the overall survival (OS) analysis of hub targets was performed using the Kaplan-Meier Plotter online tool. Results A total of 990 genes related to GC and 10 overlapping genes were determined through matching the 24 potential targets of kaempferol with disease-associated genes. The result of molecular docking indicated that kaempferol can bind with these hub targets with good binding scores. These targets were further mapped to 140 GO biological process terms and 11 remarkable pathways. In the PPI network analysis, 3 key targets were identified, including ESR1, EGFR, and SRC. The mRNA and protein expression levels of EGFR and SRC were obviously higher in GC tissues. High expression of these targets was related to poor OS in GC patients. Conclusions This study provided a novel approach to reveal the therapeutic mechanisms of kaempferol on GC, which will ease the future clinical application of kaempferol in the treatment of GC.
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20
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Luchinat E, Barbieri L, Cremonini M, Nocentini A, Supuran CT, Banci L. Intracellular Binding/Unbinding Kinetics of Approved Drugs to Carbonic Anhydrase II Observed by in-Cell NMR. ACS Chem Biol 2020; 15:2792-2800. [PMID: 32955851 PMCID: PMC7735671 DOI: 10.1021/acschembio.0c00590] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
![]()
Candidate
drugs rationally designed in vitro often
fail due to low efficacy in vivo caused by low tissue
availability or because of unwanted side effects. To overcome the
limitations of in vitro rational drug design, the
binding of candidate drugs to their target needs to be evaluated in
the cellular context. Here, we applied in-cell NMR to investigate
the binding of a set of approved drugs to the isoform II of carbonic
anhydrase (CA) in living human cells. Some compounds were originally
developed toward other targets and were later found to inhibit CAs.
We observed strikingly different dose- and time-dependent binding,
wherein some drugs exhibited a more complex behavior than others.
Specifically, some compounds were shown to gradually unbind from intracellular
CA II, even in the presence of free compound in the external medium,
therefore preventing the quantitative formation of a stable protein–ligand
complex. Such observations could be correlated to the known off-target
binding activity of these compounds, suggesting that this approach
could provide information on the pharmacokinetic profiles of lead
candidates at the early stages of multitarget drug design.
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Affiliation(s)
- Enrico Luchinat
- CERM − Magnetic Resonance Center, Università degli Studi di Firenze, Via Luigi sacconi 6, 50019 Sesto Fiorentino, Italy
- Consorzio per lo Sviluppo dei Sistemi a Grande Interfase − CSGI, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy
| | - Letizia Barbieri
- CERM − Magnetic Resonance Center, Università degli Studi di Firenze, Via Luigi sacconi 6, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine, Via Luigi Sacconi 6, Sesto Fiorentino, Italy
| | - Matteo Cremonini
- CERM − Magnetic Resonance Center, Università degli Studi di Firenze, Via Luigi sacconi 6, 50019 Sesto Fiorentino, Italy
| | - Alessio Nocentini
- Dipartimento Neurofarba, Sezione di Scienze Farmaceutiche, Università degli Studi di Firenze, Via Ugo Schiff 6, 50019 Sesto Fiorentino, Italy
| | - Claudiu T. Supuran
- Dipartimento Neurofarba, Sezione di Scienze Farmaceutiche, Università degli Studi di Firenze, Via Ugo Schiff 6, 50019 Sesto Fiorentino, Italy
- Dipartimento di Chimica, Università degli Studi di Firenze, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy
| | - Lucia Banci
- CERM − Magnetic Resonance Center, Università degli Studi di Firenze, Via Luigi sacconi 6, 50019 Sesto Fiorentino, Italy
- Dipartimento di Chimica, Università degli Studi di Firenze, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy
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21
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Chaudhari R, Fong LW, Tan Z, Huang B, Zhang S. An up-to-date overview of computational polypharmacology in modern drug discovery. Expert Opin Drug Discov 2020; 15:1025-1044. [PMID: 32452701 PMCID: PMC7415563 DOI: 10.1080/17460441.2020.1767063] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 05/06/2020] [Indexed: 12/30/2022]
Abstract
INTRODUCTION In recent years, computational polypharmacology has gained significant attention to study the promiscuous nature of drugs. Despite tremendous challenges, community-wide efforts have led to a variety of novel approaches for predicting drug polypharmacology. In particular, some rapid advances using machine learning and artificial intelligence have been reported with great success. AREAS COVERED In this article, the authors provide a comprehensive update on the current state-of-the-art polypharmacology approaches and their applications, focusing on those reports published after our 2017 review article. The authors particularly discuss some novel, groundbreaking concepts, and methods that have been developed recently and applied to drug polypharmacology studies. EXPERT OPINION Polypharmacology is evolving and novel concepts are being introduced to counter the current challenges in the field. However, major hurdles remain including incompleteness of high-quality experimental data, lack of in vitro and in vivo assays to characterize multi-targeting agents, shortage of robust computational methods, and challenges to identify the best target combinations and design effective multi-targeting agents. Fortunately, numerous national/international efforts including multi-omics and artificial intelligence initiatives as well as most recent collaborations on addressing the COVID-19 pandemic have shown significant promise to propel the field of polypharmacology forward.
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Affiliation(s)
- Rajan Chaudhari
- Intelligent Molecular Discovery Laboratory, Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, United States
| | - Long Wolf Fong
- Intelligent Molecular Discovery Laboratory, Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, United States
- MD Anderson UTHealth Graduate School of Biomedical Sciences, 6767 Bertner Avenue, Houston, Texas 77030, United States
| | - Zhi Tan
- Intelligent Molecular Discovery Laboratory, Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, United States
| | - Beibei Huang
- Intelligent Molecular Discovery Laboratory, Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, United States
| | - Shuxing Zhang
- Intelligent Molecular Discovery Laboratory, Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, United States
- MD Anderson UTHealth Graduate School of Biomedical Sciences, 6767 Bertner Avenue, Houston, Texas 77030, United States
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22
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Gong J, Chen Y, Pu F, Sun P, He F, Zhang L, Li Y, Ma Z, Wang H. Understanding Membrane Protein Drug Targets in Computational Perspective. Curr Drug Targets 2020; 20:551-564. [PMID: 30516106 DOI: 10.2174/1389450120666181204164721] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 09/03/2018] [Accepted: 09/04/2018] [Indexed: 01/16/2023]
Abstract
Membrane proteins play crucial physiological roles in vivo and are the major category of drug targets for pharmaceuticals. The research on membrane protein is a significant part in the drug discovery. The biological process is a cycled network, and the membrane protein is a vital hub in the network since most drugs achieve the therapeutic effect via interacting with the membrane protein. In this review, typical membrane protein targets are described, including GPCRs, transporters and ion channels. Also, we conclude network servers and databases that are referring to the drug, drug-target information and their relevant data. Furthermore, we chiefly introduce the development and practice of modern medicines, particularly demonstrating a series of state-of-the-art computational models for the prediction of drug-target interaction containing network-based approach and machine-learningbased approach as well as showing current achievements. Finally, we discuss the prospective orientation of drug repurposing and drug discovery as well as propose some improved framework in bioactivity data, created or improved predicted approaches, alternative understanding approaches of drugs bioactivity and their biological processes.
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Affiliation(s)
- Jianting Gong
- School of Information Science and Technology, Northeast Normal University, Changchun, China.,Institution of Computational Biology, Northeast Normal University, Changchun, China
| | - Yongbing Chen
- School of Information Science and Technology, Northeast Normal University, Changchun, China.,Institution of Computational Biology, Northeast Normal University, Changchun, China
| | - Feng Pu
- School of Information Science and Technology, Northeast Normal University, Changchun, China.,Institution of Computational Biology, Northeast Normal University, Changchun, China
| | - Pingping Sun
- School of Information Science and Technology, Northeast Normal University, Changchun, China.,Institution of Computational Biology, Northeast Normal University, Changchun, China
| | - Fei He
- School of Information Science and Technology, Northeast Normal University, Changchun, China.,Institution of Computational Biology, Northeast Normal University, Changchun, China
| | - Li Zhang
- School of Computer Science and Engineering, Changchun University of Technology, Changchun, China
| | - Yanwen Li
- School of Information Science and Technology, Northeast Normal University, Changchun, China.,Institution of Computational Biology, Northeast Normal University, Changchun, China
| | - Zhiqiang Ma
- School of Information Science and Technology, Northeast Normal University, Changchun, China.,Institution of Computational Biology, Northeast Normal University, Changchun, China
| | - Han Wang
- School of Information Science and Technology, Northeast Normal University, Changchun, China.,Institution of Computational Biology, Northeast Normal University, Changchun, China
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23
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X-ray Structure-Based Chemoinformatic Analysis Identifies Promiscuous Ligands Binding to Proteins from Different Classes with Varying Shapes. Int J Mol Sci 2020; 21:ijms21113782. [PMID: 32471121 PMCID: PMC7312685 DOI: 10.3390/ijms21113782] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 05/18/2020] [Accepted: 05/24/2020] [Indexed: 12/11/2022] Open
Abstract
(1) Background: Compounds with multitarget activity are of interest in basic research to explore molecular foundations of promiscuous binding and in drug discovery as agents eliciting polypharmacological effects. Our study has aimed to systematically identify compounds that form complexes with proteins from distinct classes and compare their bioactive conformations and molecular properties. (2) Methods: A large-scale computational investigation was carried out that combined the analysis of complex X-ray structures, ligand binding modes, compound activity data, and various molecular properties. (3) Results: A total of 515 ligands with multitarget activity were identified that included 70 organic compounds binding to proteins from different classes. These multiclass ligands (MCLs) were often flexible and surprisingly hydrophilic. Moreover, they displayed a wide spectrum of binding modes. In different target structure environments, binding shapes of MCLs were often similar, but also distinct. (4) Conclusions: Combined structural and activity data analysis identified compounds with activity against proteins with distinct structures and functions. MCLs were found to have greatly varying shape similarity when binding to different protein classes. Hence, there were no apparent canonical binding shapes indicating multitarget activity. Rather, conformational versatility characterized MCL binding.
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Waman VP, Blundell TL, Buchan DWA, Gough J, Jones D, Kelley L, Murzin A, Pandurangan AP, Sillitoe I, Sternberg M, Torres P, Orengo C. The Genome3D Consortium for Structural Annotations of Selected Model Organisms. Methods Mol Biol 2020; 2165:27-67. [PMID: 32621218 DOI: 10.1007/978-1-0716-0708-4_3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Genome3D consortium is a collaborative project involving protein structure prediction and annotation resources developed by six world-leading structural bioinformatics groups, based in the United Kingdom (namely Blundell, Murzin, Gough, Sternberg, Orengo, and Jones). The main objective of Genome3D serves as a common portal to provide both predicted models and annotations of proteins in model organisms, using several resources developed by these labs such as CATH-Gene3D, DOMSERF, pDomTHREADER, PHYRE, SUPERFAMILY, FUGUE/TOCATTA, and VIVACE. These resources primarily use SCOP- and/or CATH-based protein domain assignments. Another objective of Genome3D is to compare structural classifications of protein domains in CATH and SCOP databases and to provide a consensus mapping of CATH and SCOP protein superfamilies. CATH/SCOP mapping analyses led to the identification of total of 1429 consensus superfamilies.Currently, Genome3D provides structural annotations for ten model organisms, including Homo sapiens, Arabidopsis thaliana, Mus musculus, Escherichia coli, Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, Plasmodium falciparum, Staphylococcus aureus, and Schizosaccharomyces pombe. Thus, Genome3D serves as a common gateway to each structure prediction/annotation resource and allows users to perform comparative assessment of the predictions. It, thus, assists researchers to broaden their perspective on structure/function predictions of their query protein of interest in selected model organisms.
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Affiliation(s)
- Vaishali P Waman
- Institute of Structural and Molecular Biology, University College London, London, UK
| | - Tom L Blundell
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Daniel W A Buchan
- Department of Computer Science, University College London, London, UK
| | - Julian Gough
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | - David Jones
- Department of Computer Science, University College London, London, UK
| | - Lawrence Kelley
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, UK
| | | | | | - Ian Sillitoe
- Institute of Structural and Molecular Biology, University College London, London, UK
| | - Michael Sternberg
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, UK
| | - Pedro Torres
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Christine Orengo
- Institute of Structural and Molecular Biology, University College London, London, UK.
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25
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Chagoyen M, Ranea JAG, Pazos F. Applications of molecular networks in biomedicine. Biol Methods Protoc 2019; 4:bpz012. [PMID: 32395629 PMCID: PMC7200821 DOI: 10.1093/biomethods/bpz012] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Revised: 08/20/2019] [Accepted: 08/28/2019] [Indexed: 12/12/2022] Open
Abstract
Due to the large interdependence between the molecular components of living systems, many phenomena, including those related to pathologies, cannot be explained in terms of a single gene or a small number of genes. Molecular networks, representing different types of relationships between molecular entities, embody these large sets of interdependences in a framework that allow their mining from a systemic point of view to obtain information. These networks, often generated from high-throughput omics datasets, are used to study the complex phenomena of human pathologies from a systemic point of view. Complementing the reductionist approach of molecular biology, based on the detailed study of a small number of genes, systemic approaches to human diseases consider that these are better reflected in large and intricate networks of relationships between genes. These networks, and not the single genes, provide both better markers for diagnosing diseases and targets for treating them. Network approaches are being used to gain insight into the molecular basis of complex diseases and interpret the large datasets associated with them, such as genomic variants. Network formalism is also suitable for integrating large, heterogeneous and multilevel datasets associated with diseases from the molecular level to organismal and epidemiological scales. Many of these approaches are available to nonexpert users through standard software packages.
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Affiliation(s)
- Monica Chagoyen
- Computational Systems Biology Group, Systems Biology Program, National Centre for Biotechnology (CNB-CSIC), Madrid, Spain
| | - Juan A G Ranea
- Department of Molecular Biology and Biochemistry, University of Malaga, Malaga, Spain
- CIBER de Enfermedades Raras, Instituto de Salud Carlos III, Madrid, Spain
| | - Florencio Pazos
- Computational Systems Biology Group, Systems Biology Program, National Centre for Biotechnology (CNB-CSIC), Madrid, Spain
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Peptide Conjugates with Small Molecules Designed to Enhance Efficacy and Safety. Molecules 2019; 24:molecules24101855. [PMID: 31091786 PMCID: PMC6572008 DOI: 10.3390/molecules24101855] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Revised: 05/10/2019] [Accepted: 05/12/2019] [Indexed: 12/17/2022] Open
Abstract
Peptides constitute molecular diversity with unique molecular mechanisms of action that are proven indispensable in the management of many human diseases, but of only a mere fraction relative to more traditional small molecule-based medicines. The integration of these two therapeutic modalities offers the potential to enhance and broaden pharmacology while minimizing dose-dependent toxicology. This review summarizes numerous advances in drug design, synthesis and development that provide direction for next-generation research endeavors in this field. Medicinal studies in this area have largely focused upon the application of peptides to selectively enhance small molecule cytotoxicity to more effectively treat multiple oncologic diseases. To a lesser and steadily emerging extent peptides are being therapeutically employed to complement and diversify the pharmacology of small molecule drugs in diseases other than just cancer. No matter the disease, the purpose of the molecular integration remains constant and it is to achieve superior therapeutic outcomes with diminished adverse effects. We review linker technology and conjugation chemistries that have enabled integrated and targeted pharmacology with controlled release. Finally, we offer our perspective on opportunities and obstacles in the field.
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27
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Long MJ, Liu X, Aye Y. Genie in a bottle: controlled release helps tame natural polypharmacology? Curr Opin Chem Biol 2019; 51:48-56. [PMID: 30913473 DOI: 10.1016/j.cbpa.2019.02.014] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 02/02/2019] [Accepted: 02/12/2019] [Indexed: 02/06/2023]
Abstract
Ability to faithfully report drug-target interactions constitutes a major critical parameter in preclinical/clinical settings. Yet the assessment of target engagement remains challenging, particularly for promiscuous and/or polypharmacologic ligands. Drawing from our improved insights into native electrophile signaling and emerging technologies that profile and interrogate these non-enzyme-assisted signaling subsystems, we posit that 'trained' polypharmocologic covalent inhibitors can be designed. Accumulating evidence indicates that electrophile-modified states at fractional occupancy can alter cell fate. Thus, by understanding sensing preferences and ligandable regions favored by the natural electrophilic signals at individual protein-ligand resolution, we can better evaluate target engagement and develop a function-guided understanding of polypharmacology.
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Affiliation(s)
- Marcus Jc Long
- 47 Pudding Gate, Bishop Burton, Beverley East Riding of Yorkshire, HU17 8QH, UK
| | - Xuyu Liu
- École Polytechnique Fédérale de Lausanne, Institute of Chemical Sciences and Engineering, 1015, Lausanne, Switzerland
| | - Yimon Aye
- École Polytechnique Fédérale de Lausanne, Institute of Chemical Sciences and Engineering, 1015, Lausanne, Switzerland.
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28
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Gilberg E, Gütschow M, Bajorath J. Promiscuous Ligands from Experimentally Determined Structures, Binding Conformations, and Protein Family-Dependent Interaction Hotspots. ACS OMEGA 2019; 4:1729-1737. [PMID: 31459430 PMCID: PMC6648413 DOI: 10.1021/acsomega.8b03481] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 01/10/2019] [Indexed: 05/06/2023]
Abstract
Compound promiscuity is often attributed to nonspecific binding or assay artifacts. On the other hand, it is well-known that many pharmaceutically relevant compounds are capable of engaging multiple targets in vivo, giving rise to polypharmacology. To explore and better understand promiscuous binding characteristics of small molecules, we have searched X-ray structures (and very few qualifying solution structures) for ligands that bind to multiple distantly related or unrelated target proteins. Experimental structures of a given ligand bound to different targets represent high-confidence data for exploring promiscuous binding events. A total of 192 ligands were identified that formed crystallographic complexes with proteins from different families and for which activity data were available. These "multifamily" compounds included endogenous ligands and were often more polar than other bound compounds and active in the submicromolar range. Unexpectedly, many promiscuous ligands displayed conserved or similar binding conformations in different active sites. Others were found to conformationally adjust to binding sites of different architectures. A comprehensive analysis of ligand-target interactions revealed that multifamily ligands frequently formed different interaction hotspots in binding sites, even if their bound conformations were similar, thus providing a rationale for promiscuous binding events at the molecular level of detail. As a part of this work, all multifamily ligands we have identified and associated activity data are made freely available.
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Affiliation(s)
- Erik Gilberg
- Department
of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology
and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany
- Pharmaceutical
Institute, Rheinische Friedrich-Wilhelms-Universität, An der Immenburg 4, D-53121 Bonn, Germany
| | - Michael Gütschow
- Pharmaceutical
Institute, Rheinische Friedrich-Wilhelms-Universität, An der Immenburg 4, D-53121 Bonn, Germany
| | - Jürgen Bajorath
- Department
of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology
and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany
- E-mail: .
Phone: 49-228-2699-306 (J.B.)
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