1
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Fouad MA, Osman AA, Abdelhamid NM, Rashad MW, Nabawy AY, El Kerdawy AM. Discovery of dual kinase inhibitors targeting VEGFR2 and FAK: structure-based pharmacophore modeling, virtual screening, and molecular docking studies. BMC Chem 2024; 18:29. [PMID: 38347617 PMCID: PMC10863211 DOI: 10.1186/s13065-024-01130-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 01/22/2024] [Indexed: 02/15/2024] Open
Abstract
VEGFR2 and FAK signaling pathways are interconnected and have synergistic effects on tumor angiogenesis, growth, and metastasis. Thus, instead of the conventional targeting of each of these proteins individually with a specific inhibitor, the present work aimed to discover novel dual inhibitors targeting both VEGFR2 and FAK exploiting their association. To this end, receptor-based pharmacophore modeling technique was opted to generate 3D pharmacophore models for VEGFR2 and FAK type II kinase inhibitors. The generated pharmacophore models were validated by assessing their ability to discriminate between active and decoy compounds in a pre-compiled test set of VEGFR2 and FAK active compounds and decoys. ZINCPharmer web tool was then used to screen the ZINC database purchasable subset using the validated pharmacophore models retrieving 42,616 hits for VEGFR2 and 28,475 hits for FAK. Subsequently, they were filtered using various filters leaving 13,023 and 6,832 survived compounds for VEGFR2 and FAK, respectively, with 124 common compounds. Based on molecular docking simulations, thirteen compounds were found to satisfy all necessary interactions with VEGFR2 and FAK kinase domains. Thus, they are predicted to have a possible dual VEGFR2/FAK inhibitory activity. Finally, SwissADME web tool showed that compound ZINC09875266 is not only promising in terms of binding pattern to our target kinases, but also in terms of pharmacokinetic properties.
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Affiliation(s)
- Marwa A Fouad
- Pharmaceutical Chemistry Department, Faculty of Pharmacy, Cairo University, Kasr El-Aini St., Cairo, 11562, Egypt.
- Pharmaceutical Chemistry Department, School of Pharmacy, Newgiza University (NGU), Newgiza, Km 22 Cairo-Alexandria Desert Road, Cairo, Egypt.
| | - Alaa A Osman
- Pharmaceutical Chemistry Department, School of Pharmacy, Newgiza University (NGU), Newgiza, Km 22 Cairo-Alexandria Desert Road, Cairo, Egypt
| | - Noha M Abdelhamid
- Pharmaceutical Chemistry Department, School of Pharmacy, Newgiza University (NGU), Newgiza, Km 22 Cairo-Alexandria Desert Road, Cairo, Egypt
| | - Mai W Rashad
- Pharmaceutical Chemistry Department, School of Pharmacy, Newgiza University (NGU), Newgiza, Km 22 Cairo-Alexandria Desert Road, Cairo, Egypt
| | - Ashrakat Y Nabawy
- Pharmaceutical Chemistry Department, School of Pharmacy, Newgiza University (NGU), Newgiza, Km 22 Cairo-Alexandria Desert Road, Cairo, Egypt
| | - Ahmed M El Kerdawy
- Pharmaceutical Chemistry Department, Faculty of Pharmacy, Cairo University, Kasr El-Aini St., Cairo, 11562, Egypt
- Pharmaceutical Chemistry Department, School of Pharmacy, Newgiza University (NGU), Newgiza, Km 22 Cairo-Alexandria Desert Road, Cairo, Egypt
- School of Pharmacy, College of Health and Science, University of Lincoln, Joseph Banks Laboratories, Green Lane, Lincoln, Lincolnshire, UK
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2
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Zaky YA, Rashad MW, Zaater MA, El Kerdawy AM. Discovery of dual rho-associated protein kinase 1 (ROCK1)/apoptosis signal-regulating kinase 1 (ASK1) inhibitors as a novel approach for non-alcoholic steatohepatitis (NASH) treatment. BMC Chem 2024; 18:2. [PMID: 38172941 PMCID: PMC10765837 DOI: 10.1186/s13065-023-01081-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 11/08/2023] [Indexed: 01/05/2024] Open
Abstract
In the current study we suggest a novel approach to curb non-alcoholic steatohepatitis (NASH) progression, and we suggest privileged scaffolds for the design of novel compounds for this aim. NASH is an advanced form of non-alcoholic fatty liver disease that can further progress into fibrosis, cirrhosis, and hepatocellular carcinoma. It is a widely emerging disease affecting 25% of the global population and has no current approved treatments. Protein kinases are key regulators of cellular pathways, of which, Rho-associated protein kinase 1 (ROCK1) and apoptosis signal-regulating kinase 1 (ASK1) play an important role in the progression of NASH and they stand out as promising targets for NASH therapy. Interestingly, their kinase domains are found to be similar in sequence and topology; therefore, dual inhibition of ROCK1 and ASK1 is expected to be amenable and could achieve a more favourable outcome. To reach this goal, a training set of ROCK1 and ASK1 protein structures co-crystalized with type 1 (ATP-competitive) inhibitors was constructed to manually generate receptor-based pharmacophore models representing ROCK1 and ASK1 inhibitors' common pharmacophoric features. The models produced were assessed using a test set of both ROCK1 and ASK1 actives and decoys, and their performance was evaluated using different assessment metrics. The best pharmacophore model obtained, showing a Mathew's correlation coefficient (MCC) of 0.71, was then used to screen the ZINC purchasable database retrieving 6178 hits that were filtered accordingly using several medicinal chemistry and pharmacokinetics filters returning 407 promising compounds. To confirm that these compounds are capable of binding to the target kinases, they were subjected to molecular docking simulations at both protein structures. The results were then assessed individually and filtered, setting the spotlight on various privileged scaffolds that could be exploited as the nucleus for designing novel ROCK1/ASK1 dual inhibitors.
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Affiliation(s)
- Yara A Zaky
- Department of Chemistry, School of Pharmacy, Newgiza University (NGU), Newgiza, Km 22 Cairo-Alexandria Desert Road, Cairo, Egypt.
| | - Mai W Rashad
- Department of Chemistry, School of Pharmacy, Newgiza University (NGU), Newgiza, Km 22 Cairo-Alexandria Desert Road, Cairo, Egypt
| | - Marwa A Zaater
- Master Postgraduate Program, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Cairo University, Cairo, Egypt
| | - Ahmed M El Kerdawy
- Department of Chemistry, School of Pharmacy, Newgiza University (NGU), Newgiza, Km 22 Cairo-Alexandria Desert Road, Cairo, Egypt
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Cairo University, Cairo, Egypt
- School of Pharmacy, College of Science, University of Lincoln, Joseph Banks Laboratories, Green Lane, Lincoln, Lincolnshire, UK
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3
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Wu WJ, Xia CL, Ou SJ, Yang Y, Ma YF, Hou YL, Yang QP, Zhang J, Li JW, Qi Y, Xu CP. Novel Elongator Protein 2 Inhibitors Mitigating Tumor Necrosis Factor- α Induced Osteogenic Differentiation Inhibition. BIOMED RESEARCH INTERNATIONAL 2021; 2021:3664564. [PMID: 34853789 PMCID: PMC8629650 DOI: 10.1155/2021/3664564] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 10/12/2021] [Indexed: 11/17/2022]
Abstract
Tumor necrosis factor-α is a common cytokine that increases in inflammatory processes, slows the differentiation of bone formation, and induces osteodystrophy in the long-term inflammatory microenvironment. Our previous study confirmed that the Elongation protein 2 (ELP2) plays a significant role in osteogenesis and osteogenic differentiation, which is considered a drug discovery target in diseases related to bone formation and differentiation. In this study, we applied an in silico virtual screening method to select molecules that bind to the ELP2 protein from a chemical drug molecule library and obtained 95 candidates. Then, we included 11 candidates by observing the docking patterns and the noncovalent bonds. The binding affinity of the ELP2 protein with the candidate compounds was examined by SPR analysis, and 5 out of 11 compounds performed good binding affinity to the mouse ELP2 protein. After in vitro cell differentiation assay, candidates 2# and 5# were shown to reduce differentiation inhibition after tumor necrosis factor-α stimulation, allowing further optimization and development for potential clinical treatment of inflammation-mediated orthopedic diseases.
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Affiliation(s)
- Wen-Jiao Wu
- Department of Medical Research Center, Guangdong Second Provincial General Hospital, Guangzhou, Guangdong, China
| | - Chang-Liang Xia
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, Guangzhou, Guangdong, China
| | - Shuan-Ji Ou
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, Guangzhou, Guangdong, China
| | - Yang Yang
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, Guangzhou, Guangdong, China
| | - Yun-Fei Ma
- Department of Orthopaedics and Traumatology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Yi-Long Hou
- Department of Orthopaedics and Traumatology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Qing-Po Yang
- Department of Orthopaedics, The First People's Hospital of Kashgar Prefecture, Kashgar, Xinjiang, China
| | - Jun Zhang
- Department of Orthopaedics, The First People's Hospital of Kashgar Prefecture, Kashgar, Xinjiang, China
| | - Jian-Wei Li
- Department of Orthopaedics, Shenzhen Shekou People's Hospital, Shenzhen, Guangdong, China
| | - Yong Qi
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, Guangzhou, Guangdong, China
| | - Chang-Peng Xu
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, Guangzhou, Guangdong, China
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4
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Chukwuemeka PO, Umar HI, Iwaloye O, Oretade OM, Olowosoke CB, Elabiyi MO, Igbe FO, Oretade OJ, Eigbe JO, Adeojo FJ. Targeting p53-MDM2 interactions to identify small molecule inhibitors for cancer therapy: beyond "Failure to rescue". J Biomol Struct Dyn 2021; 40:9158-9176. [PMID: 33988074 DOI: 10.1080/07391102.2021.1924267] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
At present, disrupting p53-MDM2 interactions through small molecule ligands is a promising approach to safe treatment and management of human cancer. Tumor cells unlike the normal cells, are rapidly evolving affecting the efficacy of many approved anti-cancer agents due to drug resistance. Therefore, identifying a potential anticancer compound is crucial. Pharmacophore based virtual screening, followed by molecular docking, ADMET evaluation, and molecular dynamics studies against MDM2 protein was investigated to identify potential ligands that may act as inhibitors. The model (AHRR_1) with survival score (4.176) was selected among the top ranked generated Pharmacophore hypothesis. Validation of the model hypothesis by an external dataset of actives and inactive compounds produced significant validation attributes including; AUC = 0.85, BEDROC = 0.56 at α = 20.0, RIE = 8.18, AUAC = 0.88, and EF of 6.2 at the top 2% of the dataset. The model was use for screening the ZINC database, and the top 1375 hits satisfying the model hypothesis were subjected to molecular docking studies to understand the molecular and structural basis of selectivity of compounds for MDM2 protein. A sub-set of 25 compounds with binding energy lower than the reference inhibitors were evaluated for pharmacokinetic properties. Four compounds (ZINC02639178, ZINC06752762, ZINC38933175, and ZINC77969611) showed the most desired pharmacokinetic profile. Lastly, investigation of the dynamic behaviour of leads-protein complexes through MD simulation showed similar RMSD, RMSF, and H-bond occupancy profile compared to a reference inhibitor, suggesting stability throughout the simulation time. However, ZINC02639178 was found to satisfy the molecular enumeration the most compared to the other three leads. It may emerge as potential treatment option after extensive experimental studies. Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Prosper Obed Chukwuemeka
- Department of Biotechnology, School of Sciences (SOS), Federal University of Technology Akure, Akure, Nigeria
| | - Haruna Isiyaku Umar
- Department of Biochemistry, School of Sciences (SOS), Federal University of Technology Akure, Akure, Nigeria
| | - Opeyemi Iwaloye
- Bioinformatics and Molecular biology unit, Department of Biochemistry, School of Sciences (SOS), Federal University of Technology Akure, Akure, Nigeria
| | - Oluwaseyi Matthew Oretade
- Department of Biotechnology, School of Sciences (SOS), Federal University of Technology Akure, Akure, Nigeria
| | | | - Michael Omoniyi Elabiyi
- Department of Microbiology, School of Sciences (SOS), Federal University of Technology Akure, Akure, Nigeria
| | - Festus Omotere Igbe
- Department of Biochemistry, School of Sciences (SOS), Federal University of Technology Akure, Akure, Nigeria
| | - Oyeyemi Janet Oretade
- Department of Physiology, College of Health Science (CHS), Osun State University, Osogbo, Nigeria
| | - Joy Oseme Eigbe
- Department of Biomedical Technology, School of Health and Health Technology (SHHT), Federal University of Technology Akure, Akure, Nigeria
| | - Funmilayo Janet Adeojo
- Department of Biotechnology, School of Sciences (SOS), Federal University of Technology Akure, Akure, Nigeria
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5
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Predicting cell-penetrating peptides using machine learning algorithms and navigating in their chemical space. Sci Rep 2021; 11:7628. [PMID: 33828175 PMCID: PMC8027643 DOI: 10.1038/s41598-021-87134-w] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 03/24/2021] [Indexed: 02/01/2023] Open
Abstract
Cell-penetrating peptides (CPPs) are naturally able to cross the lipid bilayer membrane that protects cells. These peptides share common structural and physicochemical properties and show different pharmaceutical applications, among which drug delivery is the most important. Due to their ability to cross the membranes by pulling high-molecular-weight polar molecules, they are termed Trojan horses. In this study, we proposed a machine learning (ML)-based framework named BChemRF-CPPred (beyond chemical rules-based framework for CPP prediction) that uses an artificial neural network, a support vector machine, and a Gaussian process classifier to differentiate CPPs from non-CPPs, using structure- and sequence-based descriptors extracted from PDB and FASTA formats. The performance of our algorithm was evaluated by tenfold cross-validation and compared with those of previously reported prediction tools using an independent dataset. The BChemRF-CPPred satisfactorily identified CPP-like structures using natural and synthetic modified peptide libraries and also obtained better performance than those of previously reported ML-based algorithms, reaching the independent test accuracy of 90.66% (AUC = 0.9365) for PDB, and an accuracy of 86.5% (AUC = 0.9216) for FASTA input. Moreover, our analyses of the CPP chemical space demonstrated that these peptides break some molecular rules related to the prediction of permeability of therapeutic molecules in cell membranes. This is the first comprehensive analysis to predict synthetic and natural CPP structures and to evaluate their chemical space using an ML-based framework. Our algorithm is freely available for academic use at http://comptools.linc.ufpa.br/BChemRF-CPPred .
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6
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Blay V, Li MC, Ho SP, Stoller ML, Hsieh HP, Houston DR. Design of drug-like hepsin inhibitors against prostate cancer and kidney stones. Acta Pharm Sin B 2020; 10:1309-1320. [PMID: 32874830 PMCID: PMC7452031 DOI: 10.1016/j.apsb.2019.09.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 08/24/2019] [Accepted: 09/23/2019] [Indexed: 12/30/2022] Open
Abstract
Hepsin, a transmembrane serine protease abundant in renal endothelial cells, is a promising therapeutic target against several cancers, particularly prostate cancer. It is involved in the release and polymerization of uromodulin in the urine, which plays a role in kidney stone formation. In this work, we design new potential hepsin inhibitors for high activity, improved specificity towards hepsin, and promising ADMET properties. The ligands were developed in silico through a novel hierarchical pipeline. This pipeline explicitly accounts for off-target binding to the related serine proteases matriptase and HGFA (human hepatocyte growth factor activator). We completed the pipeline incorporating ADMET properties of the candidate inhibitors into custom multi-objective optimization functions. The ligands designed show excellent prospects for targeting hepsin via the blood stream and the urine and thus enable key experimental studies. The computational pipeline proposed is remarkably cost-efficient and can be easily adapted for designing inhibitors against new drug targets.
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Affiliation(s)
- Vincent Blay
- Division of Biomaterials and Bioengineering, School of Dentistry, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Urology, School of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
- Corresponding author. Tel.: +1 415 5142818.
| | - Mu-Chun Li
- Institute of Biotechnology and Pharmaceutical Research, National Health Research Institutes, Zhunan, Taiwan 350, China
| | - Sunita P. Ho
- Division of Biomaterials and Bioengineering, School of Dentistry, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Urology, School of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - Mashall L. Stoller
- Division of Biomaterials and Bioengineering, School of Dentistry, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Urology, School of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - Hsing-Pang Hsieh
- Institute of Biotechnology and Pharmaceutical Research, National Health Research Institutes, Zhunan, Taiwan 350, China
| | - Douglas R. Houston
- University of Edinburgh, Institute of Quantitative Biology, Biochemistry and Biotechnology, Edinburgh, Scotland, EH9 3BF, UK
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7
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Kumar A, Zhang KYJ. Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery. Front Chem 2018; 6:315. [PMID: 30090808 PMCID: PMC6068280 DOI: 10.3389/fchem.2018.00315] [Citation(s) in RCA: 93] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 07/09/2018] [Indexed: 12/21/2022] Open
Abstract
Molecular similarity is a key concept in drug discovery. It is based on the assumption that structurally similar molecules frequently have similar properties. Assessment of similarity between small molecules has been highly effective in the discovery and development of various drugs. Especially, two-dimensional (2D) similarity approaches have been quite popular due to their simplicity, accuracy and efficiency. Recently, the focus has been shifted toward the development of methods involving the representation and comparison of three-dimensional (3D) conformation of small molecules. Among the 3D similarity methods, evaluation of shape similarity is now gaining attention for its application not only in virtual screening but also in molecular target prediction, drug repurposing and scaffold hopping. A wide range of methods have been developed to describe molecular shape and to determine the shape similarity between small molecules. The most widely used methods include atom distance-based methods, surface-based approaches such as spherical harmonics and 3D Zernike descriptors, atom-centered Gaussian overlay based representations. Several of these methods demonstrated excellent virtual screening performance not only retrospectively but also prospectively. In addition to methods assessing the similarity between small molecules, shape similarity approaches have been developed to compare shapes of protein structures and binding pockets. Additionally, shape comparisons between atomic models and 3D density maps allowed the fitting of atomic models into cryo-electron microscopy maps. This review aims to summarize the methodological advances in shape similarity assessment highlighting advantages, disadvantages and their application in drug discovery.
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Affiliation(s)
| | - Kam Y. J. Zhang
- Laboratory for Structural Bioinformatics, Center for Biosystems Dynamics Research, RIKEN, Yokohama, Japan
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8
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Velazquez HA, Riccardi D, Xiao Z, Quarles LD, Yates CR, Baudry J, Smith JC. Ensemble docking to difficult targets in early-stage drug discovery: Methodology and application to fibroblast growth factor 23. Chem Biol Drug Des 2018; 91:491-504. [PMID: 28944571 PMCID: PMC7983124 DOI: 10.1111/cbdd.13110] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Revised: 08/30/2017] [Accepted: 09/02/2017] [Indexed: 12/23/2022]
Abstract
Ensemble docking is now commonly used in early-stage in silico drug discovery and can be used to attack difficult problems such as finding lead compounds which can disrupt protein-protein interactions. We give an example of this methodology here, as applied to fibroblast growth factor 23 (FGF23), a protein hormone that is responsible for regulating phosphate homeostasis. The first small-molecule antagonists of FGF23 were recently discovered by combining ensemble docking with extensive experimental target validation data (Science Signaling, 9, 2016, ra113). Here, we provide a detailed account of how ensemble-based high-throughput virtual screening was used to identify the antagonist compounds discovered in reference (Science Signaling, 9, 2016, ra113). Moreover, we perform further calculations, redocking those antagonist compounds identified in reference (Science Signaling, 9, 2016, ra113) that performed well on drug-likeness filters, to predict possible binding regions. These predicted binding modes are rescored with the molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) approach to calculate the most likely binding site. Our findings suggest that the antagonist compounds antagonize FGF23 through the disruption of protein-protein interactions between FGF23 and fibroblast growth factor receptor (FGFR).
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Affiliation(s)
- Hector A. Velazquez
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, TN, USA
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
| | - Demian Riccardi
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, TN, USA
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
| | - Zhousheng Xiao
- Department of Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Leigh Darryl Quarles
- Department of Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Charless Ryan Yates
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Jerome Baudry
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, TN, USA
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
| | - Jeremy C. Smith
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, TN, USA
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
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9
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Law S, Panwar P, Li J, Aguda AH, Jamroz A, Guido RVC, Brömme D. A composite docking approach for the identification and characterization of ectosteric inhibitors of cathepsin K. PLoS One 2017; 12:e0186869. [PMID: 29088253 PMCID: PMC5663397 DOI: 10.1371/journal.pone.0186869] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Accepted: 10/09/2017] [Indexed: 12/26/2022] Open
Abstract
Cathepsin K (CatK) is a cysteine protease that plays an important role in mammalian intra- and extracellular protein turnover and is known for its unique and potent collagenase activity. Through studies on the mechanism of its collagenase activity, selective ectosteric sites were identified that are remote from the active site. Inhibitors targeting these ectosteric sites are collagenase selective and do not interfere with other proteolytic activities of the enzyme. Potential ectosteric inhibitors were identified using a computational approach to screen the druggable subset of and the entire 281,987 compounds comprising Chemical Repository library of the National Cancer Institute-Developmental Therapeutics Program (NCI-DTP). Compounds were scored based on their affinity for the ectosteric site. Here we compared the scores of three individual molecular docking methods with that of a composite score of all three methods together. The composite docking method was up to five-fold more effective at identifying potent collagenase inhibitors (IC50 < 20 μM) than the individual methods. Of 160 top compounds tested in enzymatic assays, 28 compounds revealed blocking of the collagenase activity of CatK at 100 μM. Two compounds exhibited IC50 values below 5 μM corresponding to a molar protease:inhibitor concentration of <1:12. Both compounds were subsequently tested in osteoclast bone resorption assays where the most potent inhibitor, 10-[2-[bis(2-hydroxyethyl)amino]ethyl]-7,8-diethylbenzo[g]pteridine-2,4-dione, (NSC-374902), displayed an inhibition of bone resorption with an IC50-value of approximately 300 nM and no cell toxicity effects.
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Affiliation(s)
- Simon Law
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
- Centre for Blood Research, University of British Columbia, Vancouver, British Columbia, Canada
| | - Preety Panwar
- Centre for Blood Research, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Oral Biological and Medical Sciences, Faculty of Dentistry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Jody Li
- Centre for Blood Research, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Oral Biological and Medical Sciences, Faculty of Dentistry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Adeleke H. Aguda
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Andrew Jamroz
- Centre for Blood Research, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Oral Biological and Medical Sciences, Faculty of Dentistry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Rafael V. C. Guido
- Centro de Inovação em Biodiversidade e Fármacos, Instituto de Física de São Carlos, Universidade de São Paulo, São Carlos, Brazil
| | - Dieter Brömme
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
- Centre for Blood Research, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Oral Biological and Medical Sciences, Faculty of Dentistry, University of British Columbia, Vancouver, British Columbia, Canada
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10
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Xu D, Si Y, Meroueh SO. A Computational Investigation of Small-Molecule Engagement of Hot Spots at Protein-Protein Interaction Interfaces. J Chem Inf Model 2017; 57:2250-2272. [PMID: 28766941 DOI: 10.1021/acs.jcim.7b00181] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The binding affinity of a protein-protein interaction is concentrated at amino acids known as hot spots. It has been suggested that small molecules disrupt protein-protein interactions by either (i) engaging receptor protein hot spots or (ii) mimicking hot spots of the protein ligand. Yet, no systematic studies have been done to explore how effectively existing small-molecule protein-protein interaction inhibitors mimic or engage hot spots at protein interfaces. Here, we employ explicit-solvent molecular dynamics simulations and end-point MM-GBSA free energy calculations to explore this question. We select 36 compounds for which high-quality binding affinity and cocrystal structures are available. Five complexes that belong to three classes of protein-protein interactions (primary, secondary, and tertiary) were considered, namely, BRD4•H4, XIAP•Smac, MDM2•p53, Bcl-xL•Bak, and IL-2•IL-2Rα. Computational alanine scanning using MM-GBSA identified hot-spot residues at the interface of these protein interactions. Decomposition energies compared the interaction of small molecules with individual receptor hot spots to those of the native protein ligand. Pharmacophore analysis was used to investigate how effectively small molecules mimic the position of hot spots of the protein ligand. Finally, we study whether small molecules mimic the effects of the native protein ligand on the receptor dynamics. Our results show that, in general, existing small-molecule inhibitors of protein-protein interactions do not optimally mimic protein-ligand hot spots, nor do they effectively engage protein receptor hot spots. The more effective use of hot spots in future drug design efforts may result in smaller compounds with higher ligand efficiencies that may lead to greater success in clinical trials.
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Affiliation(s)
- David Xu
- Department of BioHealth Informatics, Indiana University School of Informatics and Computing , Indianapolis, Indiana 46202, United States
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11
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Chen R, Zhou J, Qin L, Chen Y, Huang Y, Liu H, Su Z. A Fusion Protein of the p53 Transaction Domain and the p53-Binding Domain of the Oncoprotein MdmX as an Efficient System for High-Throughput Screening of MdmX Inhibitors. Biochemistry 2017; 56:3273-3282. [DOI: 10.1021/acs.biochem.7b00085] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Rong Chen
- Institute
of Biomedical and Pharmaceutical Sciences and Key Laboratory of Industrial
Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, Hubei 430068, China
| | - Jingjing Zhou
- Institute
of Biomedical and Pharmaceutical Sciences and Key Laboratory of Industrial
Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, Hubei 430068, China
| | - Lingyun Qin
- Institute
of Biomedical and Pharmaceutical Sciences and Key Laboratory of Industrial
Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, Hubei 430068, China
| | - Yao Chen
- Institute
of Biomedical and Pharmaceutical Sciences and Key Laboratory of Industrial
Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, Hubei 430068, China
| | - Yongqi Huang
- Institute
of Biomedical and Pharmaceutical Sciences and Key Laboratory of Industrial
Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, Hubei 430068, China
| | - Huili Liu
- National
Center for Magnetic Resonance in Wuhan, State Key Laboratory of Magnetic
Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics
and Mathematics, Chinese Academy of Sciences, Wuhan, Hubei 430071, China
| | - Zhengding Su
- Institute
of Biomedical and Pharmaceutical Sciences and Key Laboratory of Industrial
Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, Hubei 430068, China
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12
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Dashti H, Westler WM, Markley JL, Eghbalnia HR. Unique identifiers for small molecules enable rigorous labeling of their atoms. Sci Data 2017; 4:170073. [PMID: 28534867 PMCID: PMC5441290 DOI: 10.1038/sdata.2017.73] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2017] [Accepted: 04/28/2017] [Indexed: 11/09/2022] Open
Abstract
Rigorous characterization of small organic molecules in terms of their structural and biological properties is vital to biomedical research. The three-dimensional structure of a molecule, its 'photo ID', is inefficient for searching and matching tasks. Instead, identifiers play a key role in accessing compound data. Unique and reproducible molecule and atom identifiers are required to ensure the correct cross-referencing of properties associated with compounds archived in databases. The best approach to this requirement is the International Chemical Identifier (InChI). However, the current implementation of InChI fails to provide a complete standard for atom nomenclature, and incorrect use of the InChI standard has resulted in the proliferation of non-unique identifiers. We propose a methodology and associated software tools, named ALATIS, that overcomes these shortcomings. ALATIS is an adaptation of InChI, which operates fully within the InChI convention to provide unique and reproducible molecule and all atom identifiers. ALATIS includes an InChI extension for unique atom labeling of symmetric molecules. ALATIS forms the basis for improving reproducibility and unifying cross-referencing across databases.
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Affiliation(s)
- Hesam Dashti
- National Magnetic Resonance Facility at Madison, Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - William M Westler
- National Magnetic Resonance Facility at Madison, Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - John L Markley
- National Magnetic Resonance Facility at Madison, Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Hamid R Eghbalnia
- National Magnetic Resonance Facility at Madison, Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
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Li H, Leung KS, Wong MH, Ballester PJ. USR-VS: a web server for large-scale prospective virtual screening using ultrafast shape recognition techniques. Nucleic Acids Res 2016; 44:W436-41. [PMID: 27106057 PMCID: PMC4987897 DOI: 10.1093/nar/gkw320] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2016] [Accepted: 04/06/2016] [Indexed: 12/12/2022] Open
Abstract
Ligand-based Virtual Screening (VS) methods aim at identifying molecules with a similar activity profile across phenotypic and macromolecular targets to that of a query molecule used as search template. VS using 3D similarity methods have the advantage of biasing this search toward active molecules with innovative chemical scaffolds, which are highly sought after in drug design to provide novel leads with improved properties over the query molecule (e.g. patentable, of lower toxicity or increased potency). Ultrafast Shape Recognition (USR) has demonstrated excellent performance in the discovery of molecules with previously-unknown phenotypic or target activity, with retrospective studies suggesting that its pharmacophoric extension (USRCAT) should obtain even better hit rates once it is used prospectively. Here we present USR-VS (http://usr.marseille.inserm.fr/), the first web server using these two validated ligand-based 3D methods for large-scale prospective VS. In about 2 s, 93.9 million 3D conformers, expanded from 23.1 million purchasable molecules, are screened and the 100 most similar molecules among them in terms of 3D shape and pharmacophoric properties are shown. USR-VS functionality also provides interactive visualization of the similarity of the query molecule against the hit molecules as well as vendor information to purchase selected hits in order to be experimentally tested.
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Affiliation(s)
- Hongjian Li
- Institute of Future Cities, Chinese University of Hong Kong, Hong Kong
| | - Kwong-S Leung
- Department of Computer Science and Engineering, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong
| | - Man-H Wong
- Department of Computer Science and Engineering, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong
| | - Pedro J Ballester
- Cancer Research Center of Marseille, INSERM U1068, 13009-Marseille, France
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