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Yu D, Du J, He P, Wang N, Li L, Liu Y, Yang C, Xu H, Li Y. Identification of natural xanthine oxidase inhibitors: Virtual screening, anti-xanthine oxidase activity, and interaction mechanism. Int J Biol Macromol 2024; 259:129286. [PMID: 38216015 DOI: 10.1016/j.ijbiomac.2024.129286] [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: 09/05/2023] [Revised: 01/04/2024] [Accepted: 01/04/2024] [Indexed: 01/14/2024]
Abstract
Xanthine oxidase (XO) is a crucial target for hyperuricemia treatment(s). Naturally occurred XO inhibitors with minimal toxicity and high efficacy have attracted researchers' attention. With the goal of quickly identifying natural XO inhibitors, an integrated computational screening strategy was constructed by molecular docking and calculating the free energy of binding. Twenty-seven hits were achieved from a database containing 19,377 natural molecules. This includes fourteen known XO inhibitors and four firstly-reported inhibitors (isolicoflavonol, 5,7-dihydroxycoumarin, parvifolol D and clauszoline M, IC50 < 40 μM). Iolicoflavonol (hit 8, IC50 = 8.45 ± 0.68 μM) and 5,7-dihydroxycoumarin (hit 25, IC50 = 10.91 ± 0.71 μM) displayed the great potency as mixed-type inhibitors. Docking study and molecular dynamics simulation revealed that both hits could interact with XO's primarily active site residues ARG880, MOS1328, and ASN768 of XO. Fluorescence spectroscopy studies showed that hit 8 bound to the active cavity region of XO, causing changes in XO's conformation and hydrophobicity. Hits 8 and 25 exhibit favorable Absorption, Distribution, Metabolism, and Excretion (ADME) properties. Additionally, no cytotoxicity against human liver cells was observed at their median inhibition concentrations against XO. Therefore, the present study offers isolicoflavonol and 5,7-dihydroxycoumarin with the potential to be disease-modifying agents for hyperuricemia.
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Affiliation(s)
- Dehong Yu
- School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Jiana Du
- School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Pei He
- School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Na Wang
- School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Lizi Li
- School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Yi Liu
- School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Can Yang
- School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Haiqi Xu
- School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Yanfang Li
- School of Chemical Engineering, Sichuan University, Chengdu 610065, China.
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2
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Tinivella A, Pinzi L, Rastelli G. Prediction of activity and selectivity profiles of human Carbonic Anhydrase inhibitors using machine learning classification models. J Cheminform 2021; 13:18. [PMID: 33676550 PMCID: PMC7937250 DOI: 10.1186/s13321-021-00499-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 02/22/2021] [Indexed: 11/23/2022] Open
Abstract
The development of selective inhibitors of the clinically relevant human Carbonic Anhydrase (hCA) isoforms IX and XII has become a major topic in drug research, due to their deregulation in several types of cancer. Indeed, the selective inhibition of these two isoforms, especially with respect to the homeostatic isoform II, holds great promise to develop anticancer drugs with limited side effects. Therefore, the development of in silico models able to predict the activity and selectivity against the desired isoform(s) is of central interest. In this work, we have developed a series of machine learning classification models, trained on high confidence data extracted from ChEMBL, able to predict the activity and selectivity profiles of ligands for human Carbonic Anhydrase isoforms II, IX and XII. The training datasets were built with a procedure that made use of flexible bioactivity thresholds to obtain well-balanced active and inactive classes. We used multiple algorithms and sampling sizes to finally select activity models able to classify active or inactive molecules with excellent performances. Remarkably, the results herein reported turned out to be better than those obtained by models built with the classic approach of selecting an a priori activity threshold. The sequential application of such validated models enables virtual screening to be performed in a fast and more reliable way to predict the activity and selectivity profiles against the investigated isoforms.
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Affiliation(s)
- Annachiara Tinivella
- Department of Life Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi 103, 41125, Modena, Italy.,Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia, Modena, Italy
| | - Luca Pinzi
- Department of Life Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi 103, 41125, Modena, Italy
| | - Giulio Rastelli
- Department of Life Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi 103, 41125, Modena, Italy.
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3
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Abstract
Background:
Molecular docking is probably the most popular and profitable approach in
computer-aided drug design, being the staple technique for predicting the binding mode of bioactive
compounds and for performing receptor-based virtual screening studies. The growing attention received
by docking, as well as the need for improving its reliability in pose prediction and virtual screening
performance, has led to the development of a wide plethora of new docking algorithms and scoring
functions. Nevertheless, it is unlikely to identify a single procedure outperforming the other ones in
terms of reliability and accuracy or demonstrating to be generally suitable for all kinds of protein targets.
Methods:
In this context, consensus docking approaches are taking hold in computer-aided drug design.
These computational protocols consist in docking ligands using multiple docking methods and then
comparing the binding poses predicted for the same ligand by the different methods. This analysis is
usually carried out calculating the root-mean-square deviation among the different docking results obtained
for each ligand, in order to identify the number of docking methods producing the same binding
pose.
Results:
The consensus docking approaches demonstrated to improve the quality of docking and virtual
screening results compared to the single docking methods. From a qualitative point of view, the improvement
in pose prediction accuracy was obtained by prioritizing ligand binding poses produced by a
high number of docking methods, whereas with regards to virtual screening studies, high hit rates were
obtained by prioritizing the compounds showing a high level of pose consensus.
Conclusion:
In this review, we provide an overview of the results obtained from the performance assessment
of various consensus docking protocols and we illustrate successful case studies where consensus
docking has been applied in virtual screening studies.
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Affiliation(s)
- Giulio Poli
- Department of Pharmacy, University of Pisa, Pisa, Italy
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4
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Poli G, Granchi C, Rizzolio F, Tuccinardi T. Application of MM-PBSA Methods in Virtual Screening. Molecules 2020; 25:molecules25081971. [PMID: 32340232 PMCID: PMC7221544 DOI: 10.3390/molecules25081971] [Citation(s) in RCA: 96] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 04/17/2020] [Accepted: 04/21/2020] [Indexed: 12/17/2022] Open
Abstract
Computer-aided drug design techniques are today largely applied in medicinal chemistry. In particular, receptor-based virtual screening (VS) studies, in which molecular docking represents the gold standard in silico approach, constitute a powerful strategy for identifying novel hit compounds active against the desired target receptor. Nevertheless, the need for improving the ability of docking in discriminating true active ligands from inactive compounds, thus boosting VS hit rates, is still pressing. In this context, the use of binding free energy evaluation approaches can represent a profitable tool for rescoring ligand-protein complexes predicted by docking based on more reliable estimations of ligand-protein binding affinities than those obtained with simple scoring functions. In the present review, we focused our attention on the Molecular Mechanics-Poisson Boltzman Surface Area (MM-PBSA) method for the calculation of binding free energies and its application in VS studies. We provided examples of successful applications of this method in VS campaigns and evaluation studies in which the reliability of this approach has been assessed, thus providing useful guidelines for employing this approach in VS.
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Affiliation(s)
- Giulio Poli
- Department of Pharmacy, University of Pisa, 56126 Pisa, Italy; (G.P.); (C.G.)
| | - Carlotta Granchi
- Department of Pharmacy, University of Pisa, 56126 Pisa, Italy; (G.P.); (C.G.)
| | - Flavio Rizzolio
- Department of Molecular science and Nanosystems, University Ca’ Foscari of Venice, 30170 Venice, Italy;
- Pathology unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, 33081 Aviano, Italy
| | - Tiziano Tuccinardi
- Department of Pharmacy, University of Pisa, 56126 Pisa, Italy; (G.P.); (C.G.)
- Correspondence: ; Tel.: +39-0502219595
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5
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Poli G, Galati S, Martinelli A, Supuran CT, Tuccinardi T. Development of a cheminformatics platform for selectivity analyses of carbonic anhydrase inhibitors. J Enzyme Inhib Med Chem 2020; 35:365-371. [PMID: 31854205 PMCID: PMC6968703 DOI: 10.1080/14756366.2019.1705291] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
The selectivity for a specific human Carbonic Anhydrase (hCA) isoform is an important property a hCA inhibitor (CAI) should be endowed with, in order to constitute a valuable therapeutic tool for the treatment of a desired pathology. In this context, we developed a chemoinformatic platform that allows the analysis of the structure and selectivity profile of known CAIs reported in literature, with the aim of identifying structural motifs connected to ligand selectivity, thus providing useful guidelines for the design of novel ligands selective for the desired hCA isoform. The platform is able to perform ultrafast structure and selectivity analyses through ligand fingerprint similarity, with no need of structural information about the target receptor and ligands' binding mode. It is easily accessible to the non-expert user through the implementation of a KNIME Analytic Platform workflow and could be extended to analyze the selectivity profile of known ligands of different target proteins.
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Affiliation(s)
- Giulio Poli
- Department of Pharmacy, University of Pisa, Pisa, Italy
| | | | | | - Claudiu T Supuran
- NEUROFARBA Department, Sezione di Scienze Farmaceutiche, Università degli Studi di Firenze, Florence, Italy
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6
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Russo Spena C, De Stefano L, Poli G, Granchi C, El Boustani M, Ecca F, Grassi G, Grassi M, Canzonieri V, Giordano A, Tuccinardi T, Caligiuri I, Rizzolio F. Virtual screening identifies a PIN1 inhibitor with possible antiovarian cancer effects. J Cell Physiol 2019; 234:15708-15716. [PMID: 30697729 DOI: 10.1002/jcp.28224] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 01/10/2019] [Indexed: 02/06/2023]
Abstract
Peptidyl-prolyl cis-trans isomerase, NIMA-interacting 1 (PIN1) is a peptidyl-prolyl isomerase that binds phospho-Ser/Thr-Pro motifs in proteins and catalyzes the cis-trans isomerization of proline peptide bonds. PIN1 is overexpressed in several cancers including high-grade serous ovarian cancer. Since few therapies are effective against this cancer, PIN1 could be a therapeutic target but effective PIN1 inhibitors are lacking. To identify molecules with in vivo inhibitory effects on PIN1, we used consensus docking to model existing PIN1-ligand X-ray structures and to screen a chemical database for candidate inhibitors. Ten molecules were selected and tested in cellular assays, leading to the identification of VS10 that bound and inhibited PIN1. VS10 treatment reduced the viability of ovarian cancer cell lines by inducing proteasomal PIN1 degradation, without effects on PIN1 transcription, and also reduced the levels of downstream targets β-catenin, cyclin D1, and pSer473-Akt. VS10 is a selective PIN1 inhibitor that may offer new opportunities for treating PIN1-overexpressing tumors.
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Affiliation(s)
- Concetta Russo Spena
- Pathology Unit, IRCCS CRO Aviano-National Cancer Institute, Aviano, Italy.,Doctoral School in Chemistry, University of Trieste, Trieste, Italy
| | - Lucia De Stefano
- Pathology Unit, IRCCS CRO Aviano-National Cancer Institute, Aviano, Italy.,Doctoral School in Chemistry, University of Trieste, Trieste, Italy
| | - Giulio Poli
- Department of Pharmacy, University of Pisa, Pisa, Italy
| | | | - Maguie El Boustani
- Pathology Unit, IRCCS CRO Aviano-National Cancer Institute, Aviano, Italy.,Doctoral School in Molecular Biomedicine, University of Trieste, Trieste, Italy
| | - Fabrizio Ecca
- Experimental and Clinical Pharmacology Unit, IRCCS CRO Aviano-National Cancer Institute, Aviano, Italy
| | - Gabriele Grassi
- Department of Life Sciences, Cattinara University Hospital, University of Trieste, Trieste, Italy
| | - Mario Grassi
- Department of Engineering and Architecture, University of Trieste, Trieste, Italy
| | - Vincenzo Canzonieri
- Pathology Unit, IRCCS CRO Aviano-National Cancer Institute, Aviano, Italy.,Center for Biotechnology, Sbarro Institute for Cancer Research and Molecular Medicine, College of Science and Technology, Temple University, Philadelphia, Pennsylvania.,Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
| | - Antonio Giordano
- Center for Biotechnology, Sbarro Institute for Cancer Research and Molecular Medicine, College of Science and Technology, Temple University, Philadelphia, Pennsylvania
| | - Tiziano Tuccinardi
- Department of Pharmacy, University of Pisa, Pisa, Italy.,Center for Biotechnology, Sbarro Institute for Cancer Research and Molecular Medicine, College of Science and Technology, Temple University, Philadelphia, Pennsylvania
| | - Isabella Caligiuri
- Pathology Unit, IRCCS CRO Aviano-National Cancer Institute, Aviano, Italy
| | - Flavio Rizzolio
- Pathology Unit, IRCCS CRO Aviano-National Cancer Institute, Aviano, Italy.,Center for Biotechnology, Sbarro Institute for Cancer Research and Molecular Medicine, College of Science and Technology, Temple University, Philadelphia, Pennsylvania.,Department of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, Venezia-Mestre, Italy
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7
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Li J, Fu A, Zhang L. An Overview of Scoring Functions Used for Protein-Ligand Interactions in Molecular Docking. Interdiscip Sci 2019; 11:320-328. [PMID: 30877639 DOI: 10.1007/s12539-019-00327-w] [Citation(s) in RCA: 178] [Impact Index Per Article: 35.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2018] [Revised: 02/06/2019] [Accepted: 03/06/2019] [Indexed: 12/17/2022]
Abstract
Currently, molecular docking is becoming a key tool in drug discovery and molecular modeling applications. The reliability of molecular docking depends on the accuracy of the adopted scoring function, which can guide and determine the ligand poses when thousands of possible poses of ligand are generated. The scoring function can be used to determine the binding mode and site of a ligand, predict binding affinity and identify the potential drug leads for a given protein target. Despite intensive research over the years, accurate and rapid prediction of protein-ligand interactions is still a challenge in molecular docking. For this reason, this study reviews four basic types of scoring functions, physics-based, empirical, knowledge-based, and machine learning-based scoring functions, based on an up-to-date classification scheme. We not only discuss the foundations of the four types scoring functions, suitable application areas and shortcomings, but also discuss challenges and potential future study directions.
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Affiliation(s)
- Jin Li
- College of Computer and Information Science, Southwest University, Chongqing, 400715, China.,School of Medical Information and Engineering, Southwest Medical University, Luzhou, 646000, China
| | - Ailing Fu
- College of Pharmaceutical Sciences, Southwest University, Chongqing, 400715, China
| | - Le Zhang
- College of Computer and Information Science, Southwest University, Chongqing, 400715, China. .,College of Computer Science, Sichuan University, Chengdu, 610065, China. .,Medical Big Data Center, Sichuan University, Chengdu, 610065, China. .,Zdmedical, Information Polytron Technologies Inc Chongqing, Chongqing, 401320, China.
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8
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Buran K, Bua S, Poli G, Önen Bayram FE, Tuccinardi T, Supuran CT. Novel 8-Substituted Coumarins That Selectively Inhibit Human Carbonic Anhydrase IX and XII. Int J Mol Sci 2019; 20:ijms20051208. [PMID: 30857344 PMCID: PMC6429297 DOI: 10.3390/ijms20051208] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 03/04/2019] [Accepted: 03/06/2019] [Indexed: 11/16/2022] Open
Abstract
A novel series of 8-substituted coumarin-based compounds, characterized by the presence of alkylpiperazine and arylpiperazine chains, were synthesized and tested for their inhibitory activity against four human carbonic anhydrase (hCA) isoforms. All compounds displayed nanomolar potency against the cancer-related hCA IX and hCA XII; moreover, they were shown to be devoid of any inhibitory activity toward the cytosolic hCA I and hCA II up to 10 µM concentration in the assay system. Therefore, the synthesized coumarin ligands demonstrated to be potent and selective hCA IX/XII inhibitors, and were shown to be as potent as the reference inhibitor acetazolamide against hCA XII, with single-digit nanomolar Ki values. Molecular modeling studies provided a rationale for explaining the selectivity profile of these non-classic hCA inhibitors and their interactions with the enzymes, according to their specific mechanism of action, thus paving the way for future structure-based lead optimization studies.
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Affiliation(s)
- Kerem Buran
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Yeditepe University, Kayisdagi Cad., 34755 Istanbul, Turkey.
| | - Silvia Bua
- NEUROFARBA Department, Pharmaceutical and Nutraceutical Section, University of Florence, 50019 Sesto Fiorentino, Italy.
| | - Giulio Poli
- Department of Pharmacy, University of Pisa, 56126 Pisa, Italy.
| | - F Esra Önen Bayram
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Yeditepe University, Kayisdagi Cad., 34755 Istanbul, Turkey.
| | | | - Claudiu T Supuran
- NEUROFARBA Department, Pharmaceutical and Nutraceutical Section, University of Florence, 50019 Sesto Fiorentino, Italy.
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9
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Poli G, Lapillo M, Jha V, Mouawad N, Caligiuri I, Macchia M, Minutolo F, Rizzolio F, Tuccinardi T, Granchi C. Computationally driven discovery of phenyl(piperazin-1-yl)methanone derivatives as reversible monoacylglycerol lipase (MAGL) inhibitors. J Enzyme Inhib Med Chem 2019; 34:589-596. [PMID: 30696302 PMCID: PMC6352951 DOI: 10.1080/14756366.2019.1571271] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
Abstract
Monoacylglycerol lipase (MAGL) is an attractive therapeutic target for many pathologies, including neurodegenerative diseases, cancer as well as chronic pain and inflammatory pathologies. The identification of reversible MAGL inhibitors, devoid of the side effects associated to prolonged MAGL inactivation, is a hot topic in medicinal chemistry. In this study, a novel phenyl(piperazin-1-yl)methanone inhibitor of MAGL was identified through a virtual screening protocol based on a fingerprint-driven consensus docking (CD) approach. Molecular modeling and preliminary structure-based hit optimization studies allowed the discovery of derivative 4, which showed an efficient reversible MAGL inhibition (IC50 = 6.1 µM) and a promising antiproliferative activity on breast and ovarian cancer cell lines (IC50 of 31-72 µM), thus representing a lead for the development of new and more potent reversible MAGL inhibitors. Moreover, the obtained results confirmed the reliability of the fingerprint-driven CD approach herein developed.
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Affiliation(s)
- Giulio Poli
- a Department of Pharmacy , University of Pisa , Pisa , Italy
| | | | - Vibhu Jha
- a Department of Pharmacy , University of Pisa , Pisa , Italy
| | - Nayla Mouawad
- a Department of Pharmacy , University of Pisa , Pisa , Italy.,b Pathology Unit, Department of Molecular Biology and Translational Research , National Cancer Institute and Center for Molecular Biomedicine , Aviano , Italy
| | - Isabella Caligiuri
- b Pathology Unit, Department of Molecular Biology and Translational Research , National Cancer Institute and Center for Molecular Biomedicine , Aviano , Italy
| | - Marco Macchia
- a Department of Pharmacy , University of Pisa , Pisa , Italy
| | | | - Flavio Rizzolio
- b Pathology Unit, Department of Molecular Biology and Translational Research , National Cancer Institute and Center for Molecular Biomedicine , Aviano , Italy.,c Department of Molecular Science and Nanosystems , Ca' Foscari Università di Venezia , Venezia , Italy
| | | | - Carlotta Granchi
- a Department of Pharmacy , University of Pisa , Pisa , Italy.,d Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, College of Science and Technology, Temple University , Philadelphia , PA , USA
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10
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Žuvela P, Liu JJ, Yi M, Pomastowski PP, Sagandykova G, Belka M, David J, Bączek T, Szafrański K, Żołnowska B, Sławiński J, Supuran CT, Wong MW, Buszewski B. Target-based drug discovery through inversion of quantitative structure-drug-property relationships and molecular simulation: CA IX-sulphonamide complexes. J Enzyme Inhib Med Chem 2018; 33:1430-1443. [PMID: 30220229 PMCID: PMC6151961 DOI: 10.1080/14756366.2018.1511551] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
In this work, a target-based drug screening method is proposed exploiting the synergy effect of ligand-based and structure-based computer-assisted drug design. The new method provides great flexibility in drug design and drug candidates with considerably lower risk in an efficient manner. As a model system, 45 sulphonamides (33 training, 12 testing ligands) in complex with carbonic anhydrase IX were used for development of quantitative structure-activity-lipophilicity (property)-relationships (QSPRs). For each ligand, nearly 5,000 molecular descriptors were calculated, while lipophilicity (logkw) and inhibitory activity (logKi) were used as drug properties. Genetic algorithm-partial least squares (GA-PLS) provided a QSPR model with high prediction capability employing only seven molecular descriptors. As a proof-of-concept, optimal drug structure was obtained by inverting the model with respect to reference drug properties. 3509 ligands were ranked accordingly. Top 10 ligands were further validated through molecular docking. Large-scale MD simulations were performed to test the stability of structures of selected ligands obtained through docking complemented with biophysical experiments.
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Affiliation(s)
- Petar Žuvela
- a Department of Chemistry , National University of Singapore , Singapore.,b Department of Environmental Chemistry and Bioanalytics, Faculty of Chemistry , Nicolaus Copernicus University , Toruń , Poland
| | - J Jay Liu
- c Department of Chemical Engineering , Pukyong National University , Busan , Korea
| | - Myunggi Yi
- d Department of Biomedical Engineering , Pukyong National University , Busan , Korea
| | - Paweł P Pomastowski
- b Department of Environmental Chemistry and Bioanalytics, Faculty of Chemistry , Nicolaus Copernicus University , Toruń , Poland
| | - Gulyaim Sagandykova
- e Interdisciplinary Centre for Modern Technologies, Nicolaus Copernicus University , Toruń , Poland
| | - Mariusz Belka
- f Department of Pharmaceutical Chemistry , Medical University of Gdańsk , Gdańsk , Poland
| | - Jonathan David
- a Department of Chemistry , National University of Singapore , Singapore
| | - Tomasz Bączek
- f Department of Pharmaceutical Chemistry , Medical University of Gdańsk , Gdańsk , Poland
| | - Krzysztof Szafrański
- g Department of Organic Chemistry , Medical University of Gdańsk , Gdańsk , Poland
| | - Beata Żołnowska
- g Department of Organic Chemistry , Medical University of Gdańsk , Gdańsk , Poland
| | - Jarosław Sławiński
- g Department of Organic Chemistry , Medical University of Gdańsk , Gdańsk , Poland
| | - Claudiu T Supuran
- h Dipartimento di Chimica, Universita degli Studi di Firenze , Polo Scientifico, Laboratorio di Chimica Bioinorganica , Sesto Fiorentino (Florence) , Italy.,i NEUROFARBA Department, Sezione di Scienze Farmaceutiche , Università degli Studi di Firenze , Sesto Fiorentino (Florence) , Italy
| | - Ming Wah Wong
- a Department of Chemistry , National University of Singapore , Singapore
| | - Bogusław Buszewski
- b Department of Environmental Chemistry and Bioanalytics, Faculty of Chemistry , Nicolaus Copernicus University , Toruń , Poland.,e Interdisciplinary Centre for Modern Technologies, Nicolaus Copernicus University , Toruń , Poland
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