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Degiacomi G, Gianibbi B, Recchia D, Stelitano G, Truglio GI, Marra P, Stamilla A, Makarov V, Chiarelli LR, Manetti F, Pasca MR. CanB, a Druggable Cellular Target in Mycobacterium tuberculosis. ACS OMEGA 2023; 8:25209-25220. [PMID: 37483251 PMCID: PMC10357428 DOI: 10.1021/acsomega.3c02311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 06/05/2023] [Indexed: 07/25/2023]
Abstract
Treatment against tuberculosis can lead to the selection of drug-resistant Mycobacterium tuberculosis strains. To tackle this serious threat, new targets from M. tuberculosis are needed to develop novel effective drugs. In this work, we aimed to provide a possible workflow to validate new targets and inhibitors by combining genetic, in silico, and enzymological approaches. CanB is one of the three M. tuberculosis β-carbonic anhydrases that catalyze the reversible reaction of CO2 hydration to form HCO3- and H+. To this end, we precisely demonstrated that CanB is essential for the survival of the pathogen in vitro by constructing conditional mutants. In addition, to search for CanB inhibitors, conditional canB mutants were also constructed using the Pip-ON system. By molecular docking and minimum inhibitory concentration assays, we selected three molecules that inhibit the growth in vitro of M. tuberculosis wild-type strain and canB conditional mutants, thus implementing a target-to-drug approach. The lead compound also showed a bactericidal activity by the time-killing assay. We further studied the interactions of these molecules with CanB using enzymatic assays and differential scanning fluorimetry thermal shift analysis. In conclusion, the compounds identified by the in silico screening proved to have a high affinity as CanB ligands endowed with antitubercular activity.
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Affiliation(s)
- Giulia Degiacomi
- Department
of Biology and Biotechnology “Lazzaro Spallanzani”, University of Pavia, Pavia 27100, Italy
| | - Beatrice Gianibbi
- Department
of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena 53100, Italy
| | - Deborah Recchia
- Department
of Biology and Biotechnology “Lazzaro Spallanzani”, University of Pavia, Pavia 27100, Italy
| | - Giovanni Stelitano
- Department
of Biology and Biotechnology “Lazzaro Spallanzani”, University of Pavia, Pavia 27100, Italy
| | | | - Paola Marra
- Department
of Biology and Biotechnology “Lazzaro Spallanzani”, University of Pavia, Pavia 27100, Italy
| | - Alessandro Stamilla
- Department
of Biology and Biotechnology “Lazzaro Spallanzani”, University of Pavia, Pavia 27100, Italy
| | - Vadim Makarov
- Bakh
Institute of Biochemistry, Russian Academy
of Science, Moscow 119071, Russia
| | - Laurent Robert Chiarelli
- Department
of Biology and Biotechnology “Lazzaro Spallanzani”, University of Pavia, Pavia 27100, Italy
| | - Fabrizio Manetti
- Department
of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena 53100, Italy
| | - Maria Rosalia Pasca
- Department
of Biology and Biotechnology “Lazzaro Spallanzani”, University of Pavia, Pavia 27100, Italy
- Fondazione
IRCCS Policlinico San Matteo, Pavia 27100, Italy
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Zhou W, Fan Y, Cai X, Xiang Y, Jiang P, Dai Z, Chen Y, Tan S, Yuan Z. High-accuracy QSAR models of narcosis toxicities of phenols based on various data partition, descriptor selection and modelling methods. RSC Adv 2016. [DOI: 10.1039/c6ra21076g] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The environmental protection agency thinks that quantitative structure–activity relationship (QSAR) analysis can better replace toxicity tests.
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Affiliation(s)
- Wei Zhou
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests
- Hunan Agricultural University
- Changsha 410128
- P. R. China
- Hunan Provincial Key Laboratory of Crop Germplasm Innovation and Utilization
| | - Yanjun Fan
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests
- Hunan Agricultural University
- Changsha 410128
- P. R. China
| | - Xunhui Cai
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests
- Hunan Agricultural University
- Changsha 410128
- P. R. China
| | - Yan Xiang
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests
- Hunan Agricultural University
- Changsha 410128
- P. R. China
| | - Peng Jiang
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests
- Hunan Agricultural University
- Changsha 410128
- P. R. China
| | - Zhijun Dai
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests
- Hunan Agricultural University
- Changsha 410128
- P. R. China
| | - Yuan Chen
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests
- Hunan Agricultural University
- Changsha 410128
- P. R. China
| | - Siqiao Tan
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests
- Hunan Agricultural University
- Changsha 410128
- P. R. China
| | - Zheming Yuan
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests
- Hunan Agricultural University
- Changsha 410128
- P. R. China
- Hunan Provincial Key Laboratory of Crop Germplasm Innovation and Utilization
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Mammino L, Bilonda MK. Computational study of antimalarial pyrazole alkaloids from Newbouldia laevis. J Mol Model 2014; 20:2464. [DOI: 10.1007/s00894-014-2464-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2014] [Accepted: 09/07/2014] [Indexed: 11/27/2022]
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Zhang L, Fourches D, Sedykh A, Zhu H, Golbraikh A, Ekins S, Clark J, Connelly MC, Sigal M, Hodges D, Guiguemde A, Guy RK, Tropsha A. Discovery of novel antimalarial compounds enabled by QSAR-based virtual screening. J Chem Inf Model 2013; 53:475-92. [PMID: 23252936 DOI: 10.1021/ci300421n] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Quantitative structure-activity relationship (QSAR) models have been developed for a data set of 3133 compounds defined as either active or inactive against P. falciparum. Because the data set was strongly biased toward inactive compounds, different sampling approaches were employed to balance the ratio of actives versus inactives, and models were rigorously validated using both internal and external validation approaches. The balanced accuracy for assessing the antimalarial activities of 70 external compounds was between 87% and 100% depending on the approach used to balance the data set. Virtual screening of the ChemBridge database using QSAR models identified 176 putative antimalarial compounds that were submitted for experimental validation, along with 42 putative inactives as negative controls. Twenty five (14.2%) computational hits were found to have antimalarial activities with minimal cytotoxicity to mammalian cells, while all 42 putative inactives were confirmed experimentally. Structural inspection of confirmed active hits revealed novel chemical scaffolds, which could be employed as starting points to discover novel antimalarial agents.
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Affiliation(s)
- Liying Zhang
- The Laboratory for Molecular Modeling, Eshelman School of Pharmacy, CB# 7568, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
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Rescigno A, Casañola-Martin GM, Sanjust E, Zucca P, Marrero-Ponce Y. Vanilloid derivatives as tyrosinase inhibitors driven by virtual screening-based QSAR models. Drug Test Anal 2010; 3:176-81. [PMID: 21125547 DOI: 10.1002/dta.187] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2010] [Revised: 08/19/2010] [Accepted: 08/19/2010] [Indexed: 11/06/2022]
Abstract
A number of vanilloids have been tested as tyrosinase inhibitors using Ligand-Based Virtual Screening (LBVS) driven by QSAR (Quantitative Structure-Activity Relationship) models as the multi-agent classification system. A total of 81 models were used to screen this family. Then, a preliminary cluster analysis of the selected chemicals was carried out based on their bioactivity to detect possible similar substructural features among these compounds and the active database used in the QSAR model construction. The compounds identified were tested in vitro to corroborate the results obtained in silico. Among them, two chemicals, isovanillin (K(M) (app) = 1.08 mM) near to kojic acid (reference drug) in one cluster and isovanillyl alcohol (K(M) (app) = 0.88 mM) at the same distance as hydroquinone (reference drug) in another cluster showed inhibitory activity against tyrosinase. The algorithm proposed here could result in a suitable approach for faster and more effective identification of hit and/or lead compounds with tyrosinase inhibitory activity, helping to shorten the long pipeline in the research of novel depigmenting agents to treat skin disorders.
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Affiliation(s)
- Antonio Rescigno
- Dipartimento di Scienze e Tecnologie Biomediche, Università di Cagliari, Cittadella Universitaria, Monserrato (CA), Italy
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Ojha PK, Roy K. Chemometric modelling of antimalarial activity of aryltriazolylhydroxamates. MOLECULAR SIMULATION 2010. [DOI: 10.1080/08927022.2010.492835] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Carvalho AR, Melo A. Quantum Semiempirical Energy Based (SEEB) Descriptors Performance with Benzamidine Inhibitors of Trypsin. Mol Inform 2010; 29:525-31. [DOI: 10.1002/minf.201000024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2010] [Accepted: 05/04/2010] [Indexed: 11/09/2022]
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Roy K, Ojha PK. Advances in quantitative structure–activity relationship models of antimalarials. Expert Opin Drug Discov 2010; 5:751-78. [DOI: 10.1517/17460441.2010.497812] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Cruz-Monteagudo M, Borges F, Cordeiro MNDS. Desirability-based multiobjective optimization for global QSAR studies: application to the design of novel NSAIDs with improved analgesic, antiinflammatory, and ulcerogenic profiles. J Comput Chem 2008; 29:2445-59. [PMID: 18452123 DOI: 10.1002/jcc.20994] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Up to now, very few reports have been published concerning the application of multiobjective optimization (MOOP) techniques to quantitative structure-activity relationship (QSAR) studies. However, none reports the optimization of objectives related directly to the desired pharmaceutical profile of the drug. In this work, for the first time, it is proposed a MOOP method based on Derringer's desirability function that allows conducting global QSAR studies considering simultaneously the pharmacological, pharmacokinetic and toxicological profile of a set of molecule candidates. The usefulness of the method is demonstrated by applying it to the simultaneous optimization of the analgesic, antiinflammatory, and ulcerogenic properties of a library of fifteen 3-(3-methylphenyl)-2-substituted amino-3H-quinazolin-4-one compounds. The levels of the predictor variables producing concurrently the best possible compromise between these properties is found and used to design a set of new optimized drug candidates. Our results also suggest the relevant role of the bulkiness of alkyl substituents on the C-2 position of the quinazoline ring over the ulcerogenic properties for this family of compounds. Finally, and most importantly, the desirability-based MOOP method proposed is a valuable tool and shall aid in the future rational design of novel successful drugs.
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Affiliation(s)
- Maykel Cruz-Monteagudo
- Physico-Chemical Molecular Research Unit, Department of Organic Chemistry, Faculty of Pharmacy, University of Porto, 4150-047 Porto, Portugal.
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Cruz-Monteagudo M, Borges F, Cordeiro MNDS, Cagide Fajin JL, Morell C, Ruiz RM, Cañizares-Carmenate Y, Dominguez ER. Desirability-based methods of multiobjective optimization and ranking for global QSAR studies. Filtering safe and potent drug candidates from combinatorial libraries. ACTA ACUST UNITED AC 2008; 10:897-913. [PMID: 18855460 DOI: 10.1021/cc800115y] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Up to now, very few applications of multiobjective optimization (MOOP) techniques to quantitative structure-activity relationship (QSAR) studies have been reported in the literature. However, none of them report the optimization of objectives related directly to the final pharmaceutical profile of a drug. In this paper, a MOOP method based on Derringer's desirability function that allows conducting global QSAR studies, simultaneously considering the potency, bioavailability, and safety of a set of drug candidates, is introduced. The results of the desirability-based MOOP (the levels of the predictor variables concurrently producing the best possible compromise between the properties determining an optimal drug candidate) are used for the implementation of a ranking method that is also based on the application of desirability functions. This method allows ranking drug candidates with unknown pharmaceutical properties from combinatorial libraries according to the degree of similarity with the previously determined optimal candidate. Application of this method will make it possible to filter the most promising drug candidates of a library (the best-ranked candidates), which should have the best pharmaceutical profile (the best compromise between potency, safety and bioavailability). In addition, a validation method of the ranking process, as well as a quantitative measure of the quality of a ranking, the ranking quality index (Psi), is proposed. The usefulness of the desirability-based methods of MOOP and ranking is demonstrated by its application to a library of 95 fluoroquinolones, reporting their gram-negative antibacterial activity and mammalian cell cytotoxicity. Finally, the combined use of the desirability-based methods of MOOP and ranking proposed here seems to be a valuable tool for rational drug discovery and development.
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Affiliation(s)
- Maykel Cruz-Monteagudo
- Physico-Chemical Molecular Research Unit, Department of Organic Chemistry, Faculty of Pharmacy, REQUIMTE, Department of Chemistry, and CIQ-UP, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal.
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11
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Guha R. On the interpretation and interpretability of quantitative structure–activity relationship models. J Comput Aided Mol Des 2008; 22:857-71. [DOI: 10.1007/s10822-008-9240-5] [Citation(s) in RCA: 58] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2008] [Accepted: 08/14/2008] [Indexed: 01/28/2023]
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