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Wang FS, Chen PR, Chen TY, Zhang HX. Fuzzy optimization for identifying anti-cancer targets with few side effects in constraint-based models of head and neck cancer. ROYAL SOCIETY OPEN SCIENCE 2022; 9:220633. [PMID: 36303939 PMCID: PMC9597175 DOI: 10.1098/rsos.220633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 09/27/2022] [Indexed: 06/16/2023]
Abstract
Computer-aided methods can be used to screen potential candidate targets and to reduce the time and cost of drug development. In most of these methods, synthetic lethality is used as a therapeutic criterion to identify drug targets. However, these methods do not consider the side effects during the identification stage. This study developed a fuzzy multi-objective optimization for identifying anti-cancer targets that not only evaluated cancer cell mortality, but also minimized side effects due to treatment. We identified potential anti-cancer enzymes and antimetabolites for the treatment of head and neck cancer (HNC). The identified one- and two-target enzymes were primarily involved in six major pathways, namely, purine and pyrimidine metabolism and the pentose phosphate pathway. Most of the identified targets can be regulated by approved drugs; thus, these drugs are potential candidates for drug repurposing as a treatment for HNC. Furthermore, we identified antimetabolites involved in pathways similar to those identified using a gene-centric approach. Moreover, HMGCR knockdown could not block the growth of HNC cells. However, the two-target combinations of (UMPS, HMGCR) and (CAD, HMGCR) could achieve cell mortality and improve metabolic deviation grades over 22% without reducing the cell viability grade.
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Affiliation(s)
- Feng-Sheng Wang
- Department of Chemical Engineering, National Chung Cheng University, Chiayi, Taiwan
| | - Pei-Rong Chen
- Department of Chemical Engineering, National Chung Cheng University, Chiayi, Taiwan
| | - Ting-Yu Chen
- Department of Chemical Engineering, National Chung Cheng University, Chiayi, Taiwan
| | - Hao-Xiang Zhang
- Department of Chemical Engineering, National Chung Cheng University, Chiayi, Taiwan
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Ramos PIP, Fernández Do Porto D, Lanzarotti E, Sosa EJ, Burguener G, Pardo AM, Klein CC, Sagot MF, de Vasconcelos ATR, Gales AC, Marti M, Turjanski AG, Nicolás MF. An integrative, multi-omics approach towards the prioritization of Klebsiella pneumoniae drug targets. Sci Rep 2018; 8:10755. [PMID: 30018343 PMCID: PMC6050338 DOI: 10.1038/s41598-018-28916-7] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 06/27/2018] [Indexed: 02/07/2023] Open
Abstract
Klebsiella pneumoniae (Kp) is a globally disseminated opportunistic pathogen that can cause life-threatening infections. It has been found as the culprit of many infection outbreaks in hospital environments, being particularly aggressive towards newborns and adults under intensive care. Many Kp strains produce extended-spectrum β-lactamases, enzymes that promote resistance against antibiotics used to fight these infections. The presence of other resistance determinants leading to multidrug-resistance also limit therapeutic options, and the use of 'last-resort' drugs, such as polymyxins, is not uncommon. The global emergence and spread of resistant strains underline the need for novel antimicrobials against Kp and related bacterial pathogens. To tackle this great challenge, we generated multiple layers of 'omics' data related to Kp and prioritized proteins that could serve as attractive targets for antimicrobial development. Genomics, transcriptomics, structuromic and metabolic information were integrated in order to prioritize candidate targets, and this data compendium is freely available as a web server. Twenty-nine proteins with desirable characteristics from a drug development perspective were shortlisted, which participate in important processes such as lipid synthesis, cofactor production, and core metabolism. Collectively, our results point towards novel targets for the control of Kp and related bacterial pathogens.
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Affiliation(s)
- Pablo Ivan Pereira Ramos
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (FIOCRUZ), Salvador, Bahia, Brazil
- Laboratório Nacional de Computação Científica, Petrópolis, Rio de Janeiro, Brazil
| | - Darío Fernández Do Porto
- Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina
| | - Esteban Lanzarotti
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina
| | - Ezequiel J Sosa
- Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Germán Burguener
- Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Agustín M Pardo
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina
| | - Cecilia C Klein
- Inria Grenoble Rhône-Alpes, Grenoble, France
- Université Claude Bernard Lyon 1, Lyon, France
- Centre for Genomic Regulation (CRG), Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia and Institut de Biomedicina (IBUB), Universitat de Barcelona, Barcelona, Catalonia, Spain
| | - Marie-France Sagot
- Inria Grenoble Rhône-Alpes, Grenoble, France
- Université Claude Bernard Lyon 1, Lyon, France
| | | | - Ana Cristina Gales
- Laboratório Alerta. Division of Infectious Diseases, Department of Internal Medicine. Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Marcelo Marti
- Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina
| | - Adrián G Turjanski
- Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina.
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina.
| | - Marisa F Nicolás
- Laboratório Nacional de Computação Científica, Petrópolis, Rio de Janeiro, Brazil.
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Metabolic flux analyses of Pseudomonas aeruginosa cystic fibrosis isolates. Metab Eng 2016; 38:251-263. [PMID: 27637318 DOI: 10.1016/j.ymben.2016.09.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Revised: 06/07/2016] [Accepted: 09/11/2016] [Indexed: 01/22/2023]
Abstract
Pseudomonas aeruginosa is a metabolically versatile wide-ranging opportunistic pathogen. In humans P. aeruginosa causes infections of the skin, urinary tract, blood, and the lungs of Cystic Fibrosis patients. In addition, P. aeruginosa's broad environmental distribution, relatedness to biotechnologically useful species, and ability to form biofilms have made it the focus of considerable interest. We used 13C metabolic flux analysis (MFA) and flux balance analysis to understand energy and redox production and consumption and to explore the metabolic phenotypes of one reference strain and five strains isolated from the lungs of cystic fibrosis patients. Our results highlight the importance of the oxidative pentose phosphate and Entner-Doudoroff pathways in P. aeruginosa growth. Among clinical strains we report two divergent metabolic strategies and identify changes between genetically related strains that have emerged during a chronic infection of the same patient. MFA revealed that the magnitude of fluxes through the glyoxylate cycle correlates with growth rates.
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