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Ren C, Chen L, Bai Y, Hou C, Li X, Schroyen M, Zhang D. Comparative effects of phosphorylation and acetylation on glycolysis and myofibrillar proteins degradation in postmortem muscle. Int J Biol Macromol 2024; 257:128567. [PMID: 38061521 DOI: 10.1016/j.ijbiomac.2023.128567] [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: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 12/17/2023]
Abstract
The study investigated the different effects between protein phosphorylation and acetylation on glycolytic enzyme activity and myofibrillar protein degradation. Lamb longissimus thoracis lumborum muscles were homogenized and then inhibitors were added for incubation at 4 °C. Phosphatase inhibitor was added to produce a high phosphorylation level (PI group) and lysine deacetylase inhibitor was added to produce a high acetylation level (DI group). The lactate and ATP content in the PI group was inhibited compared with that in the DI group (P < 0.05). Phosphofructokinase (PFK) activity was negatively related with the phosphorylation level and was positively related with the acetylation level in the DI group (P < 0.05). The degradation of troponin T and desmin of the DI group were restrained when compared to that in the PI group (P < 0.05). Compared with initial PFK and desmin, the simulation of phosphorylation and acetylation of PFK and desmin showed different electrostatic potential at the surface and a more unstable structure. The phosphorylation level of the DI group was increased, suggesting that the changes of protein acetylation altered protein phosphorylation. In conclusion, compared with protein phosphorylation, protein acetylation had a greater effect on promoting glycolysis and inhibiting protein degradation.
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Affiliation(s)
- Chi Ren
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences/Key Laboratory of Agro-products Quality & Safety in Harvest, Storage, Transportation, Management and Control, Ministry of Agriculture and Rural Affairs, Beijing 100193, PR China; Precision Livestock and Nutrition Unit, Gembloux Agro-Bio Tech, University of Liège, Passage des Déportés 2, Gembloux, Belgium
| | - Li Chen
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences/Key Laboratory of Agro-products Quality & Safety in Harvest, Storage, Transportation, Management and Control, Ministry of Agriculture and Rural Affairs, Beijing 100193, PR China
| | - Yuqiang Bai
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences/Key Laboratory of Agro-products Quality & Safety in Harvest, Storage, Transportation, Management and Control, Ministry of Agriculture and Rural Affairs, Beijing 100193, PR China
| | - Chengli Hou
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences/Key Laboratory of Agro-products Quality & Safety in Harvest, Storage, Transportation, Management and Control, Ministry of Agriculture and Rural Affairs, Beijing 100193, PR China
| | - Xin Li
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences/Key Laboratory of Agro-products Quality & Safety in Harvest, Storage, Transportation, Management and Control, Ministry of Agriculture and Rural Affairs, Beijing 100193, PR China.
| | - Martine Schroyen
- Precision Livestock and Nutrition Unit, Gembloux Agro-Bio Tech, University of Liège, Passage des Déportés 2, Gembloux, Belgium
| | - Dequan Zhang
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences/Key Laboratory of Agro-products Quality & Safety in Harvest, Storage, Transportation, Management and Control, Ministry of Agriculture and Rural Affairs, Beijing 100193, PR China
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Papageorgiou L, Papakonstantinou E, Salis C, Polychronidou E, Hagidimitriou M, Maroulis D, Eliopoulos E, Vlachakis D. Drugena: A Fully Automated Immunoinformatics Platform for the Design of Antibody-Drug Conjugates Against Neurodegenerative Diseases. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1194:203-215. [PMID: 32468536 DOI: 10.1007/978-3-030-32622-7_18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Antibodies are proteins that are the first line of defense in the adaptive immune response of vertebrates. Thereby, they are involved in a multitude of biochemical mechanisms and clinical manifestations with significant medical interest, such as autoimmunity, the regulation of infection, and cancer. An emerging field in antibody science that is of huge medicinal interest is the development of novel antibody-interacting drugs. Such entities are the antibody-drug conjugates (ADCs), which are a new type of targeted therapy, which consist of an antibody linked to a payload drug. Overall, the underlying principle of ADCs is the discerning delivery of a drug to a target, hoping to increase the potency of the original drug. Drugena suite is a pioneering platform that employs state-of-the-art computational biology methods in the fight against neurodegenerative diseases using ADCs. Drugena encompasses an up-to-date structural database of specialized antibodies for neurological disorders and the NCI database with over 96 million entities for the in silico development of ADCs. The pipeline of the Drugena suite has been divided into several steps and modules that are closely related with a synergistic fashion under a user-friendly graphical user interface.
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Affiliation(s)
- Louis Papageorgiou
- Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece.,Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Athens, Greece.,Division of Endocrinology and Metabolism, Center of Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Eleni Papakonstantinou
- Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece
| | - Constantinos Salis
- Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece
| | | | - Marianna Hagidimitriou
- Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece
| | - Dimitris Maroulis
- Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Athens, Greece
| | - Elias Eliopoulos
- Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece
| | - Dimitrios Vlachakis
- Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece. .,Division of Endocrinology and Metabolism, Center of Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
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Raftopoulou S, Nicolaides NC, Papageorgiou L, Amfilochiou A, Zakinthinos SG, George P, Eliopoulos E, Chrousos GP, Vlachakis D. Structural Study of the DNA: Clock/Bmal1 Complex Provides Insights for the Role of Cortisol, hGR, and HPA Axis in Stress Management and Sleep Disorders. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1195:59-71. [PMID: 32468460 DOI: 10.1007/978-3-030-32633-3_10] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Herein, we deploy an in silico pipeline of structural bioinformatics, thermodynamics, and molecular dynamics to investigate the role of cortisol in circadian rhythms, biorhythms, stress response, and even sleep disorders. Our study shows that high concentrations of cortisol intercalate in the minor groove of DNA. This phenomenon widens the adjacent major grooves and provides the Clock/Bmal1 complex with more space to dock and interact with DNA. Then, the strong charges of cortisol pull the alpha helices of the Clock/Bmal1 complex and bend it inward, thus establishing stronger interactions and prolonged signaling. Our results indicate that elevated cortisol levels play an important role in stress, inflammation, and sleep disorders as a result of prolonged and stronger dsDNA - Clock/Bmal1 interactions.
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Affiliation(s)
- Sofia Raftopoulou
- Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece.,Affidea Healthcare Company, Athens, Greece
| | - Nicolas C Nicolaides
- Division of Endocrinology and Metabolism, Center of Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.,Division of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, National and Kapodistrian University of Athens Medical School, "Aghia Sophia" Children's Hospital, Athens, Greece
| | - Louis Papageorgiou
- Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece.,Division of Endocrinology and Metabolism, Center of Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Anastasia Amfilochiou
- Sismanoglio General Hospital of Attica, Respiratory Function & Sleep Study Unit, Marousi, Greece
| | - Spyros G Zakinthinos
- Critical Care and Pulmonary Services, Evangelismos Hospital, Medical School of Athens University, Athens, Greece
| | | | - Elias Eliopoulos
- Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece
| | - George P Chrousos
- Division of Endocrinology and Metabolism, Center of Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.,Division of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, National and Kapodistrian University of Athens Medical School, "Aghia Sophia" Children's Hospital, Athens, Greece
| | - Dimitrios Vlachakis
- Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece. .,Division of Endocrinology and Metabolism, Center of Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
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Papageorgiou L, Maroulis D, Chrousos GP, Eliopoulos E, Vlachakis D. Antibody Clustering Using a Machine Learning Pipeline that Fuses Genetic, Structural, and Physicochemical Properties. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1194:41-58. [PMID: 32468522 DOI: 10.1007/978-3-030-32622-7_4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Antibody V domain clustering is of paramount importance to a repertoire of immunology-related areas. Although several approaches have been proposed for antibody clustering, still no consensus has been reached. Numerous attempts use information from genes, protein sequences, 3D structures, and 3D surfaces in an effort to elucidate unknown action mechanisms directly related to their function and to either link them directly to diseases or drive the discovery of new medicines, such as antibody drug conjugates (ADC). Herein, we describe a new V domain antibody clustering method based on the comparison of the interaction sites between each antibody and its antigen. A more specific clustering analysis of the antibody's V domain was provided using deep learning and data mining techniques. The multidimensional information was extracted from the structural resolved antibodies when they were captured to interact with other proteins. The available 3D structures of protein antigen-antibody (Ag-Ab) interfaces contain information about how antibody V domains recognize antigens as well as about which amino acids are involved in the recognition. As such, the antibody surface holds information about antigens' folding that reside with the Ab-Ag interface residues and how they interact. In order to gain insight into the nature of such interactions, we propose a new simple philosophy to transform the conserved framework (fragment regions, complementarity-determining regions) of antibody V domain in a binary form using structural features of antibody-antigen interactions, toward identifying new antibody signatures in V domain binding activity. Finally, an advanced three-level hybrid classification scheme has been set for clustering antibodies in subgroups, which can combine the information from the protein sequences, the three-dimensional structures, and specific "key patterns" of recognized interactions. The clusters provide multilevel information about antibodies and antibody-antigen complexes.
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Affiliation(s)
- Louis Papageorgiou
- Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Athens, Greece.,Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece
| | - Dimitris Maroulis
- Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Athens, Greece
| | - George P Chrousos
- Division of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, National and Kapodistrian University of Athens Medical School, "Aghia Sophia" Children's Hospital, Athens, Greece.,Division of Endocrinology and Metabolism, Center of Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Elias Eliopoulos
- Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece
| | - Dimitrios Vlachakis
- Genetics and Computational Biology Group, Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, Athens, Greece. .,Division of Endocrinology and Metabolism, Center of Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
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Olive Oil Polyphenols in Neurodegenerative Pathologies. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1195:77-91. [PMID: 32468462 DOI: 10.1007/978-3-030-32633-3_12] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Neurodegenerative diseases lead to the death of nerve cells in the brain or the spinal cord. A wide range of diseases are included within the group of neurodegenerative disorders, with the most common ones being dementia, Alzheimer's, and Parkinson's diseases. Millions of older people are suffering from such pathologies. The global increase of life expectancy unavoidably leads to a consequent increase in the number of people who will be at some degree affected by neurodegenerative-related diseases. At this moment, there is no effective therapy or treatment that can reverse the loss of neurons. A growing number of studies highlight the value of the consumption of medical foods, and in particular olive oil, as one of the most important components of the Mediterranean diet. A diet based on extra virgin olive oil seems to contribute toward the lowering of risk of age-related pathologies due to high phenol concentration. The link of a polyphenol found in extra virgin olive oil, namely, tyrosol, with the protein tyrosinase, associated to Parkinson's disease is underlined as a paradigm of affiliation between polyphenols and neurodegenerative disorders.
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Anuar NFSK, Wahab RA, Huyop F, Halim KBA, Hamid AAA. In silico mutation on a mutant lipase from Acinetobacter haemolyticus towards enhancing alkaline stability. J Biomol Struct Dyn 2019; 38:4493-4507. [DOI: 10.1080/07391102.2019.1683074] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Affiliation(s)
- Nurul Fatin Syamimi Khairul Anuar
- Department of Bioscience, Faculty of Science, Universiti Teknologi Malaysia, Johor, Bahru, Malaysia
- Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia, Johor, Bahru, Malaysia
| | - Roswanira Abdul Wahab
- Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia, Johor, Bahru, Malaysia
- Enzyme Technology and Green Synthesis Research Group, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia
| | - Fahrul Huyop
- Department of Bioscience, Faculty of Science, Universiti Teknologi Malaysia, Johor, Bahru, Malaysia
- Enzyme Technology and Green Synthesis Research Group, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia
| | - Khairul Bariyyah Abd Halim
- Department of Biotechnology, Kuliyyah of Science, International Islamic University Malaysia, Bandar Indera Mahkota Kuantan, Malaysia
| | - Azzmer Azzar Abdul Hamid
- Department of Biotechnology, Kuliyyah of Science, International Islamic University Malaysia, Bandar Indera Mahkota Kuantan, Malaysia
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Vlachakis D, Champeris Tsaniras S, Tsiliki G, Megalooikonomou V, Kossida S. 3D structural analysis of proteins using electrostatic surfaces based on image segmentation. JOURNAL OF MOLECULAR BIOCHEMISTRY 2014; 3:27-33. [PMID: 27525250 PMCID: PMC4981338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Herein, we present a novel strategy to analyse and characterize proteins using protein molecular electro-static surfaces. Our approach starts by calculating a series of distinct molecular surfaces for each protein that are subsequently flattened out, thus reducing 3D information noise. RGB images are appropriately scaled by means of standard image processing techniques whilst retaining the weight information of each protein's molecular electrostatic surface. Then homogeneous areas in the protein surface are estimated based on unsupervised clustering of the 3D images, while performing similarity searches. This is a computationally fast approach, which efficiently highlights interesting structural areas among a group of proteins. Multiple protein electrostatic surfaces can be combined together and in conjunction with their processed images, they can provide the starting material for protein structural similarity and molecular docking experiments.
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Affiliation(s)
- Dimitrios Vlachakis
- Biomedical Research Foundation of the Academy of Athens, 11527, Athens, Greece
- Bionetwork ltd. 15234, Chalandri, Athens, Greece
- Computer Engineering and Informatics Department, School of Engineering, University of Patras, 26500 Patras, Greece
| | - Spyridon Champeris Tsaniras
- Bionetwork ltd. 15234, Chalandri, Athens, Greece
- Department of Physiology, Medical School, University of Patras, 26500 Patras, Greece
| | - Georgia Tsiliki
- Biomedical Research Foundation of the Academy of Athens, 11527, Athens, Greece
| | - Vasileios Megalooikonomou
- Computer Engineering and Informatics Department, School of Engineering, University of Patras, 26500 Patras, Greece
| | - Sophia Kossida
- Biomedical Research Foundation of the Academy of Athens, 11527, Athens, Greece
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Loukatou S, Fakourelis P, Papageorgiou L, Megalooikonomou V, Kossida S, Vlachakis D. Ebola virus epidemic: a deliberate accident? JOURNAL OF MOLECULAR BIOCHEMISTRY 2014; 3:72-76. [PMID: 30175076 PMCID: PMC6114937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Affiliation(s)
- Styliani Loukatou
- Computational Biology & Medicine Group, Biomedical Research Foundation, Academy of Athens, Soranou Efessiou 4, Athens 11527, Greece
| | - Paraskevas Fakourelis
- Computational Biology & Medicine Group, Biomedical Research Foundation, Academy of Athens, Soranou Efessiou 4, Athens 11527, Greece
| | - Louis Papageorgiou
- Computational Biology & Medicine Group, Biomedical Research Foundation, Academy of Athens, Soranou Efessiou 4, Athens 11527, Greece
- Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, University Campus, Athens, 15784, Greece
| | - Vasileios Megalooikonomou
- Computer Engineering and Informatics Department, School of Engineering, University of Patras, 26500 Patras, Greece
| | - Sophia Kossida
- Computational Biology & Medicine Group, Biomedical Research Foundation, Academy of Athens, Soranou Efessiou 4, Athens 11527, Greece
| | - Dimitrios Vlachakis
- Computational Biology & Medicine Group, Biomedical Research Foundation, Academy of Athens, Soranou Efessiou 4, Athens 11527, Greece
- Computer Engineering and Informatics Department, School of Engineering, University of Patras, 26500 Patras, Greece
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