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Aktaş E, Özdemir Özgentürk N. A comprehensive examination of ACE2 receptor and prediction of spike glycoprotein and ACE2 interaction based on in silico analysis of ACE2 receptor. J Biomol Struct Dyn 2024; 42:4412-4428. [PMID: 37349943 DOI: 10.1080/07391102.2023.2220814] [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: 02/12/2023] [Accepted: 05/28/2023] [Indexed: 06/24/2023]
Abstract
The ACE2 receptor plays a vital role not only in the SARS-CoV-induced epidemic but also in various other diseases, including cardiovascular diseases and ARDS. While studies have explored the interactions between ACE2 and SARS-CoV proteins, comprehensive research utilizing bioinformatic tools on the ACE2 protein has been lacking. The one aim of present study was to extensively analyze the regions of the ACE2 protein. After utilizing all bioinformatics tools especially G104 and L108 regions on ACE2 were come forward. The results of our analysis revealed that possible mutations or deletions in the G104 and L108 regions play a critical role in both the biological functioning and the determination of the chemical-physical properties of ACE2. Additionally, these regions were found to be more susceptible to mutations or deletions compared to other regions of the ACE2 protein. Notably, the randomly selected peptide, LQQNGSSVLS (100-109), which includes G104 and L108, exhibited a crucial role in binding the RBD of the spike protein, as supported by docking scores. Furthermore, both MDs and iMODs results provided evidence that G104 and L108 influence the dynamics of ACE2-spike complexes. This study is expected to offer a new perspective on the ACE2-SARS-CoV interaction and other research areas where ACE2 plays a significant role, such as biotechnology (protein engineering, enzyme optimization), medicine (RAS, pulmonary and cardiac diseases), and basic research (structural motifs, stabilizing protein folds, or facilitating important inter molecular contacts, protein's proper structure and function).Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Emre Aktaş
- Faculty of Art and Science, Molecular Biology and Genetics, Yıldız Technical University, Istanbul, Turkey
| | - Nehir Özdemir Özgentürk
- Faculty of Art and Science, Molecular Biology and Genetics, Yıldız Technical University, Istanbul, Turkey
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Yi S, Kim SY, Vincent MP, Yuk SA, Bobbala S, Du F, Scott EA. Dendritic peptide-conjugated polymeric nanovectors for non-toxic delivery of plasmid DNA and enhanced non-viral transfection of immune cells. iScience 2022; 25:104555. [PMID: 35769884 PMCID: PMC9234717 DOI: 10.1016/j.isci.2022.104555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 04/29/2022] [Accepted: 06/02/2022] [Indexed: 10/26/2022] Open
Abstract
Plasmid DNA (pDNA) transfection is advantageous for gene therapies requiring larger genetic elements, including "all-in-one" CRISPR/Cas9 plasmids, but is limited by toxicity as well as poor intracellular release and transfection efficiency in immune cell populations. Here, we developed a synthetic non-viral gene delivery platform composed of poly(ethylene glycol)-b-poly(propylene sulfide) copolymers linked to a cationic dendritic peptide (DP) via a reduceable bond, PEG-b-PPS-ss-DP (PPDP). A library of self-assembling PPDP polymers was synthesized and screened to identify optimal constructs capable of transfecting macrophages with small (pCMV-DsRed, 4.6 kb) and large (pL-CRISPR.EFS.tRFP, 11.7 kb) plasmids. The optimized PPDP construct transfected macrophages, fibroblasts, dendritic cells, and T cells more efficiently and with less toxicity than a commercial Lipo2K reagent, regardless of pDNA size and under standard culture conditions in the presence of serum. The PPDP technology described herein is a stimuli-responsive polymeric nanovector that can be leveraged to meet diverse challenges in gene delivery.
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Affiliation(s)
- Sijia Yi
- Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Sun-Young Kim
- Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208, USA.,SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do 16419, Republic of Korea
| | - Michael P Vincent
- Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Simseok A Yuk
- Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Sharan Bobbala
- Department of Pharmaceutical Sciences, School of Pharmacy, West Virginia University, Morgantown, WV 26505, USA
| | - Fanfan Du
- Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Evan Alexander Scott
- Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208, USA.,Simpson Querrey Institute, Northwestern University, Chicago, IL 60611, USA.,Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL 60611, USA.,Department of Microbiology-Immunology, Northwestern University, Chicago, IL 60611, USA
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de Brevern AG. Analysis of Protein Disorder Predictions in the Light of a Protein Structural Alphabet. Biomolecules 2020; 10:biom10071080. [PMID: 32698546 PMCID: PMC7408373 DOI: 10.3390/biom10071080] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 07/14/2020] [Accepted: 07/18/2020] [Indexed: 12/30/2022] Open
Abstract
Intrinsically-disordered protein (IDP) characterization was an amazing change of paradigm in our classical sequence-structure-function theory. Moreover, IDPs are over-represented in major disease pathways and are now often targeted using small molecules for therapeutic purposes. This has had created a complex continuum from order-that encompasses rigid and flexible regions-to disorder regions; the latter being not accessible through classical crystallographic methodologies. In X-ray structures, the notion of order is dictated by access to resolved atom positions, providing rigidity and flexibility information with low and high experimental B-factors, while disorder is associated with the missing (non-resolved) residues. Nonetheless, some rigid regions can be found in disorder regions. Using ensembles of IDPs, their local conformations were analyzed in the light of a structural alphabet. An entropy index derived from this structural alphabet allowed us to propose a continuum of states from rigidity to flexibility and finally disorder. In this study, the analysis was extended to comparing these results to disorder predictions, underlying a limited correlation, and so opening new ideas to characterize and predict disorder.
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Affiliation(s)
- Alexandre G de Brevern
- INSERM, UMR_S 1134, DSIMB, Univ Paris, INTS, Laboratoire d'Excellence GR-Ex, 75015 Paris, France
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Uversky VN. Torches, Candles, Lamps, Lanterns, Flashlights, Spotlights, Night Vision Goggles… You Need Them All to See in Darkness. Proteomics 2020; 19:e1900085. [PMID: 30829430 DOI: 10.1002/pmic.201900085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Articles assembled in the second part of this Special Issue describe some experimental and computational approaches for the structural and functional characterization of intrinsically disordered proteins. Since these tools represent specialized gear for the focused analysis of various aspects of dark proteome, they can be viewed as torches, candles, lamps, lanterns, flashlights, spotlights, night vision goggles, and other means needed to see in darkness.
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Affiliation(s)
- Vladimir N Uversky
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, 33612, USA.,Laboratory of New Methods in Biology, Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow, 142290, Russia
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Vincent M, Schnell S. Disorder Atlas: Web-based software for the proteome-based interpretation of intrinsic disorder predictions. Comput Biol Chem 2019; 83:107090. [PMID: 31326853 PMCID: PMC7368971 DOI: 10.1016/j.compbiolchem.2019.107090] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Revised: 12/05/2018] [Accepted: 07/10/2019] [Indexed: 11/18/2022]
Abstract
Intrinsically disordered proteins lack a stable three-dimensional structure under physiological conditions. While this property has gained considerable interest within the past two decades, disorder poses substantial challenges to experimental characterization efforts. In effect, numerous computational tools have been developed to predict disorder from primary sequences, however, interpreting the output of these algorithms remains a challenge. To begin to bridge this gap, we present Disorder Atlas, web-based software that facilitates the interpretation of intrinsic disorder predictions using proteome-based descriptive statistics. This service is also equipped to facilitate large-scale systematic exploratory searches for proteins encompassing disorder features of interest, and further allows users to browse the prevalence of multiple disorder features at the proteome level. As a result, Disorder Atlas provides a user-friendly tool that places algorithm-generated disorder predictions in the context of the proteome, thereby providing an instrument to compare the results of a query protein against predictions made for an entire population. Disorder Atlas currently supports ten eukaryotic proteomes and is freely available for non-commercial users at http://www.disorderatlas.org.
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Affiliation(s)
- Michael Vincent
- Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Santiago Schnell
- Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI, USA; Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, MI, USA.
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A Suggestion of Converting Protein Intrinsic Disorder to Structural Entropy Using Shannon's Information Theory. ENTROPY 2019; 21:e21060591. [PMID: 33267305 PMCID: PMC7515080 DOI: 10.3390/e21060591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Revised: 06/11/2019] [Accepted: 06/13/2019] [Indexed: 11/16/2022]
Abstract
We propose a framework to convert the protein intrinsic disorder content to structural entropy (H) using Shannon’s information theory (IT). The structural capacity (C), which is the sum of H and structural information (I), is equal to the amino acid sequence length of the protein. The structural entropy of the residues expands a continuous spectrum, ranging from 0 (fully ordered) to 1 (fully disordered), consistent with Shannon’s IT, which scores the fully-determined state 0 and the fully-uncertain state 1. The intrinsically disordered proteins (IDPs) in a living cell may participate in maintaining the high-energy-low-entropy state. In addition, under this framework, the biological functions performed by proteins and associated with the order or disorder of their 3D structures could be explained in terms of information-gains or entropy-losses, or the reverse processes.
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Perdigão N, Rosa A. Dark Proteome Database: Studies on Dark Proteins. High Throughput 2019; 8:ht8020008. [PMID: 30934744 PMCID: PMC6630768 DOI: 10.3390/ht8020008] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2018] [Revised: 03/12/2019] [Accepted: 03/15/2019] [Indexed: 12/27/2022] Open
Abstract
The dark proteome, as we define it, is the part of the proteome where 3D structure has not been observed either by homology modeling or by experimental characterization in the protein universe. From the 550.116 proteins available in Swiss-Prot (as of July 2016), 43.2% of the eukarya universe and 49.2% of the virus universe are part of the dark proteome. In bacteria and archaea, the percentage of the dark proteome presence is significantly less, at 12.6% and 13.3% respectively. In this work, we present a necessary step to complete the dark proteome picture by introducing the map of the dark proteome in the human and in other model organisms of special importance to mankind. The most significant result is that around 40% to 50% of the proteome of these organisms are still in the dark, where the higher percentages belong to higher eukaryotes (mouse and human organisms). Due to the amount of darkness present in the human organism being more than 50%, deeper studies were made, including the identification of ‘dark’ genes that are responsible for the production of so-called dark proteins, as well as the identification of the ‘dark’ tissues where dark proteins are over represented, namely, the heart, cervical mucosa, and natural killer cells. This is a step forward in the direction of gaining a deeper knowledge of the human dark proteome.
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Affiliation(s)
- Nelson Perdigão
- Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal.
- Instituto de Sistemas e Robótica, 1049-001 Lisbon, Portugal.
| | - Agostinho Rosa
- Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal.
- Instituto de Sistemas e Robótica, 1049-001 Lisbon, Portugal.
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