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Radhouani H, Correia S, Gonçalves C, Reis RL, Oliveira JM. Synthesis and Characterization of Biocompatible Methacrylated Kefiran Hydrogels: Towards Tissue Engineering Applications. Polymers (Basel) 2021; 13:1342. [PMID: 33923932 PMCID: PMC8072540 DOI: 10.3390/polym13081342] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 04/15/2021] [Accepted: 04/18/2021] [Indexed: 02/07/2023] Open
Abstract
Hydrogel application feasibility is still limited mainly due to their low mechanical strength and fragile nature. Therefore, several physical and chemical cross-linking modifications are being used to improve their properties. In this research, methacrylated Kefiran was synthesized by reacting Kefiran with methacrylic anhydride (MA). The developed MA-Kefiran was physicochemically characterized, and its biological properties evaluated by different techniques. Chemical modification of MA-Kefiran was confirmed by 1H-NMR and FTIR and GPC-SEC showed an average Mw of 793 kDa (PDI 1.3). The mechanical data obtained revealed MA-Kefiran to be a pseudoplastic fluid with an extrusion force of 11.21 ± 2.87 N. Moreover, MA-Kefiran 3D cryogels were successfully developed and fully characterized. Through micro-CT and SEM, the scaffolds revealed high porosity (85.53 ± 0.15%) and pore size (33.67 ± 3.13 μm), thick pore walls (11.92 ± 0.44 μm) and a homogeneous structure. Finally, MA-Kefiran revealed to be biocompatible by presenting no hemolytic activity and an improved cellular function of L929 cells observed through the AlamarBlue® assay. By incorporating methacrylate groups in the Kefiran polysaccharide chain, a MA-Kefiran product was developed with remarkable physical, mechanical, and biological properties, resulting in a promising hydrogel to be used in tissue engineering and regenerative medicine applications.
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Affiliation(s)
- Hajer Radhouani
- 3B’s Research Group, I3Bs—Research Institute on Biomaterials, Biodegradables and Biomimetics, University of Minho, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, AvePark, Parque de Ciência e Tecnologia, Zona Industrial da Gandra, Barco, 4805-017 Guimarães, Portugal; (S.C.); (C.G.); (R.L.R.); (J.M.O.)
- ICVS/3B’s–PT Government Associate Laboratory, Braga, 4805-017 Guimarães, Portugal
| | - Susana Correia
- 3B’s Research Group, I3Bs—Research Institute on Biomaterials, Biodegradables and Biomimetics, University of Minho, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, AvePark, Parque de Ciência e Tecnologia, Zona Industrial da Gandra, Barco, 4805-017 Guimarães, Portugal; (S.C.); (C.G.); (R.L.R.); (J.M.O.)
- ICVS/3B’s–PT Government Associate Laboratory, Braga, 4805-017 Guimarães, Portugal
| | - Cristiana Gonçalves
- 3B’s Research Group, I3Bs—Research Institute on Biomaterials, Biodegradables and Biomimetics, University of Minho, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, AvePark, Parque de Ciência e Tecnologia, Zona Industrial da Gandra, Barco, 4805-017 Guimarães, Portugal; (S.C.); (C.G.); (R.L.R.); (J.M.O.)
- ICVS/3B’s–PT Government Associate Laboratory, Braga, 4805-017 Guimarães, Portugal
| | - Rui L. Reis
- 3B’s Research Group, I3Bs—Research Institute on Biomaterials, Biodegradables and Biomimetics, University of Minho, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, AvePark, Parque de Ciência e Tecnologia, Zona Industrial da Gandra, Barco, 4805-017 Guimarães, Portugal; (S.C.); (C.G.); (R.L.R.); (J.M.O.)
- ICVS/3B’s–PT Government Associate Laboratory, Braga, 4805-017 Guimarães, Portugal
| | - Joaquim M. Oliveira
- 3B’s Research Group, I3Bs—Research Institute on Biomaterials, Biodegradables and Biomimetics, University of Minho, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, AvePark, Parque de Ciência e Tecnologia, Zona Industrial da Gandra, Barco, 4805-017 Guimarães, Portugal; (S.C.); (C.G.); (R.L.R.); (J.M.O.)
- ICVS/3B’s–PT Government Associate Laboratory, Braga, 4805-017 Guimarães, Portugal
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Tutone M, Almerico AM. The In Silico Fischer Lock-and-Key Model: The Combined Use of Molecular Descriptors and Docking Poses for the Repurposing of Old Drugs. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2019; 2089:29-39. [PMID: 31773645 DOI: 10.1007/978-1-0716-0163-1_2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Not always lead compound and/or derivatives are suitable for the specific biological target for which they are designed but, in some cases, discarded compounds proved to be good binders for other biological targets; therefore, drug repurposing constitute a valid alternative to avoid waste of human and financial resources. Our virtual lock-and-key methods, VLKA and Conf-VLKA, furnish a strong support to predict the efficacy of a designed drug a priori its biological evaluation, or the correct biological target for a set of the selected compounds, allowing thus the repurposing of known and unknown, active and inactive compounds.
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Affiliation(s)
- Marco Tutone
- Department of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University di Palermo, Palermo, Italy.
| | - Anna Maria Almerico
- Department of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University di Palermo, Palermo, Italy
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Hou QL, Luo JX, Zhang BC, Jiang GF, Ding W, Zhang YQ. 3D-QSAR and Molecular Docking Studies on the TcPMCA1-Mediated Detoxification of Scopoletin and Coumarin Derivatives. Int J Mol Sci 2017; 18:E1380. [PMID: 28653986 PMCID: PMC5535873 DOI: 10.3390/ijms18071380] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2017] [Revised: 06/20/2017] [Accepted: 06/20/2017] [Indexed: 12/14/2022] Open
Abstract
The carmine spider mite, Tetranychus cinnabarinus (Boisduval), is an economically important agricultural pest that is difficult to prevent and control. Scopoletin is a botanical coumarin derivative that targets Ca2+-ATPase to exert a strong acaricidal effect on carmine spider mites. In this study, the full-length cDNA sequence of a plasma membrane Ca2+-ATPase 1 gene (TcPMCA1) was cloned. The sequence contains an open reading frame of 3750 bp and encodes a putative protein of 1249 amino acids. The effects of scopoletin on TcPMCA1 expression were investigated. TcPMCA1 was significantly upregulated after it was exposed to 10%, 30%, and 50% of the lethal concentration of scopoletin. Homology modeling, molecular docking, and three-dimensional quantitative structure-activity relationships were then studied to explore the relationship between scopoletin structure and TcPMCA1-inhibiting activity of scopoletin and other 30 coumarin derivatives. Results showed that scopoletin inserts into the binding cavity and interacts with amino acid residues at the binding site of the TcPMCA1 protein through the driving forces of hydrogen bonds. Furthermore, CoMFA (comparative molecular field analysis)- and CoMSIA (comparative molecular similarity index analysis)-derived models showed that the steric and H-bond fields of these compounds exert important influences on the activities of the coumarin compounds.Notably, the C3, C6, and C7 positions in the skeletal structure of the coumarins are the most suitable active sites. This work provides insights into the mechanism underlying the interaction of scopoletin with TcPMCA1. The present results can improve the understanding on plasma membrane Ca2+-ATPase-mediated (PMCA-mediated) detoxification of scopoletin and coumarin derivatives in T. cinnabarinus, as well as provide valuable information for the design of novel PMCA-inhibiting acaricides.
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Affiliation(s)
- Qiu-Li Hou
- Laboratory of Natural Products Pesticides, College of Plant Protection, Southwest University, Chongqing 400715, China.
| | - Jin-Xiang Luo
- Laboratory of Natural Products Pesticides, College of Plant Protection, Southwest University, Chongqing 400715, China.
| | - Bing-Chuan Zhang
- Laboratory of Natural Products Pesticides, College of Plant Protection, Southwest University, Chongqing 400715, China.
| | - Gao-Fei Jiang
- Laboratory of Natural Products Pesticides, College of Plant Protection, Southwest University, Chongqing 400715, China.
| | - Wei Ding
- Laboratory of Natural Products Pesticides, College of Plant Protection, Southwest University, Chongqing 400715, China.
| | - Yong-Qiang Zhang
- Laboratory of Natural Products Pesticides, College of Plant Protection, Southwest University, Chongqing 400715, China.
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Costanzo LD, Ghosh S, Zardecki C, Burley SK. Using the Tools and Resources of the RCSB Protein Data Bank. ACTA ACUST UNITED AC 2016; 55:1.9.1-1.9.35. [DOI: 10.1002/cpbi.13] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Luigi Di Costanzo
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey Piscataway New Jersey
| | - Sutapa Ghosh
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey Piscataway New Jersey
| | - Christine Zardecki
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey Piscataway New Jersey
| | - Stephen K. Burley
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey Piscataway New Jersey
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey Piscataway New Jersey
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego California
- San Diego Supercomputer Center, University of California San Diego California
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Affiliation(s)
- David S. Wishart
- Departments of Computing Science and Biological Sciences, University of Alberta Edmonton Alberta Canada
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Yang J, Zhang Y. Protein Structure and Function Prediction Using I-TASSER. CURRENT PROTOCOLS IN BIOINFORMATICS 2015; 52:5.8.1-5.8.15. [PMID: 26678386 PMCID: PMC4871818 DOI: 10.1002/0471250953.bi0508s52] [Citation(s) in RCA: 304] [Impact Index Per Article: 33.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets.
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Affiliation(s)
- Jianyi Yang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
- School of Mathematical Sciences, Nankai University, Tianjin, People's Republic of China
| | - Yang Zhang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
- Department of Biological Chemistry, University of Michigan, Ann Arbor, Michigan
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Baxevanis AD, Bateman A. The Importance of Biological Databases in Biological Discovery. ACTA ACUST UNITED AC 2015; 50:1.1.1-1.1.8. [PMID: 26094768 DOI: 10.1002/0471250953.bi0101s50] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Biological databases play a central role in bioinformatics. They offer scientists the opportunity to access a wide variety of biologically relevant data, including the genomic sequences of an increasingly broad range of organisms. This unit provides a brief overview of major sequence databases and portals, such as GenBank, the UCSC Genome Browser, and Ensembl. Model organism databases, including WormBase, The Arabidopsis Information Resource (TAIR), and those made available through the Mouse Genome Informatics (MGI) resource, are also covered. Non-sequence-centric databases, such as Online Mendelian Inheritance in Man (OMIM), the Protein Data Bank (PDB), MetaCyc, and the Kyoto Encyclopedia of Genes and Genomes (KEGG), are also discussed.
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Affiliation(s)
| | - Alex Bateman
- European Bioinformatics Institute (EMBL-EBI), Hinxton, United Kingdom
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Alshatwi AA, Hasan TN, Syed NA, Shafi G, Grace BL. Identification of functional SNPs in BARD1 gene and in silico analysis of damaging SNPs: based on data procured from dbSNP database. PLoS One 2012; 7:e43939. [PMID: 23056176 PMCID: PMC3467277 DOI: 10.1371/journal.pone.0043939] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2012] [Accepted: 07/27/2012] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND The BARD1 gene encodes for the BRCA1-associated RING domain (BARD1) protein. Germ line and somatic mutations in BARD1 are found in sporadic breast, ovarian and uterine cancers. There is a plethora of single nucleotide polymorphisms (SNPs) which may or may not be involved in the onset of female cancers. Hence, before planning a larger population study, it is advisable to sort out the possible functional SNPs. To accomplish this goal, data available in the dbSNP database and different computer programs can be used. To the best of our knowledge, until now there has been no such study on record for the BARD1 gene. Therefore, this study was undertaken to find the functional nsSNPs in BARD1. RESULT 2.85% of all SNPs in the dbSNP database were present in the coding regions. SIFT predicted 11 out of 50 nsSNPs as not tolerable and PolyPhen assessed 27 out of 50 nsSNPs as damaging. FastSNP revealed that the rs58253676 SNP in the 3' UTR may have splicing regulator and enhancer functions. In the 5' UTR, rs17489363 and rs17426219 may alter the transcriptional binding site. The intronic region SNP rs67822872 may have a medium-high risk level. The protein structures 1JM7, 3C5R and 2NTE were predicted by PDBSum and shared 100% similarity with the BARD1 amino acid sequence. Among the predicted nsSNPs, rs4986841, rs111367604, rs13389423 and rs139785364 were identified as deleterious and damaging by the SIFT and PolyPhen programs. Additionally, I-Mutant showed a decrease in stability for these nsSNPs upon mutation. Finally, the ExPASy-PROSIT program revealed that the predicted deleterious mutations are contained in the ankyrin ring and BRCT domains. CONCLUSION Using the available bioinformatics tools and the data present in the dbSNP database, the four nsSNPs, rs4986841, rs111367604, rs13389423 and rs139785364, were identified as deleterious, reducing the protein stability of BARD1. Hence, these SNPs can be used for the larger population-based studies of female cancers.
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Affiliation(s)
- Ali A Alshatwi
- Molecular Cancer Biology Research Laboratory, Department of Food Science and Nutrition, King Saud University, Riyadh, Saudi Arabia.
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Muszewska A, Hoffman-Sommer M, Grynberg M. LTR retrotransposons in fungi. PLoS One 2011; 6:e29425. [PMID: 22242120 PMCID: PMC3248453 DOI: 10.1371/journal.pone.0029425] [Citation(s) in RCA: 81] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2011] [Accepted: 11/28/2011] [Indexed: 01/17/2023] Open
Abstract
Transposable elements with long terminal direct repeats (LTR TEs) are one of the best studied groups of mobile elements. They are ubiquitous elements present in almost all eukaryotic genomes. Their number and state of conservation can be a highlight of genome dynamics. We searched all published fungal genomes for LTR-containing retrotransposons, including both complete, functional elements and remnant copies. We identified a total of over 66,000 elements, all of which belong to the Ty1/Copia or Ty3/Gypsy superfamilies. Most of the detected Gypsy elements represent Chromoviridae, i.e. they carry a chromodomain in the pol ORF. We analyzed our data from a genome-ecology perspective, looking at the abundance of various types of LTR TEs in individual genomes and at the highest-copy element from each genome. The TE content is very variable among the analyzed genomes. Some genomes are very scarce in LTR TEs (<50 elements), others demonstrate huge expansions (>8000 elements). The data shows that transposon expansions in fungi usually involve an increase both in the copy number of individual elements and in the number of element types. The majority of the highest-copy TEs from all genomes are Ty3/Gypsy transposons. Phylogenetic analysis of these elements suggests that TE expansions have appeared independently of each other, in distant genomes and at different taxonomical levels. We also analyzed the evolutionary relationships between protein domains encoded by the transposon pol ORF and we found that the protease is the fastest evolving domain whereas reverse transcriptase and RNase H evolve much slower and in correlation with each other.
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Affiliation(s)
- Anna Muszewska
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland.
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Ghosh A, Nandy A. Graphical representation and mathematical characterization of protein sequences and applications to viral proteins. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2011; 83:1-42. [PMID: 21570664 PMCID: PMC7150266 DOI: 10.1016/b978-0-12-381262-9.00001-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Graphical representation and numerical characterization (GRANCH) of nucleotide and protein sequences is a new field that is showing a lot of promise in analysis of such sequences. While formulation and applications of GRANCH techniques for DNA/RNA sequences started just over a decade ago, analyses of protein sequences by these techniques are of more recent origin. The emphasis is still on developing the underlying technique, but significant results have been achieved in using these methods for protein phylogeny, mass spectral data of proteins and protein serum profiles in parasites, toxicoproteomics, determination of different indices for use in QSAR studies, among others. We briefly mention these in this chapter, with some details on protein phylogeny and viral diseases. In particular, we cover a systematic method developed in GRANCH to determine conserved surface exposed peptide segments in selected viral proteins that can be used for drug and vaccine targeting. The new GRANCH techniques and applications for DNAs and proteins are covered briefly to provide an overview to this nascent field.
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Affiliation(s)
- Ambarnil Ghosh
- Physics Department, Jadavpur University, Jadavpur, Kolkata, India
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Hammami R, Fliss I. Current trends in antimicrobial agent research: chemo- and bioinformatics approaches. Drug Discov Today 2010; 15:540-6. [PMID: 20546918 DOI: 10.1016/j.drudis.2010.05.002] [Citation(s) in RCA: 52] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2009] [Revised: 03/23/2010] [Accepted: 05/10/2010] [Indexed: 12/16/2022]
Abstract
Databases and chemo- and bioinformatics tools that contain genomic, proteomic and functional information have become indispensable for antimicrobial drug research. The combination of chemoinformatics tools, bioinformatics tools and relational databases provides means of analyzing, linking and comparing online search results. The development of computational tools feeds on a diversity of disciplines, including mathematics, statistics, computer science, information technology and molecular biology. The computational approach to antimicrobial agent discovery and design encompasses genomics, molecular simulation and dynamics, molecular docking, structural and/or functional class prediction, and quantitative structure-activity relationships. This article reviews progress in the development of computational methods, tools and databases used for organizing and extracting biological meaning from antimicrobial research.
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Affiliation(s)
- Riadh Hammami
- STELA Dairy Research Center, Nutraceuticals and Functional Foods Institute, Université Laval, Québec, QC, Canada.
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