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  1. Article ; Online: In Silico Drug Repurposing for SARS-CoV-2 Main Proteinase and Spike Proteins.

    Maffucci, Irene / Contini, Alessandro

    Journal of proteome research

    2020  Volume 19, Issue 11, Page(s) 4637–4648

    Abstract: The pandemic caused by SARS-CoV-2 is currently representing a major health and economic threat to humanity. So far, no specific treatment to this viral infection has been developed and the emergency still requires an efficient intervention. In this work, ...

    Abstract The pandemic caused by SARS-CoV-2 is currently representing a major health and economic threat to humanity. So far, no specific treatment to this viral infection has been developed and the emergency still requires an efficient intervention. In this work, we used virtual screening to facilitate drug repurposing against SARS-CoV-2, targeting viral main proteinase and spike protein with 3000 existing drugs. We used a protocol based on a docking step followed by a short molecular dynamic simulation and rescoring by the Nwat-MMGBSA approach. Our results provide suggestions for prioritizing
    MeSH term(s) Antiviral Agents/chemistry ; Antiviral Agents/metabolism ; Betacoronavirus/chemistry ; Betacoronavirus/enzymology ; Betacoronavirus/metabolism ; COVID-19 ; Coronavirus Infections/virology ; Drug Repositioning/methods ; Humans ; Molecular Dynamics Simulation ; Pandemics ; Peptide Hydrolases/chemistry ; Peptide Hydrolases/metabolism ; Pneumonia, Viral/virology ; SARS-CoV-2 ; Spike Glycoprotein, Coronavirus/chemistry ; Spike Glycoprotein, Coronavirus/metabolism ; Viral Proteins/chemistry ; Viral Proteins/metabolism
    Chemical Substances Antiviral Agents ; Spike Glycoprotein, Coronavirus ; Viral Proteins ; spike protein, SARS-CoV-2 ; Peptide Hydrolases (EC 3.4.-)
    Keywords covid19
    Language English
    Publishing date 2020-09-21
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2078618-9
    ISSN 1535-3907 ; 1535-3893
    ISSN (online) 1535-3907
    ISSN 1535-3893
    DOI 10.1021/acs.jproteome.0c00383
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: AptaMat: a matrix-based algorithm to compare single-stranded oligonucleotides secondary structures.

    Binet, Thomas / Avalle, Bérangère / Dávila Felipe, Miraine / Maffucci, Irene

    Bioinformatics (Oxford, England)

    2022  Volume 39, Issue 1

    Abstract: Motivation: Comparing single-stranded nucleic acids (ssNAs) secondary structures is fundamental when investigating their function and evolution and predicting the effect of mutations on their structures. Many comparison metrics exist, although they are ... ...

    Abstract Motivation: Comparing single-stranded nucleic acids (ssNAs) secondary structures is fundamental when investigating their function and evolution and predicting the effect of mutations on their structures. Many comparison metrics exist, although they are either too elaborate or not sensitive enough to distinguish close ssNAs structures.
    Results: In this context, we developed AptaMat, a simple and sensitive algorithm for ssNAs secondary structures comparison based on matrices representing the ssNAs secondary structures and a metric built upon the Manhattan distance in the plane. We applied AptaMat to several examples and compared the results to those obtained by the most frequently used metrics, namely the Hamming distance and the RNAdistance, and by a recently developed image-based approach. We showed that AptaMat is able to discriminate between similar sequences, outperforming all the other here considered metrics. In addition, we showed that AptaMat was able to correctly classify 14 RFAM families within a clustering procedure.
    Availability and implementation: The python code for AptaMat is available at https://github.com/GEC-git/AptaMat.git.
    Supplementary information: Supplementary data are available at Bioinformatics online.
    MeSH term(s) Humans ; Software ; Algorithms ; Protein Structure, Secondary ; Nucleic Acids ; Cluster Analysis
    Chemical Substances Nucleic Acids
    Language English
    Publishing date 2022-11-28
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1422668-6
    ISSN 1367-4811 ; 1367-4803
    ISSN (online) 1367-4811
    ISSN 1367-4803
    DOI 10.1093/bioinformatics/btac752
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Comparative Study of Single-stranded Oligonucleotides Secondary Structure Prediction Tools.

    Binet, Thomas / Padiolleau-Lefèvre, Séverine / Octave, Stéphane / Avalle, Bérangère / Maffucci, Irene

    BMC bioinformatics

    2023  Volume 24, Issue 1, Page(s) 422

    Abstract: Background: Single-stranded nucleic acids (ssNAs) have important biological roles and a high biotechnological potential linked to their ability to bind to numerous molecular targets. This depends on the different spatial conformations they can assume. ... ...

    Abstract Background: Single-stranded nucleic acids (ssNAs) have important biological roles and a high biotechnological potential linked to their ability to bind to numerous molecular targets. This depends on the different spatial conformations they can assume. The first level of ssNAs spatial organisation corresponds to their base pairs pattern, i.e. their secondary structure. Many computational tools have been developed to predict the ssNAs secondary structures, making the choice of the appropriate tool difficult, and an up-to-date guide on the limits and applicability of current secondary structure prediction tools is missing. Therefore, we performed a comparative study of the performances of 9 freely available tools (mfold, RNAfold, CentroidFold, CONTRAfold, MC-Fold, LinearFold, UFold, SPOT-RNA, and MXfold2) on a dataset of 538 ssNAs with known experimental secondary structure.
    Results: The minimum free energy-based tools, namely mfold and RNAfold, and some tools based on artificial intelligence, namely CONTRAfold and MXfold2, provided the best results, with [Formula: see text] of exact predictions, whilst MC-fold seemed to be the worst performing tool, with only [Formula: see text] of exact predictions. In addition, UFold and SPOT-RNA are the only options for pseudoknots prediction. Including in the analysis of mfold and RNAfold results 5-10 suboptimal solutions further improved the performances of these tools. Nevertheless, we could observe issues in predicting particular motifs, such as multiple-ways junctions and mini-dumbbells, or the ssNAs whose structure has been determined in complex with a protein. In addition, our benchmark shows that some effort has to be paid for ssDNA secondary structure predictions.
    Conclusions: In general, Mfold, RNAfold, and MXfold2 seem to currently be the best choice for the ssNAs secondary structure prediction, although they still show some limits linked to specific structural motifs. Nevertheless, actual trends suggest that artificial intelligence has a high potential to overcome these remaining issues, for example the recently developed UFold and SPOT-RNA have a high success rate in predicting pseudoknots.
    MeSH term(s) Nucleic Acid Conformation ; Oligonucleotides ; Artificial Intelligence ; RNA/chemistry ; Entropy ; Algorithms
    Chemical Substances Oligonucleotides ; RNA (63231-63-0)
    Language English
    Publishing date 2023-11-08
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041484-5
    ISSN 1471-2105 ; 1471-2105
    ISSN (online) 1471-2105
    ISSN 1471-2105
    DOI 10.1186/s12859-023-05532-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: In Silico Drug Repurposing for SARS-CoV-2 Main Proteinase and Spike Proteins

    Maffucci, Irene / Contini, Alessandro

    Journal of Proteome Research

    2020  Volume 19, Issue 11, Page(s) 4637–4648

    Keywords Biochemistry ; General Chemistry ; covid19
    Language English
    Publisher American Chemical Society (ACS)
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2078618-9
    ISSN 1535-3893
    ISSN 1535-3893
    DOI 10.1021/acs.jproteome.0c00383
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: The functionality of a therapeutic antibody candidate restored by a single mutation from proline to threonine in the variable region.

    Hautiere, Marie / Maffucci, Irene / Costa, Narciso / Herbet, Amaury / Essono, Sosthene / Padiolleau-Lefevre, Séverine / Boquet, Didier

    Human vaccines & immunotherapeutics

    2023  Volume 19, Issue 3, Page(s) 2279867

    Abstract: mAbs play an essential role in the therapeutic arsenal. Our laboratory has patented the Rendomab-B49 mAb targeting the endothelin B receptor ( ... ...

    Abstract mAbs play an essential role in the therapeutic arsenal. Our laboratory has patented the Rendomab-B49 mAb targeting the endothelin B receptor (ET
    MeSH term(s) Threonine/genetics ; Antibodies, Monoclonal/therapeutic use ; Mutation
    Chemical Substances Threonine (2ZD004190S) ; Antibodies, Monoclonal
    Language English
    Publishing date 2023-11-27
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2664176-8
    ISSN 2164-554X ; 2164-5515
    ISSN (online) 2164-554X
    ISSN 2164-5515
    DOI 10.1080/21645515.2023.2279867
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: In Silico Drug Repurposing for SARS-CoV-2 Main Proteinase and Spike Proteins

    Maffucci, Irene / Contini, Alessandro

    ISSN: 1535-3893 ; EISSN: 1535-3907 ; Journal of Proteome Research ; https://hal.archives-ouvertes.fr/hal-02933669 ; Journal of Proteome Research, American Chemical Society, 2020, ⟨10.1021/acs.jproteome.0c00383⟩

    2020  

    Abstract: International ... ...

    Abstract International audience
    Keywords [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] ; covid19
    Language English
    Publishing date 2020-09-07
    Publisher HAL CCSD
    Publishing country fr
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: In Silico Drug Repurposing for SARS-CoV-2 Main Proteinase and Spike Proteins

    Maffucci, Irene / Contini, Alessandro

    ISSN: 1535-3893 ; EISSN: 1535-3907 ; Journal of Proteome Research ; https://hal.archives-ouvertes.fr/hal-02933669 ; Journal of Proteome Research, American Chemical Society, 2020, ⟨10.1021/acs.jproteome.0c00383⟩

    2020  

    Abstract: International ... ...

    Abstract International audience
    Keywords [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] ; covid19
    Language English
    Publishing date 2020-09-07
    Publisher HAL CCSD
    Publishing country fr
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: In Silico Drug Repurposing for SARS-CoV-2 Main Proteinase and Spike Proteins

    Maffucci, Irene / Contini, Alessandro

    ISSN: 1535-3893 ; EISSN: 1535-3907 ; Journal of Proteome Research ; https://hal.archives-ouvertes.fr/hal-02933669 ; Journal of Proteome Research, American Chemical Society, 2020, ⟨10.1021/acs.jproteome.0c00383⟩

    2020  

    Abstract: International ... ...

    Abstract International audience
    Keywords [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] ; covid19
    Language English
    Publishing date 2020-09-07
    Publisher HAL CCSD
    Publishing country fr
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

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  9. Article ; Online: In Silico Drug Repurposing for SARS-CoV-2 Main Proteinase and Spike Proteins

    Maffucci, Irene / Contini, Alessandro

    ISSN: 1535-3893 ; EISSN: 1535-3907 ; Journal of Proteome Research ; https://hal.archives-ouvertes.fr/hal-02933669 ; Journal of Proteome Research, American Chemical Society, 2020, ⟨10.1021/acs.jproteome.0c00383⟩

    2020  

    Abstract: International ... ...

    Abstract International audience
    Keywords [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] ; covid19
    Language English
    Publishing date 2020-09-07
    Publisher HAL CCSD
    Publishing country fr
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Comparative Study of Single-stranded Oligonucleotides Secondary Structure Prediction Tools

    Thomas Binet / Séverine Padiolleau-Lefèvre / Stéphane Octave / Bérangère Avalle / Irene Maffucci

    BMC Bioinformatics, Vol 24, Iss 1, Pp 1-

    2023  Volume 20

    Abstract: Abstract Background Single-stranded nucleic acids (ssNAs) have important biological roles and a high biotechnological potential linked to their ability to bind to numerous molecular targets. This depends on the different spatial conformations they can ... ...

    Abstract Abstract Background Single-stranded nucleic acids (ssNAs) have important biological roles and a high biotechnological potential linked to their ability to bind to numerous molecular targets. This depends on the different spatial conformations they can assume. The first level of ssNAs spatial organisation corresponds to their base pairs pattern, i.e. their secondary structure. Many computational tools have been developed to predict the ssNAs secondary structures, making the choice of the appropriate tool difficult, and an up-to-date guide on the limits and applicability of current secondary structure prediction tools is missing. Therefore, we performed a comparative study of the performances of 9 freely available tools (mfold, RNAfold, CentroidFold, CONTRAfold, MC-Fold, LinearFold, UFold, SPOT-RNA, and MXfold2) on a dataset of 538 ssNAs with known experimental secondary structure. Results The minimum free energy-based tools, namely mfold and RNAfold, and some tools based on artificial intelligence, namely CONTRAfold and MXfold2, provided the best results, with $$\sim 50\%$$ ∼ 50 % of exact predictions, whilst MC-fold seemed to be the worst performing tool, with only $$\sim 11\%$$ ∼ 11 % of exact predictions. In addition, UFold and SPOT-RNA are the only options for pseudoknots prediction. Including in the analysis of mfold and RNAfold results 5–10 suboptimal solutions further improved the performances of these tools. Nevertheless, we could observe issues in predicting particular motifs, such as multiple-ways junctions and mini-dumbbells, or the ssNAs whose structure has been determined in complex with a protein. In addition, our benchmark shows that some effort has to be paid for ssDNA secondary structure predictions. Conclusions In general, Mfold, RNAfold, and MXfold2 seem to currently be the best choice for the ssNAs secondary structure prediction, although they still show some limits linked to specific structural motifs. Nevertheless, actual trends suggest that artificial intelligence has a high potential to ...
    Keywords Single-stranded oligonucleotides ; Secondary structure ; Prediction ; Benchmark ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Biology (General) ; QH301-705.5
    Language English
    Publishing date 2023-11-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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