In Silico Subtractive Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against <em>Streptococcus pneumoniae</em> Strain D39
<i>Streptococcus pneumoniae</i> is a notorious Gram-positive pathogen present asymptomatically in the nasophayrnx of humans. According to the World Health Organization (W.H.O), pneumococcus causes approximately one million deaths yearly. Antibiotic resistance in <i>S. pneumoniae<...
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MDPI AG
2023-05-01
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| author | Ashwag Shami Nada K. Alharbi Fatimah A. Al-Saeed Aiman A. Alsaegh Khalid M. Al Syaad Ibrahim H. A. Abd El-Rahim Yasser Sabry Mostafa Ahmed Ezzat Ahmed |
| author_facet | Ashwag Shami Nada K. Alharbi Fatimah A. Al-Saeed Aiman A. Alsaegh Khalid M. Al Syaad Ibrahim H. A. Abd El-Rahim Yasser Sabry Mostafa Ahmed Ezzat Ahmed |
| author_sort | Ashwag Shami |
| collection | DOAJ |
| description | <i>Streptococcus pneumoniae</i> is a notorious Gram-positive pathogen present asymptomatically in the nasophayrnx of humans. According to the World Health Organization (W.H.O), pneumococcus causes approximately one million deaths yearly. Antibiotic resistance in <i>S. pneumoniae</i> is raising considerable concern around the world. There is an immediate need to address the major issues that have arisen as a result of persistent infections caused by <i>S. pneumoniae</i>. In the present study, subtractive proteomics was used in which the entire proteome of the pathogen consisting of 1947 proteins is effectively decreased to a finite number of possible targets. Various kinds of bioinformatics tools and software were applied for the discovery of novel inhibitors. The CD-HIT analysis revealed 1887 non-redundant sequences from the entire proteome. These non-redundant proteins were submitted to the BLASTp against the human proteome and 1423 proteins were screened as non-homologous. Further, databases of essential genes (DEGG) and J browser identified almost 171 essential proteins. Moreover, non-homologous, essential proteins were subjected in KEGG Pathway Database which shortlisted six unique proteins. In addition, the subcellular localization of these unique proteins was checked and cytoplasmic proteins were chosen for the druggability analysis, which resulted in three proteins, namely DNA binding response regulator (SPD_1085), UDP-N-acetylmuramate—L-alanine Ligase (SPD_1349) and RNA polymerase sigma factor (SPD_0958), which can act as a promising potent drug candidate to limit the toxicity caused by <i>S. pneumoniae</i>. The 3D structures of these proteins were predicted by Swiss Model, utilizing the homology modeling approach. Later, molecular docking by PyRx software 0.8 version was used to screen a library of phytochemicals retrieved from PubChem and ZINC databases and already approved drugs from DrugBank database against novel druggable targets to check their binding affinity with receptor proteins. The top two molecules from each receptor protein were selected based on the binding affinity, RMSD value, and the highest conformation. Finally, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses were carried out by utilizing the SWISS ADME and Protox tools. This research supported the discovery of cost-effective drugs against <i>S. pneumoniae</i>. However, more in vivo/in vitro research should be conducted on these targets to investigate their pharmacological efficacy and their function as efficient inhibitors. |
| first_indexed | 2024-03-11T03:34:15Z |
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| last_indexed | 2024-03-11T03:34:15Z |
| publishDate | 2023-05-01 |
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| spelling | doaj.art-372d1bc59d074c9abbbce03aa8bafb452023-11-18T02:09:03ZengMDPI AGLife2075-17292023-05-01135112810.3390/life13051128In Silico Subtractive Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against <em>Streptococcus pneumoniae</em> Strain D39Ashwag Shami0Nada K. Alharbi1Fatimah A. Al-Saeed2Aiman A. Alsaegh3Khalid M. Al Syaad4Ibrahim H. A. Abd El-Rahim5Yasser Sabry Mostafa6Ahmed Ezzat Ahmed7Department of Biology, College of Sciences, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi ArabiaDepartment of Biology, College of Sciences, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi ArabiaResearch Centre, Department of Biology, College of Science, King Khalid University, Abha 61413, Saudi ArabiaDepartment of Laboratory Medicine, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah Al-Mukarramah 24382, Saudi ArabiaBiology Department, Faculty of Science, King Khalid University, P.O. Box 9004, Abha 61413, Saudi ArabiaDepartment of Environmental and Health Research, Umm Al-Qura University, P.O. Box 6287, Makkah Al-Mukarramah 21955, Saudi ArabiaBiology Department, Faculty of Science, King Khalid University, P.O. Box 9004, Abha 61413, Saudi ArabiaBiology Department, Faculty of Science, King Khalid University, P.O. Box 9004, Abha 61413, Saudi Arabia<i>Streptococcus pneumoniae</i> is a notorious Gram-positive pathogen present asymptomatically in the nasophayrnx of humans. According to the World Health Organization (W.H.O), pneumococcus causes approximately one million deaths yearly. Antibiotic resistance in <i>S. pneumoniae</i> is raising considerable concern around the world. There is an immediate need to address the major issues that have arisen as a result of persistent infections caused by <i>S. pneumoniae</i>. In the present study, subtractive proteomics was used in which the entire proteome of the pathogen consisting of 1947 proteins is effectively decreased to a finite number of possible targets. Various kinds of bioinformatics tools and software were applied for the discovery of novel inhibitors. The CD-HIT analysis revealed 1887 non-redundant sequences from the entire proteome. These non-redundant proteins were submitted to the BLASTp against the human proteome and 1423 proteins were screened as non-homologous. Further, databases of essential genes (DEGG) and J browser identified almost 171 essential proteins. Moreover, non-homologous, essential proteins were subjected in KEGG Pathway Database which shortlisted six unique proteins. In addition, the subcellular localization of these unique proteins was checked and cytoplasmic proteins were chosen for the druggability analysis, which resulted in three proteins, namely DNA binding response regulator (SPD_1085), UDP-N-acetylmuramate—L-alanine Ligase (SPD_1349) and RNA polymerase sigma factor (SPD_0958), which can act as a promising potent drug candidate to limit the toxicity caused by <i>S. pneumoniae</i>. The 3D structures of these proteins were predicted by Swiss Model, utilizing the homology modeling approach. Later, molecular docking by PyRx software 0.8 version was used to screen a library of phytochemicals retrieved from PubChem and ZINC databases and already approved drugs from DrugBank database against novel druggable targets to check their binding affinity with receptor proteins. The top two molecules from each receptor protein were selected based on the binding affinity, RMSD value, and the highest conformation. Finally, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses were carried out by utilizing the SWISS ADME and Protox tools. This research supported the discovery of cost-effective drugs against <i>S. pneumoniae</i>. However, more in vivo/in vitro research should be conducted on these targets to investigate their pharmacological efficacy and their function as efficient inhibitors.https://www.mdpi.com/2075-1729/13/5/1128<i>Streptococcus pneumoniae</i>subtractive proteomicsmolecular dockingessential proteinsADMET analysis |
| spellingShingle | Ashwag Shami Nada K. Alharbi Fatimah A. Al-Saeed Aiman A. Alsaegh Khalid M. Al Syaad Ibrahim H. A. Abd El-Rahim Yasser Sabry Mostafa Ahmed Ezzat Ahmed In Silico Subtractive Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against <em>Streptococcus pneumoniae</em> Strain D39 Life <i>Streptococcus pneumoniae</i> subtractive proteomics molecular docking essential proteins ADMET analysis |
| title | In Silico Subtractive Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against <em>Streptococcus pneumoniae</em> Strain D39 |
| title_full | In Silico Subtractive Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against <em>Streptococcus pneumoniae</em> Strain D39 |
| title_fullStr | In Silico Subtractive Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against <em>Streptococcus pneumoniae</em> Strain D39 |
| title_full_unstemmed | In Silico Subtractive Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against <em>Streptococcus pneumoniae</em> Strain D39 |
| title_short | In Silico Subtractive Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against <em>Streptococcus pneumoniae</em> Strain D39 |
| title_sort | in silico subtractive proteomics and molecular docking approaches for the identification of novel inhibitors against em streptococcus pneumoniae em strain d39 |
| topic | <i>Streptococcus pneumoniae</i> subtractive proteomics molecular docking essential proteins ADMET analysis |
| url | https://www.mdpi.com/2075-1729/13/5/1128 |
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