Glioma-Targeted Therapeutics: Computer-Aided Drug Design Prospective
Amongst the several types of brain cancers known to humankind, glioma is one of the most severe and life-threatening types of cancer, comprising 40% of all primary brain tumors. Recent reports have shown the incident rate of gliomas to be 6 per 100,000 individuals per year globally. Despite the vari...
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| Veröffentlicht in: | The Protein Journal Jg. 40; H. 5; S. 601 - 655 |
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01.10.2021
Springer Springer Nature B.V |
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| ISSN: | 1572-3887, 1875-8355, 1573-4943, 1875-8355 |
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| Abstract | Amongst the several types of brain cancers known to humankind, glioma is one of the most severe and life-threatening types of cancer, comprising 40% of all primary brain tumors. Recent reports have shown the incident rate of gliomas to be 6 per 100,000 individuals per year globally. Despite the various therapeutics used in the treatment of glioma, patient survival rate remains at a median of 15 months after undergoing first-line treatment including surgery, radiation, and chemotherapy with Temozolomide. As such, the discovery of newer and more effective therapeutic agents is imperative for patient survival rate. The advent of computer-aided drug design in the development of drug discovery has emerged as a powerful means to ascertain potential hit compounds with distinctively high therapeutic effectiveness against glioma. This review encompasses the recent advances of bio-computational in-silico modeling that have elicited the discovery of small molecule inhibitors and/or drugs against various therapeutic targets in glioma. The relevant information provided in this report will assist researchers, especially in the drug design domains, to develop more effective therapeutics against this global disease. |
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| AbstractList | Amongst the several types of brain cancers known to humankind, glioma is one of the most severe and life-threatening types of cancer, comprising 40% of all primary brain tumors. Recent reports have shown the incident rate of gliomas to be 6 per 100,000 individuals per year globally. Despite the various therapeutics used in the treatment of glioma, patient survival rate remains at a median of 15 months after undergoing first-line treatment including surgery, radiation, and chemotherapy with Temozolomide. As such, the discovery of newer and more effective therapeutic agents is imperative for patient survival rate. The advent of computer-aided drug design in the development of drug discovery has emerged as a powerful means to ascertain potential hit compounds with distinctively high therapeutic effectiveness against glioma. This review encompasses the recent advances of bio-computational in-silico modeling that have elicited the discovery of small molecule inhibitors and/or drugs against various therapeutic targets in glioma. The relevant information provided in this report will assist researchers, especially in the drug design domains, to develop more effective therapeutics against this global disease. Amongst the several types of brain cancers known to humankind, glioma is one of the most severe and life-threatening types of cancer, comprising 40% of all primary brain tumors. Recent reports have shown the incident rate of gliomas to be 6 per 100,000 individuals per year globally. Despite the various therapeutics used in the treatment of glioma, patient survival rate remains at a median of 15 months after undergoing first-line treatment including surgery, radiation, and chemotherapy with Temozolomide. As such, the discovery of newer and more effective therapeutic agents is imperative for patient survival rate. The advent of computer-aided drug design in the development of drug discovery has emerged as a powerful means to ascertain potential hit compounds with distinctively high therapeutic effectiveness against glioma. This review encompasses the recent advances of bio-computational in-silico modeling that have elicited the discovery of small molecule inhibitors and/or drugs against various therapeutic targets in glioma. The relevant information provided in this report will assist researchers, especially in the drug design domains, to develop more effective therapeutics against this global disease.Amongst the several types of brain cancers known to humankind, glioma is one of the most severe and life-threatening types of cancer, comprising 40% of all primary brain tumors. Recent reports have shown the incident rate of gliomas to be 6 per 100,000 individuals per year globally. Despite the various therapeutics used in the treatment of glioma, patient survival rate remains at a median of 15 months after undergoing first-line treatment including surgery, radiation, and chemotherapy with Temozolomide. As such, the discovery of newer and more effective therapeutic agents is imperative for patient survival rate. The advent of computer-aided drug design in the development of drug discovery has emerged as a powerful means to ascertain potential hit compounds with distinctively high therapeutic effectiveness against glioma. This review encompasses the recent advances of bio-computational in-silico modeling that have elicited the discovery of small molecule inhibitors and/or drugs against various therapeutic targets in glioma. The relevant information provided in this report will assist researchers, especially in the drug design domains, to develop more effective therapeutics against this global disease. Amongst the several types of brain cancers known to humankind, glioma is one of the most severe and life-threatening types of cancer, comprising 40% of all primary brain tumors. Recent reports have shown the incident rate of gliomas to be 6 per 100,000 individuals per year globally. Despite the various therapeutics used in the treatment of glioma, patient survival rate remains at a median of 15 months after undergoing first-line treatment including surgery, radiation, and chemotherapy with Temozolomide. As such, the discovery of newer and more effective therapeutic agents is imperative for patient survival rate. The advent of computer-aided drug design in the development of drug discovery has emerged as a powerful means to ascertain potential hit compounds with distinctively high therapeutic effectiveness against glioma. This review encompasses the recent advances of bio-computational in-silico modeling that have elicited the discovery of small molecule inhibitors and/or drugs against various therapeutic targets in glioma. The relevant information provided in this report will assist researchers, especially in the drug design domains, to develop more effective therapeutics against this global disease. |
| Audience | Academic |
| Author | Agoni, Clement Poonan, Preantha Ibrahim, Mahmoud A. A. Soliman, Mahmoud E. S. |
| Author_xml | – sequence: 1 givenname: Preantha surname: Poonan fullname: Poonan, Preantha organization: Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus – sequence: 2 givenname: Clement surname: Agoni fullname: Agoni, Clement organization: Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus – sequence: 3 givenname: Mahmoud A. A. surname: Ibrahim fullname: Ibrahim, Mahmoud A. A. organization: Computational Chemistry Laboratory, Chemistry Department, Faculty of Science, Minia University – sequence: 4 givenname: Mahmoud E. S. orcidid: 0000-0002-0619-2109 surname: Soliman fullname: Soliman, Mahmoud E. S. email: soliman@ukzn.ac.za organization: Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34590194$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1007_s13258_022_01312_2 crossref_primary_10_1016_j_gene_2023_147489 crossref_primary_10_1111_cns_14715 crossref_primary_10_1007_s12094_023_03167_9 crossref_primary_10_2174_0109298673266672231121173432 crossref_primary_10_1002_advs_202412517 crossref_primary_10_1016_j_ejmech_2024_117171 crossref_primary_10_1002_glia_24630 crossref_primary_10_1093_neuonc_noad159 crossref_primary_10_3389_fonc_2022_993316 crossref_primary_10_1093_neuonc_noad102 crossref_primary_10_1155_2023_1680634 crossref_primary_10_2174_0929867329666220919114919 crossref_primary_10_3389_fphar_2024_1485919 |
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| ContentType | Journal Article |
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| Keywords | Glioma treatment Computer-aided drug design Small molecule inhibitors Therapeutic targets |
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| PublicationCentury | 2000 |
| PublicationDate | 20211000 2021-10-00 20211001 |
| PublicationDateYYYYMMDD | 2021-10-01 |
| PublicationDate_xml | – month: 10 year: 2021 text: 20211000 |
| PublicationDecade | 2020 |
| PublicationPlace | New York |
| PublicationPlace_xml | – name: New York – name: Netherlands |
| PublicationTitle | The Protein Journal |
| PublicationTitleAbbrev | Protein J |
| PublicationTitleAlternate | Protein J |
| PublicationYear | 2021 |
| Publisher | Springer US Springer Springer Nature B.V |
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