Force Field Parameters for Fe2+ 4S2− 4 Clusters of Dihydropyrimidine Dehydrogenase, the 5-Fluorouracil Cancer Drug Deactivation Protein: A Step towards In Silico Pharmacogenomics Studies
- Tendwa, Maureen B, Chebon-Bore, Lorna, Lobb, Kevin A, Musyoka, Thommas M, Taştan Bishop, Özlem
- Authors: Tendwa, Maureen B , Chebon-Bore, Lorna , Lobb, Kevin A , Musyoka, Thommas M , Taştan Bishop, Özlem
- Date: 2021
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/451078 , vital:75016 , xlink:href="https://doi.org/10.3390/molecules26102929 "
- Description: The dimeric dihydropyrimidine dehydrogenase (DPD), metalloenzyme, an adjunct anti-cancer drug target, contains highly specialized 4 × Fe2+4S2−4 clusters per chain. These clusters facilitate the catalysis of the rate-limiting step in the pyrimidine degradation pathway through a harmonized electron transfer cascade that triggers a redox catabolic reaction. In the process, the bulk of the administered 5-fluorouracil (5-FU) cancer drug is inactivated, while a small proportion is activated to nucleic acid antimetabolites. The occurrence of missense mutations in DPD protein within the general population, including those of African descent, has adverse toxicity effects due to altered 5-FU metabolism. Thus, deciphering mutation effects on protein structure and function is vital, especially for precision medicine purposes. We previously proposed combining molecular dynamics (MD) and dynamic residue network (DRN) analysis to decipher the molecular mechanisms of missense mutations in other proteins. However, the presence of Fe2+4S2−4 clusters in DPD poses a challenge for such in silico studies. The existing AMBER force field parameters cannot accurately describe the Fe2+ center coordination exhibited by this enzyme. Therefore, this study aimed to derive AMBER force field parameters for DPD enzyme Fe2+ centers, using the original Seminario method and the collation features Visual Force Field Derivation Toolkit as a supportive approach. All-atom MD simulations were performed to validate the results. Both approaches generated similar force field parameters, which accurately described the human DPD protein Fe2+4S2−4 cluster architecture. This information is crucial and opens new avenues for in silico cancer pharmacogenomics and drug discovery related research on 5-FU drug efficacy and toxicity issues.
- Full Text:
- Date Issued: 2021
- Authors: Tendwa, Maureen B , Chebon-Bore, Lorna , Lobb, Kevin A , Musyoka, Thommas M , Taştan Bishop, Özlem
- Date: 2021
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/451078 , vital:75016 , xlink:href="https://doi.org/10.3390/molecules26102929 "
- Description: The dimeric dihydropyrimidine dehydrogenase (DPD), metalloenzyme, an adjunct anti-cancer drug target, contains highly specialized 4 × Fe2+4S2−4 clusters per chain. These clusters facilitate the catalysis of the rate-limiting step in the pyrimidine degradation pathway through a harmonized electron transfer cascade that triggers a redox catabolic reaction. In the process, the bulk of the administered 5-fluorouracil (5-FU) cancer drug is inactivated, while a small proportion is activated to nucleic acid antimetabolites. The occurrence of missense mutations in DPD protein within the general population, including those of African descent, has adverse toxicity effects due to altered 5-FU metabolism. Thus, deciphering mutation effects on protein structure and function is vital, especially for precision medicine purposes. We previously proposed combining molecular dynamics (MD) and dynamic residue network (DRN) analysis to decipher the molecular mechanisms of missense mutations in other proteins. However, the presence of Fe2+4S2−4 clusters in DPD poses a challenge for such in silico studies. The existing AMBER force field parameters cannot accurately describe the Fe2+ center coordination exhibited by this enzyme. Therefore, this study aimed to derive AMBER force field parameters for DPD enzyme Fe2+ centers, using the original Seminario method and the collation features Visual Force Field Derivation Toolkit as a supportive approach. All-atom MD simulations were performed to validate the results. Both approaches generated similar force field parameters, which accurately described the human DPD protein Fe2+4S2−4 cluster architecture. This information is crucial and opens new avenues for in silico cancer pharmacogenomics and drug discovery related research on 5-FU drug efficacy and toxicity issues.
- Full Text:
- Date Issued: 2021
Introducing DerivatizeME and its Application in the Augmentation of a Natural Product Library
- Sigauke, Lester T, Taştan Bishop, Özlem, Lobb, Kevin A
- Authors: Sigauke, Lester T , Taştan Bishop, Özlem , Lobb, Kevin A
- Date: 2021
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/451120 , vital:75020 , xlink:href="https://doi.org/10.1142/S2737416521500101"
- Description: The large chemical space universe can be traversed by screening libraries of compounds that possess novel medicinally relevant chemistries, properties and complexity criteria. These libraries can be populated with the use of exhaustive, de novo approaches or inspired, combinatorial approaches. By assuming that natural products within screening libraries may be classified as a source of feedstock for populating virtual libraries, they can act as scaffolds upon which exhaustive approaches may be used in exploring chemical space. In order to achieve this, we have built DerivatizeME as a tool that enumerates derivatives of query compounds in order to evaluate their relevance for further assessment and development. This technique was applied to natural products present in the South African natural compound database (SANCDB). By expanding the chemical space of SANCDB compounds through the generation of SANCDB derivatives, we were able to graduate some natural products that were in undesirable regions of medicinally relevant chemical space, to acceptable regions of this chemical space. These modified scaffolds are available for further development, testing and evaluation in a manner similar to natural product driven focused libraries. The natural product parent is used, through its derivatives, instead of being discarded from screening protocols. This approach has the potential to enhance the efficiency of the natural product library in providing successful hits, amplifying the potential that they possess to access both novel bioactives and privileged scaffolds which may have otherwise been overlooked.
- Full Text:
- Date Issued: 2021
- Authors: Sigauke, Lester T , Taştan Bishop, Özlem , Lobb, Kevin A
- Date: 2021
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/451120 , vital:75020 , xlink:href="https://doi.org/10.1142/S2737416521500101"
- Description: The large chemical space universe can be traversed by screening libraries of compounds that possess novel medicinally relevant chemistries, properties and complexity criteria. These libraries can be populated with the use of exhaustive, de novo approaches or inspired, combinatorial approaches. By assuming that natural products within screening libraries may be classified as a source of feedstock for populating virtual libraries, they can act as scaffolds upon which exhaustive approaches may be used in exploring chemical space. In order to achieve this, we have built DerivatizeME as a tool that enumerates derivatives of query compounds in order to evaluate their relevance for further assessment and development. This technique was applied to natural products present in the South African natural compound database (SANCDB). By expanding the chemical space of SANCDB compounds through the generation of SANCDB derivatives, we were able to graduate some natural products that were in undesirable regions of medicinally relevant chemical space, to acceptable regions of this chemical space. These modified scaffolds are available for further development, testing and evaluation in a manner similar to natural product driven focused libraries. The natural product parent is used, through its derivatives, instead of being discarded from screening protocols. This approach has the potential to enhance the efficiency of the natural product library in providing successful hits, amplifying the potential that they possess to access both novel bioactives and privileged scaffolds which may have otherwise been overlooked.
- Full Text:
- Date Issued: 2021
SANCDB: an update on South African natural compounds and their readily available analogs
- Diallo, Bakary N, Glenister, Michael, Musyoka, Thommas M, Lobb, Kevin A, Taştan Bishop, Özlem
- Authors: Diallo, Bakary N , Glenister, Michael , Musyoka, Thommas M , Lobb, Kevin A , Taştan Bishop, Özlem
- Date: 2021
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/451154 , vital:75023 , xlink:href="https://doi.org/10.1186/s13321-021-00514-2"
- Description: The dimeric dihydropyrimidine dehydrogenase (DPD), metalloenzyme, an adjunct anti-cancer drug target, contains highly specialized 4 × Fe2+4S2−4 clusters per chain. These clusters facilitate the catalysis of the rate-limiting step in the pyrimidine degradation pathway through a harmonized electron transfer cascade that triggers a redox catabolic reaction. In the process, the bulk of the administered 5-fluorouracil (5-FU) cancer drug is inactivated, while a small proportion is activated to nucleic acid antimetabolites. The occurrence of missense mutations in DPD protein within the general population, including those of African descent, has adverse toxicity effects due to altered 5-FU metabolism. Thus, deciphering mutation effects on protein structure and function is vital, especially for precision medicine purposes. We previously proposed combining molecular dynamics (MD) and dynamic residue network (DRN) analysis to decipher the molecular mechanisms of missense mutations in other proteins. However, the presence of Fe2+4S2−4 clusters in DPD poses a challenge for such in silico studies. The existing AMBER force field parameters cannot accurately describe the Fe2+ center coordination exhibited by this enzyme. Therefore, this study aimed to derive AMBER force field parameters for DPD enzyme Fe2+ centers, using the original Seminario method and the collation features Visual Force Field Derivation Toolkit as a supportive approach. All-atom MD simulations were performed to validate the results. Both approaches generated similar force field parameters, which accurately described the human DPD protein Fe2+4S2−4 cluster architecture. This information is crucial and opens new avenues for in silico cancer pharmacogenomics and drug discovery related research on 5-FU drug efficacy and toxicity issues.
- Full Text:
- Date Issued: 2021
- Authors: Diallo, Bakary N , Glenister, Michael , Musyoka, Thommas M , Lobb, Kevin A , Taştan Bishop, Özlem
- Date: 2021
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/451154 , vital:75023 , xlink:href="https://doi.org/10.1186/s13321-021-00514-2"
- Description: The dimeric dihydropyrimidine dehydrogenase (DPD), metalloenzyme, an adjunct anti-cancer drug target, contains highly specialized 4 × Fe2+4S2−4 clusters per chain. These clusters facilitate the catalysis of the rate-limiting step in the pyrimidine degradation pathway through a harmonized electron transfer cascade that triggers a redox catabolic reaction. In the process, the bulk of the administered 5-fluorouracil (5-FU) cancer drug is inactivated, while a small proportion is activated to nucleic acid antimetabolites. The occurrence of missense mutations in DPD protein within the general population, including those of African descent, has adverse toxicity effects due to altered 5-FU metabolism. Thus, deciphering mutation effects on protein structure and function is vital, especially for precision medicine purposes. We previously proposed combining molecular dynamics (MD) and dynamic residue network (DRN) analysis to decipher the molecular mechanisms of missense mutations in other proteins. However, the presence of Fe2+4S2−4 clusters in DPD poses a challenge for such in silico studies. The existing AMBER force field parameters cannot accurately describe the Fe2+ center coordination exhibited by this enzyme. Therefore, this study aimed to derive AMBER force field parameters for DPD enzyme Fe2+ centers, using the original Seminario method and the collation features Visual Force Field Derivation Toolkit as a supportive approach. All-atom MD simulations were performed to validate the results. Both approaches generated similar force field parameters, which accurately described the human DPD protein Fe2+4S2−4 cluster architecture. This information is crucial and opens new avenues for in silico cancer pharmacogenomics and drug discovery related research on 5-FU drug efficacy and toxicity issues.
- Full Text:
- Date Issued: 2021
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