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Novel PARP14 inhibitors: their potency, their selectivity and their structures

Hansson, Anton LU (2024) KEML10 20232
Department of Chemistry
Abstract
Introduction: PARP14 is overexpressed and plays an essential role in the survival of many kinds of cancer cells and in inflammatory diseases, and its inhibition could prove to be a future medical treatment.
Background: It is still unknown which structures contribute more to PARP14 binding, and because of how conserved the catalytic domain is in the PARP family, the inhibitors need to be selective so as to not bind to an unrelated PARP enzyme.
Aim(s): Which molecules are the better PARP14 inhibitors, how do their structures play a role, and how selective are they?
Methods: A PARP14 protein construct was expressed with a His tag in BL21(DE3) E. Coli cells, which were lysed and then purified through IMAC FPLC. The purity was observed... (More)
Introduction: PARP14 is overexpressed and plays an essential role in the survival of many kinds of cancer cells and in inflammatory diseases, and its inhibition could prove to be a future medical treatment.
Background: It is still unknown which structures contribute more to PARP14 binding, and because of how conserved the catalytic domain is in the PARP family, the inhibitors need to be selective so as to not bind to an unrelated PARP enzyme.
Aim(s): Which molecules are the better PARP14 inhibitors, how do their structures play a role, and how selective are they?
Methods: A PARP14 protein construct was expressed with a His tag in BL21(DE3) E. Coli cells, which were lysed and then purified through IMAC FPLC. The purity was observed through SDS-PAGE, the concentration was measured through spectrophotometry and the activity was determined using the MacroGreen assay.
Results: The purified PARP14 batches had concentrations of 0.198 ± 0.016 mg/mL and 0.724 ± 0.028 mg/mL. The batches were less concentrated, less active and more impure than a batch from a previous study, so that one was used for inhibition tests instead. These tests showed the most effective inhibitors were, from most to least inhibitive: 7, Takeda, 12, 35, 37, 3, 6 and 2. Comparison of compound structures showed that hexanol groups, five- or six-membered rings and possibly an amine group contributed to PARP14 inhibition, while a sulphur atom in one position decreased inhibition significantly. Similar tests with PARP1 and 10 showed 7 preferred PARP1 and 35 preferred both PARP1 and 10, while Takeda, which was also tested with PARP15, preferred PARP14 over all of them.
Conclusion: 7 was the best PARP14 inhibitor, while Takeda was the most PARP14-selective. Having a five- or six-membered ring, a hexanol group and possibly an amine group increased inhibition, but a sulphur atom in one position decreased it. However, further research is required in regards to structural analysis. (Less)
Popular Abstract
Cancer is a major public health issue that plagues millions of people around the world every year. Its cell reproduction rate, its many variants and its connection to the host’s own DNA means that it cannot be treated like most other diseases. One of the possible treatments for cancers includes the administration of drugs that selectively target the cancerous cells, such as inhibitors, which are molecules made to block enzymes that keep the cancer cells alive. Poly-ADP-ribose polymerase 14 (PARP14) is one of these enzymes, and the goal of this study was to test several inhibitors to see which were best at blocking PARP14.
This was tested by another protein called MacroGreen that binds to proteins, including PARP14 itself, that have been... (More)
Cancer is a major public health issue that plagues millions of people around the world every year. Its cell reproduction rate, its many variants and its connection to the host’s own DNA means that it cannot be treated like most other diseases. One of the possible treatments for cancers includes the administration of drugs that selectively target the cancerous cells, such as inhibitors, which are molecules made to block enzymes that keep the cancer cells alive. Poly-ADP-ribose polymerase 14 (PARP14) is one of these enzymes, and the goal of this study was to test several inhibitors to see which were best at blocking PARP14.
This was tested by another protein called MacroGreen that binds to proteins, including PARP14 itself, that have been chemically transformed by the enzyme, creating fluorescent light. This is a useful tool for measuring inhibitors’ efficiency because the better they are at blocking PARP14 activity, the less fluorescent light will be produced. Through this, inhibitor potency can be determined by comparing the relative fluorescent light levels at different inhibitor concentrations together with PARP14. This test was also carried out with a few other members of the PARP enzyme family, because we don’t want the inhibitors to block any enzymes that are unrelated to the cancer.
The results showed that inhibitor 7 was the best at blocking PARP14 out of those tested, while inhibitor 2 was the weakest. Some did not have a clear result at all due to weak and varying signals, most likely because the inhibitor solutions’ molecules had started to fall out of solution, making inhibition harder. Despite being the best PARP14 inhibitor, 7 was better at blocking PARP1, meaning it isn’t very specific to PARP14. More inhibitors need to be tested with other PARPs to give a clearer picture, however.
Structural comparisons between inhibitors also highlighted which kinds of structures made it easier to block PARP14, and this information can be used for the designs of future inhibitors. (Less)
Please use this url to cite or link to this publication:
author
Hansson, Anton LU
supervisor
organization
course
KEML10 20232
year
type
M2 - Bachelor Degree
subject
keywords
ADP-ribosylation, Biochemistry, Inhibition, MacroGreen, PARP, Selectivity
language
English
id
9143848
date added to LUP
2024-01-12 10:06:23
date last changed
2024-01-12 10:06:23
@misc{9143848,
  abstract     = {{Introduction: PARP14 is overexpressed and plays an essential role in the survival of many kinds of cancer cells and in inflammatory diseases, and its inhibition could prove to be a future medical treatment.
Background: It is still unknown which structures contribute more to PARP14 binding, and because of how conserved the catalytic domain is in the PARP family, the inhibitors need to be selective so as to not bind to an unrelated PARP enzyme.
Aim(s): Which molecules are the better PARP14 inhibitors, how do their structures play a role, and how selective are they?
Methods: A PARP14 protein construct was expressed with a His tag in BL21(DE3) E. Coli cells, which were lysed and then purified through IMAC FPLC. The purity was observed through SDS-PAGE, the concentration was measured through spectrophotometry and the activity was determined using the MacroGreen assay.
Results: The purified PARP14 batches had concentrations of 0.198 ± 0.016 mg/mL and 0.724 ± 0.028 mg/mL. The batches were less concentrated, less active and more impure than a batch from a previous study, so that one was used for inhibition tests instead. These tests showed the most effective inhibitors were, from most to least inhibitive: 7, Takeda, 12, 35, 37, 3, 6 and 2. Comparison of compound structures showed that hexanol groups, five- or six-membered rings and possibly an amine group contributed to PARP14 inhibition, while a sulphur atom in one position decreased inhibition significantly. Similar tests with PARP1 and 10 showed 7 preferred PARP1 and 35 preferred both PARP1 and 10, while Takeda, which was also tested with PARP15, preferred PARP14 over all of them.
Conclusion: 7 was the best PARP14 inhibitor, while Takeda was the most PARP14-selective. Having a five- or six-membered ring, a hexanol group and possibly an amine group increased inhibition, but a sulphur atom in one position decreased it. However, further research is required in regards to structural analysis.}},
  author       = {{Hansson, Anton}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Novel PARP14 inhibitors: their potency, their selectivity and their structures}},
  year         = {{2024}},
}