Investigating the Interaction Mechanism of CAT-BT-Br and Key Residue Mutations for Castration-Resistant Prostate Cancer through Molecular Dynamics Simulation
Bibliographic record
Abstract
Prostate cancer is the second most common cancer in men, second only to lung cancer. Castration-resistant prostate cancer (CRPC) was formerly known as hormone-resistant prostate cancer. The aim of this study is to reveal the effect of key residue mutations on the binding mechanism between catalase (CAT) and benzaldehyde thiourea derivatives (BT-Br), providing theoretical support for the development of novel CAT inhibitors. This article analyzes the structural stability, binding energy and decomposition, hydrogen bonding, etc. of wild-type (WT) and multiple mutations systems. The results showed that, in addition to the R203A mutant, all mutation systems significantly enhanced the binding ability of CAT to BT-Br, and their binding free energy contribution mainly came from van der Waals interactions. Hydrogen bond analysis shows that the hydrogen bond occupancy rate of the WT system is relatively low, while mutations such as V302A have a hydrogen bond occupancy rate as high as 93.05%, indicating a significant enhancement in their binding ability. In addition, mutations have limited impact on the overall stability of proteins, but some mutations such as Y215A and V302A significantly alter the binding site and direction of proteins. The results of principal component analysis (PCA) in other systems are consistent with those of root mean square fluctuation (RMSF) analysis, and the binding site shows little movement. This study not only elucidates the microscopic effects of key residue mutations on the binding mechanism between CAT and BT-Br but also provides new targets and drug design ideas for prostate cancer treatment based on iron death induction strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".