Computational Study of Triterpenoids of Ganoderma lucidum with Aspartic Protease Enzymes for Discovering HIV-1 and Plasmepsin Inhibitors
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Bibliographic record
Abstract
Rapid resistance development of HIV-1 and Plasmodium falciparum parasite requires discovery of more potent new drugs. Aspartic protease enzymes expressed by HIV-1 and P. falciparum could be used as important drug targets. The catalytic site is located at the bottom of a cleft in the enzyme surface and consists of triad Asp25, Thr26, Gly27. Important aspartic acids are Asp32 and Asp215. Aspartic proteases are inhibited by pepstatin-A, a naturally occurring peptide containing two statins, which replace the amino acids. The hydroxyl group of the statin binds tightly to the catalytically-active aspartic acid residues in the active site of protease, thereby mimicking the transition state of the peptide cleavage. Previous study proved that ganoderiol-F, a triterpenoid isolated from the stem of Ganoderma sinense showed higher affinity towards HIV-1 protease (binding energy= -11.40 kcal/mol and Ki= 4.68 nM) than to plasmepsin I (binding energy= -9.96 kcal/mol and Ki= 50.94 nM). In this paper, computational studies of G. lucidum triterpenoids with aspartic protease enzymes of HIV-1 and plasmepsin I, were performed using AutoDock 4.2. Nelfinavir and KNI-10006 were used as the standards for HIV-1 protease and plasmepsin I, respectively. The four triterpenoids are able to interact with both enzymes. Ganoderat acid-B showed the best affinity to HIV-1 protease (binding energy= -7.49 kcal/mol and Ki= 0.001 mM) which is better than nelfinavir. Furthermore, the best affinity to Plasmepsin I is showed by ganodermanondiol (binding energy= -7.14 kcal/mol and Ki= 0.005 mM which is better than KNI-10006. According to the values of binding energy and inhibition constant, triterpenoids of G. lucidum could be developed further as both anti-HIV and anti-malaria.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it