Function Switch of a Fungal Sesterterpene Synthase through Molecular Dynamics Simulation Assisted Alteration of an Aromatic Residue Cluster in the Active Pocket of PfNS
Bibliographic record
Abstract
Terpene synthases (TPSs) play pivotal roles in generating diverse terpenoids through complex cyclization pathways. Protein engineering of TPSs offers a crucial approach to expanding terpene diversity. However, significant potential remains untapped due to limited understanding of the structure-function relationships of TPSs. In this investigation, using a joint approach of molecular dynamics simulations-assisted engineering and site-directed mutagenesis, we manipulated the aromatic residue cluster (ARC) of a bifunctional terpene synthase (BFTPS), Pestalotiopsis fici nigtetraene synthase (PfNS). This led to the discovery of previously unreported catalytic functions yielding different cyclization patterns of sesterterpenes. Specifically, a quadruple variant (F89A/Y113F/W193L/T194W) completely altered PfNS's function, converting it from producing the bicyclic sesterterpene nigtetraene to the tricyclic ophiobolin F. Additionally, analysis of catalytic profiles by double, triple, and quadruple variants demonstrated that the ARC functions as a switch, unprecedently redirecting the production of 5/11 bicyclic (Type B) sesterterpenes to 5/15 bicyclic (Type A) ones. Molecular dynamics simulations and theozyme calculations further elucidated that, in addition to cation-π interactions, C-H⋅⋅⋅π interactions also play a key role in the cyclization patterns. This study offers a feasible strategy in protein engineering of TPSs for various industrial applications.
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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 | 0.000 |
| 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) | 0.001 | 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".