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Record W1975085381 · doi:10.1371/journal.pone.0096390

In Silico Docking of Forchlorfenuron (FCF) to Septins Suggests that FCF Interferes with GTP Binding

2014· article· en· W1975085381 on OpenAlexfundno aff
Dimitrios Angelis, Eva Karasmanis, Xiaobo Bai, Elias T. Spiliotis

Bibliographic record

VenuePLoS ONE · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFungal and yeast genetics research
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesUniversity of TorontoUniversity of Pennsylvania
KeywordsSeptinGTP'Docking (animal)ChemistryIn silicoGTPaseNucleotideBinding siteBiochemistryGuanineStereochemistryEnzymeCytokinesisCell divisionCellGene

Abstract

fetched live from OpenAlex

Septins are GTP-binding proteins that form cytoskeleton-like filaments, which are essential for many functions in eukaryotic organisms. Small molecule compounds that disrupt septin filament assembly are valuable tools for dissecting septin functions with high temporal control. To date, forchlorfenuron (FCF) is the only compound known to affect septin assembly and functions. FCF dampens the dynamics of septin assembly inducing the formation of enlarged stable polymers, but the underlying mechanism of action is unknown. To investigate how FCF binds and affects septins, we performed in silico simulations of FCF docking to all available crystal structures of septins. Docking of FCF with SEPT2 and SEPT3 indicated that FCF interacts preferentially with the nucleotide-binding pockets of septins. Strikingly, FCF is predicted to form hydrogen bonds with residues involved in GDP-binding, mimicking nucleotide binding. FCF docking with the structure of SEPT2-GppNHp, a nonhydrolyzable GTP analog, and SEPT7 showed that FCF may assume two alternative non-overlapping conformations deeply into and on the outer side of the nucleotide-binding pocket. Surprisingly, FCF was predicted to interact with the P-loop Walker A motif GxxxxGKS/T, which binds the phosphates of GTP, and the GTP specificity motif AKAD, which interacts with the guanine base of GTP, and highly conserved amino acids including a threonine, which is critical for GTP hydrolysis. Thus, in silico FCF exhibits a conserved mechanism of binding, interacting with septin signature motifs and residues involved in GTP binding and hydrolysis. Taken together, our results suggest that FCF stabilizes septins by locking them into a conformation that mimics a nucleotide-bound state, preventing further GTP binding and hydrolysis. Overall, this study provides the first insight into how FCF may bind and stabilize septins, and offers a blueprint for the rational design of FCF derivatives that could target septins with higher affinity and specificity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.038
GPT teacher head0.261
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations35
Published2014
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicFungal and yeast genetics researchFrench-language works237,207