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Design, Synthesis, and Biological Evaluation of Triazole-Linked Lignan–Monoterpenoid-Based Hybrid Molecules as Xanthine Oxidase Inhibitors with Potent In Vivo Efficacy

2025· article· en· W4414293358 on OpenAlexaff
Karanvir Singh, Atamjit Singh, Arprita Malhan, Mridul Guleria, Aanchal Khanna, Aman Sharma, Jyoti Jyoti, Rahul Sharma, Harbinder Singh, Subheet Kumar Jain, Preet Mohinder Singh Bedi

Bibliographic record

VenueACS Medicinal Chemistry Letters · 2025
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsCentre for Drug Research and Development
FundersDepartment of Biotechnology, Ministry of Science and Technology, India
KeywordsHyperuricemiaXanthine oxidaseIn vivoGoutUric acidIn vitroCytotoxic T cellCancer

Abstract

fetched live from OpenAlex

A novel series of triazole-tethered monoterpenoid–lignan hybrid molecules has been designed to target xanthine oxidase (XO), the enzyme responsible for hyperuricemia when it is up-regulated, resulting in gout and other metabolic disorders. Designed molecules were synthesized and initially evaluated for their XO inhibitory potential, and MT7 was most active (XO: IC 50 = 0.263 ± 0.06 μM) with radical scavenging efficacy. MT7 showed higher cytotoxic potential against XO harboring cancer cells (MBDA-MB-231 breast cancer cells) than non-XO-harboring cells (A547 skin cancer cells), confirming intracellular XO inhibition. MT7 was nontoxic to mouse fibroblast cells (L929) and had favorable pharmacokinetic profiles. In vivo investigations in rodent-based animal models revealed the LD 50 (300 mg/kg) value of MT7 and a dose-dependent reduction in serum uric acid. Overall, this suggests MT7 as an effective lead molecule for further investigations as a potential clinical candidate for the management of hyperuricemia via XO inhibition.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.274
Teacher spread0.252 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations2
Published2025
Admission routes1
Has abstractyes

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Same venueACS Medicinal Chemistry LettersSame topicGout, Hyperuricemia, Uric AcidFrench-language works237,207