Exploring the Potential of Pyridine Carboxylic Acid Isomers to Discover New Enzyme Inhibitors
Bibliographic record
Abstract
Sana Yaqoob,1– 3,* Farooq-Ahmad Khan,1– 3,* Nimra Tanveer,2,3 Shujaat Ali,2,3 Abdul Hameed,4 Hesham El-Seedi,5 Zi-Hua Jiang,6 Yan Wang1,3 1Key Laboratory for Chemistry and Molecular Engineering of Medicinal Resources (Ministry of Education of China), Guangxi Key Laboratory of Chemistry and Molecular Engineering of Medicinal Resources, School of Chemistry and Pharmaceutical Sciences, Guangxi Normal University, Guilin, Guangxi, People’s Republic of China; 2Third World Center for Science and Technology, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, Sindh, Pakistan; 3H. E. J. Research Institute of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, Sindh, Pakistan; 4Department of Chemistry, University of Sahiwal, Sahiwal, Punjab, Pakistan; 5Department of Chemistry, Faculty of Science, Islamic University of Madinah, Madinah 42351, Saudi Arabia; 6Department of Chemistry, Lakehead University, Thunder Bay, ON, Canada*These authors contributed equally to this workCorrespondence: Farooq-Ahmad Khan, Email farooq.khan@iccs.edu Yan Wang, Email yan.wang@iccs.eduAbstract: Pyridine carboxylic acid isomers — picolinic acid, nicotinic acid, and isonicotinic acid — have historically resulted in a plethora of drugs against tuberculosis, cancer, diabetes, Alzheimer’s, angina, dementia, depression, allergy, respiratory acidosis, psoriasis, acne, hypertension, hyperlipidemia, HIV/AIDS (specifically HIV-1), among others. Despite the large number of therapeutic agents derived from these isomers, the research involving these scaffolds is still exceptionally active. The current surge in enzyme inhibitory activities by the compounds derived from them has further created space for the discovery of new drug candidates. This review focuses on the medicinal relevance of these isomers by analyzing structure-activity relationships (SARs) and highlighting emerging trends from patents filed over the last decade. Notably, pharmaceutical giants like Bayer, Bristol-Myers Squibb, Novartis, Curis, and Aurigene have developed enzyme inhibitors based on these scaffolds with nanomolar potency. The role of these isomers in the development of antiviral agents, including protease inhibitors, is also discussed. Overall, this review brings to the readers, a pragmatic opportunity to comprehend the recent literature, highlighting the scaffolds’ importance in the design of new enzyme inhibitors. Furthermore, it discusses the structure-activity relationship of pyridine carboxylic acid-derived compounds and highlights the current patenting trends in medicinal chemistry. Keywords: pyridine, enzyme inhibitors, nitrogen heterocycles, patents, pharmaceuticals, current trend, substituent effect
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".