2015/10/19 by J. C. Phillips · 1 citation
Biochemistry, Genetics and Molecular Biology · Chemistry · Computer Science · Mathematics · Pharmacology, Toxicology and Pharmaceutics · #Allosteric regulation #Biochemistry #Biology #Chemistry #Computational Drug Discovery Methods #Computational biology #Enzyme #Isozyme #Mathematics #Metabolomics and Mass Spectrometry Studies #Pharmacogenetics and Drug Metabolism #Scaling #q-bio.QM
paper · pdf · doi:10.1016/j.physa.2016.03.038
published in Physica A Statistical Mechanics and its Applications 457, 289-294 (Elsevier BV) · 12 pages, 5 figures
arxiv created 2015/10/19 · openalex publication_date 2016/04/01 · arxiv updated 2016/05/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Allosteric (long-range) interactions can be surprisingly strong in proteins of biomedical interest. Here we use bioinformatic scaling to connect prior results on nonsteroidal anti-inflammatory drugs to promising new drugs that inhibit cancer cell metabolism. Many parallel features are apparent, which explain how even one amino acid mutation, remote from active sites, can alter medical results. The enzyme twins involved are cyclooxygenase (aspirin) and isocitrate dehydrogenase (IDH). The IDH results are accurate to 1% and are overdetermined by adjusting a single bioinformatic scaling parameter. It appears that the final stage in optimizing protein functionality may involve leveling of the hydrophobic cutoffs of the arms of conformational hydrophilic hinges.