Identification and prediction of promiscuous aggregating inhibitors among known drugs.

Some small molecules, often hits from screening, form aggregates in solution that inhibit many enzymes. In contrast, drugs are thought to act specifically. To investigate this assumption, 50 unrelated drugs were tested for promiscuous inhibition via aggregation. Each drug was tested against three unrelated model enzymes: beta-lactamase, chymotrypsin, and malate dehydrogenase, none of which are considered targets of these drugs. To be judged promiscuous, the drugs had to inhibit all three enzymes, do so in a time-dependent manner, be sensitive to detergent and to enzyme concentration, and form particles detectable by light scattering. Of the 50 drugs tested, 43 were nonpromiscuous by these criteria. Surprisingly, four of the drugs showed promiscuous, aggregation-based inhibition at concentrations below 100 microM: clotrimazole, benzyl benzoate, nicardipine, and delavirdine. Three other drugs also behaved as aggregation-based inhibitors, but only at high concentrations (about 400 microM). To investigate possible structure-activity relationships among promiscuous drugs, five analogues of the antifungal clotrimazole were studied. Three of these, miconazole, econazole, and sulconazole, were promiscuous but the other two, fluconazole and ketoconazole, were not. Using recursive partitioning, these experimental results were used to develop a model for predicting aggregate-based promiscuity. This model correctly classified 94% of 111 compounds-47 aggregators and 64 nonaggregators-that have been studied for this effect. To evaluate the model, it was used to predict the behavior of 75 drugs not previously investigated for aggregation. Several preliminary points emerge. Most drugs are not promiscuous, even at high concentrations. Nevertheless, at high enough concentrations (20-400 microM), some drugs can aggregate and act promiscuously, suggesting that aggregation may be common among small molecules at micromolar concentrations, at least in biochemical buffers.

[1]  Veerabahu Shanmugasundaram,et al.  Estimation of Aqueous Solubility of Organic Compounds with QSPR Approach , 2004, Pharmaceutical Research.

[2]  Brian K Shoichet,et al.  Kinase inhibitors: not just for kinases anymore. , 2003, Journal of medicinal chemistry.

[3]  Jürgen Bajorath,et al.  Integration of virtual and high-throughput screening , 2002, Nature Reviews Drug Discovery.

[4]  Brian K. Shoichet,et al.  Structure-Based Discovery of a Novel, Noncovalent Inhibitor of AmpC β-Lactamase , 2002 .

[5]  B. Shoichet,et al.  A common mechanism underlying promiscuous inhibitors from virtual and high-throughput screening. , 2002, Journal of medicinal chemistry.

[6]  Wolfgang Guba,et al.  Development of a virtual screening method for identification of "frequent hitters" in compound libraries. , 2002, Journal of medicinal chemistry.

[7]  I. Muegge,et al.  Simple selection criteria for drug-like chemical matter. , 2001, Journal of medicinal chemistry.

[8]  René Barone,et al.  A New and Simple Approach to Chemical Complexity. Application to the Synthesis of Natural Products , 2001, J. Chem. Inf. Comput. Sci..

[9]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. , 2001, Advanced drug delivery reviews.

[10]  Robert Bywater,et al.  Improving the Odds in Discriminating "Drug-like" from "Non Drug-like" Compounds , 2000, J. Chem. Inf. Comput. Sci..

[11]  P. Selzer,et al.  Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its application to the prediction of drug transport properties. , 2000, Journal of medicinal chemistry.

[12]  Jun Xu,et al.  Drug-like Index: A New Approach To Measure Drug-like Compounds and Their Diversity , 2000, J. Chem. Inf. Comput. Sci..

[13]  Tudor I. Oprea,et al.  Property distribution of drug-related chemical databases* , 2000, J. Comput. Aided Mol. Des..

[14]  M. Myerscough,et al.  Studies in vitro on the relative efficacy of current acaricides for Sarcoptes scabiei var. hominis. , 2000, Transactions of the Royal Society of Tropical Medicine and Hygiene.

[15]  David Back,et al.  Pharmacokinetics and Potential Interactions Amongst Antiretroviral Agents Used To Treat Patients with HIV Infection , 1999, Clinical pharmacokinetics.

[16]  I. Roterman,et al.  Supramolecular ligands: monomer structure and protein ligation capability. , 1998, Biochimie.

[17]  G S Weston,et al.  Structure-based enhancement of boronic acid-based inhibitors of AmpC beta-lactamase. , 1998, Journal of medicinal chemistry.

[18]  G. Rishton.  Reactive compounds and in vitro false positives in HTS , 1997 .

[19]  D. Hawkins,et al.  Analysis of a Large Structure‐Activity Data Set Using Recursive Partitioning , 1997 .

[20]  Thompson N. Doman,et al.  Algorithm5: A Technique for Fuzzy Similarity Clustering of Chemical Inventories , 1996, J. Chem. Inf. Comput. Sci..

[21]  F. Oehme.  Goodman and Gilman 's: The pharmacological basis of therapeutics , 1996 .

[22]  Lemont B. Kier,et al.  Electrotopological State Indices for Atom Types: A Novel Combination of Electronic, Topological, and Valence State Information , 1995, J. Chem. Inf. Comput. Sci..

[23]  H. W. Ruelius,et al.  Effects of Food on Oxaprozin Bioavailability , 1984, Journal of clinical pharmacology.

[24]  A. Camerman,et al.  Stereochemical basis of anticonvulsant drug action. II. Molecular structure of diazepam. , 1972, Journal of the American Chemical Society.

[25]  A. Camerman,et al.  The stereochemical basis of anticonvulsant drug action. 3. The structure of procyclidine hydrochloride. , 1971, Molecular pharmacology.

[26]  L. Goodman,et al.  THE PHARMACOLOGICAL BASIS OF THERAPEUTICS , 1966 .