QSAR model for drug human oral bioavailability.

The quantitative structure-bioavailability relationship of 232 structurally diverse drugs was studied to evaluate the feasibility of constructing a predictive model for the human oral bioavailability of prospective new medicinal agents. The oral bioavailability determined in human adults was assigned one of four ratings and analyzed in relation to physicochemical and structural factors by the ORMUCS (ordered multicategorical classification method using the simplex technique) method. A systematic examination of various physicochemical parameters relating primarily to absorption, and structural elements which could influence metabolism, was carried out to analyze their effects on the bioavailabilty classification of drugs in the data set. Lipophilicity, expressed as the distribution coefficient at pH 6.5, was found to be a significant factor influencing bioavailability. The observation that acids generally had better bioavailability characteristics than bases, with neutral compounds between, led to the formulation of a new parameter, Delta log D (log D(6.5) - log D(7.4)), which proved to be an important contributor in improving the classification results. The addition of 15 structural descriptors relating primarily to well-known metabolic processes yielded a satisfactory QSAR equation which had a correct classification rate of 71% (97% within one class) and a Spearman rank correlation coefficient (R(s)) of 0.851, despite the diversity of structure and pharmacological activity in the compound set. In leave-one-out tests, an average of 67% of drugs were correctly classified (96% within one class) with an R(s) of 0.812. The relationship formulated identified significant factors influencing bioavailability and assigned them quantitative values expressing their contribution. The predictive power of the model was evaluated using a separate test set of 40 compounds, of which 60% (95% within one class) were correctly classified. Since the necessary physicochemical parameters can be calculated or estimated and the structural descriptors are obtained from an inspection of the structure, the model enables a rough estimate to be made of the prospective human oral bioavailability of unsynthesized compounds. Also, the model has the advantage of transparency in that it indicates which factors may affect bioavailabilty and the extent of that effect. This could be useful in designing compounds which are more bioavailable. Refinement of the model is possible as more bioavailability data becomes available. Potential uses are in drug design, prioritization of compounds for synthesis, and selection for detailed studies of early compound leads in drug discovery programs.

University education of medicinal chemists: comparison of eight countries.

Medicinal chemists are mainly taught in faculties or schools of pharmacy and are available for employment. Yet major pharmaceutical research companies seek organic chemists, rather than medicinal chemists, for new drug discovery. This apparent contradiction led the Medicinal Chemistry Section of IUPAC to send a questionnaire regarding postgraduate academic education for medicinal chemists to the faculties or schools of pharmacy in eight countries, namely, France, Germany, Italy, Japan, Spain, Switzerland, UK and USA. The questionnaire aimed to elicit information about postgraduate medicinal chemistry students, their courses and training, and the occupations taken up after graduation. The replies representing 109 medicinal chemistry departments or sections have been analysed and the results are presented to provide a data base on modern medicinal chemistry curricula for comparative purposes. The information should help guide discussion of the optimum paths to be followed by students in preparation for their careers. The evidence suggests that academic training of medicinal chemists equips them to enter a wide range of occupations, many of which are in industry.

Medicinal chemistry in the development of societies. Biodiversity and natural products.

This document has been elaborated by the IUPAC Medicinal Chemistry section and is backed by a large number of scientists, many of whom have had direct involvement and whose names appear at the end of the article. This work discusses the role that the discovery of new medicinal agents has in the development of societies as well as in the conservation of biodiversity in terms of work carried out on natural products. Also included are several recommendations for countries which are presently in search of their own scientific and technological development in medicinal agents. The IUPAC Medicinal Chemistry section would appreciate the collaboration of the scientific societies in every country to aid in the diffusion of this document.

The measurement of molecular diversity by receptor site interaction simulation.

The assembly of large compound libraries for the purpose of screening against various receptor targets to identify chemical leads for drug discovery programs has created a need for methods to measure the molecular diversity of such libraries. The method described here, for which we propose the acronym RESIS (for Receptor Site Interaction Simulation), relates directly to this use. A database is built of three-dimensional representations of the compounds in the library and a set of three-point three-dimensional theoretical receptor sites is generated based on putative hydrophobic and polar interactions. A series of flexible, three-dimensional searches is then performed over the database, using each of the theoretical sites as the basis for one such search. The resulting pattern of hits across the grid of theoretical receptor sites provides a measure of the molecular diversity of the compound library. This can be conveniently displayed as a density map which provides a readily comprehensible visual impression of the library diversity characteristics. A library of 7500 drug compounds derived from the CIPSLINEPC databases was characterized with respect to molecular diversity using the RESIS method. Some specific uses for the information obtained from application of the method are discussed. A comparison was made of the results from the RESIS method with those from a recently published two-dimensional approach for assessing molecular diversity using sets of compounds from the Maybridge database (MAY).

Education of medicinal chemists in Departments of Medicinal Chemistry (U.S.A.).

The present state of faculties, student bodies, and curricula in departments of medicinal chemistry have been surveyed by questionnaire and analyzed in the context of perceptions of quality and content. The results reveal a healthy diversity of educational objectives and a broader range of educational objectives than those uncovered in previous surveys of the perceived needs of industrial departments of medicinal chemistry in their search for drug discovery personnel.

Unified model for the corneal permeability of related and diverse compounds with respect to their physicochemical properties.

Corneal permeability data taken from the literature were analyzed for possible quantitative relationships with physicochemical properties. Although a parabolic relationship was obtained with good correlation between lipophilicity, as expressed by the 1-octanol-water partition coefficients, log Poctanol (or the distribution coefficients, log D for ionizable compounds), and the permeability in individual analyses of compound classes such as beta-adrenoceptor blockers and steroids, the correlation was reduced when taken together. However, delta log P (i.e., log Poctanol-log Palkane) correlated inversely with the combined permeability data for beta-blockers and steroids and played a key role as a unifying variable. To a lesser extent, lipophilicity itself also contributes positively to corneal permeation. Even with the addition of miscellaneous compounds such as methanol and ibuprofen, the delta log P and lipophilicity terms were still significant. However, small molecules were likely to be underestimated, which is consistent with penetration via another pathway besides that governed by delta log P and lipophilicity.

Chance factors in studies of quantitative structure-activity relationships.

Multiple regression analysis is a basic statistical tool used for QSAR studies in drug design. However, there is a risk or arriving at fortuitous correlations when too many variables are screened relative to the number of available observations. In this regard, a critical distinction must be made between the number of variables screened for possible correlation and the number which actually appear in the regression equation. Using a modified Fortran stepwise multiple-regression analysis program, simulated QSAR studies employing random numbers were run for many different combinations of screened variables and observations. Under certain conditions, a substantial incidence of correlations with high r2 values were found, although the overall degree of chance correlation noted was less than that reported in a previous study. Analysis of the results has provided a basis for making judgements concerning the level of risk of encountering chance correlations for a wide range of combinations of observations and screened variables in QSAR studies using multiple-regression analysis. For illustrative purposes, some examples involving published QSAR studies have been considered and the reported correlations shown to be less significant than originally presented through the influence of unrecognized chance factors.

A manual method for applying the Hansch approach to drug design.

A procedure is described in which an initial small group of compounds is selected, tested, and ordered according to potency. The potency order in the group is then compared to the tabulated potency order calculated for various parameter dependencies relating to hydrophobic, electronic, and steric effects. From this activity pattern analysis the probable operative parameters can be deduced and a new substituent selection made for the synthesis of potentially more potent analogues. Application of the method is illustrated with a series of examples. It differs from a previously described decision tree, single compound stepwise approach in that it involves the batchwise analysis of small groups of compounds, usually the preferred procedure for logistical reasons if the compounds are relatively easy to synthesize.

Quantitative structure-activity relationships in the delta6-6-substituted progesterone series. A reappraisal.

A quantitative structure-activity analysis concerning the progestational activity of a series of delta6-6-substituted progesterone is presented which differs from that published recently by other authors. In the current study all compounds in the data set for which parameters are available are included and activity is shown to relate to primarily lipophilic but also steric effects.