Receptor site binding is shown to be localized in selected atoms or substructures with relatively minor contributions from the remaining molecular framework.
Related compounds can be overlayed to form a lowest common structure or hyper‐molecule that defines every possible binding site for the series. Any attempt to analyze binding data on an atom‐by‐atom basis would clearly fail if all or most of the positions were involved in the energetics. In most data sets, analysis becomes feasible when most of the variance depends on a minority of the total occupied positions. This appears to be the case in most of the sets analyzed to date, providing us with a unique opportunity. By using atomic descriptors to model lipophilicity, London forces, steric repulsion and charge interactions, the binding site can be mapped by regression analysis. Each important site of interaction and the nature of the binding force can be clearly identified. This procedure provides a statistical method based on measured data that fully complements the visual fitting of modeled drugs into defined receptor sites by computer graphics. It has enormous potential for analysis of drug, agrochemical and toxicological binding data where crystallized enzymes and fully defined sites are unknown and may long remain so.
The method is illustrated by examples drawn from acetylcholinesterase receptor site binding.