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It has been widely recognised over the recent years that parallel modulation of multiple biological targets can be beneficial for treatment of diseases with complex etiologies such as cancer asthma, and psychiatric disease. In this article, current strategies for the generation of ligands with a specific multi-target profile (designed multiple ligands or DMLs) are described and a number of illustrative example are given. Designing multiple ligands is frequently a challenging endeavour for medicinal chemists, with the need to appropriately balance affinity for 2 or more targets whilst obtaining physicochemical and pharmacokinetic properties that are consistent with the administration of an oral drug. Given that the properties of DMLs are influenced to a large extent by the proteomic superfamily to which the targets belong and the lead generation strategy that is pursued, an early assessment of the feasibility of any given DML project is essential.

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Compounds designed to bind more than one target can provide a therapeutic benefit relative to highly target-selective ligands. The physicochemical properties of designed multiple ligands were found to be less druglike than those for preclinical compounds in general. These properties are controlled by the superfamily to which the targets belong and the lead discovery strategy that was followed. The properties for peptide G-protein-coupled receptor (GPCR) ligands were the least favorable for oral delivery, whereas transporter, monoamine GPCR, and oxidase ligands were the most druglike. The lead discovery strategy, framework combination or screening, exerts a profound influence on the property values. Combining the frameworks from two selective ligands often results in large, complex dual ligands, but druglike ligands can be achieved if the degree of framework overlap is maximized and the size of the selective ligands minimized. For some target combinations, a screening approach may provide a route to smaller, less complex leads.

The target families of greatest interest in drug discovery can be differentiated on the basis of the physicochemical properties of their pre-clinical ligands. The ligands for peptidergic targets, such as peptide GPCRs and integrin receptors, possess significantly higher median property values than those for aminergic targets, such as monoamine transporters and GPCRs. The ligands for peptide GPCRs were found to be less efficient, in terms of their binding energy per unit of molecular weight or lipophilicity, than ligands for monoamine GPCRs. The changes in the property values during the optimization process were found to vary only slightly across the target families, with the main determinant of the drug-likeness of the optimized compounds being the profile of the starting compounds. Agonists for monoamine GPCRs, opioid receptors and ion channels were typically smaller and less lipophilic than the antagonists, but there was no difference between the agonists and the antagonists for peptide GPCRs and nuclear receptors.

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