A key component to success in structure-based drug design is reliable information on protein-ligand interactions. Recent development in NMR techniques has accelerated this process by overcoming some of the limitations of X-ray crystallography and computational protein-ligand docking. In this work we present a new scoring protocol based on NMR-derived interligand INPHARMA NOEs to guide the selection of computationally generated docking modes. We demonstrate the performance in a range of scenarios, encompassing traditionally difficult cases such as docking to homology models and ligand dependent domain rearrangements. Ambiguities associated with sparse experimental information are lifted by searching a consensus solution based on simultaneously fitting multiple ligand pairs. This study provides a previously unexplored integration between molecular modeling and experimental data, in which interligand NOEs represent the key element in the rescoring algorithm. The presented protocol should be widely applicable for protein-ligand docking also in a different context from drug design and highlights the important role of NMR-based approaches to describe intermolecular ligand-receptor interactions.

Within the last few decades, structure-based drug design (SBDD) has evolved into a powerful tool for the optimization of many low-molecular-weight lead compounds into highly potent drugs.[1] The principle of SBDD lies in the combination of different chemical moieties with the aim of obtaining a molecule that, while possessing the pharmacological properties necessary for a drug, is complementary in shape to the receptor binding pocket. This process requires knowledge of the exact structure of the protein/ligand complex. At present, structural genomics initiatives provide protein structures of biomedically relevant targets at an increasing rate [2] and recent structures of ion channels [3] and G-protein-coupled receptors (GPCRs) [4][5][6] bring these protein classes within reach for SBDD. Despite these successes, the daily work of pharmaceutical discovery is often limited by the ability to obtain high-resolution crystal structures of the target proteins in complex with the lower affinity ligands (lead structures) that are commonly identified by high-throughput screening or by fragment-based lead discovery.[1] In view of this limitation, SBDD would benefit from methods providing the relative orientations of different chemical fragments binding competitively to a receptor site. Such an approach would provide protein/ligand structures of novel ligands or fragments in relation to the known cocrystal structure of a reference ligand.Recently, we reported the observation by NMR spectroscopy of interligand NOE peaks occurring between two small ligands binding weakly and competitively to the same binding pocket of a common macromolecular receptor (Figure 1). [7,8] The measured mixture in solution contained two ligands (L A and L B ) in a 10-to 50-fold excess relative to the target receptor (T). As the ligands were competitive binders, these NOEs did not originate from a direct transfer of magnetization between the two ligands, [9] but rather from a spindiffusion process mediated by the protons of the receptor binding pocket. We proposed that such interligand NOEs can be used to define the relative orientation of the two ligands in the receptor binding pocket (the relative binding mode) and we termed the novel effect INPHARMA (internuclear NOEs for pharmacophore mapping; [8] Figure 1). INPHARMA can be observed for complexes with a dissociation constant (K d ) in the low micromolar to millimolar range.The scope of this work is to demonstrate for the first time that the INPHARMA method allows the determination of the relative, and in favorable cases even the absolute, binding mode of two low-affinity ligands binding competitively to a common receptor site and that it can thus be applied in the context of SBDD. In accordance with existing SBDD workflows, the experimental information derived from INPHARMA was used to select the correct binding mode

The flexible superimposition of biologically active ligands is a crucial step in ligand-based drug design. Here we present pharmACOphore, a new approach for pairwise as well as multiple flexible alignment of ligands based on ant colony optimization (ACO; Dorigo M. Stützle T. Dorigo M. Stützle T. Ant Colony OptimizationMIT PressCambridge, MA, USA2004). An empirical scoring function is used, which describes ligand similarity by minimizing the distance of pharmacophoric features. The scoring function was parametrized on pairwise alignments of ligand sets for four proteins from diverse protein families (cyclooxygenase-2, cyclin-dependent kinase 2, factor Xa and peroxisome proliferator-activated receptor γ). The derived parameters were assessed with respect to pose prediction performance on the independent FlexS data set ( Lemmen C. Lengauer T. Klebe G. Lemmen C. Lengauer T. Klebe G. J. Med. Chem.) in exhausting pairwise alignments. Additionally, multiple flexible alignment experiments were carried out for the pharmacologically relevant targets trypsin and poly (ADP-ribose) polymerase (PARP). The results obtained show that the new procedure provides a robust and efficient way for the pairwise as well as multiple flexible alignment of small molecules.