Virtual Screening

Recent examples of molecular bioinformatic predictions of receptor structure are not content to use the concept of evolutionary entropy to map the conserved cores of global residues, but seek to delineate discrete areas that can be ascribed to different functionalities.26,27 The conserved core of the global consensus receptor and the individual receptor signatures hint at discrete functionalities within the receptor, although again localized to predictable areas: around the "binding pocket" and that for G protein activation, with a communicating network between the two. Receptor signatures are then used for virtual screening (VS), the tuning of combinatorial libraries, and the generation of privileged scaffolds. The retention of the "binding pocket" imposes a practical boundary on any library, as molecules are flagged for their minimally aromatic qualities. A concept of privileged scaffolds, such as the spiro-piperidine-indane-based ligands,27 is fulfilled before it is even tested. Inevitably, common skeletons produce a problem of cross-reactivity at other receptors, explaining why off-target effects are so often seen with prospective small molecule antagonists. The retention of the retinal "binding pocket" by most receptors, certainly in virtuo and perhaps also in vivo, does not enforce the endogenous cognate ligand to use this site, opening up other potential binding sites for possibly more precise pharmaceutical intervention. A conserved pocket may mean that an undiscovered ubiquitous allosteric modulator uses this pocket in many, if not all, receptors.

The generation of multiple comparative data from receptor models and VS places extraordinary demands on the analysis and interpretation of the results. The development of descriptors appropriate to clustering analysis is a fine art and an exacting science. Two recent examples of pattern analysis provide an interesting twist to receptor and pharmacophore fingerprinting, with one applied to cluster analysis of the receptors28 and the other to the derivation of privileged scaffolds.29 Suel and coauthors28 considered that evolutionary conserved residues in structural proximity will coassociate in clustering analyses, providing structural constraints and mutual dependency information. The scoring of these associations in a matrix of primary sequence and protein identity was converted to pseudocolor and analyzed using code originally developed for gene expression chips. Von Korff and Steger29 used principal component analysis to generate self-organizing color maps to cluster pharmacophore information, providing distinctive patterns characteristic of ligand specificities.

In 2000, Caterina Bissantz and co-workers provided the original reference publication30 for virtual screening and docking program assessment from known 3D structures (of soluble proteins, enzymes and a nuclear receptor), by which the performances of all subsequent programs are evaluated. The same group has now published a comparison of docking programs and scoring functions after a virtual screen of 1000-member chemical databases using homology models of five 7TMRs: dopamine D3, muscarinic M1, vasopressin Via, p2-adrenergic, and 5-opioid receptors.3132 As may be expected from a homology model, with ~25% sequence identity for the TM regions, the performance of the VS was only mediocre, although better with antagonist-constrained models than when using agonists. They concluded that all antagonists stabilize a very similar ground state, simplifying the screen, but that agonists support several different bound states, complicating the screen because of receptor flexibility.

Structure prediction of the activated state of the receptors is absolutely necessary for any realistic attempts at VS and, in the absence of any surrogate structural information, it is extremely difficult and imprecise. Recently, an all-evidence prediction of the active and inactive opsin structures was extrapolated to the p2-AR and a VS run was performed on the two receptor states which exhibited marked preferences for agonists or antagonists, respectively.33 Insufficient data coverage was identified for TM4, in particular, and it was suggested that the NPxxY motif enforced a kink in TM7 when the receptor was activated. The directions of helix movements upon accommodation of ligand were predicted to be similar to that reported for photoactivated rhodopsin, although the absolute extents were perceived to be less for the p-AR, which is probably an inevitable consequence of consensus modeling minimization.

Unfortunately, most analyses are quite conservative, often only reinforcing the current paradigm and not offering much in the way of novelty. The formulation of the query can constrain the results, as occurs when model parameterization favors retention of the rhodopsin template too assiduously. Most publications argue for a conserved network of core receptor residues that are responsible for allosteric communication from "out" to "in" and are predicted to be part of the machinery of the activation cascade. Modeling approaches break down if it is assumed that more than two molecules are involved in the formation of homodimers or heterodimers and higher order complexes,34 or that the helices are free to move. This degree of flexibility is anathema to the practitioners of molecular modeling, docking routines, and virtual screening.7

A possible way out of this dilemma is to step back and take a fresh look at a comparison of sequence and structure, searching for major clues that could be interpreted as an activation mechanism via ligand-induced conformational alteration of the receptor.

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