BACKGROUND OF THE INVENTION

Throughout this application various publications are referred to. Full citations for the references may be found at the end of the specification. The disclosures of these publications are hereby incorporated by reference in their entirety into the subject application to more fully describe the art to which the subject invention pertains.

The immunoglobulin superfamily (IgSF) is one of the largest domain families in the human proteome (Lander et al., 2001). Excluding antibodies, the human proteome contains 477 cell-surface and secreted IgSF proteins (extracellular IgSFs′) that regulate a broad spectrum of biological processes, ranging from neural development to immune response, primarily through specific cell-to-cell (trans) IgSF-IgSF interactions involving their N-terminal Ig domains (Barclay, 2003). Extracellular IgSFs represent a biomedically important class of proteins implicated in cancers (Lee et al., 2012; Wai Wong et al., 2012; Xue et al., 2005), infectious (Bergelson et al., 1997; Mendelsohn et al., 1989; White and Littman, 1989), and autoimmune diseases (Bucciarelli et al., 2002; Lebar et al., 1986; Sharpe and Freeman, 2002). They are also proven targets and therapeutic constructs for immunosuppressive drugs (Mansh, 2011; Weber, 2007) and cancer therapies (Watanabe et al., 2005). The importance of extracellular IgSFs is well-documented in immune regulation, where trans-cellular IgSF receptor ligand interactions initiate the molecular cascade that culminates in the destruction of foreign pathogens and malignancies, as well as regulate the tolerance mechanisms that protect the host from harmful autoimmune responses (Lenschow et al., 1996; Salomon and Bluestone, 2001).

A systematic understanding of cognate IgSF receptor-ligand relationships, i.e. binding partners and poses, will provide critical insights into the molecular basis of these diseases and help engineer therapeutic strategies to modulate the underlying receptor-ligand interactions, such as high-affinity mutants of cognate ligands (Larsen et al., 2005). Current knowledge of IgSF interactions is limited: our recent survey of the STRING protein-protein interaction database (Szklarczyk et al., 2011) showed that only 106 (25%) of the extracellular IgSFs have known trans-cellular binding partners supported by high-quality, experimental evidence (Yap et al., 2014). Of these, only 16 IgSF:IgSF complexes have their structures solved by X-ray crystallography to provide detailed insights into the binding interfaces. These 16 IgSF:IgSF complexes are formed by 25 types of IgSF proteins, which can be classified into nine functional families, out of 72 that were identified (Rubinstein et al., 2013). While advances in experimental automation have made possible large-scale screening of up to 1000 receptor-ligand interactions in anecdotal cases (Yu et al., 2009), a brute-force screening of all IgSF-IgSF pairs in the extracellular IgSF subproteome (more than a 100,000 unique combinations) remains intractable. Computational screening is necessary to shortlist potential receptor-ligand pairs for experimental verification. Novel receptor-ligand relationships can be inferred from known relationships in (i) homologous sequences (Rubinstein et al., 2013), (ii) orthologous receptor-ligand pairs (‘interology’ (Arslan et al., 2008)), and (iii) receptor-ligand pairs sharing similar interface features (Tuncbag et al., 2011). Sequence-based methods have been developed to assign IgSF proteins into coarse-(Rubinstein et al., 2013) and fine-grained (Yap et al., 2014) functional families. These classifications allow transferring of known ligand information within a functional family to predict putative receptor-ligand pairs for testing. In practice, however, inference methods are limited by the paucity of known IgSF-IgSF receptor-ligand information.

In contrast, inference-free, structure-based methods can be applied to any IgSF with a known or modeled structure. However, these approaches are faced with a more challenging question: given an IgSF receptor structure, which protein ligand(s) could be potential binding partners amongst the entire extracellular IgSF subproteome? Existing structure-based methods are not suitable for predicting IgSF receptor-ligand interactions. A major class of such methods relates to small-molecule virtual drug screening, where all possible conformations of a candidate ligand are docked onto the target receptor, and an empirical scoring function is used to identify candidates with high affinity (Fradera and Mestres, 2004). Small-molecule methods cannot be directly applied to protein ligands, because the search space (ligand conformations and poses) scales exponentially with ligand size, rendering these methods computationally intractable for a protein ligand. Another class of structure-based methods is based on protein-protein docking methods, which were traditionally developed for predicting binding poses for two proteins that are known to bind (Smith and Sternberg, 2002). These methods are extensively evaluated in the community wide Critical Assessment of Prediction of Interaction (CAPRI) (Janin, 2005).

Attempts to re-purpose protein-protein docking methods to predict potential ligands for a given target are limited by the difficulty of predicting binding affinities accurately (de Vries et al., 2006). A recent community-wide critical assessment demonstrated that, when current state-of-the-art protein-protein docking methods were used to score and distinguish binders from non-binders, no method could consistently identify cognate binders, and the correlation between docking scores and binding affinity was at best weak (Fleishman et al., 2011). The candidate ligand library in our IgSF-specific application poses additional challenges for protein-protein docking methods, since all candidates from the IgSF subproteome share the same fold topology, and docking methods that rely heavily on receptor-ligand shape complementarity would be less effective in discriminating cognate from non-cognate IgSFs.

The present invention addresses the need for a new method and system for identifying cognate protein ligands.

SUMMARY OF THE INVENTION

A method is provided for identifying a cognate ligand molecule for a known biological receptor comprised of amino acid residues, comprising:

determining interaction energy map data for the known biological receptor, wherein the interaction energy data are determined for the known biological receptor with one or more predefined molecular entities;

determining residue-specific pharmacophore data for the activity of the known biological receptor;

generating ligand spatial interface structure data for the known biological receptor from combining the interaction energy map data and the pharmacophore data;

and screening a candidate ligand molecule for binding to the generated ligand interface structure, and identifying the candidate ligand molecule as a cognate ligand molecule wherein the candidate ligand molecule binds to the generated ligand interface structure, or identifying the candidate ligand molecule as not being a cognate ligand molecule wherein the candidate ligand molecule does not bind to the generated ligand interface structure.

Also provided is a system for identifying a cognate ligand molecule for a known biological receptor comprised of amino acid residues, comprising:

one or more data processing apparatus;

a graphical user interface; and

a non-transitory computer-readable medium coupled to the one or more data processing apparatus having instructions stored thereon which, when executed by the one or more data processing apparatus, cause the one or more data processing apparatus to perform a method comprising:
determining interaction energy map data for the known biological receptor, wherein the interaction energy data are determined for the known biological receptor with one or more predefined molecular entities;
transmitting the interaction energy map data to a viewer application to cause a corresponding interaction energy map to display in the graphical user interface;
determining residue-specific pharmacophore data for the activity of the known biological receptor;
generating ligand spatial interface structure data for the known biological receptor from combining the interaction energy map data and the pharmacophore data;
transmitting the ligand spatial interface structure data to the viewer application to cause display in the graphical user interface of the ligand interface structure as a visual combination of the displayed residue-specific pharmacophore and the displayed interaction energy map; and
screening a candidate ligand molecule for binding to the generated ligand interface structure, and identifying the candidate ligand molecule as a cognate ligand molecule wherein the candidate ligand molecule binds to the generated ligand interface structure, or identifying the candidate ligand molecule as not being a cognate ligand molecule wherein the candidate ligand molecule does not bind to the generated ligand interface structure.

A non-transitory computer readable medium comprising instructions stored thereon for performing the methods described herein is also provided.

Additional objects of the invention will be apparent from the description which follows.

