An expanded chemical space is essential for improved identification of small molecules for emerging therapeutic targets. However, the identification of targets for novel compounds is biased towards the synthesis of known scaffolds that bind familiar protein families, limiting the exploration of chemical space. To change this paradigm, we validated a new pipeline that identifies small molecule-protein interactions and works even for compounds lacking similarity to known drugs. Based on differential mRNA profiles in multiple cell types exposed to drugs and in which gene knockdowns (KD) were conducted, we showed that drugs induce gene regulatory networks that correlate with those produced after silencing protein-coding genes. Next, we applied supervised machine learning to exploit drug-KD signature correlations and enriched our predictions using an orthogonal structure-based screen. As a proof-of-principle for this regimen, top-10/top-100 target prediction accuracies of 26% and 41%, respectively, were achieved on a validation of set 152 FDA-approved drugs and 3104 potential targets. We then predicted targets for 1680 compounds and validated chemical interactors with four targets that have proven difficult to chemically modulate, including non-covalent inhibitors of HRAS and KRAS. Importantly, drug-target interactions manifest as gene expression correlations between drug treatment and both target gene KD and KD of genes that act up- or down-stream of the target, even for relatively weak binders. These correlations provide new insights on the cellular response of disrupting protein interactions and highlight the complex genetic phenotypes of drug treatment. With further refinement, our pipeline may accelerate the identification and development of novel chemical classes by screening compound-target interactions.

Induced fit or protein flexibility can make a given structure less useful for docking and/or scoring. The 2015 Drug Design Data Resource (D3R) Grand Challenge provided a unique opportunity to prospectively test optimal strategies for virtual screening in these type of targets: heat shock protein 90 (HSP90), a protein with multiple ligand-induced binding modes; and, mitogen-activated protein kinase kinase kinase kinase 4 (MAP4K4), a kinase with a large flexible pocket. Using previously known co-crystal structures, we tested predictions from methods that keep the receptor structure fixed and used (a) multiple receptor/ligand co-crystals as binding templates for minimization or docking (“close”), (b) methods that align or dock to a single receptor (“cross”), and (c) a hybrid approach that chose from multiple bound ligands as initial templates for minimization to a single receptor (“min-cross”). Pose prediction using our “close” models resulted in average ligand RMSDs of 0.32 Å and 1.6 Å for HSP90 and MAP4K4, respectively, the most accurate models of the community-wide challenge. On the other hand, affinity ranking using our “cross” methods performed well overall despite the fact that a fixed receptor cannot model ligand-induced structural changes,. In addition, “close” methods that leverage the co-crystals of the different binding modes of HSP90 also predicted the best affinity ranking. Our studies suggest that analysis of changes on the receptor structure upon ligand binding can help select an optimal virtual screening strategy.

The neuronal cell death-promoting loss of cytoplasmic K+ following injury is mediated by an increase in Kv2.1 potassium channels in the plasma membrane. This phenomenon relies on Kv2.1 binding to syntaxin 1A via 9 amino acids within the channel intrinsically disordered C terminus. Preventing this interaction with a cell and blood-brain barrier-permeant peptide is neuroprotective in an in vivo stroke model. Here a rational approach was applied to define the key molecular interactions between syntaxin and Kv2.1, some of which are shared with mammalian uncoordinated-18 (munc18). Armed with this information, we found a small molecule Kv2.1–syntaxin-binding inhibitor (cpd5) that improves cortical neuron survival by suppressing SNARE-dependent enhancement of Kv2.1-mediated currents following excitotoxic injury. We validated that cpd5 selectively displaces Kv2.1–syntaxin-binding peptides from syntaxin and, at higher concentrations, munc18, but without affecting either synaptic or neuronal intrinsic properties in brain tissue slices at neuroprotective concentrations. Collectively, our findings provide insight into the role of syntaxin in neuronal cell death and validate an important target for neuroprotection.

C-terminus of Hsc/p70-Interacting Protein (CHIP) is a homodimeric E3 ubiquitin ligase. Each CHIP monomer consists of a tetratricopeptide-repeat (TPR), helix-turn-helix (HH), and U-box domain. In contrast to nearly all homodimeric proteins, CHIP is asymmetric. To uncover the origins of asymmetry, we performed molecular dynamics simulations of dimer assembly. We determined that a CHIP monomer is most stable when the HH domain has an extended helix that supports intra-monomer TPR-U-box interaction, blocking the E2-binding surface of the U-box. We also discovered that monomers first dimerize symmetrically through their HH domains, which then triggers U-box dimerization. This brings the extended helices into close proximity, including a repulsive stretch of positively charged residues. Unable to smoothly unwind, this conflict bends the helices until the helix of one protomer breaks to relieve the repulsion. The abrupt snapping of the helix forces the C-terminal residues of the other protomer to disrupt that protomer's TPR-U-box tight binding interface, swiftly exposing and activating one of the E2 binding sites. Mutagenesis and biochemical experiments confirm that C-terminal residues are necessary both to maintain CHIP stability and function. This novel mechanism indicates how a ubiquitin ligase maintains an inactive monomeric form that rapidly activates only after asymmetric assembly.Generally, the lowest energy state of protein assembly is symmetrical, whereas asymmetry is associated with energy frustration and structural instability 1 . However, symmetry is not evolutionarily constrained, and many oligomeric enzymes are known to be asymmetric with only half-of-sites active 2-5 . In the majority of such oligomers, asymmetry results from conformational changes triggered by ligand binding 2,6,7 . Another mechanism to fold and activate asymmetric dimers requires that one of the ligand-binding sites is deformed 3,6,7 . However, very few of the vast number of known homo-multimeric proteins assemble into asymmetric structures 6 . Among the exceptions are the C-terminus of Hsc/p70-Interacting Protein (CHIP) 8 , an E3 ubiquitin ligase that associates with cyoplasmic Hsp70 and Hsp90 chaperones, and Hikeshi 9 , a nuclear import protein that also binds Hsp70. Unveiling the mechanism of symmetry breaking in homo-oligomers will shed light on new principles of folding and assembly for this important class of proteins.The CHIP homodimer consists of three domains: tetratricopeptide repeat (TPR), helix-turn-helix (HH), and U-box 8 (Fig. 1). CHIP targets misfolded, chaperone-bound substrates for proteasomal degradation by transferring ubiquitin from a compatible E2 ubiquitin conjugating-enzyme, which associates with the U-box domain, to a lysine residue on the target protein 10, 11 . The crystal structure of murine CHIP (CHIP, PDB: 2C2L), which differs from human CHIP by one residue at the N-terminus, showcases an asymmetric homodimer in which only one U-box domain has an accessible E2-binding surface. The E2 binding site/U-box in t...