Computationally Designed Bispecific MD2/CD14 Binding Peptides Show TLR4 Agonist Activity.

Toll-like receptor 4 plays an important role in the regulation of the innate and adaptive immune response. The majority of TLR4 activators currently in clinical use are derivatives of its prototypic ligand LPS. The discovery of innovative TLR4 activators has the potential of providing new therapeutic immunomodulators and adjuvants. We used computational design methods to predict and optimize a total of 53 cyclic and linear peptides targeting myeloid differentiation 2 (MD2) and cluster of differentiation 14 (CD14), both coreceptors of human TLR4. Activity of the designed peptides was first assessed using NF-κB reporter cell lines expressing either TLR4/MD2 or TLR4/CD14 receptors, then binding to CD14 and MD2 confirmed and quantified using MicroScale Thermophoresis. Finally, we incubated select peptides in human whole blood and observed their ability to induce cytokine production, either alone or in synergy with LPS. Our data demonstrate the advantage of computational design for the discovery of new TLR4 peptide activators with little structural resemblance to known ligands and indicate an efficient strategy with which to identify TLR4 targeting peptides that could be used as easy-to-produce alternatives to LPS-derived molecules in a variety of settings.

Structural basis of glycogen branching enzyme deficiency and pharmacologic rescue by rational peptide design.

Glycogen branching enzyme 1 (GBE1) plays an essential role in glycogen biosynthesis by generating α-1,6-glucosidic branches from α-1,4-linked glucose chains, to increase solubility of the glycogen polymer. Mutations in the GBE1 gene lead to the heterogeneous early-onset glycogen storage disorder type IV (GSDIV) or the late-onset adult polyglucosan body disease (APBD). To better understand this essential enzyme, we crystallized human GBE1 in the apo form, and in complex with a tetra- or hepta-saccharide. The GBE1 structure reveals a conserved amylase core that houses the active centre for the branching reaction and harbours almost all GSDIV and APBD mutations. A non-catalytic binding cleft, proximal to the site of the common APBD mutation p.Y329S, was found to bind the tetra- and hepta-saccharides and may represent a higher-affinity site employed to anchor the complex glycogen substrate for the branching reaction. Expression of recombinant GBE1-p.Y329S resulted in drastically reduced protein yield and solubility compared with wild type, suggesting this disease allele causes protein misfolding and may be amenable to small molecule stabilization. To explore this, we generated a structural model of GBE1-p.Y329S and designed peptides ab initio to stabilize the mutation. As proof-of-principle, we evaluated treatment of one tetra-peptide, Leu-Thr-Lys-Glu, in APBD patient cells. We demonstrate intracellular transport of this peptide, its binding and stabilization of GBE1-p.Y329S, and 2-fold increased mutant enzymatic activity compared with untreated patient cells. Together, our data provide the rationale and starting point for the screening of small molecule chaperones, which could become novel therapies for this disease.

Computational Discovery and Experimental Confirmation of TLR9 Receptor Antagonist Leads.

Toll-like receptors (TLR) are receptors of innate immunity that recognize pathogen associated molecular patterns. They play a critical role in many pathological states, in acute and chronic inflammatory processes. TLR9 is a promising target for drug discovery, since it has been implicated in several pathologies, including defense against viral infections and psoriasis. Immune-modulators are promising molecules for therapeutic intervention in these indications. TLR9 is located in the endosome and activated by dsDNA with CpG motives encountered in microbial DNA. Here we report on a combined approach to discover new TLR9 antagonists by computational chemistry and cell based assays. We used our in-house iterative stochastic elimination (ISE) algorithm to create models that distinguish between TLR9 antagonists ("actives") and other molecules ("inactives"), based on molecular physicochemical properties. Subsequent screening and scoring of a data set of 1.8 million commercially available molecules led to the purchasing of top scored molecules, which were tested in a new cell based system based on human pattern recognition receptors (PRRs) stably expressed in NIH3T3 fibroblasts. As described previously, this cell line shows a very low endogenous PRR-activity and contains a reporter gene which is selectively activated by the integrated human PRR enabling rapid screening of potential ligands. IC50 values of each of these top scored molecules were determined. Out of 60 molecules tested, 56 showed antagonistic activity. We discovered 21 new highly potential antagonists with IC50 values lower than 10 µM, with 5 of them having IC50 values under 1 µM.

Discovery of Novel GABAAR Allosteric Modulators Through Reinforcement Learning.

BACKGROUND: As not all target proteins can be easily screened in vitro, advanced virtual screening is becoming critical. OBJECTIVE: In this study, we demonstrate the application of reinforcement learning guided virtual screening for γ-aminobutyric acid A receptor (GABAAR) modulating peptides. METHODS: Structure-based virtual screening was performed on a receptor homology model. Screened molecules deemed to be novel were synthesized and analyzed using patch-clamp analysis. RESULTS: 13 molecules were synthesized and 11 showed positive allosteric modulation, with two showing 50% activation at the low micromolar range. CONCLUSION: Reinforcement learning guided virtual screening is a viable method for the discovery of novel molecules that modulate a difficult to screen transmembrane receptor.