Design-rules for stapled peptides with in vivo activity and their application to Mdm2/X antagonists.

Although stapled α-helical peptides can address challenging targets, their advancement is impeded by poor understandings for making them cell permeable while avoiding off-target toxicities. By synthesizing >350 molecules, we present workflows for identifying stapled peptides against Mdm2(X) with in vivo activity and no off-target effects. Key insights include a clear correlation between lipophilicity and permeability, removal of positive charge to avoid off-target toxicities, judicious anionic residue placement to enhance solubility/behavior, optimization of C-terminal length/helicity to enhance potency, and optimization of staple type/number to avoid polypharmacology. Workflow application gives peptides with >292x improved cell proliferation potencies and no off-target cell proliferation effects ( > 3800x on-target index). Application of these 'design rules' to a distinct Mdm2(X) peptide series improves ( > 150x) cellular potencies and removes off-target toxicities. The outlined workflow should facilitate therapeutic impacts, especially for those targets such as Mdm2(X) that have hydrophobic interfaces and are targetable with a helical motif.

NanoClick: A High Throughput, Target-Agnostic Peptide Cell Permeability Assay.

Macrocyclic peptides open new opportunities to target intracellular protein-protein interactions (PPIs) that are often considered nondruggable by traditional small molecules. However, engineering sufficient membrane permeability into these molecules is a central challenge for identifying clinical candidates. Currently, there is a lack of high-throughput assays to assess peptide permeability, which limits our capacity to engineer this property into macrocyclic peptides for advancement through drug discovery pipelines. Accordingly, we developed a high throughput and target-agnostic cell permeability assay that measures the relative cumulative cytosolic exposure of a peptide in a concentration-dependent manner. The assay was named NanoClick as it combines in-cell Click chemistry with an intracellular NanoBRET signal. We validated the approach using known cell penetrating peptides and further demonstrated a correlation to cellular activity using a p53/MDM2 model system. With minimal change to the peptide sequence, NanoClick enables the ability to measure uptake of molecules that enter the cell via different mechanisms such as endocytosis, membrane translocation, or passive permeability. Overall, the NanoClick assay can serve as a screening tool to uncover predictive design rules to guide structure-activity-permeability relationships in the optimization of functionally active molecules.

Incorporation of Putative Helix-Breaking Amino Acids in the Design of Novel Stapled Peptides: Exploring Biophysical and Cellular Permeability Properties.

Stapled α-helical peptides represent an emerging superclass of macrocyclic molecules with drug-like properties, including high-affinity target binding, protease resistance, and membrane permeability. As a model system for probing the chemical space available for optimizing these properties, we focused on dual Mdm2/MdmX antagonist stapled peptides related to the p53 N-terminus. Specifically, we first generated a library of ATSP-7041 (Chang et al., 2013) analogs iteratively modified by L-Ala and D-amino acids. Single L-Ala substitutions beyond the Mdm2/(X) binding interfacial residues (i.e., Phe3, Trp7, and Cba10) had minimal effects on target binding, α-helical content, and cellular activity. Similar binding affinities and cellular activities were noted at non-interfacial positions when the template residues were substituted with their d-amino acid counterparts, despite the fact that d-amino acid residues typically 'break' right-handed α-helices. d-amino acid substitutions at the interfacial residues Phe3 and Cba10 resulted in the expected decreases in binding affinity and cellular activity. Surprisingly, substitution at the remaining interfacial position with its d-amino acid equivalent (i.e., Trp7 to d-Trp7) was fully tolerated, both in terms of its binding affinity and cellular activity. An X-ray structure of the d-Trp7-modified peptide was determined and revealed that the indole side chain was able to interact optimally with its Mdm2 binding site by a slight global re-orientation of the stapled peptide. To further investigate the comparative effects of d-amino acid substitutions we used linear analogs of ATSP-7041, where we replaced the stapling amino acids by Aib (i.e., R84 to Aib4 and S511 to Aib11) to retain the helix-inducing properties of α-methylation. The resultant analog sequence Ac-Leu-Thr-Phe-Aib-Glu-Tyr-Trp-Gln-Leu-Cba-Aib-Ser-Ala-Ala-NH2 exhibited high-affinity target binding (Mdm2 Kd = 43 nM) and significant α-helicity in circular dichroism studies. Relative to this linear ATSP-7041 analog, several d-amino acid substitutions at Mdm2(X) non-binding residues (e.g., d-Glu5, d-Gln8, and d-Leu9) demonstrated decreased binding and α-helicity. Importantly, circular dichroism (CD) spectroscopy showed that although helicity was indeed disrupted by d-amino acids in linear versions of our template sequence, stapled molecules tolerated these residues well. Further studies on stapled peptides incorporating N-methylated amino acids, l-Pro, or Gly substitutions showed that despite some positional dependence, these helix-breaking residues were also generally tolerated in terms of secondary structure, binding affinity, and cellular activity. Overall, macrocyclization by hydrocarbon stapling appears to overcome the destabilization of α-helicity by helix breaking residues and, in the specific case of d-Trp7-modification, a highly potent ATSP-7041 analog (Mdm2 Kd = 30 nM; cellular EC50 = 600 nM) was identified. Our findings provide incentive for future studies to expand the chemical diversity of macrocyclic α-helical peptides (e.g., d-amino acid modifications) to explore their biophysical properties and cellular permeability. Indeed, using the library of 50 peptides generated in this study, a good correlation between cellular permeability and lipophilicity was observed.

Rapid and accurate structure-based therapeutic peptide design using GPU accelerated thermodynamic integration.

Peptide-based therapeutics are an alternative to small molecule drugs as they offer superior specificity, lower toxicity, and easy synthesis. Here we present an approach that leverages the dramatic performance increase afforded by the recent arrival of GPU accelerated thermodynamic integration (TI). GPU TI facilitates very fast, highly accurate binding affinity optimization of peptides against therapeutic targets. We benchmarked TI predictions using published peptide binding optimization studies. Prediction of mutations involving charged side-chains was found to be less accurate than for non-charged, and use of a more complex 3-step TI protocol was found to boost accuracy in these cases. Using the 3-step protocol for non-charged side-chains either had no effect or was detrimental. We use the benchmarked pipeline to optimize a peptide binding to our recently discovered cancer target: EME1. TI calculations predict beneficial mutations using both canonical and non-canonical amino acids. We validate these predictions using fluorescence polarization and confirm that binding affinity is increased. We further demonstrate that this increase translates to a significant reduction in pancreatic cancer cell viability.

Inhibitor of intramembrane protease RseP blocks the σE response causing lethal accumulation of unfolded outer membrane proteins.

The outer membrane (OM) of Gram-negative bacteria forms a robust permeability barrier that blocks entry of toxins and antibiotics. Most OM proteins (OMPs) assume a ß-barrel fold, and some form aqueous channels for nutrient uptake and efflux of intracellular toxins. The Bam machine catalyzes rapid folding and assembly of OMPs. Fidelity of OMP biogenesis is monitored by the σE stress response. When OMP folding defects arise, the proteases DegS and RseP act sequentially to liberate σE into the cytosol, enabling it to activate transcription of the stress regulon. Here, we identify batimastat as a selective inhibitor of RseP that causes a lethal decrease in σE activity in Escherichia coli, and we further identify RseP mutants that are insensitive to inhibition and confer resistance. Remarkably, batimastat treatment allows the capture of elusive intermediates in the OMP biogenesis pathway and offers opportunities to better understand the underlying basis for σE essentiality.

Uncertainty Quantification in Alchemical Free Energy Methods.

Alchemical free energy methods have gained much importance recently from several reports of improved ligand-protein binding affinity predictions based on their implementation using molecular dynamics simulations. A large number of variants of such methods implementing different accelerated sampling techniques and free energy estimators are available, each claimed to be better than the others in its own way. However, the key features of reproducibility and quantification of associated uncertainties in such methods have barely been discussed. Here, we apply a systematic protocol for uncertainty quantification to a number of popular alchemical free energy methods, covering both absolute and relative free energy predictions. We show that a reliable measure of error estimation is provided by ensemble simulation-an ensemble of independent MD simulations-which applies irrespective of the free energy method. The need to use ensemble methods is fundamental and holds regardless of the duration of time of the molecular dynamics simulations performed.

Macrocyclic α helical peptide therapeutic modality: A perspective of learnings and challenges.

Macrocyclic α-helical peptides have emerged as a compelling new therapeutic modality to tackle targets confined to the intracellular compartment. Within the scope of hydrocarbon-stapling there has been significant progress to date, including the first stapled α-helical peptide to enter into clinical trials. The principal design concept of stapled α-helical peptides is to mimic a cognate (protein) ligand relative to binding its target via an α-helical interface. However, it was the proclivity of such stapled α-helical peptides to exhibit cell permeability and proteolytic stability that underscored their promise as unique macrocyclic peptide drugs for intracellular targets. This perspective highlights key learnings as well as challenges in basic research with respect to structure-based design, innovative chemistry, cell permeability and proteolytic stability that are essential to fulfill the promise of stapled α-helical peptide drug development.

Performance of multiple docking and refinement methods in the pose prediction D3R prospective Grand Challenge 2016.

We describe the performance of multiple pose prediction methods for the D3R 2016 Grand Challenge. The pose prediction challenge includes 36 ligands, which represent 4 chemotypes and some miscellaneous structures against the FXR ligand binding domain. In this study we use a mix of fully automated methods as well as human-guided methods with considerations of both the challenge data and publicly available data. The methods include ensemble docking, colony entropy pose prediction, target selection by molecular similarity, molecular dynamics guided pose refinement, and pose selection by visual inspection. We evaluated the success of our predictions by method, chemotype, and relevance of publicly available data. For the overall data set, ensemble docking, visual inspection, and molecular dynamics guided pose prediction performed the best with overall mean RMSDs of 2.4, 2.2, and 2.2 Å respectively. For several individual challenge molecules, the best performing method is evaluated in light of that particular ligand. We also describe the protein, ligand, and public information data preparations that are typical of our binding mode prediction workflow.

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort.

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

Antibacterial small molecules targeting the conserved TOPRIM domain of DNA gyrase.

To combat the threat of antibiotic-resistant Gram-negative bacteria, novel agents that circumvent established resistance mechanisms are urgently needed. Our approach was to focus first on identifying bioactive small molecules followed by chemical lead prioritization and target identification. Within this annotated library of bioactives, we identified a small molecule with activity against efflux-deficient Escherichia coli and other sensitized Gram-negatives. Further studies suggested that this compound inhibited DNA replication and selection for resistance identified mutations in a subunit of E. coli DNA gyrase, a type II topoisomerase. Our initial compound demonstrated weak inhibition of DNA gyrase activity while optimized compounds demonstrated significantly improved inhibition of E. coli and Pseudomonas aeruginosa DNA gyrase and caused cleaved complex stabilization, a hallmark of certain bactericidal DNA gyrase inhibitors. Amino acid substitutions conferring resistance to this new class of DNA gyrase inhibitors reside exclusively in the TOPRIM domain of GyrB and are not associated with resistance to the fluoroquinolones, suggesting a novel binding site for a gyrase inhibitor.

Toward Fast and Accurate Binding Affinity Prediction with pmemdGTI: An Efficient Implementation of GPU-Accelerated Thermodynamic Integration.

We report the implementation of the thermodynamic integration method on the pmemd module of the AMBER 16 package on GPUs (pmemdGTI). The pmemdGTI code typically delivers over 2 orders of magnitude of speed-up relative to a single CPU core for the calculation of ligand-protein binding affinities with no statistically significant numerical differences and thus provides a powerful new tool for drug discovery applications.

The importance of protonation and tautomerization in relative binding affinity prediction: a comparison of AMBER TI and Schrödinger FEP.

In drug discovery, protonation states and tautomerization are easily overlooked. Through a Merck-Rutgers collaboration, this paper re-examined the initial settings and preparations for the Thermodynamic Integration (TI) calculation in AMBER Free-Energy Workflows, demonstrating the value of careful consideration of ligand protonation and tautomer state. Finally, promising results comparing AMBER TI and Schrödinger FEP+ are shown that should encourage others to explore the value of TI in routine Structure-based Drug Design.

Selective small-molecule inhibition of an RNA structural element.

Riboswitches are non-coding RNA structures located in messenger RNAs that bind endogenous ligands, such as a specific metabolite or ion, to regulate gene expression. As such, riboswitches serve as a novel, yet largely unexploited, class of emerging drug targets. Demonstrating this potential, however, has proven difficult and is restricted to structurally similar antimetabolites and semi-synthetic analogues of their cognate ligand, thus greatly restricting the chemical space and selectivity sought for such inhibitors. Here we report the discovery and characterization of ribocil, a highly selective chemical modulator of bacterial riboflavin riboswitches, which was identified in a phenotypic screen and acts as a structurally distinct synthetic mimic of the natural ligand, flavin mononucleotide, to repress riboswitch-mediated ribB gene expression and inhibit bacterial cell growth. Our findings indicate that non-coding RNA structural elements may be more broadly targeted by synthetic small molecules than previously expected.

Discovery and Structure Enabled Synthesis of 2,6-Diaminopyrimidin-4-one IRAK4 Inhibitors.

We report the identification and synthesis of a series of aminopyrimidin-4-one IRAK4 inhibitors. Through high throughput screening, an aminopyrimidine hit was identified and modified via structure enabled design to generate a new, potent, and kinase selective pyrimidin-4-one chemotype. This chemotype is exemplified by compound 16, which has potent IRAK4 inhibition activity (IC50 = 27 nM) and excellent kinase selectivity (>100-fold against 99% of 111 tested kinases), and compound 31, which displays potent IRAK4 activity (IC50 = 93 nM) and good rat bioavailability (F = 42%).

Use of molecular modeling aided design to dial out hERG liability in adenosine A(2A) receptor antagonists.

Molecular modeling was performed on a triazolo quinazoline lead compound to help develop a series of adenosine A2A receptor antagonists with improved hERG profile. Superposition of the lead compound onto MK-499, a benchmark hERG inhibitor, combined with pKa calculations and measurement, identified terminal fluorobenzene to be responsible for hERG activity. Docking of the lead compound into an A2A crystal structure suggested that this group is located at a flexible, spacious, and solvent-exposed opening of the binding pocket, making it possible to tolerate various functional groups. Transformation analysis (MMP, matched molecular pair) of in-house available experimental data on hERG provided suggestions for modifications in order to mitigate this liability. This led to the synthesis of a series of compounds with significantly reduced hERG activity. The strategy used in the modeling work can be applied to other medicinal chemistry programs to help improve hERG profile.

Murgocil is a highly bioactive staphylococcal-specific inhibitor of the peptidoglycan glycosyltransferase enzyme MurG.

Modern medicine is founded on the discovery of penicillin and subsequent small molecules that inhibit bacterial peptidoglycan (PG) and cell wall synthesis. However, the discovery of new chemically and mechanistically distinct classes of PG inhibitors has become exceedingly rare, prompting speculation that intracellular enzymes involved in PG precursor synthesis are not 'druggable' targets. Here, we describe a ß-lactam potentiation screen to identify small molecules that augment the activity of ß-lactams against methicillin-resistant Staphylococcus aureus (MRSA) and mechanistically characterize a compound resulting from this screen, which we have named murgocil. We provide extensive genetic, biochemical, and structural modeling data demonstrating both in vitro and in whole cells that murgocil specifically inhibits the intracellular membrane-associated glycosyltransferase, MurG, which synthesizes the lipid II PG substrate that penicillin binding proteins (PBPs) polymerize and cross-link into the cell wall. Further, we demonstrate that the chemical synergy and cidality achieved between murgocil and the ß-lactam imipenem is mediated through MurG dependent localization of PBP2 to the division septum. Collectively, these data validate our approach to rationally identify new target-specific bioactive ß-lactam potentiation agents and demonstrate that murgocil now serves as a highly selective and potent chemical probe to assist our understanding of PG biosynthesis and cell wall biogenesis across Staphylococcal species.

De novo design of protein kinase inhibitors by in silico identification of hinge region-binding fragments.

Protein kinases constitute an attractive family of enzyme targets with high relevance to cell and disease biology. Small molecule inhibitors are powerful tools to dissect and elucidate the function of kinases in chemical biology research and to serve as potential starting points for drug discovery. However, the discovery and development of novel inhibitors remains challenging. Here, we describe a structure-based de novo design approach that generates novel, hinge-binding fragments that are synthetically feasible and can be elaborated to small molecule libraries. Starting from commercially available compounds, core fragments were extracted, filtered for pharmacophoric properties compatible with hinge-region binding, and docked into a panel of protein kinases. Fragments with a high consensus score were subsequently short-listed for synthesis. Application of this strategy led to a number of core fragments with no previously reported activity against kinases. Small libraries around the core fragments were synthesized, and representative compounds were tested against a large panel of protein kinases and subjected to co-crystallization experiments. Each of the tested compounds was active against at least one kinase, but not all kinases in the panel were inhibited. A number of compounds showed high ligand efficiencies for therapeutically relevant kinases; among them were MAPKAP-K3, SRPK1, SGK1, TAK1, and GCK for which only few inhibitors are reported in the literature.

Mitogen-activated protein kinase-activated protein kinase 2 (MAPKAP-K2) as an antiinflammatory target: discovery and in vivo activity of selective pyrazolo[1,5-a]pyrimidine inhibitors using a focused library and structure-based optimization approach.

A novel class of mitogen-activated protein kinase-activated protein kinase 2 (MAPKAP-K2) inhibitors was discovered through screening a kinase-focused library. A homology model of MAPKAP-K2 was generated and used to guide the initial SAR studies and to rationalize the observed selectivity over CDK2. An X-ray crystal structure of a compound from the active series bound to crystalline MAPKAP-K2 confirmed the predicted binding mode. This has enabled the discovery of a series of pyrazolo[1,5-a]pyrimidine derivatives showing good in vitro cellular potency as anti-TNF-α agents and in vivo efficacy in a mouse model of endotoxin shock.

Optimisation of 6-substituted isoquinolin-1-amine based ROCK-I inhibitors.

Rho kinase is an important target implicated in a variety of cardiovascular diseases. Herein, we report the optimisation of the fragment derived ATP-competitive ROCK inhibitors 1 and 2 into lead compound 14A. The initial goal of improving ROCK-I potency relative to 1, whilst maintaining a good PK profile, was achieved through removal of the aminoisoquinoline basic centre. Lead 14A was equipotent against both ROCK-I and ROCK-II, showed good in vivo efficacy in the spontaneous hypertensive rat model, and was further optimised to demonstrate the scope for improving selectivity over PKA versus hydroxy Fasudil 3.

Discovery and optimisation of a selective non-steroidal glucocorticoid receptor antagonist.

High-throughput screening of 3.87 million compounds delivered a novel series of non-steroidal GR antagonists. Subsequent rounds of optimisation allowed progression from a non-selective ligand with a poor ADMET profile to an orally bioavailable, selective, stable, glucocorticoid receptor antagonist.