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.

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.

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.

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%).

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 β-lactam potentiation screen to identify small molecules that augment the activity of β-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 β-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 β-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.

Evaluation of rat intestinal absorption data and correlation with human intestinal absorption

The absorption of 111 drug and drug-like compounds was evaluated from 111 references based on the ratio of urinary excretion of drugs following oral and intravenous administration to intact rats and biliary excretion of bile duct-cannulated rats. Ninety-eight drug compounds for which both human and rat absorption data were available were selected for correlation analysis between the human and rat absorption. The result shows that the extent of absorption in these two species is similar. For 94% of the drugs the absorption difference between humans and rats is less than 20% and for 98% of drugs the difference is less than 30%. There is only one drug for which human absorption is significantly different from rat absorption. The standard deviation is 11% between human and rat absorption. The linear relationship between human and rat absorption forced through the origin, as determined by least squares regression, is %Absorption (human)=0.997%Absorption (rat) (n=98, SD=11). It is suggested that the absorption in rats could be used as an alternative method to human absorption in pre-clinical oral absorption studies.

Rate-limited steps of human oral absorption and QSAR studies

PURPOSE

To classify the dissolution and diffusion rate-limited drugs and establish quantitative relationships between absorption and molecular descriptors.

METHODS

Absorption consists of kinetic transit processes in which dissolution, diffusion, or perfusion processes can become the rate-limited step. The absorption data of 238 drugs have been classified into either dissolution or diffusion rate-limited based on an equilibrium method developed from solubility, dose, and percentage of absorption. A nonlinear absorption model derived from first-order kinetics has been developed to identify the relationship between percentage of drug absorption and molecular descriptors.

RESULTS

Regression analysis was performed between percentage of absorption and molecular descriptors. The descriptors used were ClogP, molecular polar surface area, the number of hydrogen-bonding acceptors and donors, and Abraham descriptors. Good relationships were found between absorption and Abraham descriptors or ClogP.

CONCLUSIONS

The absorption models can predict the following three BCS (Biopharmaceutics Classification Scheme) classes of compounds: class I, high solubility and high permeability; class III, high solubility and low permeability; class IV, low solubility and low permeability. The absorption models overpredict the absorption of class II, low solubility and high permeability compounds because dissolution is the rate-limited step of absorption.

On the mechanism of human intestinal absorption

In order to investigate whether the main step in intestinal absorption in humans is dominated by partition or by diffusion, we have transformed % human intestinal absorption into a first-order rate constant, and have regressed the latter, as logk, against our solvation parameters. The obtained regression coefficients are compared with those for diffusion and partition processes. The coefficients in the logk equation are completely different to those for water/solvent partitions, but are very similar to those for processes (not involving transport through membranes) in which diffusion is the major step. It is suggested that the main step in the absorption process is diffusion through a stagnant mucus layer, together with transfer across the mucusmid R:membrane interface. It is further shown that for strong Bronsted acids and bases, the rate constant for absorption of ionic species is close to that for absorption of the corresponding neutral species, so that to a first approximation the % intestinal absorption can be calculated from properties of the neutral species.

Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure–activity relationship (QSAR) with the Abraham descriptors

The human intestinal absorption of 241 drugs was evaluated. Three main methods were used to determine the human intestinal absorption: bioavailability, percentage of urinary excretion of drug-related material following oral administration, and the ratio of cumulative urinary excretion of drug-related material following oral and intravenous administration. The general solvation equation developed by Abraham's group was used to model the human intestinal absorption data of 169 drugs we considered to have reliable data. The model contains five Abraham descriptors calculated by the ABSOLV program. The results show that Abraham descriptors can successfully predict human intestinal absorption if the human absorption data is carefully classified based on solubility and administration dose to humans.