Optimization of Potent, Efficacious, Selective and Blood-Brain Barrier Penetrating Inhibitors Targeting EGFR Exon20 Insertion Mutations.

Herein, we report the optimization of a series of epidermal growth factor receptor (EGFR) Exon20 insertion (Ex20Ins) inhibitors using structure-based drug design (SBDD), leading to the discovery of compound 28, a potent and wild type selective molecule, which demonstrates efficacy in multiple EGFR Ex20Ins xenograft models and blood-brain barrier penetration in preclinical species. Building on our earlier discovery of an in vivo probe, SBDD was used to design a novel bicyclic core with a lower molecular weight to facilitate blood-brain barrier penetration. Further optimization including strategic linker replacement and diversification of the ring system interacting with the c-helix enabled photolytic and metabolic stability improvements. Together with refinement of molecular properties important for achieving high brain exposure, including molecular weight, H-bonding, and polarity, 28 was identified.

Vinylpyridine as a Tunable Covalent Warhead Targeting C797 in EGFR.

To further facilitate the discovery of cysteine reactive covalent inhibitors, there is a need to develop new reactive groups beyond the traditional acrylamide-type warheads. Herein we describe the design and synthesis of covalent EGFR inhibitors that use vinylpyridine as the reactive group. Structure-based design identified the quinazoline-containing vinylpyridine 6 as a starting point. Further modifications focused on reducing reactivity resulted in substituted vinyl compound 12, which shows high EGFR potency and good kinase selectivity, as well as significantly reduced reactivity compared to the starting compound 6, confirming that vinylpyridines can be applied as an alternative cysteine reactive warhead with tunable reactivity.

Discovery and Optimization of Potent, Efficacious and Selective Inhibitors Targeting EGFR Exon20 Insertion Mutations.

Herein, we report the identification and optimization of a series of potent inhibitors of EGFR Exon20 insertions with significant selectivity over wild-type EGFR. A strategically designed HTS campaign, multiple iterations of structure-based drug design (SBDD), and tactical linker replacement led to a potent and wild-type selective series of molecules and ultimately the discovery of 36. Compound 36 is a potent and selective inhibitor of EGFR Exon20 insertions and has demonstrated encouraging efficacy in NSCLC EGFR CRISPR-engineered H2073 xenografts that carry an SVD Exon20 insertion and reduced efficacy in a H2073 wild-type EGFR xenograft model compared to CLN-081 (5), indicating that 36 may have lower EGFR wild-type associated toxicity.

Targeting Cytotoxic Agents through EGFR-Mediated Covalent Binding and Release.

A major drawback of cytotoxic chemotherapy is the lack of selectivity toward noncancerous cells. The targeted delivery of cytotoxic drugs to tumor cells is a longstanding goal in cancer research. We proposed that covalent inhibitors could be adapted to deliver cytotoxic agents, conjugated to the ß-position of the Michael acceptor, via an addition-elimination mechanism promoted by covalent binding. Studies on model systems showed that conjugated 5-fluorouracil (5FU) could be released upon thiol addition in relevant time scales. A series of covalent epidermal growth factor receptor (EGFR) inhibitors were synthesized as their 5FU derivatives. Achieving the desired release of 5FU was demonstrated to depend on the electronics and geometry of the compounds. Mass spectrometry and NMR studies demonstrated an anilinoquinazoline acrylate ester conjugate bound to EGFR with the release of 5FU. This work establishes that acrylates can be used to release conjugated molecules upon covalent binding to proteins and could be used to develop targeted therapeutics.

Basic prerequisites for on-line, high-volume hemodiafiltration.

High-volume hemodiafiltration involves filtration of >23 L/treatment and its replacement by sterile non-pyrogenic substitution fluid, while maintaining the patient's fluid balance. That volume of substitution fluid precludes the use of prepackaged sterile fluid. Instead, substitution fluid must be prepared on-line using machines that incorporate a series of bacteria- and endotoxin-retentive filters. The sterilizing ultrafilters are validated to deliver sterile, non-pyrogenic fluid to the patient when operated according to the machine manufacturer's instructions and in compliance with international standards and regulatory oversight. A successful hemodiafiltration program also places important responsibilities on the user. Specifically, the user is responsible for ensuring that the dialysis water or dialysis fluid delivered to the sterilizing filters of the hemodiafiltration machine meets the machine manufacturer's specifications and is consistent with the quality used in the sterilization validation process. The user is also responsible for ensuring that the treatment prescription allows a filtration volume >23 L/treatment to be achieved by careful selection of a dialyzer, blood flow rate and treatment time. Questions related to assurance that the substitution fluid will routinely be sterile and non-pyrogenic have limited the uptake of on-line hemodiafiltration as a therapeutic option in some countries, such as the United States.

Generation of Quantum Configurational Ensembles Using Approximate Potentials.

Conformational analysis is of paramount importance in drug design: it is crucial to determine pharmacological properties, understand molecular recognition processes, and characterize the conformations of ligands when unbound. Molecular Mechanics (MM) simulation methods, such as Monte Carlo (MC) and molecular dynamics (MD), are usually employed to generate ensembles of structures due to their ability to extensively sample the conformational space of molecules. The accuracy of these MM-based schemes strongly depends on the functional form of the force field (FF) and its parametrization, components that often hinder their performance. High-level methods, such as ab initio MD, provide reliable structural information but are still too computationally expensive to allow for extensive sampling. Therefore, to overcome these limitations, we present a multilevel MC method that is capable of generating quantum configurational ensembles while keeping the computational cost at a minimum. We show that FF reparametrization is an efficient route to generate FFs that reproduce QM results more closely, which, in turn, can be used as low-cost models to achieve the gold standard QM accuracy. We demonstrate that the MC acceptance rate is strongly correlated with various phase space overlap measurements and that it constitutes a robust metric to evaluate the similarity between the MM and QM levels of theory. As a more advanced application, we present a self-parametrizing version of the algorithm, which combines sampling and FF parametrization in one scheme, and apply the methodology to generate the QM/MM distribution of a ligand in aqueous solution.

Potent and Selective Inhibitors of the Epidermal Growth Factor Receptor to Overcome C797S-Mediated Resistance.

The epidermal growth factor receptor (EGFR) harboring activating mutations is a clinically validated target in non-small-cell lung cancer, and a number of inhibitors of the EGFR tyrosine kinase domain, including osimertinib, have been approved for clinical use. Resistance to these therapies has emerged due to a variety of molecular events including the C797S mutation which renders third-generation C797-targeting covalent EGFR inhibitors considerably less potent against the target due to the loss of the key covalent-bond-forming residue. We describe the medicinal chemistry optimization of a biochemically potent but modestly cell-active, reversible EGFR inhibitor starting point with sub-optimal physicochemical properties. These studies culminated in the identification of compound 12 that showed improved cell potency, oral exposure, and in vivo activity in clinically relevant EGFR-mutant-driven disease models, including an Exon19 deletion/T790M/C797S triple-mutant mouse xenograft model.

Structural basis of the effect of activating mutations on the EGF receptor.

Mutations within the kinase domain of the epidermal growth factor receptor (EGFR) are common oncogenic driver events in non-small cell lung cancer. Although the activation of EGFR in normal cells is primarily driven by growth-factor-binding-induced dimerization, mutations on different exons of the kinase domain of the receptor have been found to affect the equilibrium between its active and inactive conformations giving rise to growth-factor-independent kinase activation. Using molecular dynamics simulations combined with enhanced sampling techniques, we compare here the conformational landscape of the monomers and homodimers of the wild-type and mutated forms of EGFR ΔELREA and L858R, as well as of two exon 20 insertions, D770-N771insNPG, and A763-Y764insFQEA. The differences in the conformational energy landscapes are consistent with multiple mechanisms of action including the regulation of the hinge motion, the stabilization of the dimeric interface, and local unfolding transitions. Overall, a combination of different effects is caused by the mutations and leads to the observed aberrant signaling.

Drugging the undruggable: a computational chemist's view of KRASG12C.

In recent years, the emergence of targeted covalent inhibitors which bind to the G12C mutant of KRAS have offered a solution to this previously intractable target. Inhibitors of KRASG12C tend to be structurally complex, displaying features such as atropisomerism, chiral centres and a reactive covalent warhead. Such molecules result in lengthy and challenging syntheses, and as a consequence critical decisions need to be made at the design level to maximise the chances of success. Here we take a retrospective look into how computational chemistry can help guide and prioritise medicinal chemistry efforts in the context of a series of conformationally restricted tetracyclic quinolines.

ParaMol: A Package for Automatic Parameterization of Molecular Mechanics Force Fields.

The ensemble of structures generated by molecular mechanics (MM) simulations is determined by the functional form of the force field employed and its parameterization. For a given functional form, the quality of the parameterization is crucial and will determine how accurately we can compute observable properties from simulations. While accurate force field parameterizations are available for biomolecules, such as proteins or DNA, the parameterization of new molecules, such as drug candidates, is particularly challenging as these may involve functional groups and interactions for which accurate parameters may not be available. Here, in an effort to address this problem, we present ParaMol, a Python package that has a special focus on the parameterization of bonded and nonbonded terms of druglike molecules by fitting to ab initio data. We demonstrate the software by deriving bonded terms' parameters of three widely known drug molecules, viz. aspirin, caffeine, and a norfloxacin analogue, for which we show that, within the constraints of the functional form, the methodologies implemented in ParaMol are able to derive near-ideal parameters. Additionally, we illustrate the best practices to follow when employing specific parameterization routes. We also determine the sensitivity of different fitting data sets, such as relaxed dihedral scans and configurational ensembles, to the parameterization procedure, and discuss the features of the various weighting methods available to weight configurations. Owing to ParaMol's capabilities, we propose that this software can be introduced as a routine step in the protocol normally employed to parameterize druglike molecules for MM simulations.

Preclinical Comparison of the Blood-brain barrier Permeability of Osimertinib with Other EGFR TKIs.

PURPOSE: Osimertinib is a potent and selective EGFR tyrosine kinase inhibitor (EGFR-TKI) of both sensitizing and T790M resistance mutations. To treat metastatic brain disease, blood-brain barrier (BBB) permeability is considered desirable for increasing clinical efficacy. EXPERIMENTAL DESIGN: We examined the level of brain penetration for 16 irreversible and reversible EGFR-TKIs using multiple in vitro and in vivo BBB preclinical models. RESULTS: In vitro osimertinib was the weakest substrate for human BBB efflux transporters (efflux ratio 3.2). In vivo rat free brain to free plasma ratios (Kpuu) show osimertinib has the most BBB penetrance (0.21), compared with the other TKIs (Kpuu ≤ 0.12). PET imaging in Cynomolgus macaques demonstrated osimertinib was the only TKI among those tested to achieve significant brain penetrance (C max %ID 1.5, brain/blood Kp 2.6). Desorption electrospray ionization mass spectroscopy images of brains from mouse PC9 macrometastases models showed osimertinib readily distributes across both healthy brain and tumor tissue. Comparison of osimertinib with the poorly BBB penetrant afatinib in a mouse PC9 model of subclinical brain metastases showed only osimertinib has a significant effect on rate of brain tumor growth. CONCLUSIONS: These preclinical studies indicate that osimertinib can achieve significant exposure in the brain compared with the other EGFR-TKIs tested and supports the ongoing clinical evaluation of osimertinib for the treatment of EGFR-mutant brain metastasis. This work also demonstrates the link between low in vitro transporter efflux ratios and increased brain penetrance in vivo supporting the use of in vitro transporter assays as an early screen in drug discovery.

Challenges and Opportunities in Cancer Drug Resistance.

There has been huge progress in the discovery of targeted cancer therapies in recent years. However, even for the most successful and impactful cancer drugs which have been approved, both innate and acquired mechanisms of resistance are commonplace. These emerging mechanisms of resistance have been studied intensively, which has enabled drug discovery scientists to learn how it may be possible to overcome such resistance in subsequent generations of treatments. In some cases, novel drug candidates have been able to supersede previously approved agents; in other cases they have been used sequentially or in combinations with existing treatments. This review summarizes the current field in terms of the challenges and opportunities that cancer resistance presents to drug discovery scientists, with a focus on small molecule therapeutics. As part of this review, common themes and approaches have been identified which have been utilized to successfully target emerging mechanisms of resistance. This includes the increase in target potency and selectivity, alternative chemical scaffolds, change of mechanism of action (covalents, PROTACs), increases in blood-brain barrier permeability (BBBP), and the targeting of allosteric pockets. Finally, wider approaches are covered such as monoclonal antibodies (mAbs), bispecific antibodies, antibody drug conjugates (ADCs), and combination therapies.

AZD0364 Is a Potent and Selective ERK1/2 Inhibitor That Enhances Antitumor Activity in KRAS-Mutant Tumor Models when Combined with the MEK Inhibitor, Selumetinib.

The RAS-regulated RAF-MEK1/2-ERK1/2 (RAS/MAPK) signaling pathway is a major driver in oncogenesis and is frequently dysregulated in human cancers, primarily by mutations in BRAF or RAS genes. The clinical benefit of inhibitors of this pathway as single agents has only been realized in BRAF-mutant melanoma, with limited effect of single-agent pathway inhibitors in KRAS-mutant tumors. Combined inhibition of multiple nodes within this pathway, such as MEK1/2 and ERK1/2, may be necessary to effectively suppress pathway signaling in KRAS-mutant tumors and achieve meaningful clinical benefit. Here, we report the discovery and characterization of AZD0364, a novel, reversible, ATP-competitive ERK1/2 inhibitor with high potency and kinase selectivity. In vitro, AZD0364 treatment resulted in inhibition of proximal and distal biomarkers and reduced proliferation in sensitive BRAF-mutant and KRAS-mutant cell lines. In multiple in vivo xenograft models, AZD0364 showed dose- and time-dependent modulation of ERK1/2-dependent signaling biomarkers resulting in tumor regression in sensitive BRAF- and KRAS-mutant xenografts. We demonstrate that AZD0364 in combination with the MEK1/2 inhibitor, selumetinib (AZD6244 and ARRY142886), enhances efficacy in KRAS-mutant preclinical models that are moderately sensitive or resistant to MEK1/2 inhibition. This combination results in deeper and more durable suppression of the RAS/MAPK signaling pathway that is not achievable with single-agent treatment. The AZD0364 and selumetinib combination also results in significant tumor regressions in multiple KRAS-mutant xenograft models. The combination of ERK1/2 and MEK1/2 inhibition thereby represents a viable clinical approach to target KRAS-mutant tumors.

Alkynyl Benzoxazines and Dihydroquinazolines as Cysteine Targeting Covalent Warheads and Their Application in Identification of Selective Irreversible Kinase Inhibitors.

With a resurgence in interest in covalent drugs, there is a need to identify new moieties capable of cysteine bond formation that are differentiated from commonly employed systems such as acrylamide. Herein, we report on the discovery of new alkynyl benzoxazine and dihydroquinazoline moieties capable of covalent reaction with cysteine. Their utility as alternative electrophilic warheads for chemical biological probes and drug molecules is demonstrated through site-selective protein modification and incorporation into kinase drug scaffolds. A potent covalent inhibitor of JAK3 kinase was identified with superior selectivity across the kinome and improvements in in vitro pharmacokinetic profile relative to the related acrylamide-based inhibitor. In addition, the use of a novel heterocycle as a cysteine reactive warhead is employed to target Cys788 in c-KIT, where acrylamide has previously failed to form covalent interactions. These new reactive and selective heterocyclic warheads supplement the current repertoire for cysteine covalent modification while avoiding some of the limitations generally associated with established moieties.

Insight into the Therapeutic Selectivity of the Irreversible EGFR Tyrosine Kinase Inhibitor Osimertinib through Enzyme Kinetic Studies.

Osimertinib is a covalent, third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) approved for treating non-small cell lung cancer patients with activating EGFR mutations (Exon19del or L858R) or with the T790M resistance mutation following disease progression on first- or second-generation EGFR TKIs. The aim of this work is to rationalize and understand how osimertinib achieves mutant EGFR selectivity over the wild-type (WT) by evaluating its kinetic mechanism of action. In doing so, we developed methodologies combining steady-state and pre-steady-state kinetics to determine the covalent inactivation rates (kinact) and reversible binding affinities (Ki) for osimertinib against WT, L858R, and L858R/T790M EGFR and compared these data to the inhibition kinetics of earlier generations of EGFR TKIs. The kinact/KI values indicate osimertinib inactivates L858R and L858R/T790M with 20- and 50-fold higher overall efficiencies, respectively, compared to that for WT. The Ki and kinact values reveal that osimertinib binds 3-fold tighter to and reacts 3-fold faster with L858R than WT EGFR and binds 17-fold tighter to and reacts 3-fold faster with L858R/T790M than with the WT EGFR. We conclude that osimertinib overcomes the T790M mutation through improved affinities from stronger hydrophobic interactions with Met790 versus Thr790 and an improved rate of covalent bond formation via better positioning of the acrylamide warhead, while osimertinib targets the L858R mutation through better affinities and reactivities with the mutant in the context of differential binding affinities of the competing substrate ATP. This work highlights the importance of optimizing both reversible drug-target interactions and inactivation rates for covalent inhibitors to achieve selectivity in targeting mutant EGFRs.

Discovery of a Potent and Selective Oral Inhibitor of ERK1/2 (AZD0364) That Is Efficacious in Both Monotherapy and Combination Therapy in Models of Nonsmall Cell Lung Cancer (NSCLC).

The RAS/MAPK pathway is a major driver of oncogenesis and is dysregulated in approximately 30% of human cancers, primarily by mutations in the BRAF or RAS genes. The extracellular-signal-regulated kinases (ERK1 and ERK2) serve as central nodes within this pathway. The feasibility of targeting the RAS/MAPK pathway has been demonstrated by the clinical responses observed through the use of BRAF and MEK inhibitors in BRAF V600E/K metastatic melanoma; however, resistance frequently develops. Importantly, ERK1/2 inhibition may have clinical utility in overcoming acquired resistance to RAF and MEK inhibitors, where RAS/MAPK pathway reactivation has occurred, such as relapsed BRAF V600E/K melanoma. We describe our structure-based design approach leading to the discovery of AZD0364, a potent and selective inhibitor of ERK1 and ERK2. AZD0364 exhibits high cellular potency (IC50 = 6 nM) as well as excellent physicochemical and absorption, distribution, metabolism, and excretion (ADME) properties and has demonstrated encouraging antitumor activity in preclinical models.

Predicting protein-ligand binding affinity and correcting crystal structures with quantum mechanical calculations: lactate dehydrogenase A.

Accurately computing the geometry and energy of host-guest and protein-ligand interactions requires a physically accurate description of the forces in action. Quantum mechanics can provide this accuracy but the calculations can require a prohibitive quantity of computational resources. The size of the calculations can be reduced by including only the atoms of the receptor that are in close proximity to the ligand. We show that when combined with log P values for the ligand (which can be computed easily) this approach can significantly improve the agreement between computed and measured binding energies. When the approach is applied to lactate dehydrogenase A, it can make quantitative predictions about conformational, tautomeric and protonation state preferences as well as stereoselectivity and even identifies potential errors in structures deposited in the Protein Data Bank for this enzyme. By broadening the evidence base for these structures from only the diffraction data, more chemically realistic structures can be proposed.