Multivalent Small-Molecule Pan-RAS Inhibitors.

Design of small molecules that disrupt protein-protein interactions, including the interaction of RAS proteins and their effectors, may provide chemical probes and therapeutic agents. We describe here the synthesis and testing of potential small-molecule pan-RAS ligands, which were designed to interact with adjacent sites on the surface of oncogenic KRAS. One compound, termed 3144, was found to bind to RAS proteins using microscale thermophoresis, nuclear magnetic resonance spectroscopy, and isothermal titration calorimetry and to exhibit lethality in cells partially dependent on expression of RAS proteins. This compound was metabolically stable in liver microsomes and displayed anti-tumor activity in xenograft mouse cancer models. These findings suggest that pan-RAS inhibition may be an effective therapeutic strategy for some cancers and that structure-based design of small molecules targeting multiple adjacent sites to create multivalent inhibitors may be effective for some proteins.

AutoDesigner, a De Novo Design Algorithm for Rapidly Exploring Large Chemical Space for Lead Optimization: Application to the Design and Synthesis of d-Amino Acid Oxidase Inhibitors.

The lead optimization stage of a drug discovery program generally involves the design, synthesis, and assaying of hundreds to thousands of compounds. The design phase is usually carried out via traditional medicinal chemistry approaches and/or structure-based drug design (SBDD) when suitable structural information is available. Two of the major limitations of this approach are (1) difficulty in rapidly designing potent molecules that adhere to myriad project criteria, or the multiparameter optimization (MPO) problem, and (2) the relatively small number of molecules explored compared to the vast size of chemical space. To address these limitations, we have developed AutoDesigner, a de novo design algorithm. AutoDesigner employs a cloud-native, multistage search algorithm to carry out successive rounds of chemical space exploration and filtering. Millions to billions of virtual molecules are explored and optimized while adhering to a customizable set of project criteria such as physicochemical properties and potency. Additionally, the algorithm only requires a single ligand with measurable affinity and a putative binding model as a starting point, making it amenable to the early stages of an SBDD project where limited data are available. To assess the effectiveness of AutoDesigner, we applied it to the design of novel inhibitors of d-amino acid oxidase (DAO), a target for the treatment of schizophrenia. AutoDesigner was able to generate and efficiently explore over 1 billion molecules to successfully address a variety of project goals. The compounds generated by AutoDesigner that were synthesized and assayed (1) simultaneously met not only physicochemical criteria, clearance, and central nervous system (CNS) penetration (Kp,uu) cutoffs but also potency thresholds and (2) fully utilize structural data to discover and explore novel interactions and a previously unexplored subpocket in the DAO active site. The reported data demonstrate that AutoDesigner can play a key role in accelerating the discovery of novel, potent chemical matter within the constraints of a given drug discovery lead optimization campaign.

FINO2 initiates ferroptosis through GPX4 inactivation and iron oxidation.

Ferroptosis is a non-apoptotic form of regulated cell death caused by the failure of the glutathione-dependent lipid-peroxide-scavenging network. FINO2 is an endoperoxide-containing 1,2-dioxolane that can initiate ferroptosis selectively in engineered cancer cells. We investigated the mechanism and structural features necessary for ferroptosis initiation by FINO2. We found that FINO2 requires both an endoperoxide moiety and a nearby hydroxyl head group to initiate ferroptosis. In contrast to previously described ferroptosis inducers, FINO2 does not inhibit system xc- or directly target the reducing enzyme GPX4, as do erastin and RSL3, respectively, nor does it deplete GPX4 protein, as does FIN56. Instead, FINO2 both indirectly inhibits GPX4 enzymatic function and directly oxidizes iron, ultimately causing widespread lipid peroxidation. These findings suggest that endoperoxides such as FINO2 can initiate a multipronged mechanism of ferroptosis.

Combining Cloud-Based Free-Energy Calculations, Synthetically Aware Enumerations, and Goal-Directed Generative Machine Learning for Rapid Large-Scale Chemical Exploration and Optimization.

The hit identification process usually involves the profiling of millions to more recently billions of compounds either via traditional experimental high-throughput screens (HTS) or computational virtual high-throughput screens (vHTS). We have previously demonstrated that, by coupling reaction-based enumeration, active learning, and free energy calculations, a similarly large-scale exploration of chemical space can be extended to the hit-to-lead process. In this work, we augment that approach by coupling large scale enumeration and cloud-based free energy perturbation (FEP) profiling with goal-directed generative machine learning, which results in a higher enrichment of potent ideas compared to large scale enumeration alone, while simultaneously staying within the bounds of predefined drug-like property space. We can achieve this by building the molecular distribution for generative machine learning from the PathFinder rules-based enumeration and optimizing for a weighted sum QSAR-based multiparameter optimization function. We examine the utility of this combined approach by designing potent inhibitors of cyclin-dependent kinase 2 (CDK2) and demonstrate a coupled workflow that can (1) provide a 6.4-fold enrichment improvement in identifying <10 nM compounds over random selection and a 1.5-fold enrichment in identifying <10 nM compounds over our previous method, (2) rapidly explore relevant chemical space outside the bounds of commercial reagents, (3) use generative ML approaches to "learn" the SAR from large scale in silico enumerations and generate novel idea molecules for a flexible receptor site that are both potent and within relevant physicochemical space, and (4) produce over 3 000 000 idea molecules and run 1935 FEP simulations, identifying 69 ideas with a predicted IC50 < 10 nM and 358 ideas with a predicted IC50 < 100 nM. The reported data suggest combining both reaction-based and generative machine learning for ideation results in a higher enrichment of potent compounds over previously described approaches and has the potential to rapidly accelerate the discovery of novel chemical matter within a predefined potency and property space.

K-RasG12D Has a Potential Allosteric Small Molecule Binding Site.

KRAS is the most commonly mutated oncogene in human cancer, with particularly high mutation frequencies in pancreatic cancers, colorectal cancers, and lung cancers [Ostrem, J. M., and Shokat, K. M. (2016) Nat. Rev. Drug Discovery 15, 771-785]. The high prevalence of KRAS mutations and its essential role in many cancers make it a potentially attractive drug target; however, it has been difficult to create small molecule inhibitors of mutant K-Ras proteins. Here, we identified a putative small molecule binding site on K-RasG12D using computational analyses of the protein structure and then used a combination of computational and biochemical approaches to discover small molecules that may bind to this pocket, which we have termed the P110 site, due to its adjacency to proline 110. We confirmed that one compound, named K-Ras allosteric ligand KAL-21404358, bound to K-RasG12D, as measured by microscale thermophoresis, a thermal shift assay, and nuclear magnetic resonance spectroscopy. KAL-21404358 did not bind to four mutants in the P110 site, supporting our hypothesis that KAL-21404358 binds to the P110 site of K-RasG12D. This compound impaired the interaction of K-RasG12D with B-Raf and disrupted the RAF-MEK-ERK and PI3K-AKT signaling pathways. We synthesized additional compounds, based on the KAL-21404358 scaffold with more potent binding and greater aqueous solubility. In summary, these findings suggest that the P110 site is a potential site for binding of small molecule allosteric inhibitors of K-RasG12D.

Reaction-Based Enumeration, Active Learning, and Free Energy Calculations To Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin-Dependent Kinase 2 Inhibitors.

The hit-to-lead and lead optimization processes usually involve the design, synthesis, and profiling of thousands of analogs prior to clinical candidate nomination. A hit finding campaign may begin with a virtual screen that explores millions of compounds, if not more. However, this scale of computational profiling is not frequently performed in the hit-to-lead or lead optimization phases of drug discovery. This is likely due to the lack of appropriate computational tools to generate synthetically tractable lead-like compounds in silico, and a lack of computational methods to accurately profile compounds prospectively on a large scale. Recent advances in computational power and methods provide the ability to profile much larger libraries of ligands than previously possible. Herein, we report a new computational technique, referred to as "PathFinder", that uses retrosynthetic analysis followed by combinatorial synthesis to generate novel compounds in synthetically accessible chemical space. In this work, the integration of PathFinder-driven compound generation, cloud-based FEP simulations, and active learning are used to rapidly optimize R-groups, and generate new cores for inhibitors of cyclin-dependent kinase 2 (CDK2). Using this approach, we explored >300 000 ideas, performed >5000 FEP simulations, and identified >100 ligands with a predicted IC50 < 100 nM, including four unique cores. To our knowledge, this is the largest set of FEP calculations disclosed in the literature to date. The rapid turnaround time, and scale of chemical exploration, suggests that this is a useful approach to accelerate the discovery of novel chemical matter in drug discovery campaigns.

Tandem dienone photorearrangement-cycloaddition for the rapid generation of molecular complexity.

A tandem dienone photorearrangement-cycloaddition (DPC) reaction of novel cyclohexadienone substrates tethered with various 2π and 4π reaction partners resulted in the formation of polycyclic, bridged frameworks. In particular, use of alkynyl ether-tethered substrates led to (3 + 2) cycloaddition to afford strained alkenes which could be further elaborated by intra- and intermolecular cycloaddition chemistry to produce complex, polycyclic chemotypes.

Asymmetric allylic alkylation of acyclic allylic ethers with organolithium reagents.

A highly efficient, regio- and enantioselective Cu(I)/phosphoramidite-catalyzed asymmetric allylic alkylation of allyl ethers with organolithium reagents is reported (see scheme). The use of organolithium reagents is essential for this catalytic C-C bond formation due to their compatibility with different Lewis acids. The versatility of allylic ethers under the copper-catalyzed reaction conditions with organolithium reagents is demonstrated in the shortest synthesis of (S)-Arundic acid.

Catalytic asymmetric conjugate addition of dialkylzinc reagents to alpha,beta-unsaturated sulfones.

An efficient method is reported for the highly enantioselective copper-catalyzed conjugate addition of dialkylzinc reagents to alpha,beta-unsaturated sulfones using a monodentate phosphoramidite ligand.

Development of MAP4 Kinase Inhibitors as Motor Neuron-Protecting Agents.

Disease-causing mutations in many neurodegenerative disorders lead to proteinopathies that trigger endoplasmic reticulum (ER) stress. However, few therapeutic options exist for patients with these diseases. Using an in vitro screening platform to identify compounds that protect human motor neurons from ER stress-mediated degeneration, we discovered that compounds targeting the mitogen-activated protein kinase kinase kinase kinase (MAP4K) family are neuroprotective. The kinase inhibitor URMC-099 (compound 1) stood out as a promising lead compound for further optimization. We coupled structure-based compound design with functional activity testing in neurons subjected to ER stress to develop a series of analogs with improved MAP4K inhibition and concomitant increases in potency and efficacy. Further structural modifications were performed to enhance the pharmacokinetic profiles of the compound 1 derivatives. Prostetin/12k emerged as an exceptionally potent, metabolically stable, and blood-brain barrier-penetrant compound that is well suited for future testing in animal models of neurodegeneration.

Stereoselective synthesis of 2,3,7-trimethylcyclooctanone and related compounds and determination of their relative and absolute configurations by the MalphaNP acid method.

The copper/chiral phosphoramidite (L(1))-catalyzed conjugate addition of dimethylzinc to cycloocta-2,7-dienone 4, followed by the methylation of the intermediate enolate, yielded a single isomer of 7,8-dimethylcyclooct-2-enone (+)-5. Compound (+)-5 was subjected to the second conjugate addition with ent-L(1) giving only one stereoisomer of 2,3,7-trimethylcyclooctanone (+)-6, which was converted to 2,3,7-trimethylcyclooctanol 7. To determine the relative and absolute configurations of these compounds, the (1)H NMR anisotropy method using (S)-(+)-2-methoxy-2-(1-naphthyl)propionic acid {(S)-(+)-MalphaNP acid} 1 was applied. Racemic alcohol (+/-)-7 was esterified with (S)-(+)-MalphaNP acid 1 yielding diastereomeric esters, which were efficiently separated by HPLC on silica gel affording the first-eluted MalphaNP ester (-)-10a and the second-eluted one (-)-10b. The relative and absolute configurations of ester (-)-10a were determined to be (S;1R,2S,3R,7S) by analyzing the (1)H and (13)C NMR spectra of (-)-10a and (-)-10b, especially their HSQC-TOCSY and NOESY spectra, and by applying the MalphaNP anisotropy method. The alcohol 7 formed from (+)-6 was similarly esterified with (S)-(+)-MalphaNP acid 1 yielding an MalphaNP ester, which was identical with (-)-10a, and the relative and absolute configurations of 2,3,7-trimethylcyclooctanone (+)-6 were determined to be (2S,3R,7S).

Copper-Binding Small Molecule Induces Oxidative Stress and Cell-Cycle Arrest in Glioblastoma-Patient-Derived Cells.

Transition metals are essential, but deregulation of their metabolism causes toxicity. Here, we report that the compound NSC319726 binds copper to induce oxidative stress and arrest glioblastoma-patient-derived cells at picomolar concentrations. Pharmacogenomic analysis suggested that NSC319726 and 65 other structural analogs exhibit lethality through metal binding. Although NSC319726 has been reported to function as a zinc ionophore, we report here that this compound binds to copper to arrest cell growth. We generated and validated pharmacogenomic predictions: copper toxicity was substantially inhibited by hypoxia, through an hypoxia-inducible-factor-1α-dependent pathway; copper-bound NSC319726 induced the generation of reactive oxygen species and depletion of deoxyribosyl purines, resulting in cell-cycle arrest. These results suggest that metal-induced DNA damage may be a consequence of exposure to some xenobiotics, therapeutic agents, as well as other causes of copper dysregulation, and reveal a potent mechanism for targeting glioblastomas.

Cu-catalyzed enantioselective allylic alkylation with organolithium reagents.

This protocol describes a method for the catalytic enantioselective synthesis of tertiary and quaternary carbon stereogenic centers, which are widely present in pharmaceutical and natural products. The method is based on the direct reaction between organolithium compounds, which are cheap, readily available and broadly used in chemical synthesis, and allylic electrophiles, using chiral copper catalysts. The methodology involves the asymmetric allylic alkylation (AAA) of allyl bromides, chlorides and ethers with organolithium compounds using catalyst systems based on Cu-Taniaphos and Cu-phosphoramidites. The protocol contains a complete description of the reaction setup, a method based on 1H-NMR, gas chromatography-mass spectrometry (GC-MS) and chiral HPLC for assaying the regioselectivity and enantioselectivity of the product, and isolation, purification and characterization procedures. Six Cu-catalyzed AAA reactions between different organolithium reagents and allylic systems are detailed in the text as representative examples of these procedures. These reactions proceed within 1-10 h, depending on the nature of the allylic substrate (bromide, chloride, or ether and disubstituted or trisubstituted) or the chiral ligand used (Taniaphos or phosphoramidite). However, the entire protocol, including workup and purification, generally requires an additional 4-7 h to complete.

Synthetic Study toward Total Synthesis of (±)-Germine: Synthesis of (±)-4-Methylenegermine.

The total synthesis of 4-methylenegermine is described.

Catalyst-controlled reverse selectivity in C-C bond formation: NHC-Cu-catalyzed α-selective allylic alkylation with organolithium reagents.

An efficient and highly α-selective copper-catalyzed allylic alkylation of allylic halides with organolithium reagents is presented. The use of N-heterocyclic carbenes as ligands is key to reverse the common γ-selectivity of this transformation and gives rise to the corresponding linear products with high levels of regioselectivity.

Copper-catalyzed asymmetric ring opening of oxabicyclic alkenes with organolithium reagents.

A highly efficient method is reported for the asymmetric ring opening of oxabicyclic alkenes with organolithium reagents. Using a copper/chiral phosphoramidite complex together with a Lewis acid (BF(3)·OEt(2)), full selectivity for the anti isomer and excellent enantioselectivities were obtained for the ring opened products.

Catalytic asymmetric carbon-carbon bond formation via allylic alkylations with organolithium compounds.

Carbon-carbon bond formation is the basis for the biogenesis of nature's essential molecules. Consequently, it lies at the heart of the chemical sciences. Chiral catalysts have been developed for asymmetric C-C bond formation to yield single enantiomers from several organometallic reagents. Remarkably, for extremely reactive organolithium compounds, which are among the most broadly used reagents in chemical synthesis, a general catalytic methodology for enantioselective C-C formation has proven elusive, until now. Here, we report a copper-based chiral catalytic system that allows carbon-carbon bond formation via allylic alkylation with alkyllithium reagents, with extremely high enantioselectivities and able to tolerate several functional groups. We have found that both the solvent used and the structure of the active chiral catalyst are the most critical factors in achieving successful asymmetric catalysis with alkyllithium reagents. The active form of the chiral catalyst has been identified through spectroscopic studies as a diphosphine copper monoalkyl species.

Catalytic asymmetric conjugate addition of grignard reagents to alpha,beta-unsaturated sulfones.

A highly efficient method is reported for the asymmetric conjugate addition of Grignard reagents to alpha,beta-unsaturated 2-pyridylsulfones. Using a Cu/TolBinap complex, excellent enantioselectivities and high yields are obtained for a wide variety of aliphatic substrates.