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This feature article discusses synthetic metal complexes that are capable of catalyzing chemical transformations in living organisms. Photodynamic therapy exemplifies what is probably the most established artificial catalytic process exploited in medicine, namely the photosensitized catalytic generation of cell-damaging singlet oxygen. Different redox catalysts have been designed over the last two decades to target a variety of redox alterations in cancer and other diseases. For example, pentaazamacrocyclic manganese(ii) complexes catalyze the dismutation of superoxide to O(2) and H(2)O(2)in vivo and thus reduce oxidative stress in analogy to the native enzyme superoxide dismutase. Recently, piano-stool ruthenium and iridium complexes were reported to influence cellular redox homeostasis indirectly by catalytic glutathione oxidation and catalytic transfer hydrogenation using the coenzyme NADH, respectively. Over the last few years, significant progress has been made towards the application of non-biological reactions in living systems, ranging from the organoruthenium-catalyzed cleavage of allylcarbamates and a gold-catalyzed intramolecular hydroarylation to palladium-catalyzed Suzuki-Miyaura and Sonogashira cross-couplings within the cytoplasm or on the surface of living cells. The design of bioorthogonal catalyst/substrate pairs, which can passively diffuse into cells, combines the advantages of small molecules with catalysis and promises to provide exciting new tools for future chemical biology studies.

In the quest for the identification of catalytic transformations to be used in chemical biology and medicinal chemistry, we identified iron(III) meso-tetraarylporphines as efficient catalysts for the reduction of aromatic azides to their amines. The reaction uses thiols as reducing agents and tolerates water, air, and other biological components. A caged fluorophore was employed to demonstrate that the reduction can be performed even in living mammalian cells. However, in vivo experiments in nematodes (Caenorhabditis elegans) and zebrafish (Danio rerio) revealed a limitation to this method: the metabolic reduction of aromatic azides.

Combretastatin A4 is a stilbenoid tubulin binding mitotic inhibitor whose conformation greatly influences its potency, making it an excellent candidate for adaptation as a photoactivatable tool. Herein we report a novel synthesis, the facile isomerization with commercial grade equipment, and biological activity of azo-combretastatin A4 in vitro and in human cancer cells. Photoisomerized azo-combretestatin A4 is at least 200-fold more potent in cellular culture, making it a promising phototherapeutic and biomedical research tool.

Substitution mutations in the BRAF serine/threonine kinase are found in a variety of human cancers. Such mutations occur in ∼70% of human malignant melanomas, and a single hyperactivating V600E mutation is found in the activation segment of the kinase domain and accounts for more than 90% of these mutations. Given this correlation, the molecular mechanism for BRAF regulation as well as oncogenic activation has attracted considerable interest, and activated forms of BRAF, such as BRAF V600E , have become attractive targets for small molecule inhibition. Here we report on the identification and subsequent optimization of a potent BRAF inhibitor, CS292, based on an organometallic kinase inhibitor scaffold. A cocrystal structure of CS292 in complex with the BRAF kinase domain reveals that CS292 binds to the ATP binding pocket of the kinase and is an ATP competitive inhibitor. The structure of the kinase-inhibitor complex also demonstrates that CS292 binds to BRAF in an active conformation and suggests a mechanism for regulation of BRAF by phosphorylation and BRAF V600E oncogene-induced activation. The structure of CS292 bound to the active form of the BRAF kinase also provides a novel scaffold for the design of BRAF V600E oncogene selective BRAF inhibitors for therapeutic application.RAF 1 kinases were originally identified as cellular homologues of v-raf oncogenes acquired by retroviruses and contain three members: CRAF (RAF-1 or c-RAF-1), BRAF, and ARAF (1-3). RAF family kinases are central players in the highly conserved mitogen-activated protein kinase (MAPK) signaling pathway (RAS-RAF-MEK-ERK) which relays signals from the extracellular space through receptor tyrosine kinases (RTKs) to the nucleus to promote the expression of genes involved in cell proliferation and survival. RAF kinases function by specifically phosphorylating MEK1/2 within the kinase activation loop leading to the subsequent activation of MEK1/2, which in turn activates ERK1/2. Activated ERK1/2 translocates into the nucleus and activates transcription factors to promote cellular outcomes, including survival, growth, proliferation, and differentiation (4). RAF family kinases are † This work was supported by Grant CA 114046 from the National Institutes of Health.* To whom correspondence should be addressed. Telephone: (215) 898-5006. Fax: (215) 898-0381. marmor@wistar.org. ‖ Current address: Department of Chemistry, Philipps-Universität Marburg, Marburg, Germany 1 Abbreviations: CI, chemical ionization; c-KIT, proto-oncogene receptor tyrosine kinase; DCC, dicyclohexylcarbodiimide; DCM, dichloromethane; ERK, extracellular signal-regulated kinase; ES, electrospray; FDA, Food and Drug Administration; GSK3β, glycogen synthase kinase 3 β isoform; HRP, horseradish peroxidase; MAPK, mitogen-activated protein kinase; MEK, dual-specificity mitogenactivated protein kinase kinase; PDB, Protein Data Bank; PDGFR, platelet-derived growth factor receptor; PI3K, phosphatidylinositol 3-kinase; RAF, RAF proto-oncogene serine/threonine-protein kinase (sub...

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Therapeutic antibody development requires selection and engineering of molecules with high affinity and other drug-like biophysical properties. Co-optimization of multiple antibody properties remains a difficult and time-consuming process that impedes drug development. Here we evaluate the use of machine learning to simplify antibody co-optimization for a clinical-stage antibody (emibetuzumab) that displays high levels of both on-target (antigen) and off-target (non-specific) binding. We mutate sites in the antibody complementarity-determining regions, sort the antibody libraries for high and low levels of affinity and non-specific binding, and deep sequence the enriched libraries. Interestingly, machine learning models trained on datasets with binary labels enable predictions of continuous metrics that are strongly correlated with antibody affinity and non-specific binding. These models illustrate strong tradeoffs between these two properties, as increases in affinity along the co-optimal (Pareto) frontier require progressive reductions in specificity. Notably, models trained with deep learning features enable prediction of novel antibody mutations that co-optimize affinity and specificity beyond what is possible for the original antibody library. These findings demonstrate the power of machine learning models to greatly expand the exploration of novel antibody sequence space and accelerate the development of highly potent, drug-like antibodies.

The success of antibody therapeutics is strongly influenced by their multifunctional nature that couples antigen recognition mediated by their variable regions with effector functions and half-life extension mediated by a subset of their constant regions. Nevertheless, the monospecific IgG format is not optimal for many therapeutic applications, and this has led to the design of a vast number of unique multispecific antibody formats that enable targeting of multiple antigens or multiple epitopes on the same antigen. Despite the diversity of these formats, a common challenge in generating multispecific antibodies is that they display suboptimal physical and chemical properties relative to conventional IgGs and are more difficult to develop into therapeutics. Here we review advances in the design and engineering of multispecific antibodies with drug-like properties, including favorable stability, solubility, viscosity, specificity and pharmacokinetic properties. We also highlight emerging experimental and computational methods for improving the next generation of multispecific antibodies, as well as their constituent antibody fragments, with natural IgG-like properties. Finally, we identify several outstanding challenges that need to be addressed to increase the success of multispecific antibodies in the clinic.