Src family kinases (SFKs) are nonreceptor tyrosine kinases that are reported to be critical for cancer progression. We report here a novel subseries of C-5-substituted anilinoquinazolines that display high affinity and specificity for the tyrosine kinase domain of the c-Src and Abl enzymes. These compounds exhibit high selectivity for SFKs over a panel of recombinant protein kinases, excellent pharmacokinetics, and in vivo activity following oral dosing. N-(5-Chloro-1,3-benzodioxol-4-yl)-7-[2-(4-methylpiperazin-1-yl)ethoxy]-5-(tetrahydro-2H-pyran-4-yloxy)quinazolin-4-amine (AZD0530) inhibits c-Src and Abl enzymes at low nanomolar concentrations and is highly selective over a range of kinases. AZD0530 displays excellent pharmacokinetic parameters in animal preclinically and in man (t(1/2) = 40 h). AZD0530 is a potent inhibitor of tumor growth in a c-Src-transfected 3T3-fibroblast xenograft model in vivo and led to a significant increase in survival in a highly aggressive, orthotopic model of human pancreatic cancer when dosed orally once daily. AZD0530 is currently undergoing clinical evaluation in man.

Lactate dehydrogenase A (LDHA) catalyzes the conversion of pyruvate to lactate, utilizing NADH as a cofactor. It has been identified as a potential therapeutic target in the area of cancer metabolism. In this manuscript we report our progress using fragment-based lead generation (FBLG), assisted by X-ray crystallography to develop small molecule LDHA inhibitors. Fragment hits were identified through NMR and SPR screening and optimized into lead compounds with nanomolar binding affinities via fragment linking. Also reported is their modification into cellular active compounds suitable for target validation work.

The discovery of an orally bioavailable selective estrogen receptor downregulator (SERD) with equivalent potency and preclinical pharmacology to the intramuscular SERD fulvestrant is described. A directed screen identified the 1-aryl-2,3,4,9-tetrahydro-1H-pyrido[3,4-b]indole motif as a novel, druglike ER ligand. Aided by crystal structures of novel ligands bound to an ER construct, medicinal chemistry iterations led to (E)-3-(3,5-difluoro-4-((1R,3R)-2-(2-fluoro-2-methylpropyl)-3-methyl-2,3,4,9-tetrahydro-1H-pyrido[3,4-b]indol-1-yl)phenyl)acrylic acid (30b, AZD9496), a clinical candidate with high oral bioavailability across preclinical species that is currently being evaluated in phase I clinical trials for the treatment of advanced estrogen receptor (ER) positive breast cancer.

Fulvestrant is an estrogen receptor (ER) antagonist administered to breast cancer patients by monthly intramuscular injection. Given its present limitations of dosing and route of administration, a more flexible orally available compound has been sought to pursue the potential benefits of this drug in patients with advanced metastatic disease. Here we report the identification and characterization of AZD9496, a nonsteroidal small-molecule inhibitor of ERa, which is a potent and selective antagonist and downregulator of ERa in vitro and in vivo in ER-positive models of breast cancer. Significant tumor growth inhibition was observed as low as 0.5 mg/kg dose in the estrogen-dependent MCF-7 xenograft model, where this effect was accompanied by a dose-dependent decrease in PR protein levels, demonstrating potent antagonist activity.Combining AZD9496 with PI3K pathway and CDK4/6 inhibitors led to further growth-inhibitory effects compared with monotherapy alone. Tumor regressions were also seen in a long-term estrogen-deprived breast model, where significant downregulation of ERa protein was observed. AZD9496 bound and downregulated clinically relevant ESR1 mutants in vitro and inhibited tumor growth in an ESR1-mutant patient-derived xenograft model that included a D538G mutation. Collectively, the pharmacologic evidence showed that AZD9496 is an oral, nonsteroidal, selective estrogen receptor antagonist and downregulator in ER þ breast cells that could provide meaningful benefit to ER þ breast cancer patients. AZD9496 is currently being evaluated in a phase I clinical trial. Cancer Res; 76(11); 3307-18. Ó2016 AACR.

Antibodies are proteins that recognize the molecular surfaces of potentially noxious molecules to mount an adaptive immune response or, in the case of autoimmune diseases, molecules that are part of healthy cells and tissues. Due to their binding versatility, antibodies are currently the largest class of biotherapeutics, with five monoclonal antibodies ranked in the top 10 blockbuster drugs. Computational advances in protein modelling and design can have a tangible impact on antibody-based therapeutic development. Antibody-specific computational protocols currently benefit from an increasing volume of data provided by next generation sequencing and application to related drug modalities based on traditional antibodies, such as nanobodies. Here we present a structured overview of available databases, methods and emerging trends in computational antibody analysis and contextualize them towards the engineering of candidate antibody therapeutics.