ATG-101 Is a Tetravalent PD-L1×4-1BB Bispecific Antibody That Stimulates Antitumor Immunity through PD-L1 Blockade and PD-L1-Directed 4-1BB Activation.

Unlabelled: Immune checkpoint inhibitors (ICI) have transformed cancer treatment. However, only a minority of patients achieve a profound response. Many patients are innately resistant while others acquire resistance to ICIs.

Early Feasibility Assessment: A Method for Accurately Predicting Biotherapeutic Dosing to Inform Early Drug Discovery Decisions.

The application of model-informed drug discovery and development (MID3) approaches in the early stages of drug discovery can help determine feasibility of drugging a target, prioritize between targets, or define optimal drug properties for a target product profile (TPP). However, applying MID3 in early discovery can be challenging due to the lack of pharmacokinetic (PK) and pharmacodynamic (PD) data at this stage. Early Feasibility Assessment (EFA) is the application of mechanistic PKPD models, built from first principles, and parameterized by data that is readily available early in drug discovery to make effective dose predictions.

The intrinsically disordered protein SPE-18 promotes localized assembly of MSP in spermatocytes.

Many specialized cells use unconventional strategies of cytoskeletal control. Nematode spermatocytes discard their actin and tubulin following meiosis, and instead employ the regulated assembly/disassembly of the Major Sperm Protein (MSP) to drive sperm motility. However, prior to the meiotic divisions, MSP is sequestered through its assembly into paracrystalline structures called fibrous bodies (FBs).

Quantitative modeling predicts competitive advantages of a next generation anti-NKG2A monoclonal antibody over monalizumab for the treatment of cancer.

A semimechanistic pharmacokinetic (PK)/receptor occupancy (RO) model was constructed to differentiate a next generation anti-NKG2A monoclonal antibody (KSQ mAb) from monalizumab, an immune checkpoint inhibitor in multiple clinical trials for the treatment of solid tumors. A three-compartment model incorporating drug PK, biodistribution, and NKG2A receptor interactions was parameterized using monalizumab PK, in vitro affinity measurements for both monalizumab and KSQ mAb, and receptor burden estimates from the literature. Following calibration against monalizumab PK data in patients with rheumatoid arthritis, the model successfully predicted the published PK and RO observed in gynecological tumors and in patients with squamous cell carcinoma of the head and neck.

Quantitative Proteomics of Xenopus Embryos I, Sample Preparation.

Xenopus oocytes and embryos are model systems optimally suited for quantitative proteomics. This is due to the availability of large amount of protein material and the ease of physical manipulation. Furthermore, facile in vitro fertilization provides superbly synchronized embryos for cell cycle and developmental stages.

Proteomics of phosphorylation and protein dynamics during fertilization and meiotic exit in the egg.

Fertilization releases the meiotic arrest and initiates the events that prepare the egg for the ensuing developmental program. Protein degradation and phosphorylation are known to regulate protein activity during this process. However, the full extent of protein loss and phosphoregulation is still unknown.

The Nuclear Proteome of a Vertebrate.

The composition of the nucleoplasm determines the behavior of key processes such as transcription, yet there is still no reliable and quantitative resource of nuclear proteins. Furthermore, it is still unclear how the distinct nuclear and cytoplasmic compositions are maintained. To describe the nuclear proteome quantitatively, we isolated the large nuclei of frog oocytes via microdissection and measured the nucleocytoplasmic partitioning of ∼9,000 proteins by mass spectrometry.

Deep proteomics of the Xenopus laevis egg using an mRNA-derived reference database.

Background: Mass spectrometry-based proteomics enables the global identification and quantification of proteins and their posttranslational modifications in complex biological samples. However, proteomic analysis requires a complete and accurate reference set of proteins and is therefore largely restricted to model organisms with sequenced genomes.

Results: Here, we demonstrate the feasibility of deep genome-free proteomics by using a reference proteome derived from heterogeneous mRNA data.