The present invention relates to a method for analysing protein variants of a recombinant protein of interest, such as antibodies or Fc-fusion proteins, in a liquid sample of a mammal. Specifically the method comprises a step of affinity purifying the recombinant protein of interest from the sample together with an internal standard, and analyzing the protein variants using an analytic separating method such as HPLC, capillary electrophoresis or MS. This method is particularly suited to measure pharmacokinetic parameters of a recombinant protein of interest, such as a biopharmaceutical, in a mammal in clinical or pre-clinical studies. It allows for the use of a small sample volume and the possibility to operate with high throughput, such as in a 96-well plate sample preparation. It also provides high sensitivity and allows analysis of protein variants individually.

The present invention is directed to methods for detecting a plasma cell dyscrasia like myeloma or MGUS, methods for determining whether a plasma cell dyscrasiais stable or progressive, methods for determining a risk for disease relapse, and methods for determining a response by a subject having a plasma cell dyscrasia to a therapy.

Methods and tools for determining the structure of biomacromolecules such as proteins in a sample using mass spectrometry. More particularly the methods allow determining the presence of a biomacromolecule of an organism in a sample by comparing an observed mass spectrum of the sample with a theoretical fragment ion spectrum comprising theoretical fragment ion masses.

The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data. The systems and methods achieve improvements in sequencing accuracy over existing systems and methods and enables complete assembly of novel protein sequences without assisting databases. The present systems and methods are re-trainable to adapt to new sources of data and provides a complete end-to-end training and prediction solution, which is advantageous given the growing massive amount of data. The systems and methods combine deep learning and dynamic programming to solve optimization problems.

The present description provides methods, assays and reagents useful for sequencing proteins. Sequencing proteins in a broad sense involves observing the plausible identity and order of amino acids, which is useful for sequencing single polypeptide molecules or multiple molecules of a single polypeptide. In one aspect, the methods are useful for sequencing multiple polypeptides. The methods and reagents described herein can be useful for high resolution interrogation of the proteome and enabling ultrasensitive diagnostics critical for early detection of diseases.

Aspects of the application provide methods of identifying and sequencing proteins, polypeptides, and amino acids, and compositions useful for the same. In some aspects, the application provides amino acid recognition molecules, such as amino acid binding proteins and fusion polypeptides thereof. In some aspects, the application provides amino acid recognition molecules comprising a shielding element that enhances photostability in polypeptide sequencing reactions.

The application relates to proteome analysis in single cells. Specifically, disclosed are high throughput methods of detecting proteins in single cells using barcoding, aptamers and single cell sequencing. Solid supports used in recording the cell-of-origin of target proteins and target proteins expressed in the cell-of-origin are disclosed. Additionally, methods of detecting proteins and mRNA in single cells are disclosed. Additionally, methods of detecting protein interactions are disclosed. Additionally, methods of detecting post translationally modified proteins in single cells are disclosed. The application also relates to solid supports or beads and methods of producing said solid supports or beads for use in the described methods.

Disclosed are methods and compositions for labeling target molecules or associated target molecule tags with origin-specific nucleic acid barcodes. The identity, quantity, and/or activity of target molecules originating from particular discrete volumes, such as droplets, for example water-in-oil emulsions, can be determined by determining the sequence of the origin-specific nucleic acid barcodes (optionally in combination with additional barcodes, such as one or more additional nucleic acid and/or peptide barcode).

Disclosed are a conotoxin polypeptide -CPTx-bt101, a method for preparation thereof, and an application thereof. The conotoxin polypeptide of the present invention consists of 18 amino acids, has a molecular weight of 1872.72 daltons, and has the full sequence KCCTMSVCQPPPVCTCCA (SEQ. ID NO. 1).

Disclosed herein are methods and systems for detection and discrimination of optical signals from a densely packed substrate. These have broad applications for biomolecule detection near or below the diffraction limit of optical systems, including in improving the efficiency and accuracy of polynucleotide sequencing applications.