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Trypsin

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Refinement of paramagnetic bead-based digestion protocol for automatic sample preparation using an artificial neural network.

Talanta
Despite technological advances in the proteomics field, sample preparation still represents the main bottleneck in mass spectrometry (MS) analysis. Bead-based protein aggregation techniques have recently emerged as an efficient, reproducible, and hig...

Interpretable Machine Learning of Amino Acid Patterns in Proteins: A Statistical Ensemble Approach.

Journal of chemical theory and computation
Explainable and interpretable unsupervised machine learning helps one to understand the underlying structure of data. We introduce an ensemble analysis of machine learning models to consolidate their interpretation. Its application shows that restric...

Prognostic assessment capability of a five-gene signature in pancreatic cancer: a machine learning based-study.

BMC gastroenterology
BACKGROUND: A prognostic assessment method with good sensitivity and specificity plays an important role in the treatment of pancreatic cancer patients. Finding a way to evaluate the prognosis of pancreatic cancer is of great significance for the tre...

Extraction, identification and structure-activity relationship of antioxidant peptides from sesame (Sesamum indicum L.) protein hydrolysate.

Food research international (Ottawa, Ont.)
To elucidate the sequence, origin and structure-activity relationship of antioxidant peptides from sesame protein, sesame protein was hydrolysed by a dual-enzyme system comprised alcalase and trypsin, then this hydrolysate was fractionated by ultrafi...

Protease inhibitors in various flours and breads: Effect of fermentation, baking and in vitro digestion on trypsin and chymotrypsin inhibitory activities.

Food chemistry
In this study trypsin (TIA) and chymotrypsin inhibitory (CIA) activities were determined in the extracts of wheat, rye mix, mixed cereals and, whole wheat flours and, breads made with these flours. In addition, effects of fermentation, baking and in ...

Ultrasensitive Protease Sensors Using Selective Affinity Binding, Selective Proteolytic Reaction, and Proximity-Dependent Electrochemical Reaction.

Analytical chemistry
The development of a fast and ultrasensitive protease detection method is a challenging task. This paper reports ultrasensitive protease sensors exploiting (i) selective affinity binding, (ii) selective proteolytic reaction, and (iii) proximity-depen...

A comparative study of family-specific protein-ligand complex affinity prediction based on random forest approach.

Journal of computer-aided molecular design
The assessment of binding affinity between ligands and the target proteins plays an essential role in drug discovery and design process. As an alternative to widely used scoring approaches, machine learning methods have also been proposed for fast pr...

History Dependence in a Chemical Reaction Network Enables Dynamic Switching.

Small (Weinheim an der Bergstrasse, Germany)
This work describes an enzymatic autocatalytic network capable of dynamic switching under out-of-equilibrium conditions. The network, wherein a molecular fuel (trypsinogen) and an inhibitor (soybean trypsin inhibitor) compete for a catalyst (trypsin)...

AlphaFold - A Personal Perspective on the Impact of Machine Learning.

Journal of molecular biology
I outline how over my career as a protein scientist Machine Learning has impacted my area of science and one of my pastimes, chess, where there are some interesting parallels. In 1968, modelling of three-dimensional structures was initiated based on ...

Investigation and Highly Accurate Prediction of Missed Tryptic Cleavages by Deep Learning.

Journal of proteome research
Trypsin is one of the most important and widely used proteolytic enzymes in mass spectrometry (MS)-based proteomic research. It exclusively cleaves peptide bonds at the C-terminus of lysine and arginine. However, the cleavage is also affected by seve...