AIMC Topic: Peptide Hydrolases
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Data-driven protease engineering by DNA-recording and epistasis-aware machine learning.
Nature communications
Jul 1, 2025
Protein engineering has recently seen tremendous transformation due to machine learning (ML) tools that predict structure from sequence at unprecedented precision. Predicting catalytic activity, however, remains challenging, restricting our capabilit...
Statistical versus neural network-embedded swarm intelligence optimization of a metallo-neutral-protease production: activity kinetics and food industry applications.
Preparative biochemistry & biotechnology
Mar 16, 2024
An integrated approach involving response surface methodology (RSM) and artificial neural network-ant-colony hybrid optimization (ANN-ACO) was adopted to develop a bioprocess medium to increase the yield of neutral protease under submerged fermentat...
In silico evolution of autoinhibitory domains for a PD-L1 antagonist using deep learning models.
Proceedings of the National Academy of Sciences of the United States of America
Nov 30, 2023
There has been considerable progress in the development of computational methods for designing protein-protein interactions, but engineering high-affinity binders without extensive screening and maturation remains challenging. Here, we test a protein...
AlphaFold-Multimer predicts cross-kingdom interactions at the plant-pathogen interface.
Nature communications
Sep 27, 2023
Adapted plant pathogens from various microbial kingdoms produce hundreds of unrelated small secreted proteins (SSPs) with elusive roles. Here, we used AlphaFold-Multimer (AFM) to screen 1879 SSPs of seven tomato pathogens for interacting with six def...
Higher-order structure formation using refined monomer structures of lipid raft markers, Stomatin, Prohibitin, Flotillin, and HflK/C-related proteins.
FEBS open bio
Mar 17, 2023
Currently, information on the higher-order structure of Stomatin, Prohibitin, Flotillin, and HflK/C (SPFH)-domain proteins is limited. Briefly, the coordinate information (Refined PH1511.pdb) of the stomatin ortholog, PH1511 monomer, was obtained usi...
DeepDetect: Deep Learning of Peptide Detectability Enhanced by Peptide Digestibility and Its Application to DIA Library Reduction.
Analytical chemistry
Mar 12, 2023
In tandem mass spectrometry-based proteomics, proteins are digested into peptides by specific protease(s), but generally only a fraction of peptides can be detected. To characterize detectable proteotypic peptides, we have developed a series of metho...
Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics.
PLoS computational biology
Jan 20, 2023
Generating and analyzing overlapping peptides through multienzymatic digestion is an efficient procedure for de novo protein using from bottom-up mass spectrometry (MS). Despite improved instrumentation and software, de novo MS data analysis remains ...
Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria.
eLife
Dec 28, 2022
To reach their final destinations, outer membrane proteins (OMPs) of gram-negative bacteria undertake an eventful journey beginning in the cytosol. Multiple molecular machines, chaperones, proteases, and other enzymes facilitate the translocation and...
Development of a deep learning-based quantitative structure-activity relationship model to identify potential inhibitors against the 3C-like protease of SARS-CoV-2.
Future medicinal chemistry
Sep 30, 2022
In the recent COVID-19 pandemic, SARS-CoV-2 infection spread worldwide. The 3C-like protease (3CLpro) is a promising drug target for SARS-CoV-2. We constructed a deep learning-based convolutional neural network-quantitative structure-activity relat...
DeepDigest: Prediction of Protein Proteolytic Digestion with Deep Learning.
Analytical chemistry
Apr 7, 2021
Proteolytic digestion of proteins by one or more proteases is a key step in shotgun proteomics, in which the proteolytic products, i.e., peptides, are taken as the surrogates of their parent proteins for further qualitative or quantitative analysis. ...
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