{"id":1954,"date":"2024-01-24T15:00:09","date_gmt":"2024-01-24T06:00:09","guid":{"rendered":"https:\/\/prismbiolab.com\/?p=1954"},"modified":"2024-02-05T16:48:32","modified_gmt":"2024-02-05T07:48:32","slug":"dlip-ppi-library-for-keap1-nrf2-ppi-inhibitor-identification-and-discovery","status":"publish","type":"post","link":"https:\/\/prismbiolab.com\/ja\/dlip-ppi-library-for-keap1-nrf2-ppi-inhibitor-identification-and-discovery\/","title":{"rendered":"DLiP-PPI library for Keap1\/Nrf2 PPI Inhibitor Identification and Discovery"},"content":{"rendered":"
\n
\n\t

Protein-protein interactions (PPIs) library is an indispensable and invaluable tool for PPI drug discovery and development. 2P2Idb v21)<\/sup>, TIMBAL v22)<\/sup>, iPPI-DB3)<\/sup>\u00a0have been the libraries focused on PPIs and data availability in the recently elucidated cases were limited for long. It will open up to everyone a great opportunity to initiate another PPIs-targeted drug discovery program if well-curated relational database (RDB).<\/p>\n

The time has come. DLiP-PPI (Database of Chemical Library for Protein-Protein Interaction) is released in 2023.4), 5)<\/sup>\u00a0DLiP-PPI is a small-to-medium sized molecule database developed in an AMED project driven by Ikeda group at Keio University and other groups from industry and academia.<\/p>\n

The library containing ones over the Lipinski\u2019s rule-of-five. For example, molecular weight ranges from 450 to 650, which is over rule-of-five (MW<500). Library data have been gathered from accumulated in public sources as well as predicted binders of PPI interfaces by 3D docking simulations by FRED software. After filtering a specific range of molecular properties and druggability at a hit stage, and it enabled inclusion of 15,214 molecules at the time of library release.<\/p>\n

DLiP-PPI is a web-based, readily available and free library with search and analysis functions. Physicochemical properties, drug-likeness and structure-based search are available. Also, PPI curation search by compound and target is built-in in the web system.<\/p>\n

The authors demonstrated the usefulness of DLiP-PPI in combination with machine learning in identification and discovery of inhibitors of Keap1\/Nrf2 PPI.6),7)<\/sup>\u00a0They first performed ligand-based virtual screening (LBVS) and applied two random forest (RT) models, named RF-TI and RF-PI. RF-TI model was generated from truly active and inactive compounds from databases, while PF-PI includes commercial compounds as the putative inactive ones. PF-PI would work as an expansion model in terms of structures and targets. TR-FRET (time-resolved fluorescence resonance energy transfer) assays revealed 15 out of 620 compounds. 5 out of the 15 hits possessed a common substructure and it worked as a hit-expansion methodology.<\/p>\n

In the second report, the authors applied DNN (deep learning network) with RF and performed iterative LBVS for improvement. In addition, they switched from RF-TI and RF-PI models to utilization of two different library sets: DLiP1 library for a structure-based drug design, and DLiP2 library for non-flat (sphere-like, spiro, or so) compounds suitable for PPI inhibitors.<\/p>\n

First machine learning was conveyed with DLiP1, initial batch of LBVS and TR-FRET assay dataset (FA), the database from the previous work and public data (DB). Then RF\/DNN models were performed with these data and DLip2 and TR-FRET activities were measured for selected compounds.<\/p>\n

The authors tried five models in this paper and the hit rates ranged 20.0%-27.3%. Compared to random model (1.0%), RF-TI (2.7%) and RF-PI (5.9%), it is obvious that model improvement and iterative approach bumped up the performance of prediction.<\/p>\n

The combination of a reliable and target-nature-oriented database and a sophisticated machine learning model produce a broad and expanding opportunity. We will continuously try application of AI-based approaches for drug discovery. We would appreciate it if you are interested in our unique PepMetics library to initiate a collaborative project for PPIs targeted drug discovery and development.<\/p>\n

https:\/\/doi.org\/10.1093\/database\/baw007<\/a>
\nhttps:\/\/doi.org\/10.1093\/database\/bat039<\/a>
\nhttps:\/\/doi.org\/10.1016\/j.drudis.2013.05.003<\/a>
\nhttps:\/\/doi.org\/10.3389\/fchem.2022.1090643<\/a>
\nhttps:\/\/skb-insilico.com\/dlip<\/a>
\nhttps:\/\/doi.org\/10.1038\/s41598-021-86616-1<\/a>
\nhttps:\/\/doi.org\/10.1039\/D3CC01283B<\/a><\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>","protected":false},"excerpt":{"rendered":"

Protein-protein interactions (PPIs) library is an indispensable and invaluable tool for PPI drug discovery and development. 2P2Idb v21)<\/sup>, TIMBAL v22)<\/sup>, iPPI-DB3)<\/sup>\u00a0have been the libraries focused on PPIs and data availability in the recently elucidated cases were limited for long. It will open up to everyone a great opportunity to initiate another PPIs-targeted drug discovery program if …<\/p>","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[18],"tags":[],"class_list":["post-1954","post","type-post","status-publish","format-standard","hentry","category-blog"],"yoast_head":"\nDLiP-PPI library for Keap1\/Nrf2 PPI Inhibitor Identification and Discovery - PRISM BioLab<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/prismbiolab.com\/ja\/dlip-ppi-library-for-keap1-nrf2-ppi-inhibitor-identification-and-discovery\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"DLiP-PPI library for Keap1\/Nrf2 PPI Inhibitor Identification and Discovery - PRISM BioLab\" \/>\n<meta property=\"og:description\" content=\"Protein-protein interactions (PPIs) library is an indispensable and invaluable tool for PPI drug discovery and development. 2P2Idb v21), TIMBAL v22), iPPI-DB3)\u00a0have been the libraries focused on PPIs and data availability in the recently elucidated cases were limited for long. 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