AIMC Topic: Protease Inhibitors

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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
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...

Prediction of Potential Commercially Available Inhibitors against SARS-CoV-2 by Multi-Task Deep Learning Model.

Biomolecules
The outbreak of COVID-19 caused millions of deaths worldwide, and the number of total infections is still rising. It is necessary to identify some potentially effective drugs that can be used to prevent the development of severe symptoms, or even dea...

Design of SARS-CoV-2 Mpro, PLpro dual-target inhibitors based on deep reinforcement learning and virtual screening.

Future medicinal chemistry
Since December 2019, SARS-CoV-2 has continued to spread rapidly around the world. The effective drugs may provide a long-term strategy to combat this virus. The main protease (Mpro) and papain-like protease (PLpro) are two important targets for the ...

De novo design of novel protease inhibitor candidates in the treatment of SARS-CoV-2 using deep learning, docking, and molecular dynamic simulations.

Computers in biology and medicine
The main protease of SARS-CoV-2 is a critical target for the design and development of antiviral drugs. 2.5 M compounds were used in this study to train an LSTM generative network via transfer learning in order to identify the four best candidates ca...

Computational investigation of drug bank compounds against 3C-like protease (3CL) of SARS-CoV-2 using deep learning and molecular dynamics simulation.

Molecular diversity
Blocking the main replicating enzyme, 3 Chymotrypsin-like protease (3CL) is the most promising drug development strategy against the SARS-CoV-2 virus, responsible for the current COVID-19 pandemic. In the present work, 9101 drugs obtained from the dr...

Classification of beta-site amyloid precursor protein cleaving enzyme 1 inhibitors by using machine learning methods.

Chemical biology & drug design
The beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) is a transmembrane aspartyl-protease, that cleaves amyloid precursor protein (APP) at the β-site. The sequential proteolytic cleavage of APP, first by β-secretase and then by γ-secreta...

Navigating Chemical Space by Interfacing Generative Artificial Intelligence and Molecular Docking.

Journal of chemical information and modeling
Here, we report the implementation and application of a simple, structure-aware framework to generate target-specific screening libraries. Our approach combines advances in generative artificial intelligence (AI) with conventional molecular docking t...

Deep learning model for virtual screening of novel 3C-like protease enzyme inhibitors against SARS coronavirus diseases.

Computers in biology and medicine
In the context of the recently emerging COVID-19 pandemic, we developed a deep learning model that can be used to predict the inhibitory activity of 3CLpro in severe acute respiratory syndrome coronavirus (SARS-CoV) for unknown compounds during the v...

New machine learning and physics-based scoring functions for drug discovery.

Scientific reports
Scoring functions are essential for modern in silico drug discovery. However, the accurate prediction of binding affinity by scoring functions remains a challenging task. The performance of scoring functions is very heterogeneous across different tar...