AIMC Topic: Proteolysis

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HIV OctaScanner: A Machine Learning Approach to Unveil Proteolytic Cleavage Dynamics in HIV-1 Protease Substrates.

Journal of chemical information and modeling
The rise of resistance to antiretroviral drugs due to mutations in human immunodeficiency virus-1 (HIV-1) protease is a major obstacle to effective treatment. These mutations alter the drug-binding pocket of the protease and reduce the drug efficacy ...

A synthetic protein-level neural network in mammalian cells.

Science (New York, N.Y.)
Artificial neural networks provide a powerful paradigm for nonbiological information processing. To understand whether similar principles could enable computation within living cells, we combined de novo-designed protein heterodimers and engineered v...

AI-DPAPT: a machine learning framework for predicting PROTAC activity.

Molecular diversity
Proteolysis Targeting Chimeras are part of targeted protein degradation (TPD) techniques, which are significant for pharmacological and therapy development. Small-molecule interaction with the targeted protein is a complicated endeavor and a challeng...

Application of machine learning models for property prediction to targeted protein degraders.

Nature communications
Machine learning (ML) systems can model quantitative structure-property relationships (QSPR) using existing experimental data and make property predictions for new molecules. With the advent of modalities such as targeted protein degraders (TPD), the...

PROTACable Is an Integrative Computational Pipeline of 3-D Modeling and Deep Learning To Automate the De Novo Design of PROTACs.

Journal of chemical information and modeling
Proteolysis-targeting chimeras (PROTACs) that engage two biological targets at once are a promising technology in degrading clinically relevant protein targets. Since factors that influence the biological activities of PROTACs are more complex than t...

Emerging Pharmacotherapeutic Strategies to Overcome Undruggable Proteins in Cancer.

International journal of biological sciences
Targeted therapies in cancer treatment can improve efficacy and reduce adverse effects by altering the tissue exposure of specific biomolecules. However, there are still large number of target proteins in cancer are still undruggable, owing to the f...

Sulfur-containing marine natural products as leads for drug discovery and development.

Current opinion in chemical biology
Among the large series of marine natural products (MNPs), sulfur-containing MNPs have emerged as potential therapeutic agents for the treatment of a range of diseases. Herein, we reviewed 95 new sulfur-containing MNPs isolated during the period betwe...

Bifunctional robots inducing targeted protein degradation.

European journal of medicinal chemistry
The gaining importance of Targeted Protein Degradation (TPD) and PROTACs (PROteolysis-TArgeting Chimeras) have drawn the scientific community's attention. PROTACs are considered bifunctional robots owing to their avidity for the protein of interest (...

Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence.

Journal of the American Chemical Society
Only around 20% of the human proteome is considered to be druggable with small-molecule antagonists. This leaves some of the most compelling therapeutic targets outside the reach of ligand discovery. The concept of targeted protein degradation (TPD) ...

Machine Learning Modeling of Protein-intrinsic Features Predicts Tractability of Targeted Protein Degradation.

Genomics, proteomics & bioinformatics
Targeted protein degradation (TPD) has rapidly emerged as a therapeutic modality to eliminate previously undruggable proteins by repurposing the cell's endogenous protein degradation machinery. However, the susceptibility of proteins for targeting by...