AIMC Topic: Protease Inhibitors
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Classification of beta-site amyloid precursor protein cleaving enzyme 1 inhibitors by using machine learning methods.
Chemical biology & drug design
Oct 11, 2021
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
Oct 11, 2021
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...
Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2.
BioMed research international
May 25, 2021
A global pandemic has emerged following the appearance of the new severe acute respiratory virus whose official name is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), strongly affecting the health sector as well as the world econom...
Small Molecule Libraries
Protein Structure, Secondary
Protein Interaction Domains and Motifs
Coronavirus 3C Proteases
Biological Products
Gene Expression
Kinetics
COVID-19 Drug Treatment
Catalytic Domain
Substrate Specificity
Thermodynamics
Protease Inhibitors
Molecular Docking Simulation
Drug Design
Humans
Antiviral Agents
Neural Networks, Computer
Protein Binding
SARS-CoV-2
Deep learning model for virtual screening of novel 3C-like protease enzyme inhibitors against SARS coronavirus diseases.
Computers in biology and medicine
Mar 6, 2021
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
Feb 4, 2021
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...
Repurposing potential of FDA-approved and investigational drugs for COVID-19 targeting SARS-CoV-2 spike and main protease and validation by machine learning algorithm.
Chemical biology & drug design
Dec 22, 2020
The present study aimed to assess the repurposing potential of existing antiviral drug candidates (FDA-approved and investigational) against SARS-CoV-2 target proteins that facilitates viral entry and replication into the host body. To evaluate molec...
Virtual screening of anti-HIV1 compounds against SARS-CoV-2: machine learning modeling, chemoinformatics and molecular dynamics simulation based analysis.
Scientific reports
Nov 23, 2020
COVID-19 caused by the SARS-CoV-2 is a current global challenge and urgent discovery of potential drugs to combat this pandemic is a need of the hour. 3-chymotrypsin-like cysteine protease (3CLpro) enzyme is the vital molecular target against the SAR...
Predictive modeling by deep learning, virtual screening and molecular dynamics study of natural compounds against SARS-CoV-2 main protease.
Journal of biomolecular structure & dynamics
Aug 5, 2020
The whole world is facing a great challenging time due to Coronavirus disease (COVID-19) caused by SARS-CoV-2. Globally, more than 14.6 M people have been diagnosed and more than 595 K deaths are reported. Currently, no effective vaccine or drugs are...
Combined Ensemble Docking and Machine Learning in Identification of Therapeutic Agents with Potential Inhibitory Effect on Human CES1.
Molecules (Basel, Switzerland)
Jul 29, 2019
The human carboxylesterase 1 (CES1), responsible for the biotransformation of many diverse therapeutic agents, may contribute to the occurrence of adverse drug reactions and therapeutic failure through drug interactions. The present study is designed...
Characterization and Identification of Cryptic Biopeptides in (Wangenh K. Koch) Storage Proteins.
BioMed research international
Nov 27, 2017
The objective of this research was to identify and characterize the encoded peptides present in nut storage proteins of . It was found, through in silico prediction, proteomic analysis, and MS spectrometry, that bioactive peptides were mainly found i...
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