AIMC Topic: Protease Inhibitors

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Characterization and Identification of Cryptic Biopeptides in (Wangenh K. Koch) Storage Proteins.

BioMed research international
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...

QSAR studies of the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by multiple linear regression (MLR) and support vector machine (SVM).

Bioorganic & medicinal chemistry letters
In this study, quantitative structure-activity relationship (QSAR) models using various descriptor sets and training/test set selection methods were explored to predict the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by using a ...

Protease inhibitors in various flours and breads: Effect of fermentation, baking and in vitro digestion on trypsin and chymotrypsin inhibitory activities.

Food chemistry
In this study trypsin (TIA) and chymotrypsin inhibitory (CIA) activities were determined in the extracts of wheat, rye mix, mixed cereals and, whole wheat flours and, breads made with these flours. In addition, effects of fermentation, baking and in ...

Protease Inhibitors in View of Peptide Substrate Databases.

Journal of chemical information and modeling
Protease substrate profiling has nowadays almost become a routine task for experimentalists, and the knowledge on protease peptide substrates is easily accessible via the MEROPS database. We present a shape-based virtual screening workflow using vROC...

A deep learning model for structure-based bioactivity optimization and its application in the bioactivity optimization of a SARS-CoV-2 main protease inhibitor.

European journal of medicinal chemistry
Bioactivity optimization is a crucial and technical task in the early stages of drug discovery, traditionally carried out through iterative substituent optimization, a process that is often both time-consuming and expensive. To address this challenge...

Determination of Novel SARS-CoV-2 Inhibitors by Combination of Machine Learning and Molecular Modeling Methods.

Medicinal chemistry (Shariqah (United Arab Emirates))
INTRODUCTION: Within the scope of the project, this study aimed to find novel inhibitors by combining computational methods. In order to design inhibitors, it was aimed to produce molecules similar to the RdRp inhibitor drug Favipiravir by using the ...

Classification models of HCV NS3 protease inhibitors based on support vector machine (SVM).

Combinatorial chemistry & high throughput screening
Inhibition of the hepatitis C virus (HCV) non-structural protein 3 (NS3) serine protease by molecule inhibitors is an attractive strategy for the treatment of hepatitis C. We built four classification models based on a dataset of 413 HCV NS3 protease...