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Antiviral Agents

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Machine learning assisted in Silico discovery and optimization of small molecule inhibitors targeting the Nipah virus glycoprotein.

Scientific reports
The Nipah virus (NiV), a lethal pathogen from the Paramyxoviridae family, presents a significant global health threat as a result of its high mortality rate and inter-human transmission. This investigation employed in silico methods that were assiste...

Direct-acting antivirals (DAA) positively affect depression and cognitive function in patients with chronic hepatitis C.

PloS one
The aim of the study was to determine how depression and cognitive dysfunction in patients with chronic hepatitis C virus (HCV) infection are affected by treatment with direct-acting antivirals (DAA). Fifty-two chronic hepatitis C patients underwent ...

Machine Learning-Guided Screening and Molecular Docking for Proposing Naturally Derived Drug Candidates Against MERS-CoV 3CL Protease.

International journal of molecular sciences
In this study, we utilized machine learning techniques to identify potential inhibitors of the MERS-CoV 3CL protease. Among the models evaluated, the Random Forest (RF) algorithm exhibited the highest predictive performance, achieving an accuracy of ...

Enhancing HCV NS3 Inhibitor Classification with Optimized Molecular Fingerprints Using Random Forest.

International journal of molecular sciences
The classification of Hepatitis C virus (HCV) NS3 inhibitors is essential for identifying potential antiviral agents through computational methods. This study aims to develop an optimized machine learning (ML) model using random forest (RF) and molec...

Exploring the repository of de novo-designed bifunctional antimicrobial peptides through deep learning.

eLife
Antimicrobial peptides (AMPs) are attractive candidates to combat antibiotic resistance for their capability to target biomembranes and restrict a wide range of pathogens. It is a daunting challenge to discover novel AMPs due to their sparse distribu...

COVID-19 Patients Benefitting From Remdesivir for Improved Survival: A Neural Network-Based Approach.

Journal of medical virology
Conflicting results from randomized trials regarding the efficacy of remdesivir for COVID-19 have been reported. We aimed to develop a neural network (NN) to identify COVID-19 patients who would derive the greatest survival benefit from remdesivir. T...

Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis.

Journal of medical Internet research
BACKGROUND: While the COVID-19 pandemic has induced massive discussion of available medications on social media, traditional studies focused only on limited aspects, such as public opinions, and endured reporting biases, inefficiency, and long collec...

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...

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Scientific reports
Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic diseases. Nipah virus (NiV) of Paramyxoviridae family and Henipavirus genus is transmitted by Pteropus bats. Climate-induced changes in bat migration pa...