[HTML][HTML] Prediction of repurposed drugs for Coronaviruses using artificial intelligence and machine learning
The world is facing the COVID-19 pandemic caused by Severe Acute Respiratory Syndrome
Coronavirus 2 (SARS-CoV-2). Likewise, other viruses of the Coronaviridae family were …
Coronavirus 2 (SARS-CoV-2). Likewise, other viruses of the Coronaviridae family were …
Anti-biofilm: Machine learning assisted prediction of IC50 activity of chemicals against biofilms of microbes causing antimicrobial resistance and implications in drug …
Biofilms are one of the leading causes of antibiotic resistance. It acts as a physical barrier
against the human immune system and drugs. The use of anti-biofilm agents helps in …
against the human immune system and drugs. The use of anti-biofilm agents helps in …
Computational identification of potential multitarget inhibitors of Nipah virus by molecular docking and molecular dynamics
Nipah virus (NiV) is a recently emerged paramyxovirus that causes severe encephalitis and
respiratory diseases in humans. Despite the severe pathogenicity of this virus and its …
respiratory diseases in humans. Despite the severe pathogenicity of this virus and its …
Multiple machine learning comparisons of HIV cell-based and reverse transcriptase data sets
The human immunodeficiency virus (HIV) causes over a million deaths every year and has a
huge economic impact in many countries. The first class of drugs approved were nucleoside …
huge economic impact in many countries. The first class of drugs approved were nucleoside …
Application of deep learning and molecular modeling to identify small drug-like compounds as potential HIV-1 entry inhibitors
AM Andrianov, GI Nikolaev, NA Shuldov… - Journal of …, 2022 - Taylor & Francis
A generative adversarial autoencoder for the rational design of potential HIV-1 entry
inhibitors able to block CD4-binding site of the viral envelope protein gp120 was developed …
inhibitors able to block CD4-binding site of the viral envelope protein gp120 was developed …
Discovery of novel HIV protease inhibitors using modern computational techniques
SN Okafor, P Angsantikul, H Ahmed - International Journal of Molecular …, 2022 - mdpi.com
The human immunodeficiency virus type 1 (HIV-1) has continued to be a global concern.
With the new HIV incidence, the emergence of multi-drug resistance and the untoward side …
With the new HIV incidence, the emergence of multi-drug resistance and the untoward side …
A comprehensive comparison of molecular feature representations for use in predictive modeling
Abstract Machine learning methods are commonly used for predicting molecular properties
to accelerate material and drug design. An important part of this process is deciding how to …
to accelerate material and drug design. An important part of this process is deciding how to …
Small molecules of natural origin as potential anti-HIV agents: a computational approach
L Crisan, A Bora - Life, 2021 - mdpi.com
The human immunodeficiency virus type 1 (HIV-1), one of the leading causes of infectious
death globally, generates severe damages to people's immune systems and makes them …
death globally, generates severe damages to people's immune systems and makes them …
[HTML][HTML] Targeting non-structural proteins of Hepatitis C virus for predicting repurposed drugs using QSAR and machine learning approaches
Hepatitis C virus (HCV) infection causes viral hepatitis leading to hepatocellular carcinoma.
Despite the clinical use of direct-acting antivirals (DAAs) still there is treatment failure in 5 …
Despite the clinical use of direct-acting antivirals (DAAs) still there is treatment failure in 5 …
LigTMap: ligand and structure-based target identification and activity prediction for small molecular compounds
Target prediction is a crucial step in modern drug discovery. However, existing experimental
approaches to target prediction are time-consuming and costly. Here, we introduce …
approaches to target prediction are time-consuming and costly. Here, we introduce …