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Andrographis paniculata (Burm. f.) Wall. ex Nees: An Updated Review of Phytochemistry, Antimicrobial Pharmacology, and Clinical Safety and Efficacy
Infectious disease (ID) is one of the top-most serious threats to human health globally,
further aggravated by antimicrobial resistance and lack of novel immunization options …
further aggravated by antimicrobial resistance and lack of novel immunization options …
Machine learning approaches and databases for prediction of drug–target interaction: a survey paper
The task of predicting the interactions between drugs and targets plays a key role in the
process of drug discovery. There is a need to develop novel and efficient prediction …
process of drug discovery. There is a need to develop novel and efficient prediction …
Network medicine framework for identifying drug-repurposing opportunities for COVID-19
The COVID-19 pandemic has highlighted the need to quickly and reliably prioritize clinically
approved compounds for their potential effectiveness for severe acute respiratory syndrome …
approved compounds for their potential effectiveness for severe acute respiratory syndrome …
Network-based prediction of drug combinations
Drug combinations, offering increased therapeutic efficacy and reduced toxicity, play an
important role in treating multiple complex diseases. Yet, our ability to identify and validate …
important role in treating multiple complex diseases. Yet, our ability to identify and validate …
[HTML][HTML] Artificial intelligence in pharmaceutical sciences
Drug discovery and development affects various aspects of human health and dramatically
impacts the pharmaceutical market. However, investments in a new drug often go …
impacts the pharmaceutical market. However, investments in a new drug often go …
Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases
The identification of interactions between drugs/compounds and their targets is crucial for
the development of new drugs. In vitro screening experiments (ie bioassays) are frequently …
the development of new drugs. In vitro screening experiments (ie bioassays) are frequently …
Deep learning improves prediction of drug–drug and drug–food interactions
Drug interactions, including drug–drug interactions (DDIs) and drug–food constituent
interactions (DFIs), can trigger unexpected pharmacological effects, including adverse drug …
interactions (DFIs), can trigger unexpected pharmacological effects, including adverse drug …
Discovering Anti-Cancer Drugs via Computational Methods
New drug discovery has been acknowledged as a complicated, expensive, time-consuming,
and challenging project. It has been estimated that around 12 years and 2.7 billion USD, on …
and challenging project. It has been estimated that around 12 years and 2.7 billion USD, on …
Network-based approach to prediction and population-based validation of in silico drug repurposing
Here we identify hundreds of new drug-disease associations for over 900 FDA-approved
drugs by quantifying the network proximity of disease genes and drug targets in the human …
drugs by quantifying the network proximity of disease genes and drug targets in the human …
[HTML][HTML] Computational methods in drug discovery
SP Leelananda, S Lindert - Beilstein journal of organic …, 2016 - beilstein-journals.org
The process for drug discovery and development is challenging, time consuming and
expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut …
expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut …