Combining machine learning and computational chemistry for predictive insights into chemical systems
Machine learning models are poised to make a transformative impact on chemical sciences
by dramatically accelerating computational algorithms and amplifying insights available from …
by dramatically accelerating computational algorithms and amplifying insights available from …
Mapping the landscape of artificial intelligence applications against COVID-19
COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by
the World Health Organization, which has reported over 18 million confirmed cases as of …
the World Health Organization, which has reported over 18 million confirmed cases as of …
Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2
Human coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus
(SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead …
(SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead …
[HTML][HTML] Predicting commercially available antiviral drugs that may act on the novel coronavirus (SARS-CoV-2) through a drug-target interaction deep learning model
The infection of a novel coronavirus found in Wuhan of China (SARS-CoV-2) is rapidly
spreading, and the incidence rate is increasing worldwide. Due to the lack of effective …
spreading, and the incidence rate is increasing worldwide. Due to the lack of effective …
Artificial intelligence in drug discovery: recent advances and future perspectives
J Jiménez-Luna, F Grisoni, N Weskamp… - Expert opinion on drug …, 2021 - Taylor & Francis
Introduction: Artificial intelligence (AI) has inspired computer-aided drug discovery. The
widespread adoption of machine learning, in particular deep learning, in multiple scientific …
widespread adoption of machine learning, in particular deep learning, in multiple scientific …
Contrastive learning in protein language space predicts interactions between drugs and protein targets
Sequence-based prediction of drug–target interactions has the potential to accelerate drug
discovery by complementing experimental screens. Such computational prediction needs to …
discovery by complementing experimental screens. Such computational prediction needs to …
Rapid identification of potential inhibitors of SARS‐CoV‐2 main protease by deep docking of 1.3 billion compounds
Abstract The recently emerged 2019 Novel Coronavirus (SARS‐CoV‐2) and associated
COVID‐19 disease cause serious or even fatal respiratory tract infection and yet no …
COVID‐19 disease cause serious or even fatal respiratory tract infection and yet no …
Therapeutics data commons: Machine learning datasets and tasks for drug discovery and development
Therapeutics machine learning is an emerging field with incredible opportunities for
innovatiaon and impact. However, advancement in this field requires formulation of …
innovatiaon and impact. However, advancement in this field requires formulation of …
Molecular docking: shifting paradigms in drug discovery
L Pinzi, G Rastelli - International journal of molecular sciences, 2019 - mdpi.com
Molecular docking is an established in silico structure-based method widely used in drug
discovery. Docking enables the identification of novel compounds of therapeutic interest …
discovery. Docking enables the identification of novel compounds of therapeutic interest …
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 …