AIMC Topic: COVID-19 Drug Treatment

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Artificial intelligence revolution in drug discovery: A paradigm shift in pharmaceutical innovation.

International journal of pharmaceutics
Integrating artificial intelligence (AI) into drug discovery has revolutionized pharmaceutical innovation, addressing the challenges of traditional methods that are costly, time-consuming, and suffer from high failure rates. By utilizing machine lear...

CACHE Challenge #2: Targeting the RNA Site of the SARS-CoV-2 Helicase Nsp13.

Journal of chemical information and modeling
A critical assessment of computational hit-finding experiments (CACHE) challenge was conducted to predict ligands for the SARS-CoV-2 Nsp13 helicase RNA binding site, a highly conserved COVID-19 target. Twenty-three participating teams comprised of co...

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...

Use of Machine Learning to Compare Disease Risk Scores and Propensity Scores Across Complex Confounding Scenarios: A Simulation Study.

Pharmacoepidemiology and drug safety
PURPOSE: The surge of treatments for COVID-19 in the second quarter of 2020 had a low prevalence of treatment and high outcome risk. Motivated by that, we conducted a simulation study comparing disease risk scores (DRS) and propensity scores (PS) usi...

Drug repurposing targeting COVID-19 3CL protease using molecular docking and machine learning regression approaches.

Scientific reports
The COVID-19 pandemic has initiated a global health emergency, with an exigent need for an effective cure. Progressively, drug repurposing is emerging as a promising solution for saving time, cost, and labor. However, the number of drug candidates th...

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...

EACVP: An ESM-2 LM Framework Combined CNN and CBAM Attention to Predict Anti-coronavirus Peptides.

Current medicinal chemistry
BACKGROUND: The novel coronavirus pneumonia (COVID-19) outbreak in late 2019 killed millions worldwide. Coronaviruses cause diseases such as severe acute respiratory syndrome (SARS-CoV) and SARS-CoV-2. Many peptides in the host defense system have an...

A tailored machine learning approach for mortality prediction in severe COVID-19 treated with glucocorticoids.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease
BACKGROUNDThe impact of severe COVID-19 pneumonia on healthcare systems highlighted the need for accurate predictions to improve patient outcomes. Despite the established efficacy of glucocorticoids (GCs), variable patient respons...

Leveraging Artificial Intelligence for Synergies in Drug Discovery: From Computers to Clinics.

Current pharmaceutical design
Over the period of the preceding decade, artificial intelligence (AI) has proved an outstanding performance in entire dimensions of science including pharmaceutical sciences. AI uses the concept of machine learning (ML), deep learning (DL), and neura...