Kenneth López-Pérez,Juan F Avellaneda-Tamayo,Lexin Chen et al.
Kenneth López-Pérez et al.
Molecular similarity pervades much of our understanding and rationalization of chemistry. This has become particularly evident in the current data-intensive era of chemical research, with similarity measures serving as the backbone of many ...
Machine learning models to predict ligand binding affinity for the orexin 1 receptor [0.03%]
预测食欲肽1受体配体结合亲和力的机器学习模型
Vanessa Y Zhang,Shayna L O&#x;Connor,William J Welsh et al.
Vanessa Y Zhang et al.
The orexin 1 receptor (OX1R) is a G-protein coupled receptor that regulates a variety of physiological processes through interactions with the neuropeptides orexin A and B. Selective OX1R antagonists exhibit therapeutic effects in preclinic...
Yuanzhe Zhou,Shi-Jie Chen
Yuanzhe Zhou
RNA molecules play multifaceted functional and regulatory roles within cells and have garnered significant attention in recent years as promising therapeutic targets. With remarkable successes achieved by artificial intelligence (AI) in dif...
Predicting anti-SARS-CoV-2 activities of chemical compounds using machine learning models [0.03%]
利用机器学习模型预测化学物质的抗SARS-CoV-2活性
Beihong Ji,Yuhui Wu,Elena N Thomas et al.
Beihong Ji et al.
To accelerate the discovery of novel drug candidates for Coronavirus Disease 2019 (COVID-19) therapeutics, we reported a series of machine learning (ML)-based models to accurately predict the anti-SARS-CoV-2 activities of screening compound...
Evaluating point-prediction uncertainties in neural networks for protein-ligand binding prediction [0.03%]
评估神经网络在蛋白质-配体结合预测中的点预测不确定性
Ya Ju Fan,Jonathan E Allen,Kevin S McLoughlin et al.
Ya Ju Fan et al.
Neural Network (NN) models provide potential to speed up the drug discovery process and reduce its failure rates. The success of NN models requires uncertainty quantification (UQ) as drug discovery explores chemical space beyond the trainin...