用QSAR模型对新设计的分子进行优先级排序——SARS-CoV-2 Mpro抑制剂的2D与3D QSAR研究 Case study | 3 min read 开发稳健、预测性的抗SARS-CoV-2 Mpro活性的定量结构活性关系(QSAR)模型,可以阐明活性、为新分子设计提供信息。Cresset Discovery CRO团队使用一个包含76个已知实验活性、常见结合模式的化合物数据集1-6,在分子建模解决方案FlareTM中构建预测性机器学习(ML)和Field 3D-QSAR方法模型7。
Calculating binding free energies for G protein-coupled receptors (GPCRs) accurately capturing lipid exposed binding interactions in P2Y1 Poster pdf
Accelerating small-molecule drug discovery using Free Energy Perturbation calculations Whitepaper | 1 min read Focus your laboratory testing on the most promising candidates by computationally assessing binding affinities of small molecules to their protein targets. Learn more about accelerating drug discovery using free energy ... pdf
A ligand-based approach to PDE10A activity prediction: predictive QSAR models of a high-quality published data set Case study | 21 min read In this case study, a dataset of 77 crystal structures of phosphodiesterase 10A was used to demonstrate the predictive capabilities of 3D QSAR methods in Flare™.
基于配体的方法进行PDE10A的活性预测:高质量公开数据集的预测性QSAR模型 Case study | 7 min read 理解Flare 3D-QSAR在构建 PDE10A抑制剂活性预测模型的预测能力与优势
Free Energy Perturbations (FEP) on membrane targets: capturing lipid exposed binding in the P2Y1 GPCR complex Case study | 16 min read This case study showcases the use of Flare™ FEP for accurately calculating binding affinities for a dataset of 30 ligands that bind between the lipid and GPCR interface in P2Y1.
膜蛋白的自由能微扰计算——用Flare FEP精确地计算暴露于脂质与GPCR P2Y1界面上配体的结合亲合力 Case study | 5 min read 本案例研究演示了如何用Flare™ FEP精确地计算30个结合在P2Y1脂质与GPCR界面上配体数据集的结合亲和力。
How the AI revolution can accelerate early drug discovery Publication | Drug Target Review | 2023 Can AI and ML accelerate delivery of a final drug candidate?
Accelerating drug discovery using Free Energy Perturbation Identification of Potential Inhibitors of SARS-Cov-2 Mpro Cystein Protease Poster pdf