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Data-Driven and Task-Specific Scoring Functions for Predicting Ligand Binding Poses and Affinity and for Screening Enrichment.

机译：数据驱动的和特定于任务的评分功能，用于预测配体结合位置和亲和力以及筛选富集。

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作者
Ashtawy, Hossam M.;
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作者单位

Michigan State University.;

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授予单位 Michigan State University.;
学科 Electrical engineering.
学位 Ph.D.
年度 2017
页码 205 p.
总页数 205
原文格式 PDF
正文语种 eng
中图分类
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专利

1. Task-Specific Scoring Functions for Predicting Ligand Binding Poses and Affinity and for Screening Enrichment [J] . Hossam M. Ashtawy, Nihar R. Mahapatra Journal of chemical information and modeling . 2018,第1期

机译：用于预测配体结合姿势和亲和力的任务特异性评分功能和用于筛选富集
2. Using physics-based pose predictions and free energy perturbation calculations to predict binding poses and relative binding affinities for FXR ligands in the D3R Grand Challenge 2 [J] . Christina Athanasiou, Sofia Vasilakaki, Dimitris Dellis, Journal of Computer-Aided Molecular Design . 2018,第1期

机译：使用基于物理的姿态预测和自由能扰动计算，以预测D3R大挑战2中FXR配体的结合姿势和相对结合亲和力
3. Large-scale validation of a quantum mechanics based scoring function: Predicting the binding affinity and the binding mode of a diverse set of protein-ligand complexes [J] . Raha K, Merz KM Journal of Medicinal Chemistry . 2005,第14期

机译：基于量子力学的评分功能的大规模验证：预测各种蛋白质-配体配合物的结合亲和力和结合方式
4. A Comparative Assessment of Conventional and Machine-Learning-Based Scoring Functions in Predicting Binding Affinities of Protein-Ligand Complexes [C] . Ashtawy Hossam M., Mahapatra Nihar R. 2011 IEEE International Conference on Bioinformatics and Biomedicine . 2011

机译：常规和基于机器学习的评分功能在预测蛋白质-配体复合物结合亲和力中的比较评估
5. A comparative study of machine-learning-based scoring functions in predicting protein-ligand binding affinity [D] . Ashtawy, Hossam Mohamed Farg 2011

机译：基于机器学习的评分功能预测蛋白质-配体结合亲和力的比较研究
6. Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme [O] . Max K. Leong, Ren-Guei Syu, Yi-Lung Ding, -1

机译：一种新型的SVM-姿势/ SVM-分数组合组合对接方案预测N-甲基-D-天冬氨酸受体GluN1-配体的结合亲和力。
7. Large-Scale Validation of a Quantum Mechanics Based Scoring Function: Predicting the Binding Affinity and the Binding Mode of a Diverse Set of Protein-Ligand Complexes [O] . -1

机译：基于量子力学的评分功能的大规模验证：预测多样性蛋白质 - 配体复合物的结合亲和力和结合模式

Data-Driven and Task-Specific Scoring Functions for Predicting Ligand Binding Poses and Affinity and for Screening Enrichment.

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