Optimizing the Signal-to-Noise Ratio of Scoring Functions for Protein−Ligand Docking-Reference-Cited by-同舟云学术

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Optimizing the Signal-to-Noise Ratio of Scoring Functions for Protein−Ligand Docking

Published:2008-02-23 Issue:3 Volume:48 Page:602-612
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Seifert Markus H. J.¹

Affiliation:

1. 4SC AG, Am Klopferspitz 19a, D-82152 Planegg-Martinsried, Germany

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ci700345n

Reference46 articles.

1. Protein-Ligand Binding Affinity Predictions by Implicit Solvent Simulations: A Tool for Lead Optimization?

2. Towards Predictive Ligand Design With Free-Energy Based Computational Methods?

3. Validation and Use of the MM-PBSA Approach for Drug Discovery

4. Approaches to the Description and Prediction of the Binding Affinity of Small-Molecule Ligands to Macromolecular Receptors

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Supervised Machine Learning Methods Applied to Predict Ligand- Binding Affinity;Current Medicinal Chemistry;2017-09-11

2. Enhance the performance of current scoring functions with the aid of 3D protein-ligand interaction fingerprints;BMC Bioinformatics;2017-07-18

3. In Silico ADME Techniques Used in Early-Phase Drug Discovery;Translating Molecules into Medicines;2017

4. Scoring Functions of Protein-Ligand Interactions;Oncology;2017

5. Scoring Functions of Protein-Ligand Interactions;Methods and Algorithms for Molecular Docking-Based Drug Design and Discovery;2016

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