Electrophilicity index.

By Pratim Kumar Chattaraj, U. Sarkar, D. R. Roy. Chemical Reviews, 2006

4,645 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Electrochemistry, Organic Chemistry

View Paper: https://www.semanticscholar.org/paper/db463bd9b9efb483e082364cf43a7263257cf512

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In Electrical and Electronic Engineering

1. Alexander Tropsha
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3. Jui-Hua Hsieh
4. Shuangye Yin
5. Shubin Liu

In Electrochemistry

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2. N. V. Dokholyan
3. Jui-Hua Hsieh
4. Shuangye Yin
5. Shubin Liu

In Organic Chemistry

1. Alexander Tropsha
2. N. V. Dokholyan
3. Jui-Hua Hsieh
4. Shuangye Yin
5. Shubin Liu

Citations in the corpus

• Combined application of cheminformatics- and physical force field-based scoring functions improves binding affinity prediction for CSAR datasets (2011, methodology): “Herein, we develop novel descriptors by incorporating conceptual DFT atomic properties 12 into the generation of protein (cid:1) ligand interfacial descriptors and use high-quality CSAR-NRC sets to construct and validate QSBAR models that are used to predict the binding a ffi nity of ligands in…”
• Cheminformatics Meets Molecular Mechanics: A Combined Application of Knowledge-based Pose Scoring and Physical Force Field-based Hit Scoring Functions Improves the Accuracy of Structure-Based Virtual Screening (2011, methodology): “As shown in Figure 1, poses with lower RMSD value typically have smaller distances to the native pose in the PL/MCT-tess descriptor space.”