Robust classification of "relevant" water molecules in putative protein binding sites.

By Alessio Amadasi, J. A. Surface, F. Spyrakis, P. Cozzini, A. Mozzarelli, G. Kellogg. 2008

99 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology, Computational Biology & Bioinformatics, Computational Chemistry & Drug Discovery

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Glaucius Oliva
2. L. Ferreira
3. Ricardo N Dos Santos
4. Adriano Defini Andricopulo
5. Luca Pinzi
6. Giulio Rastelli

In Materials Chemistry

1. Glaucius Oliva
2. Adriano Defini Andricopulo
3. L. Ferreira
4. Ricardo N Dos Santos

In Molecular Biology

1. Glaucius Oliva
2. L. Ferreira
3. Ricardo N Dos Santos
4. Adriano Defini Andricopulo

In Computational Biology & Bioinformatics

1. Glaucius Oliva
2. Adriano Defini Andricopulo
3. L. Ferreira
4. Ricardo N Dos Santos

In Computational Chemistry & Drug Discovery

1. Glaucius Oliva
2. Adriano Defini Andricopulo
3. L. Ferreira
4. Ricardo N Dos Santos
5. Giulio Rastelli
6. Luca Pinzi

Citations in the corpus

• Molecular Docking and Structure-Based Drug Design Strategies (2015, background): “Another strategy is the analysis of geometric parameters of the protein environment surrounding each crystallographic water molecule [111].”
• Rapid and Accurate Prediction and Scoring of Water Molecules in Protein Binding Sites (2012, unknown): “Amadasi and coworkers have combined the HINT forcefield [63] with the Rank score [64] to classify water molecules into 2 broad categories; conserved/functionally displaced and sterically displaced/missing [65,66].”