Prediction of water and metal binding sites and their affinities by using the Fold-X force field.

By Joost Schymkowitz, Frederic Rousseau, I. C. Martins, Jesper Ferkinghoff-Borg, Francois Stricher, Luis Serrano. 2005

328 citations recorded by the source corpus.

Subfields: Materials Chemistry, Molecular Biology, Spectroscopy

How researchers see this paper

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

In Materials Chemistry

1. Jian Peng
2. Yang Liu
3. Jeffrey R. Brender
4. Richard Lavery
5. Patrick Barth
6. Gregory A. Ross
7. F. Boas
8. Pehr Harbury

In Molecular Biology

1. Jian Peng
2. Yang Zhang
3. Yang Liu
4. Jeffrey R. Brender
5. Richard Lavery
6. Patrick Barth
7. Gregory A. Ross
8. F. Boas

In Spectroscopy

1. Jian Peng
2. Gregory A. Ross
3. Philip C. Biggin
4. Yang Zhang
5. Garrett M. Morris
6. Yufeng Su
7. Robin Pearce

Citations in the corpus

• Evolutionary context-integrated deep sequence modeling for protein engineering (2020, background): “Rational design is oftentimes assisted by quantitative approaches to evaluate sequences that fold into a specific structure, including biophysical modeling [3,4] , force field approximations [5–7] , structure prediction [8–10] , and molecular dynamics simulations [11] .”
• Relationship between protein thermodynamic constraints and variation of evolutionary rates among sites (2014, methodology): “We calculated ΔΔ G values with the program FoldX, following the default protocol (Guerois et al. 2002, Schymkowitz et al. 2005).”
• Potential energy functions for protein design. (2007, methodology): “[34] developed a method for predicting the positions of tightly bound water molecules in proteins.”
• Rapid and Accurate Prediction and Scoring of Water Molecules in Protein Binding Sites (2012, background): “similarly used water distributions around amino acids to predict buried water molecules [58].”
• Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles (2015, methodology): “For all the sequence and physics based energies except the docking functions PIE [45], PISA [46], and DCOMPLEX [47] and the all atomic energy functions Talaris 2013 [44] and FoldX [42, 43, 63] energies were calculated separately for the mutant and WT complex structures and Recognizing Mutations on P”
• Enhancing structure prediction and design of soluble and membrane proteins with explicit solvent-protein interactions (2017, methodology): “Consistent with the lower accuracy prediction of water molecule positions, Fold-X was also substantially outperformed by SPaDES in de novo modeling solvent-interacting side-chain conformations (Figure 3A,B).”