Pablo Englebienne
Computational Theory and Mathematics · 2008–2009
A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Computational Theory and Mathematics — 49 citations into it; #5,661 of 12,182 by trust here, #3,681 by citations
- Molecular Biology — 41 citations into it; #6,608 of 17,773 by trust here, #16,527 by citations
- Computational Chemistry & Drug Discovery — 31 citations into it; #184 of 425 by trust here, #398 by citations
Whom Pablo Englebienne trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Pablo Englebienne overall
- L. Ferreira
- S. J. Macalino
- Ricardo N Dos Santos
- Vijayakumar Gosu
- Glaucius Oliva
- Elizabeth Yuriev
- Sunhye Hong
Papers from Pablo Englebienne's perspective
Ordered by how strongly the researchers Pablo Englebienne trusts endorse each paper. Same corpus, a different order for every researcher.
- Molecular recognition of the inhibitor AG-1343 by HIV-1 protease: conformationally flexible docking by evolutionary programming.
- A fast flexible docking method using an incremental construction algorithm.
- Detailed analysis of scoring functions for virtual screening. (Journal of Medicinal Chemistry)
- SMoG: de Novo Design Method Based on Simple, Fast, and Accurate Free Energy Estimates. 1. Methodology and Supporting Evidence
- Automated docking to multiple target structures: Incorporation of protein mobility and structural water heterogeneity in AutoDock (Proteins: Structure, Function, and Bioinformatics)
- Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations. (Journal of Medicinal Chemistry)
- Development and validation of a modular, extensible docking program: DOCK 5 (J. Comput. Aided Mol. Des.)
- Rational automatic search method for stable docking models of protein and ligand.
- Knowledge-based scoring function to predict protein-ligand interactions.
- Virtual Screening Using Protein-Ligand Docking: Avoiding Artificial Enrichment (Journal of Chemical Information and Modeling)