Gerhard Klebe
Molecular Biology · 1994–2011
A researcher in the Science corpus: 14 papers; trusts 32 researchers and is trusted by 62 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 88 citations into it; #694 of 17,773 by trust here, #1,804 by citations
- Computational Theory and Mathematics — 79 citations into it; #525 of 12,182 by trust here, #176 by citations
- Computational Chemistry & Drug Discovery — 74 citations into it; #24 of 425 by trust here, #40 by citations
- Materials Chemistry — 41 citations into it; #1,355 of 11,513 by trust here, #3,180 by citations
- Computational Biology & Bioinformatics — 19 citations into it
- Organic Chemistry — 17 citations into it
- Radiology, Nuclear Medicine and Imaging — 13 citations into it
- Spectroscopy — 12 citations into it; #756 of 1,674 by trust here, #683 by citations
Whom Gerhard Klebe trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Marcel L. Verdonk
- Matthias Rarey
- Manfred Hendlich
- Hans-Joachim Böhm
- Jason C. Cole
- Holger Gohlke
- Christopher W. Murray
- Christopher A. Lipinski
- Robin Taylor
- Renxiao Wang
Who trusts Gerhard Klebe overall
- Jean-Louis Reymond
- Sean Ekins
- Nicolas Moitessier
- Zhong-Ru Xie
- Lars Ruddigkeit
- Jordi Mestres
- I. Kapetanovic
- Shengyou Huang
- John B. O. Mitchell
- Sérgio Filipe Sousa
Papers from Gerhard Klebe's perspective
Ordered by how strongly the researchers Gerhard Klebe trusts endorse each paper. Same corpus, a different order for every researcher.
- A general and fast scoring function for protein-ligand interactions: a simplified potential approach.
- The Protein Data Bank: a computer-based archival file for macromolecular structures.
- \the Protein Data Bank: a Computer-based Archival Le for Macromolecular Structures,"
- RASMOL: biomolecular graphics for all.
- The Protein Data Bank: unifying the archive (Nucleic Acids Res.)
- Structure-Based Strategies for Drug Design and Discovery
- A new test set for validating predictions of protein–ligand interaction (Proteins: Structure, Function, and Bioinformatics)
- A new approach to protein fold recognition
- SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules
- A method to identify protein sequences that fold into a known three-dimensional structure.
Their papers
- Relibase: design and development of a database for comprehensive analysis of protein-ligand interactions. (2003) — 312 citations
- Knowledge-based scoring function to predict protein-ligand interactions. (2000) — 1,037 citations
- Virtual ligand screening: strategies, perspectives and limitations (2006) — 639 citations
- Assessing scoring functions for protein-ligand interactions. (2004) — 440 citations
- PDB2PQR: expanding and upgrading automated preparation of biomolecular structures for molecular simulations (2007) — 1,956 citations
- Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptors. (2002) — 687 citations
- DrugScore(CSD)-knowledge-based scoring function derived from small molecule crystal data with superior recognition rate of near-native ligand poses and better affinity prediction. (2005) — 333 citations
- A new method to detect related function among proteins independent of sequence and fold homology. (2002) — 425 citations
- SFCscore: Scoring functions for affinity prediction of protein–ligand complexes (2008) — 111 citations
- DSX: A Knowledge-Based Scoring Function for the Assessment of Protein-Ligand Complexes (2011) — 276 citations
- A small nonrule of 3 compatible fragment library provides high hit rate of endothiapepsin crystal structures with various fragment chemotypes. (2011) — 99 citations
- AffinDB: a freely accessible database of affinities for protein–ligand complexes from the PDB (2005) — 87 citations
- A fast flexible docking method using an incremental construction algorithm. (1996)
- Comparison of Automatic Three-Dimensional Model Builders Using 639 X-ray Structures (1994)