Garrett M. Morris

Molecular Biology · 1996–2023

A researcher in the Science corpus: 10 papers; trusts 14 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 66 citations into it; #2,537 of 17,773 by trust here, #5,705 by citations
• Computational Theory and Mathematics — 64 citations into it; #1,766 of 12,182 by trust here, #417 by citations
• Computational Chemistry & Drug Discovery — 28 citations into it; #160 of 425 by trust here, #266 by citations
• Materials Chemistry — 23 citations into it; #2,220 of 11,513 by trust here, #6,473 by citations
• Spectroscopy — 12 citations into it
• Organic Chemistry — 11 citations into it
• Computational Biology & Bioinformatics — 9 citations into it
• Radiology, Nuclear Medicine and Imaging — 5 citations into it

Whom Garrett M. Morris trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Helen M. Berman
2. Ruth Huey
3. C. Hetényi
4. Sérgio Filipe Sousa
5. Arthur J. Olson
6. Marcel L. Verdonk
7. Jung-Hsin Lin
8. David S. Goodsell
9. Jason C. Cole
10. D. van der Spoel

Who trusts Garrett M. Morris overall

1. C. Hetényi
2. Stefano Forli
3. D. van der Spoel
4. Jinn-Moon Yang
5. Diane Joseph-McCarthy
6. Sandro Cosconati
7. Abdo A. Elfiky
8. Brian K. Shoichet
9. Veronica Salmaso
10. Ragul Gowthaman

Papers from Garrett M. Morris's perspective

Ordered by how strongly the researchers Garrett M. Morris trusts endorse each paper. Same corpus, a different order for every researcher.

1. The Protein Data Bank
2. A semiempirical free energy force field with charge‐based desolvation (Journal of Computational Chemistry)
3. The Protein Data Bank.
4. Computational drug design accommodating receptor flexibility: the relaxed complex scheme. (Journal of the American Chemical Society)
5. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading
6. Comparing protein–ligand docking programs is difficult
7. Diverse, high-quality test set for the validation of protein-ligand docking performance.
8. Efficient docking of peptides to proteins without prior knowledge of the binding site (Protein Science)
9. Evaluation of docking performance: comparative data on docking algorithms. (Journal of Medicinal Chemistry)
10. Protein–ligand docking: Current status and future challenges

Their papers

• A semiempirical free energy force field with charge‐based desolvation (2007) — 2,152 citations
• AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility (2009) — 23,062 citations
• Rapid and Accurate Prediction and Scoring of Water Molecules in Protein Binding Sites (2012) — 182 citations
• PoseBusters: AI-based docking methods fail to generate physically valid poses or generalise to novel sequences (2023) — 343 citations
• Automated docking to multiple target structures: Incorporation of protein mobility and structural water heterogeneity in AutoDock (2002) — 455 citations
• Using AutoDock for Ligand‐Receptor Docking (2008) — 1,222 citations
• Protein-Ligand Interaction Graphs: Learning from Ligand-Shaped 3D Interaction Graphs to Improve Binding Affinity Prediction (2022) — 24 citations
• Crystal Structure of a Neutralizing Human IgG Against HIV-1: A Template for Vaccine Design (2001) — 947 citations
• Alteration of Substrate and Inhibitor Specificity of Feline Immunodeficiency Virus Protease (2000) — 34 citations
• Distributed automated docking of flexible ligands to proteins: Parallel applications of AutoDock 2.4 (1996)