David E. Shaw

Molecular Biology · 2004–2023

A researcher in the Science corpus: 27 papers; trusts 17 researchers and is trusted by 30 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 208 citations into it; #1,275 of 17,773 by trust here, #509 by citations
• Materials Chemistry — 106 citations into it; #933 of 11,513 by trust here, #1,515 by citations
• Atomic and Molecular Physics, and Optics — 47 citations into it; #6,922 of 7,135 by trust here, #2,157 by citations
• Spectroscopy — 39 citations into it; #661 of 1,674 by trust here, #195 by citations
• Genetics — 8 citations into it
• Public Health, Environmental and Occupational Health — 5 citations into it

Whom David E. Shaw trusts overall

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

1. K. Lindorff‐Larsen
2. Stefano Piana
3. W. L. Jorgensen
4. Robert B. Best
5. Stewart A. Adcock
6. Alexander D. MacKerell
7. James Andrew McCammon
8. Ron O. Dror
9. Sarel Jacob Fleishman
10. Gerhard Hummer

Who trusts David E. Shaw overall

1. W. Sinko
2. Paul Robustelli
3. Stefano Piana
4. Veronica Salmaso
5. Scott A. Hollingsworth
6. David W. Borhani
7. Gregory Sliwoski
8. Ron O. Dror
9. K. Lindorff‐Larsen
10. Robin Pearce

Papers from David E. Shaw's perspective

Ordered by how strongly the researchers David E. Shaw trusts endorse each paper. Same corpus, a different order for every researcher.

1. Comparison of simple potential functions for simulating liquid water
2. GPU-Accelerated Molecular Modeling Coming Of Age (Journal of Molecular Graphics and Modelling)
3. A point‐charge force field for molecular mechanics simulations of proteins based on condensed‐phase quantum mechanical calculations (Journal of Computational Chemistry)
4. Simultaneous determination of protein structure and dynamics (Nature)
5. Markov models of molecular kinetics: generation and validation.
6. All-atom empirical potential for molecular modeling and dynamics studies of proteins.
7. Scalable molecular dynamics with NAMD
8. Long-timescale molecular dynamics simulations of protein structure and function. (Current Opinion in Structural Biology)
9. Water dispersion interactions strongly influence simulated structural properties of disordered protein states. (Journal of Physical Chemistry B)
10. Molecular dynamics: survey of methods for simulating the activity of proteins. (Chemical Reviews)

Their papers

• Parallel random numbers: As easy as 1, 2, 3 (2011) — 318 citations
• How Fast-Folding Proteins Fold (2011) — 1,934 citations
• Supporting Online Material Materials and Methods Figs. S1 to S10 Table S1 References Movies S1 to S3 Atomic-level Characterization of the Structural Dynamics of Proteins — 1,242 citations
• A hierarchical approach to all‐atom protein loop prediction (2004) — 2,320 citations
• Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. (2004) — 8,978 citations
• Pathway and mechanism of drug binding to G-protein-coupled receptors (2011) — 717 citations
• Improved side-chain torsion potentials for the Amber ff99SB protein force field (2010) — 5,790 citations
• Developing a molecular dynamics force field for both folded and disordered protein states (2018) — 920 citations
• Systematic Validation of Protein Force Fields against Experimental Data (2012) — 659 citations
• Anton, a special-purpose machine for molecular dynamics simulation (2008) — 583 citations
• Assessing the accuracy of physical models used in protein-folding simulations: quantitative evidence from long molecular dynamics simulations. (2014) — 449 citations
• Anton, a special-purpose machine for molecular dynamics simulation (2007) — 489 citations
• Biomolecular simulation: a computational microscope for molecular biology. (2012) — 1,126 citations
• How robust are protein folding simulations with respect to force field parameterization? (2011) — 809 citations
• Water dispersion interactions strongly influence simulated structural properties of disordered protein states. (2015) — 773 citations
• Long-timescale molecular dynamics simulations of protein structure and function. (2009) — 744 citations
• PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results (2006) — 1,140 citations
• Structure and Function of an Irreversible Agonist-β2 Adrenoceptor complex (2011) — 766 citations
• Structure and Dynamics of the M3 Muscarinic Acetylcholine Receptor (2012) — 789 citations
• Activation mechanism of the β2-adrenergic receptor (2011) — 603 citations