David L. Mobley

Molecular Biology · 2009–2021

A researcher in the Science corpus: 10 papers; trusts 20 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 110 citations into it; #3,221 of 17,773 by trust here, #4,510 by citations
• Materials Chemistry — 45 citations into it
• Atomic and Molecular Physics, and Optics — 40 citations into it; #2,162 of 7,135 by trust here, #1,800 by citations
• Computational Theory and Mathematics — 40 citations into it
• Spectroscopy — 15 citations into it
• Physical and Theoretical Chemistry — 14 citations into it
• Computational Chemistry & Drug Discovery — 13 citations into it
• Statistical and Nonlinear Physics — 7 citations into it

Whom David L. Mobley trusts overall

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

1. Michael R. Shirts
2. Junmei Wang
3. K. Henzler-Wildman
4. John D. Chodera
5. A. W. Sousa da Silva
6. Alan E. Mark
7. David A. Case
8. Dorothee Kern
9. W. V. van Gunsteren
10. Wim F. Vranken

Who trusts David L. Mobley overall

1. Hyeoncheol Cho
2. Garrett B. Goh
3. Junying Li
4. Xibing He
5. Long-Kai Huang
6. Xiaomin Fang
7. Insung S. Choi
8. Charles Siegel
9. Deng Cai
10. John D. Chodera

Papers from David L. Mobley's perspective

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

1. Automatic atom type and bond type perception in molecular mechanical calculations. (Journal of Molecular Graphics and Modelling)
2. A smooth particle mesh Ewald method
3. Efficient estimation of free energy differences from Monte Carlo data
4. The Protein Data Bank.
5. Fast parallel algorithms for short-range molecular dynamics
6. Scalable molecular dynamics with NAMD
7. GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. (Journal of Chemical Theory and Computation)
8. Anton, a special-purpose machine for molecular dynamics simulation
9. Everything you wanted to know about Markov State Models but were afraid to ask (Methods)
10. Development and testing of a general amber force field

Their papers

• FreeSolv: A database of experimental and calculated hydration free energies, with input files (2014) — 502 citations
• Alchemical free energy methods for drug discovery: Progress and challenges (2011) — 538 citations
• Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field. (2015) — 1,186 citations
• Guidelines for the analysis of free energy calculations (2015) — 477 citations
• Binding of Small-Molecule Ligands to Proteins: “What You See” Is Not Always “What You Get” (2009) — 560 citations
• Predicting binding free energies: Frontiers and benchmarks (2016) — 354 citations
• Blind prediction of solvation free energies from the SAMPL4 challenge (2014) — 140 citations
• Best Practices for Constructing, Preparing, and Evaluating Protein-Ligand Binding Affinity Benchmarks [Article v1.0] (2021) — 73 citations
• Lessons learned from comparing molecular dynamics engines on the SAMPL5 dataset (2016) — 338 citations
• Current Status of the AMOEBA Polarizable Force Field (2010) — 1,280 citations