David A. Pearlman

8.1k total citations · 2 hit papers
62 papers, 6.5k citations indexed

About

David A. Pearlman is a scholar working on Molecular Biology, Atomic and Molecular Physics, and Optics and Materials Chemistry. According to data from OpenAlex, David A. Pearlman has authored 62 papers receiving a total of 6.5k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Molecular Biology, 16 papers in Atomic and Molecular Physics, and Optics and 14 papers in Materials Chemistry. Recurrent topics in David A. Pearlman's work include Protein Structure and Dynamics (33 papers), DNA and Nucleic Acid Chemistry (18 papers) and Spectroscopy and Quantum Chemical Studies (14 papers). David A. Pearlman is often cited by papers focused on Protein Structure and Dynamics (33 papers), DNA and Nucleic Acid Chemistry (18 papers) and Spectroscopy and Quantum Chemical Studies (14 papers). David A. Pearlman collaborates with scholars based in United States, France and Netherlands. David A. Pearlman's co-authors include Peter A. Kollman, David M. Ferguson, Wilson S. Ross, George Seibel, Thomas E. Cheatham, James W. Caldwell, David A. Case, Paul S. Charifson, Christophe Chipot and Woody Sherman and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

David A. Pearlman

61 papers receiving 6.4k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

AMBER, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules

1995 2.7k citations David A. Pearlman, David M. Ferguson et al. profile →
Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery

2020 247 citations Tai‐Sung Lee, Bryce K. Allen et al. Journal of Chemical Information and Modeling profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
David A. Pearlman United States	33	4.5k	1.2k	1.2k	934	723	62	6.5k
Michael L. Connolly United States	23	4.4k 1.0×	2.1k 1.7×	737 0.6×	798 0.9×	790 1.1×	35	7.7k
Scott J. Weiner United States	9	4.8k 1.1×	1.5k 1.2×	1.4k 1.2×	618 0.7×	1.2k 1.7×	10	7.4k
Jonathan W. Essex United Kingdom	46	4.4k 1.0×	1.1k 0.9×	1.3k 1.2×	1.3k 1.4×	895 1.2×	154	6.2k
Djamal Bouzida United States	13	4.8k 1.1×	1.8k 1.5×	1.5k 1.3×	513 0.5×	654 0.9×	24	7.1k
Rudi van Drunen Netherlands	4	4.5k 1.0×	1.7k 1.4×	1.3k 1.1×	615 0.7×	999 1.4×	5	8.4k
Emil Alexov United States	50	7.2k 1.6×	1.7k 1.4×	1.2k 1.0×	1.0k 1.1×	613 0.8×	196	9.3k
Donald Bashford United States	40	7.3k 1.6×	2.0k 1.7×	1.8k 1.6×	931 1.0×	1.2k 1.7×	71	10.0k
Eva Darian United States	9	3.4k 0.8×	952 0.8×	765 0.7×	822 0.9×	791 1.1×	10	5.9k
Shuichi Miyamoto Japan	21	4.6k 1.0×	1.2k 1.0×	1.2k 1.0×	483 0.5×	976 1.3×	90	7.7k
Andreas W. Götz United States	32	4.3k 1.0×	1.6k 1.4×	1.6k 1.4×	779 0.8×	1.0k 1.4×	83	7.8k

Countries citing papers authored by David A. Pearlman

Since Specialization

Citations

This map shows the geographic impact of David A. Pearlman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David A. Pearlman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David A. Pearlman more than expected).

Fields of papers citing papers by David A. Pearlman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David A. Pearlman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David A. Pearlman. The network helps show where David A. Pearlman may publish in the future.

Co-authorship network of co-authors of David A. Pearlman

This figure shows the co-authorship network connecting the top 25 collaborators of David A. Pearlman. A scholar is included among the top collaborators of David A. Pearlman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David A. Pearlman. David A. Pearlman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Cournia, Zoe, Bryce K. Allen, Thijs Beuming, et al.. (2020). Rigorous Free Energy Simulations in Virtual Screening. Journal of Chemical Information and Modeling. 60(9). 4153–4169. 125 indexed citations

Lee, Tai‐Sung, Bryce K. Allen, Timothy J. Giese, et al.. (2020). Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery. Journal of Chemical Information and Modeling. 60(11). 5595–5623. 247 indexed citations breakdown →

Negron, Christopher, David A. Pearlman, & Guillermo del Angel. (2019). Predicting mutations deleterious to function in beta-lactamase TEM1 using MM-GBSA. PLoS ONE. 14(3). e0214015–e0214015. 12 indexed citations

Salam, Noeris K., et al.. (2014). Structure-based approach to the prediction of disulfide bonds in proteins. Protein Engineering Design and Selection. 27(10). 365–374. 75 indexed citations

Kuai, Letian, Shao‐En Ong, Jon M. Madison, et al.. (2011). AAK1 Identified as an Inhibitor of Neuregulin-1/ErbB4-Dependent Neurotrophic Factor Signaling Using Integrative Chemical Genomics and Proteomics. Europe PMC (PubMed Central). 18(7). 891–906. 24 indexed citations

Pearlman, David A., B. Govinda Rao, & Paul S. Charifson. (2008). FURSMASA: A new approach to rapid scoring functions that uses a MD‐averaged potential energy grid and a solvent‐accessible surface area term with parameters GA fit to experimental data. Proteins Structure Function and Bioinformatics. 71(3). 1519–1538. 7 indexed citations

Pearlman, David A.. (1996). FINGAR: A new genetic algorithm-based method for fitting NMR data. Journal of Biomolecular NMR. 8(1). 49–66. 18 indexed citations

Pearlman, David A. & Patrick R. Connelly. (1995). Determination of the Differential Effects of Hydrogen Bonding and Water Release on the Binding of FK506 to Native and Tyr82→Phe82 FKBP-12 Proteins using Free Energy Simulations. Journal of Molecular Biology. 248(3). 696–717. 35 indexed citations

Itoh, Susumu, Maureen T. DeCenzo, David J. Livingston, David A. Pearlman, & Manuel A. Navia. (1995). Conformation of FK506 in X-ray structures of its complexes with human recombinant FKBP12 mutants. Bioorganic & Medicinal Chemistry Letters. 5(17). 1983–1988. 25 indexed citations

10.

Pearlman, David A.. (1994). How well do time-averaged J-coupling restraints work?. Journal of Biomolecular NMR. 4(2). 279–99. 28 indexed citations

11.

Lepre, Christopher A., et al.. (1994). Solution Structure of FK506 Bound to the R42K, H87V Double Mutant of FKBP-12. Biochemistry. 33(46). 13571–13580. 10 indexed citations

12.

Singh, Suresh B., David A. Pearlman, & Peter A. Kollman. (1993). Free energy component analysis: application to the “Z-Phobicity” of A · T base pairs. Journal of Biomolecular Structure and Dynamics. 11(2). 303–311. 4 indexed citations

13.

Hurle, Mark R., Charles D. Eads, David A. Pearlman, et al.. (1992). Comparison of solution structures of mutant bovine pancreatic trypsin inhibitor proteins using two‐dimensional nuclear magnetic resonance. Protein Science. 1(1). 91–106. 24 indexed citations

14.

Ferguson, David M., David A. Pearlman, William C. Swope, & Peter A. Kollman. (1992). Free energy perturbation calculations involving potential function changes. Journal of Computational Chemistry. 13(3). 362–370. 25 indexed citations

15.

Schmitz, Uli, David A. Pearlman, & Thomas Leroy James. (1991). Solution structure of [d(GTATATAC)]2 via restrained molecular dynamics simulations with nuclear magnetic resonance constraints derived from relaxation matrix analysis of two-dimensional nuclear overhauser effect experiments. Journal of Molecular Biology. 221(1). 271–292. 33 indexed citations

16.

Pearlman, David A., et al.. (1990). Atomic charges for DNA constituents derived from single-crystal X-ray diffraction data. Journal of Molecular Biology. 211(1). 171–187. 39 indexed citations

17.

Pearlman, David A. & Peter A. Kollman. (1990). The calculated free energy effects of 5‐methyl cytosine on the B to Z transition in DNA. Biopolymers. 29(8-9). 1193–1209. 24 indexed citations

18.

Kim, Sung‐Hou, Milan Tomić, David E. Wemmer, David A. Pearlman, & Stephen R. Holbrook. (1988). Structure of DNA damaged by UV and psoralen. Biochemical Pharmacology. 37(9). 1791–1791. 2 indexed citations

19.

Pearlman, David A. & Sung‐Hou Kim. (1986). Conformational Studies of Nucleic Acids: III. Empirical Multiple Correlation Functions for Nucleic Acid Torsion Angles. Journal of Biomolecular Structure and Dynamics. 4(1). 49–67. 21 indexed citations

20.

Pearlman, David A. & Sung‐Hou Kim. (1985). Determinations of atomic partial charges for nucleic acid constituents from x‐ray diffraction data. I. 2′‐Deoxycytidine‐5′‐monophosphate. Biopolymers. 24(2). 327–357. 31 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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