Scott P. Brown

2.0k total citations
22 papers, 1.3k citations indexed

About

Scott P. Brown is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Scott P. Brown has authored 22 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 8 papers in Computational Theory and Mathematics and 8 papers in Materials Chemistry. Recurrent topics in Scott P. Brown's work include Protein Structure and Dynamics (12 papers), Computational Drug Discovery Methods (8 papers) and Enzyme Structure and Function (6 papers). Scott P. Brown is often cited by papers focused on Protein Structure and Dynamics (12 papers), Computational Drug Discovery Methods (8 papers) and Enzyme Structure and Function (6 papers). Scott P. Brown collaborates with scholars based in United States and Italy. Scott P. Brown's co-authors include Steven W. Muchmore, Philip J. Hajduk, Brian Kelley, Gregory L. Warren, Teresa Head‐Gordon, Nicolas L. Fawzi, Georgia B. McGaughey, Andrew C. Good, Jennifer Grant and Neysa Nevins and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Accounts of Chemical Research and Journal of Medicinal Chemistry.

In The Last Decade

Scott P. Brown

22 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Scott P. Brown United States 15 812 557 229 217 183 22 1.3k
Kunqian Yu China 23 844 1.0× 326 0.6× 197 0.9× 211 1.0× 95 0.5× 56 1.4k
Gregory A. Ross United States 17 1.2k 1.4× 507 0.9× 294 1.3× 290 1.3× 140 0.8× 26 2.0k
Gregory Sliwoski United States 11 1.1k 1.3× 793 1.4× 199 0.9× 296 1.4× 182 1.0× 17 1.9k
Tatu Pantsar Finland 13 947 1.2× 401 0.7× 168 0.7× 204 0.9× 204 1.1× 28 1.6k
Edward W. Lowe United States 11 976 1.2× 828 1.5× 238 1.0× 314 1.4× 175 1.0× 24 1.8k
Andrean Goede Germany 25 1.3k 1.6× 467 0.8× 277 1.2× 129 0.6× 170 0.9× 52 1.9k
Mark McGann United States 7 893 1.1× 600 1.1× 157 0.7× 303 1.4× 144 0.8× 11 1.4k
Brian Y. Feng United States 11 1.2k 1.5× 599 1.1× 157 0.7× 322 1.5× 212 1.2× 18 1.9k
Johannes Voigt United States 23 1.0k 1.3× 513 0.9× 123 0.5× 351 1.6× 176 1.0× 42 1.5k
Allison K. Doak United States 14 1.1k 1.4× 813 1.5× 177 0.8× 251 1.2× 208 1.1× 14 1.8k

Countries citing papers authored by Scott P. Brown

Since Specialization
Citations

This map shows the geographic impact of Scott P. Brown'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 Scott P. Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scott P. Brown more than expected).

Fields of papers citing papers by Scott P. Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Scott P. Brown. 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 Scott P. Brown. The network helps show where Scott P. Brown may publish in the future.

Co-authorship network of co-authors of Scott P. Brown

This figure shows the co-authorship network connecting the top 25 collaborators of Scott P. Brown. A scholar is included among the top collaborators of Scott P. Brown 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 Scott P. Brown. Scott P. Brown is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Oh, Younghoon, Sean K. Bedingfield, Severin T. Schneebeli, et al.. (2025). Challenges and opportunities in computational studies for lipid nanoparticle development. 2(1). 1 indexed citations
2.
Brown, Scott P., Philip Jones, Liming Shao, et al.. (2021). Ulotaront: A TAAR1 Agonist for the Treatment of Schizophrenia. ACS Medicinal Chemistry Letters. 13(1). 92–98. 47 indexed citations
3.
Lee, Michael, et al.. (2018). Current and Future Applications of Machine Learning for the US Army. 4 indexed citations
4.
Spear, Kerry L. & Scott P. Brown. (2017). The evolution of library design: crafting smart compound collections for phenotypic screens. Drug Discovery Today Technologies. 23. 61–67. 14 indexed citations
5.
Kelley, Brian, Scott P. Brown, Gregory L. Warren, & Steven W. Muchmore. (2015). POSIT: Flexible Shape-Guided Docking For Pose Prediction. Journal of Chemical Information and Modeling. 55(8). 1771–1780. 108 indexed citations
6.
Terry-Lorenzo, Ryan T., Lawrence Chun, Scott P. Brown, et al.. (2014). Novel humanD-amino acid oxidase inhibitors stabilize an active-site lid-open conformation. Bioscience Reports. 34(4). 28 indexed citations
7.
Nicholls, Anthony, Georgia B. McGaughey, Robert P. Sheridan, et al.. (2010). Molecular Shape and Medicinal Chemistry: A Perspective. Journal of Medicinal Chemistry. 53(10). 3862–3886. 254 indexed citations
8.
Brown, Scott P., Steven W. Muchmore, & Philip J. Hajduk. (2009). Healthy skepticism: assessing realistic model performance. Drug Discovery Today. 14(7-8). 420–427. 97 indexed citations
9.
Brown, Scott P. & Steven W. Muchmore. (2009). Corrections to Large-Scale Application of High-Throughput Molecular Mechanics with Poisson−Boltzmann Surface Area for Routine Physics-Based Scoring of Protein−Ligand Complexes. Journal of Medicinal Chemistry. 52(14). 4549–4549. 3 indexed citations
10.
Brown, Scott P. & Steven W. Muchmore. (2009). Large-Scale Application of High-Throughput Molecular Mechanics with Poisson−Boltzmann Surface Area for Routine Physics-Based Scoring of Protein−Ligand Complexes. Journal of Medicinal Chemistry. 52(10). 3159–3165. 80 indexed citations
11.
Muchmore, Steven W., Derek A. Debe, James T. Metz, et al.. (2008). Application of Belief Theory to Similarity Data Fusion for Use in Analog Searching and Lead Hopping. Journal of Chemical Information and Modeling. 48(5). 941–948. 121 indexed citations
12.
Wang, Xueqing, Karen Kage, Di Zhang, et al.. (2008). Synthesis and Evaluation of Benzothiazole-Based Analogues as Novel, Potent, and Selective Fatty Acid Amide Hydrolase Inhibitors. Journal of Medicinal Chemistry. 52(1). 170–180. 139 indexed citations
13.
Fawzi, Nicolas L., et al.. (2008). Contrasting Disease and Nondisease Protein Aggregation by Molecular Simulation. Accounts of Chemical Research. 41(8). 1037–1047. 28 indexed citations
14.
Brown, Scott P. & Steven W. Muchmore. (2007). Rapid Estimation of Relative Protein−Ligand Binding Affinities Using a High-Throughput Version of MM-PBSA. Journal of Chemical Information and Modeling. 47(4). 1493–1503. 45 indexed citations
15.
Brown, Scott P. & Steven W. Muchmore. (2007). Rapid Estimation of Relative Protein—Ligand Binding Affinities Using a High‐Throughput Version of MM‐PBSA.. ChemInform. 38(40). 1 indexed citations
16.
Brown, Scott P. & Philip J. Hajduk. (2006). Effects of Conformational Dynamics on Predicted Protein Druggability. ChemMedChem. 1(1). 70–72. 37 indexed citations
17.
18.
Fawzi, Nicolas L., Victor Chubukov, Louis A. Clark, Scott P. Brown, & Teresa Head‐Gordon. (2005). Influence of denatured and intermediate states of folding on protein aggregation. Protein Science. 14(4). 993–1003. 39 indexed citations
19.
Brown, Scott P. & Teresa Head‐Gordon. (2004). Intermediates and the folding of proteins L and G. Protein Science. 13(4). 958–970. 3 indexed citations
20.
Brown, Scott P., Nicolas L. Fawzi, & Teresa Head‐Gordon. (2003). Coarse-grained sequences for protein folding and design. Proceedings of the National Academy of Sciences. 100(19). 10712–10717. 92 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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