Frank Lovering

7.1k total citations · 2 hit papers
28 papers, 5.2k citations indexed

About

Frank Lovering is a scholar working on Molecular Biology, Organic Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Frank Lovering has authored 28 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 9 papers in Organic Chemistry and 7 papers in Computational Theory and Mathematics. Recurrent topics in Frank Lovering's work include Computational Drug Discovery Methods (7 papers), Chemical Synthesis and Analysis (6 papers) and Protein Kinase Regulation and GTPase Signaling (6 papers). Frank Lovering is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Chemical Synthesis and Analysis (6 papers) and Protein Kinase Regulation and GTPase Signaling (6 papers). Frank Lovering collaborates with scholars based in United States, United Kingdom and Canada. Frank Lovering's co-authors include Christine Humblet, Jack Bikker, William H. Pearson, R. Aldrin Denny, Ray Unwalla, A. Richard Chamberlin, Richard J. Bridges, Xing Li, Huanyu Zhou and Mark E. Bunnage and has published in prestigious journals such as Journal of the American Chemical Society, Scientific Reports and Journal of Medicinal Chemistry.

In The Last Decade

Frank Lovering

28 papers receiving 5.0k citations

Hit Papers

Escape from Flatland: Increasing Saturation as an Approac... 2009 2026 2014 2020 2009 2012 1000 2.0k 3.0k

Peers

Frank Lovering
Jack Bikker United States
Simon J. F. Macdonald United Kingdom
Christine Humblet United States
Christopher J. Helal United States
Allan M. Jordan United Kingdom
David C. Rees United Kingdom
Antonia F. Stepan United States
Hing L. Sham United States
Jack Bikker United States
Frank Lovering
Citations per year, relative to Frank Lovering Frank Lovering (= 1×) peers Jack Bikker

Countries citing papers authored by Frank Lovering

Since Specialization
Citations

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

Fields of papers citing papers by Frank Lovering

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frank Lovering. 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 Frank Lovering. The network helps show where Frank Lovering may publish in the future.

Co-authorship network of co-authors of Frank Lovering

This figure shows the co-authorship network connecting the top 25 collaborators of Frank Lovering. A scholar is included among the top collaborators of Frank Lovering 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 Frank Lovering. Frank Lovering 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.
Sultan, Mohammad M., R. Aldrin Denny, Ray Unwalla, Frank Lovering, & Vijay S. Pande. (2017). Millisecond dynamics of BTK reveal kinome-wide conformational plasticity within the apo kinase domain. Scientific Reports. 7(1). 15604–15604. 38 indexed citations
2.
Li, Xing, David C. Blakemore, Arjun Narayanan, et al.. (2015). Fluorine in Drug Design: A Case Study with Fluoroanisoles. ChemMedChem. 10(4). 715–726. 122 indexed citations
3.
Lovering, Frank, Jeanne S. Chang, Christoph M. Dehnhardt, et al.. (2015). Imidazotriazines: Spleen Tyrosine Kinase (Syk) Inhibitors Identified by Free‐Energy Perturbation (FEP). ChemMedChem. 11(2). 217–233. 35 indexed citations
4.
Lovering, Frank, Joseph J. McDonald, Gavin A. Whitlock, et al.. (2012). Identification of Type‐II Inhibitors Using Kinase Structures. Chemical Biology & Drug Design. 80(5). 657–664. 17 indexed citations
5.
Malamas, Michael S., Keith D. Barnes, Hui Yu, et al.. (2010). Novel pyrrolyl 2-aminopyridines as potent and selective human β-secretase (BACE1) inhibitors. Bioorganic & Medicinal Chemistry Letters. 20(7). 2068–2073. 30 indexed citations
6.
Zhang, Chunchun, Frank Lovering, Mark L. Behnke, et al.. (2009). Synthesis and activity of quinolinylmethyl P1′ α-sulfone piperidine hydroxamate inhibitors of TACE. Bioorganic & Medicinal Chemistry Letters. 19(13). 3445–3448. 8 indexed citations
7.
Huang, Adrian, Diane Joseph‐McCarthy, Frank Lovering, et al.. (2007). Structure-based design of TACE selective inhibitors: Manipulations in the S1′–S3′ pocket. Bioorganic & Medicinal Chemistry. 15(18). 6170–6181. 24 indexed citations
8.
Lee, Katherine L., Megan A. Foley, Lih-Ren Chen, et al.. (2007). Discovery of Ecopladib, an Indole Inhibitor of Cytosolic Phospholipase Α2α. Journal of Medicinal Chemistry. 50(6). 1380–1400. 69 indexed citations
9.
Lombart, Henry‐Georges, Eric Feyfant, Diane Joseph‐McCarthy, et al.. (2007). Design and synthesis of 3,3-piperidine hydroxamate analogs as selective TACE inhibitors. Bioorganic & Medicinal Chemistry Letters. 17(15). 4333–4337. 12 indexed citations
10.
Joseph‐McCarthy, Diane, Jeremy I. Levin, Henry‐Georges Lombart, et al.. (2006). Identification of potent and selective TACE inhibitors via the S1 pocket. Bioorganic & Medicinal Chemistry Letters. 17(1). 34–39. 34 indexed citations
11.
McKew, John C., Megan A. Foley, Paresh Thakker, et al.. (2006). Inhibition of Cytosolic Phospholipase A 2 α: Hit to Lead Optimization. 10 indexed citations
12.
Bridges, Kristie Grove, Rajiv Chopra, Laura Lin, et al.. (2006). A novel approach to identifying β-secretase inhibitors: Bis-statine peptide mimetics discovered using structure and spot synthesis. Peptides. 27(7). 1877–1885. 6 indexed citations
13.
Lovering, Frank, et al.. (2005). Therapeutic Potential of TACE Inhibitors in Stroke. PubMed. 4(2). 161–168. 37 indexed citations
14.
Joseph‐McCarthy, Diane, Kevin Parris, Adrian Huang, et al.. (2005). Use of Structure-Based Drug Design Approaches to Obtain Novel Anthranilic Acid Acyl Carrier Protein Synthase Inhibitors. Journal of Medicinal Chemistry. 48(25). 7960–7969. 27 indexed citations
15.
Wu, Junjun, Thomas S. Rush, Rajeev Hotchandani, et al.. (2005). Identification of potent and selective MMP-13 inhibitors. Bioorganic & Medicinal Chemistry Letters. 15(18). 4105–4109. 60 indexed citations
16.
Hu, Baihua, Kristi Fan, Kristie Grove Bridges, et al.. (2004). Synthesis and SAR of bis-statine based peptides as BACE 1 inhibitors. Bioorganic & Medicinal Chemistry Letters. 14(13). 3457–3460. 18 indexed citations
17.
McKew, John C., Frank Lovering, James D. Clark, et al.. (2003). Structure–activity relationships of indole cytosolic phospholipase A 2 α inhibitors: substrate mimetics. Bioorganic & Medicinal Chemistry Letters. 13(24). 4501–4504. 18 indexed citations
19.
Wacker, Dean A., Frank Lovering, Richard J. Bridges, et al.. (1997). A Selective Photoaffinity Ligand for the Kainate Class of Excitatory Amino Acid Receptor. Synlett. 1997(Sup. I). 503–504. 2 indexed citations
20.
Bridges, Richard J., Frank Lovering, Hans P. Koch, Carl W. Cotman, & A. Richard Chamberlin. (1994). A conformationally constrained competitive inhibitor of the sodium-dependent glutamate transporter in forebrain synaptosomes: l-anti-endo-3,4-methanopyrrolidine dicarboxylate. Neuroscience Letters. 174(2). 193–197. 42 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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