Peter Kolb

3.9k total citations · 1 hit paper
83 papers, 2.5k citations indexed

About

Peter Kolb is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Computational Theory and Mathematics. According to data from OpenAlex, Peter Kolb has authored 83 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Molecular Biology, 30 papers in Cellular and Molecular Neuroscience and 23 papers in Computational Theory and Mathematics. Recurrent topics in Peter Kolb's work include Receptor Mechanisms and Signaling (41 papers), Neuropeptides and Animal Physiology (25 papers) and Computational Drug Discovery Methods (23 papers). Peter Kolb is often cited by papers focused on Receptor Mechanisms and Signaling (41 papers), Neuropeptides and Animal Physiology (25 papers) and Computational Drug Discovery Methods (23 papers). Peter Kolb collaborates with scholars based in Germany, United States and United Kingdom. Peter Kolb's co-authors include John J. Irwin, Amedeo Caflisch, Brian K. Shoichet, Daniel M. Rosenbaum, Florent Chevillard, Juan Carlos Mobarec, Danzhi Huang, Jie Yin, Brian K. Kobilka and Juan José Fung and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Peter Kolb

77 papers receiving 2.5k citations

Hit Papers

Structure-based discovery of β 2 -adrenergic receptor lig... 2009 2026 2014 2020 2009 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Kolb Germany 29 1.8k 830 627 263 252 83 2.5k
Jens Carlsson Sweden 34 2.5k 1.4× 897 1.1× 797 1.3× 266 1.0× 343 1.4× 74 3.3k
Hugo Gutiérrez‐de‐Terán Sweden 28 1.7k 0.9× 398 0.5× 606 1.0× 151 0.6× 389 1.5× 103 2.3k
Huaiyu Yang China 29 1.9k 1.1× 261 0.3× 565 0.9× 251 1.0× 378 1.5× 105 3.3k
Caterina Bissantz Switzerland 21 1.9k 1.1× 1.1k 1.3× 420 0.7× 202 0.8× 685 2.7× 46 3.2k
Dennis Underwood United States 22 1.5k 0.8× 427 0.5× 679 1.1× 207 0.8× 336 1.3× 41 2.4k
Wolfgang Guba Switzerland 26 1.2k 0.7× 646 0.8× 280 0.4× 108 0.4× 504 2.0× 60 2.0k
Tatsuro Shimamura Japan 26 2.3k 1.3× 267 0.3× 777 1.2× 380 1.4× 135 0.5× 49 3.1k
Syed Tasadaque Ali Shah Germany 21 2.9k 1.6× 248 0.3× 1.3k 2.1× 423 1.6× 409 1.6× 49 3.8k
Ben Capuano Australia 24 1.5k 0.9× 271 0.3× 887 1.4× 141 0.5× 468 1.9× 93 2.1k
Ingebrigt Sylte Norway 27 1.5k 0.9× 337 0.4× 569 0.9× 93 0.4× 497 2.0× 127 2.7k

Countries citing papers authored by Peter Kolb

Since Specialization
Citations

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

Fields of papers citing papers by Peter Kolb

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Kolb

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Kolb. A scholar is included among the top collaborators of Peter Kolb 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 Peter Kolb. Peter Kolb 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.
Günther, Stefan, Lisa Hahnefeld, Jamal Shamsara, et al.. (2025). Orphan G protein-coupled receptor GPRC5B controls macrophage function by facilitating prostaglandin E receptor 2 signaling. Nature Communications. 16(1). 1448–1448. 2 indexed citations
2.
Bünemann, Moritz, et al.. (2024). Investigation of Muscarinic Acetylcholine Receptor M3 Activation in Atomistic Detail: A Chemist's Viewpoint. ChemMedChem. 20(3). e202400633–e202400633.
3.
Παπαδόπουλος, Μάνθος Γ., Brian Medel-Lacruz, Angela Ladurner, et al.. (2024). Discovery and characterization of small-molecule TGR5 ligands with agonistic activity. European Journal of Medicinal Chemistry. 276. 116616–116616. 3 indexed citations
4.
Schihada, Hannes, Dovile Januliene, Kristian Parey, et al.. (2024). Cryo-EM structure of cell-free synthesized human histamine 2 receptor/Gs complex in nanodisc environment. Nature Communications. 15(1). 1831–1831. 6 indexed citations
5.
Santos, Lucianna Helene, et al.. (2023). Structure-based discovery of novel cruzain inhibitors with distinct trypanocidal activity profiles. European Journal of Medicinal Chemistry. 257. 115498–115498. 8 indexed citations
6.
Kurz, Michael, Jingchen Shao, Horst Lemoine, et al.. (2023). EP4 Receptor Conformation Sensor Suited for Ligand Screening and Imaging of Extracellular Prostaglandins. Molecular Pharmacology. 104(3). 80–91. 4 indexed citations
7.
Kolb, Peter, et al.. (2023). Development of Fluorescent AF64394 Analogues Enables Real-Time Binding Studies for the Orphan Class A GPCR GPR3. Journal of Medicinal Chemistry. 66(21). 15025–15041. 8 indexed citations
9.
Kolb, Peter, Terry Kenakin, S P H Alexander, et al.. (2022). Community guidelines for GPCR ligand bias: IUPHAR review 32. British Journal of Pharmacology. 179(14). 3651–3674. 121 indexed citations
10.
Schihada, Hannes, et al.. (2022). Isoforms of GPR35 have distinct extracellular N-termini that allosterically modify receptor-transducer coupling and mediate intracellular pathway bias. Journal of Biological Chemistry. 298(9). 102328–102328. 19 indexed citations
11.
Chevillard, Florent, et al.. (2021). Fragment evolution for GPCRs: the role of secondary binding sites in optimization. Chemical Communications. 57(81). 10516–10519. 5 indexed citations
12.
Sydow, Dominique, et al.. (2021). Analyzing Kinase Similarity in Small Molecule and Protein Structural Space to Explore the Limits of Multi-Target Screening. Molecules. 26(3). 629–629. 8 indexed citations
13.
Gunera, Jakub, Jillian G. Baker, Niek van Hilten, Daniel M. Rosenbaum, & Peter Kolb. (2020). Structure-Based Discovery of Novel Ligands for the Orexin 2 Receptor. Journal of Medicinal Chemistry. 63(19). 11045–11053. 7 indexed citations
14.
Chevillard, Florent, Anna Karawajczyk, Els Pardon, et al.. (2019). Interrogating dense ligand chemical space with a forward-synthetic library. Proceedings of the National Academy of Sciences. 116(23). 11496–11501. 18 indexed citations
15.
Hilten, Niek van, Florent Chevillard, & Peter Kolb. (2019). Virtual Compound Libraries in Computer-Assisted Drug Discovery. Journal of Chemical Information and Modeling. 59(2). 644–651. 51 indexed citations
16.
Pardon, Els, Cecilia Betti, Toon Laeremans, et al.. (2018). Nanobody‐Enabled Reverse Pharmacology on G‐Protein‐Coupled Receptors. Angewandte Chemie International Edition. 57(19). 5292–5295. 30 indexed citations
17.
Chevillard, Florent, Cecilia Betti, Els Pardon, et al.. (2018). Binding-Site Compatible Fragment Growing Applied to the Design of β2-Adrenergic Receptor Ligands. Journal of Medicinal Chemistry. 61(3). 1118–1129. 37 indexed citations
18.
Pardon, Els, Cecilia Betti, Toon Laeremans, et al.. (2018). Nanobody‐Enabled Reverse Pharmacology on G‐Protein‐Coupled Receptors. Angewandte Chemie. 130(19). 5390–5393. 2 indexed citations
19.
Gunera, Jakub, et al.. (2017). Similarity- and Substructure-Based Development of β2-Adrenergic Receptor Ligands Based on Unusual Scaffolds. ACS Medicinal Chemistry Letters. 8(5). 481–485. 5 indexed citations
20.
Munk, Christian, Vignir Ísberg, Stefan Mordalski, et al.. (2016). GPCRdb: the G protein‐coupled receptor database – an introduction. British Journal of Pharmacology. 173(14). 2195–2207. 151 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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