Daniel Seeliger

5.2k total citations · 1 hit paper
43 papers, 3.8k citations indexed

About

Daniel Seeliger is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Daniel Seeliger has authored 43 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 14 papers in Computational Theory and Mathematics and 11 papers in Materials Chemistry. Recurrent topics in Daniel Seeliger's work include Protein Structure and Dynamics (23 papers), Computational Drug Discovery Methods (14 papers) and Monoclonal and Polyclonal Antibodies Research (10 papers). Daniel Seeliger is often cited by papers focused on Protein Structure and Dynamics (23 papers), Computational Drug Discovery Methods (14 papers) and Monoclonal and Polyclonal Antibodies Research (10 papers). Daniel Seeliger collaborates with scholars based in Germany, United States and United Kingdom. Daniel Seeliger's co-authors include Bert L. de Groot, Vytautas Gapsys, Servaas Michielssens, Christofer S. Tautermann, Juergen Haas, Eckhard Spohr, C. Hartnig, Laura Pérez‐Benito, Matteo Aldeghi and Herman van Vlijmen and has published in prestigious journals such as Nucleic Acids Research, Angewandte Chemie International Edition and PLoS ONE.

In The Last Decade

Daniel Seeliger

43 papers receiving 3.7k citations

Hit Papers

align trajectories

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.

Ligand docking and binding site analysis with PyMOL and Autodock/Vina

2010 1.8k citations Daniel Seeliger, Bert L. de Groot Journal of Computer-Aided Molecular Design profile →

Peers

Countries citing papers authored by Daniel Seeliger

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Seeliger

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Seeliger

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Seeliger. A scholar is included among the top collaborators of Daniel Seeliger 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 Daniel Seeliger. Daniel Seeliger 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

#	Work	Indexed citations
1	Evaluating the use of absolute binding free energy in the fragment optimisation process 2022 ·Communications Chemistry ·(unknown), Aniket Magarkar, Daniel Seeliger, Philip C. Biggin	39
2	Fragment Binding Pose Predictions Using Unbiased Simulations and Markov-State Models 2019 ·Journal of Chemical Theory and Computation ·Stephanie M. Linker, Aniket Magarkar, Jürgen Köfinger, Gerhard Hummer, Daniel Seeliger	13
3	Enhancing Drug Residence Time by Shielding of Intra-Protein Hydrogen Bonds: A Case Study on CCR2 Antagonists 2019 ·ACS Medicinal Chemistry Letters ·Aniket Magarkar, Gisela Schnapp, (unknown), Daniel Seeliger, Christofer S. Tautermann	10
4	Prediction and Reduction of the Aggregation of Monoclonal Antibodies 2017 ·Journal of Molecular Biology ·Rob van der Kant, Anne R. Karow‐Zwick, Joost Van Durme, Michaela Blech, Rodrigo Gallardo, Daniel Seeliger, (unknown), Pieter Baatsen, Griet Compernolle, Ann Gils, Joey Studts, Patrick Schulz, Patrick Garidel, Joost Schymkowitz, Frédéric Rousseau	115
5	Insights from the First Principles Based Large Scale Protein Thermostability Calculations 2016 ·Biophysical Journal ·Vytautas Gapsys, Servaas Michielssens, Daniel Seeliger, Bert L. de Groot	1
6	Structural Mechanisms of Voltage Sensing in G Protein-Coupled Receptors 2016 ·Structure ·Owen N. Vickery, Jan‐Philipp Machtens, (unknown), Daniel Seeliger, Ulrich Zachariae	42
7	Boosting antibody developability through rational sequence optimization 2015 ·mAbs ·Daniel Seeliger, Patrick Schulz, Tobias Litzenburger, (unknown), S. Hoerer, Michaela Blech, Barbara Enenkel, Joey Studts, Patrick Garidel, (unknown)	55
8	The impact of data integrity on decision making in early lead discovery 2015 ·Journal of Computer-Aided Molecular Design ·Bernd Beck, Daniel Seeliger, Jan M. Kriegl	8
9	A Designed Conformational Shift To Control Protein Binding Specificity 2014 ·Angewandte Chemie International Edition ·Servaas Michielssens, (unknown), David Ban, Supriya Pratihar, Daniel Seeliger, Monika Sharma, Karin Giller, T. Michael Sabo, Stefan Becker, Donghan Lee, Christian Griesinger, Bert L. de Groot	46
10	A Designed Conformational Shift To Control Protein Binding Specificity 2014 ·Angewandte Chemie ·Servaas Michielssens, (unknown), David Ban, Supriya Pratihar, Daniel Seeliger, Monika Sharma, Karin Giller, T. Michael Sabo, Stefan Becker, Donghan Lee, Christian Griesinger, Bert L. de Groot	7
11	What can we learn from molecular dynamics simulations for GPCR drug design? 2014 ·Computational and Structural Biotechnology Journal ·Christofer S. Tautermann, Daniel Seeliger, Jan M. Kriegl	52
12	Development of Scoring Functions for Antibody Sequence Assessment and Optimization 2013 ·PLoS ONE ·Daniel Seeliger	22
13	Linear-Scaling Soft Core Scheme for Alchemical Free Energy Calculations 2011 ·Biophysical Journal ·Floris Buelens, Daniel Seeliger, Bert L. de Groot, (unknown)	1
14	Towards computional specificity screening of DNA-binding proteins 2011 ·Nucleic Acids Research ·Daniel Seeliger, Floris Buelens, (unknown), Bert L. de Groot, Helmut Grubmüller	20
15	Conformational Transitions upon Ligand Binding: Holo-Structure Prediction from Apo Conformations 2010 ·PLoS Computational Biology ·Daniel Seeliger, Bert L. de Groot	119
16	Ligand docking and binding site analysis with PyMOL and Autodock/Vina breakdown → 2010 ·Journal of Computer-Aided Molecular Design ·Daniel Seeliger, Bert L. de Groot	1809
17	The Thermodynamic Influence of Trapped Water Molecules on a Protein–Ligand Interaction 2009 ·Angewandte Chemie International Edition ·Christian Stegmann, Daniel Seeliger, George M. Sheldrick, Bert L. de Groot, M.C. Wahl	34
18	The Molecular Mechanism of Toxin-Induced Conformational Changes in a Potassium Channel: Relation to C-Type Inactivation 2008 ·Structure ·Ulrich Zachariae, Robert C. Schneider, Phanindra Velisetty, Adam Lange, Daniel Seeliger, Sören Wacker, Yasmin Karimi‐Nejad, Gert Vriend, Stefan Becker, Olaf Pongs, Marc Baldus, Bert L. de Groot	41
19	tCONCOORD‐GUI: Visually supported conformational sampling of bioactive molecules 2008 ·Journal of Computational Chemistry ·Daniel Seeliger, Bert L. de Groot	33
20	Atomic contacts in protein structures. A detailed analysis of atomic radii, packing, and overlaps 2007 ·Proteins Structure Function and Bioinformatics ·Daniel Seeliger, Bert L. de Groot	29

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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