His primary areas of study are Protein structure, Crystallography, Protein structure prediction, Nuclear magnetic resonance spectroscopy and Computational biology. His Protein structure research is multidisciplinary, incorporating elements of Docking, Root-mean-square deviation, Biological system, Site-directed spin labeling and Algorithm. Jens Meiler interconnects Small molecule and Bioinformatics in the investigation of issues within Docking.
His Crystallography research includes elements of Arrestin, Biophysics, Protein folding, Receptor and Rhodopsin. His Nuclear magnetic resonance spectroscopy research incorporates elements of Pharmacophore and Chemical shift. The concepts of his Computational biology study are interwoven with issues in Data mining, Differential effects, Selective modulation, Data science and Drug discovery.
His primary scientific interests are in Biophysics, Protein structure, Computational biology, Biochemistry and Crystallography. His work deals with themes such as Helix, Receptor, Transmembrane domain, Membrane protein and Binding site, which intersect with Biophysics. His Protein structure study deals with Biological system intersecting with Artificial neural network.
His Computational biology research is multidisciplinary, incorporating elements of Homology modeling, Docking, Function and Drug discovery. Jens Meiler combines subjects such as Nuclear magnetic resonance spectroscopy and Protein secondary structure with his study of Crystallography. His Protein structure prediction study combines topics in areas such as Protein tertiary structure, Protein design and Protein folding.
Jens Meiler spends much of his time researching Biophysics, Cell biology, Computational biology, Receptor and Docking. His Biophysics research is multidisciplinary, relying on both Integral membrane protein, Electrophysiology, Membrane, Transmembrane domain and Ion channel. His studies in Computational biology integrate themes in fields like Antigen, Function, Homology modeling, Protein structure prediction and Sequence.
The Receptor study combines topics in areas such as C-terminus and Peptide. His biological study spans a wide range of topics, including Machine learning, Small molecule, Drug discovery and Artificial intelligence. The study incorporates disciplines such as Pharmacophore and Artificial neural network in addition to Virtual screening.
His main research concerns Docking, Computational biology, Antibody, Biophysics and Homology modeling. The various areas that Jens Meiler examines in his Docking study include Receptor, Small molecule, Drug discovery and Artificial intelligence. His research investigates the link between Computational biology and topics such as Protein structure prediction that cross with problems in Monte Carlo method, Site-directed spin labeling, Spin label and Leverage.
He interconnects Antigen and Virology in the investigation of issues within Antibody. His study on Biophysics also encompasses disciplines like
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ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules.
Andrew Leaver-Fay;Michael Tyka;Steven M. Lewis;Oliver F. Lange.
Methods in Enzymology (2011)
Computational Methods in Drug Discovery
Gregory Sliwoski;Sandeepkumar Kothiwale;Jens Meiler;Edward W. Lowe.
Pharmacological Reviews (2014)
Recognition Dynamics Up to Microseconds Revealed from an RDC-Derived Ubiquitin Ensemble in Solution
Oliver F. Lange;Nils Alexander Lakomek;Christophe Farès;Gunnar F. Schröder.
Structure of a Class C GPCR Metabotropic Glutamate Receptor 1 Bound to an Allosteric Modulator
Huixian Wu;Chong Wang;Karen J. Gregory;Karen J. Gregory;Gye Won Han.
Rosettaligand : Protein-small molecule docking with full side-chain flexibility
Jens Meiler;David Baker.
Practically Useful: What the Rosetta Protein Modeling Suite Can Do for You
Kristian W. Kaufmann;Gordon H. Lemmon;Samuel L. DeLuca;Jonathan H. Sheehan.
New algorithms and an in silico benchmark for computational enzyme design
Alexandre Zanghellini;Lin Jiang;Andrew M. Wollacott;Gong Cheng.
Protein Science (2006)
RosettaScripts: A Scripting Language Interface to the Rosetta Macromolecular Modeling Suite
Sarel J. Fleishman;Andrew Leaver-Fay;Jacob E. Corn;Eva Maria Strauch.
PLOS ONE (2011)
Potently neutralizing and protective human antibodies against SARS-CoV-2.
Seth J. Zost;Pavlo Gilchuk;James Brett Case;Elad Binshtein.
Model-Free Approach to the Dynamic Interpretation of Residual Dipolar Couplings in Globular Proteins
Jens Meiler;Jeanine J. Prompers;Wolfgang Peti;Christian Griesinger.
Journal of the American Chemical Society (2001)
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