@article{ZahoGhirlandoAlfonsoetal.2015,
  author    = {Zaho, Huaying and Ghirlando, Rodolfo and Alfonso, Carlos and Arisaka, Fumio and Attali, Ilan and Bain, David L. and Bakhtina, Marina M. and Becker, Donald F. and Bedwell, Gregory J. and Bekdemir, Ahmet and Besong, Tabot M. D. and Birck, Catherine and Brautigam, Chad A. and Brennerman, William and Byron, Olwyn and Bzowska, Agnieszka and Chaires, Jonathan B. and Chaton, Catherine T. and Coelfen, Helmbut and Connaghan, Keith D. and Crowley, Kimberly A. and Curth, Ute and Daviter, Tina and Dean, William L. and Diez, Ana I. and Ebel, Christine and Eckert, Debra M. and Eisele, Leslie E. and Eisenstein, Edward and England, Patrick and Escalante, Carlos and Fagan, Jeffrey A. and Fairman, Robert and Finn, Ron M. and Fischle, Wolfgang and Garcia de la Torre, Jose and Gor, Jayesh and Gustafsson, Henning and Hall, Damien and Harding, Stephen E. and Hernandez Cifre, Jose G. and Herr, Andrew B. and Howell, Elizabeth E. and Isaac, Richard S. and Jao, Shu-Chuan and Jose, Davis and Kim, Soon-Jong and Kokona, Bashkim and Kornblatt, Jack A. and Kosek, Dalibor and Krayukhina, Elena and Krzizike, Daniel and Kusznir, Eric A. and Kwon, Hyewon and Larson, Adam and Laue, Thomas M. and Le Roy, Aline and Leech, Andrew P. and Lilie, Hauke and Luger, Karolin and Luque-Ortega, Juan R. and Ma, Jia and May, Carrie A. and Maynard, Ernest L. and Modrak-Wojcik, Anna and Mok, Yee-Foong and M{\"u}cke, Norbert and Nagel-Steger, Luitgard and Narlikar, Geeta J. and Noda, Masanori and Nourse, Amanda and Obsil, Thomas and Park, Chad K and Park, Jin-Ku and Pawelek, Peter D. and Perdue, Erby E. and Perkins, Stephen J. and Perugini, Matthew A. and Peterson, Craig L. and Peverelli, Martin G. and Piszczek, Grzegorz and Prag, Gali and Prevelige, Peter E. and Raynal, Bertrand D. E. and Rezabkova, Lenka and Richter, Klaus and Ringel, Alison E. and Rosenberg, Rose and Rowe, Arthur J. and Rufer, Arne C. and Scott, David J. and Seravalli, Javier G. and Solovyova, Alexandra S. and Song, Renjie and Staunton, David and Stoddard, Caitlin and Stott, Katherine and Strauss, Holder M. and Streicher, Werner W. and Sumida, John P. and Swygert, Sarah G. and Szczepanowski, Roman H. and Tessmer, Ingrid and Toth, Ronald T. and Tripathy, Ashutosh and Uchiyama, Susumu and Uebel, Stephan F. W. and Unzai, Satoru and Gruber, Anna Vitlin and von Hippel, Peter H. and Wandrey, Christine and Wang, Szu-Huan and Weitzel, Steven E and Wielgus-Kutrowska, Beata and Wolberger, Cynthia and Wolff, Martin and Wright, Edward and Wu, Yu-Sung and Wubben, Jacinta M. and Schuck, Peter},
  title     = {A Multilaboratory Comparison of Calibration Accuracy and the Performance of External References in Analytical Ultracentrifugation},
  series = {PLoS ONE},
  volume    = {10},
  journal   = {PLoS ONE},
  number    = {5},
  doi       = {10.1371/journal.pone.0126420},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-151903},
  pages     = {e0126420},
  year      = {2015},
  abstract  = {Analytical ultracentrifugation (AUC) is a first principles based method to determine absolute sedimentation coefficients and buoyant molar masses of macromolecules and their complexes, reporting on their size and shape in free solution. The purpose of this multi-laboratory study was to establish the precision and accuracy of basic data dimensions in AUC and validate previously proposed calibration techniques. Three kits of AUC cell assemblies containing radial and temperature calibration tools and a bovine serum albumin (BSA) reference sample were shared among 67 laboratories, generating 129 comprehensive data sets. These allowed for an assessment of many parameters of instrument performance, including accuracy of the reported scan time after the start of centrifugation, the accuracy of the temperature calibration, and the accuracy of the radial magnification. The range of sedimentation coefficients obtained for BSA monomer in different instruments and using different optical systems was from 3.655 S to 4.949 S, with a mean and standard deviation of (4.304\(\pm\)0.188) S (4.4\%). After the combined application of correction factors derived from the external calibration references for elapsed time, scan velocity, temperature, and radial magnification, the range of s-values was reduced 7-fold with a mean of 4.325 S and a 6-fold reduced standard deviation of \(\pm\)0.030 S (0.7\%). In addition, the large data set provided an opportunity to determine the instrument-to-instrument variation of the absolute radial positions reported in the scan files, the precision of photometric or refractometric signal magnitudes, and the precision of the calculated apparent molar mass of BSA monomer and the fraction of BSA dimers. These results highlight the necessity and effectiveness of independent calibration of basic AUC data dimensions for reliable quantitative studies.},
  language  = {en}
}
@article{SchulteSoldaSpaenigetal.2022,
  author    = {Schulte, Clemens and Sold{\`a}, Alice and Sp{\"a}nig, Sebastian and Adams, Nathan and Bekić, Ivana and Streicher, Werner and Heider, Dominik and Strasser, Ralf and Maric, Hans Michael},
  title     = {Multivalent binding kinetics resolved by fluorescence proximity sensing},
  series = {Communications Biology},
  volume    = {5},
  journal   = {Communications Biology},
  doi       = {10.1038/s42003-022-03997-3},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-301157},
  year      = {2022},
  abstract  = {Multivalent protein interactors are an attractive modality for probing protein function and exploring novel pharmaceutical strategies. The throughput and precision of state-of-the-art methodologies and workflows for the effective development of multivalent binders is currently limited by surface immobilization, fluorescent labelling and sample consumption. Using the gephyrin protein, the master regulator of the inhibitory synapse, as benchmark, we exemplify the application of Fluorescence proximity sensing (FPS) for the systematic kinetic and thermodynamic optimization of multivalent peptide architectures. High throughput synthesis of +100 peptides with varying combinatorial dimeric, tetrameric, and octameric architectures combined with direct FPS measurements resolved on-rates, off-rates, and dissociation constants with high accuracy and low sample consumption compared to three complementary technologies. The dataset and its machine learning-based analysis deciphered the relationship of specific architectural features and binding kinetics and thereby identified binders with unprecedented protein inhibition capacity; thus, highlighting the value of FPS for the rational engineering of multivalent inhibitors.},
  language  = {en}
}