Publications by authors named "J Schilz"

14 Publications

Molecular recognition of structurally disordered Pro/Ala-rich sequences (PAS) by antibodies involves an Ala residue at the hot spot of the epitope.

J Mol Biol 2021 Sep 20;433(18):167113. Epub 2021 Jun 20.

Lehrstuhl für Biologische Chemie, Technische Universität München, Emil-Erlenmeyer-Forum 5, 85354 Freising, Germany; XL-protein GmbH, Lise-Meitner-Strasse 30, 85354 Freising, Germany. Electronic address:

Pro/Ala-rich sequences (PAS) are polypeptides that were developed as a biological alternative to poly-ethylene glycol (PEG) to generate biopharmaceuticals with extended plasma half-life. Like PEG, PAS polypeptides are conformationally disordered and show high solubility in water. Devoid of any charged or prominent hydrophobic side chains, these biosynthetic polymers represent an extreme case of intrinsically disordered proteins. Despite lack of immunogenicity of PAS tags in numerous animal studies we now succeeded in generating monoclonal antibodies (MAbs) against three different PAS versions. To this end, mice were immunized with a PAS#1, P/A#1 or APSA 40mer peptide conjugated to keyhole limpet hemocyanin as highly immunogenic carrier protein. In each case, one MAb with high binding activity and specificity towards a particular PAS motif was obtained. The apparent affinity was strongly dependent on the avidity effect and most pronounced for the bivalent MAb when interacting with a long PAS repeat. X-ray structural analysis of four representative anti-PAS Fab fragments in complex with their cognate PAS epitope peptides revealed interactions dominated by hydrogen bond networks involving the peptide backbone as well as multiple Van der Waals contacts arising from intimate shape complementarity. Surprisingly, Ala, the L-amino acid with the smallest side chain, emerged as a crucial feature for epitope recognition, contributing specific contacts at the center of the paratope in several anti-PAS complexes. Apart from these insights into how antibodies can recognize feature-less peptides without secondary structure, the MAbs characterized in this study offer valuable reagents for the preclinical and clinical development of PASylated biologics.
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http://dx.doi.org/10.1016/j.jmb.2021.167113DOI Listing
September 2021

The Effectiveness of Serial Casting and Ankle Foot Orthoses in Treating Toe Walking in Children With Autism Spectrum Disorder.

Pediatr Phys Ther 2021 04;33(2):83-90

Division of Physical Therapy (Drs Barkocy, Schilz, Chee, Valdez, and Redmond) and Department of Pediatrics (Dr Heimerl), The University of New Mexico, Albuquerque, New Mexico.

Purpose: This proof of concept study examined the effectiveness of serial casting (SC) and ankle foot orthoses (AFOs) in children with autism spectrum disorder (Ch-ASD) who toe walk (TW). Data collected determined effects of SC, followed by AFO intervention on ankle dorsiflexion (A-DF) passive range of motion and kinematics, and parent-reported functional outcomes for children with autism spectrum disorder who TW and have limited A-DF passive range of motion.

Summary Of Key Points: The 5 participants increased passive range of motion with SC, except for 1 participant's left ankle. Two of 4 participants had near typical A-DF kinematic patterns following SC. The 5 participants improved A-DF during walking following 6 months of AFO use.

Conclusions: Serial casting increased A-DF ROM and kinematics during walking. Consistent AFO use for walking training improved function and reduced toe walking. Serial casting followed by AFOs is a potential intervention for children with autism spectrum disorder who TW.
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http://dx.doi.org/10.1097/PEP.0000000000000784DOI Listing
April 2021

Differential response of human T-lymphocytes to arsenic and uranium.

Toxicol Lett 2020 Oct 28;333:269-278. Epub 2020 Aug 28.

Department of Pharmaceutical Sciences, College of Pharmacy, University of New Mexico, 1 University of New Mexico, Albuquerque, NM, United States. Electronic address:

Elevated levels of arsenic and uranium have been detected in water sources near abandoned uranium mines in the Southwest. Evidence suggests uranium exposure increases the likelihood of immune dysfunction and this study investigates the impact of arsenic and uranium on human immune cell lines. Concentration-dependent cytotoxicity occurred following exposure to arsenite, whereas cells remained viable after 48 -h treatment with up to 100 μM uranyl acetate despite uptake of uranium into cells. Arsenite stimulated an oxidative stress response as detected by Nrf-2 nuclear accumulation and induction of HMOX-1 and NQO1, which was not detected with up to 30 μM uranyl acetate. Cellular oxidative stress can promote DNA damage and arsenite, but not uranium, stimulated DNA damage as measured by pH2AX. Arsenic enhanced the cytotoxic response to etoposide suggesting an inhibition of DNA repair, unlike uranium. Similarly, uranium did not inhibit PARP-1 activity. Because uranium reportedly stimulates oxidative stress, DNA damage and cytotoxicity in adherent epithelial cells, the current study suggests distinct cell type differences in response to uranium that may relate to generation of oxidative stress and associated downstream consequences. Delineating the actions of uranium across different cell targets will be important for understanding the potential health effects of uranium exposures.
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http://dx.doi.org/10.1016/j.toxlet.2020.08.013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7590629PMC
October 2020

A multi-institutional initiative on patient-related quality assurance: Independent computational dose verification of fluence-modulated treatment techniques.

Z Med Phys 2020 May 21;30(2):155-165. Epub 2020 Jan 21.

Department of Radiation Oncology, University Hospital Jena, Bachstraße 18, 07743, Jena, Germany.

Purpose: This multi-institutional study investigates whether computational verification of fluence-modulated treatment plans using independent software with its own Strahlerkopfmodel is an appropriate method for patient-related quality assurance (PRQA) in the context of various combinations of linear accelerators (linacs), treatment techniques and treatment planning systems (TPS).

Materials And Methods: The PRQA-software's (Mobius3D) recalculations of 9 institutions' treatment plans were analyzed for a horseshoe-shaped planning target volume (PTV) inside a phantom. The recomputed dose distributions were compared to a) the dose distributions as calculated by all TPS's and b) the measured dose distributions, which were acquired using the same independent measuring system for all institutions. Furthermore, dose volume histograms were examined. The penumbra deviations and mean gamma values were quantified using Verisoft (PTW). Additionally, workflow requirements for computational verification were discussed.

Results: Mobius3D is compatible with all examined TPSs, treatment techniques and linacs. The mean PTV dose differences (Mobius3D-TPS, <3.0%) and 3D gamma passing rates (>95.0%) led to a positive plan acceptance result in all cases. These results are similar to the outcome of the dosimetric measurements with one exception. The mean gamma values (<0.5) show a good agreement between Mobius3D and the TPS dose distributions.

Conclusion: Using Mobius3D was proven to be an appropriate computational PRQA method for the tested combinations of linacs, treatment techniques and TPS's. The clinical use of Mobius3D has to be complemented with regular dosimetric measurements and thorough linac and TPS QA. Mobius3D's computational verification reduced measurement effort and personnel needs in comparison to dosimetric verifications.
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http://dx.doi.org/10.1016/j.zemedi.2019.12.003DOI Listing
May 2020

Antibody complementarity determining region design using high-capacity machine learning.

Bioinformatics 2020 04;36(7):2126-2133

MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA.

Motivation: The precise targeting of antibodies and other protein therapeutics is required for their proper function and the elimination of deleterious off-target effects. Often the molecular structure of a therapeutic target is unknown and randomized methods are used to design antibodies without a model that relates antibody sequence to desired properties.

Results: Here, we present Ens-Grad, a machine learning method that can design complementarity determining regions of human Immunoglobulin G antibodies with target affinities that are superior to candidates derived from phage display panning experiments. We also demonstrate that machine learning can improve target specificity by the modular composition of models from different experimental campaigns, enabling a new integrative approach to improving target specificity. Our results suggest a new path for the discovery of therapeutic molecules by demonstrating that predictive and differentiable models of antibody binding can be learned from high-throughput experimental data without the need for target structural data.

Availability And Implementation: Sequencing data of the phage panning experiment are deposited at NIH's Sequence Read Archive (SRA) under the accession number SRP158510. We make our code available at https://github.com/gifford-lab/antibody-2019.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btz895DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141872PMC
April 2020
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