---
OA_place: publisher
OA_type: hybrid
PlanS_conform: '1'
_id: '21929'
abstract:
- lang: eng
  text: 'The import of proteins into mitochondria poses fundamental mechanistic challenges:
    aggregation-prone precursor proteins must be maintained in aqueous compartments
    and threaded through narrow pores without becoming stuck or mislocalized. Recent
    evidence from mitochondrial protein import studies and other chaperone systems
    underscores the critical role of dynamics in balancing sufficiently tight binding,
    promiscuity, specificity, and release. Dynamic binding of client precursor proteins
    to import machinery components arises naturally from the avidity of their interactions.
    Conformational entropy enhances their stability, while the multivalent nature
    of these interactions ensures that client transfer to downstream insertases occurs
    without a substantial energy barrier. Here, we discuss this emerging paradigm
    of dynamic protein handling, using examples where dynamic structures have been
    resolved and highlight outstanding questions.'
acknowledgement: We gratefully acknowledge research funding by the Austrian Science
  Fund (FWF), projects 10.55776/PAT1647625 and 10.55776/I6223. We thank Prof. Long
  Li (Peking University) for providing structural models and EM density for the TOM
  and TIM23 complexes, used to generate part of Figure 3. Open Access funding provided
  by Institute of Science and Technology Austria.
article_number: e70630
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Jakob
  full_name: Schneider, Jakob
  id: 64368429-eb97-11eb-a6c2-c980b1f44415
  last_name: Schneider
- first_name: Undina
  full_name: Guillerm, Undina
  id: bb74f472-ae54-11eb-9835-bc9c22fb1183
  last_name: Guillerm
- first_name: Caroline
  full_name: Simoes Pereira, Caroline
  id: 87266c4a-96d2-11ef-be2c-fe5633233ec3
  last_name: Simoes Pereira
- first_name: Paul
  full_name: Schanda, Paul
  id: 7B541462-FAF6-11E9-A490-E8DFE5697425
  last_name: Schanda
  orcid: 0000-0002-9350-7606
citation:
  ama: Schneider J, Guillerm U, Simoes Pereira C, Schanda P. Dynamic disorder is crucial
    for mitochondrial protein import. <i>Protein Science</i>. 2026;35(6). doi:<a href="https://doi.org/10.1002/pro.70630">10.1002/pro.70630</a>
  apa: Schneider, J., Guillerm, U., Simoes Pereira, C., &#38; Schanda, P. (2026).
    Dynamic disorder is crucial for mitochondrial protein import. <i>Protein Science</i>.
    Wiley. <a href="https://doi.org/10.1002/pro.70630">https://doi.org/10.1002/pro.70630</a>
  chicago: Schneider, Jakob, Undina Guillerm, Caroline Simoes Pereira, and Paul Schanda.
    “Dynamic Disorder Is Crucial for Mitochondrial Protein Import.” <i>Protein Science</i>.
    Wiley, 2026. <a href="https://doi.org/10.1002/pro.70630">https://doi.org/10.1002/pro.70630</a>.
  ieee: J. Schneider, U. Guillerm, C. Simoes Pereira, and P. Schanda, “Dynamic disorder
    is crucial for mitochondrial protein import,” <i>Protein Science</i>, vol. 35,
    no. 6. Wiley, 2026.
  ista: Schneider J, Guillerm U, Simoes Pereira C, Schanda P. 2026. Dynamic disorder
    is crucial for mitochondrial protein import. Protein Science. 35(6), e70630.
  mla: Schneider, Jakob, et al. “Dynamic Disorder Is Crucial for Mitochondrial Protein
    Import.” <i>Protein Science</i>, vol. 35, no. 6, e70630, Wiley, 2026, doi:<a href="https://doi.org/10.1002/pro.70630">10.1002/pro.70630</a>.
  short: J. Schneider, U. Guillerm, C. Simoes Pereira, P. Schanda, Protein Science
    35 (2026).
corr_author: '1'
date_created: 2026-05-31T22:02:12Z
date_published: 2026-06-01T00:00:00Z
date_updated: 2026-06-02T07:26:34Z
day: '01'
ddc:
- '572'
department:
- _id: GradSch
- _id: PaSc
doi: 10.1002/pro.70630
external_id:
  pmid:
  - '42159315'
file:
- access_level: open_access
  checksum: e0163459a7238fdcc3fc5e17bedcce9a
  content_type: application/pdf
  creator: dernst
  date_created: 2026-06-02T07:23:12Z
  date_updated: 2026-06-02T07:23:12Z
  file_id: '21937'
  file_name: 2026_ProteinScience_Schneider.pdf
  file_size: 3897305
  relation: main_file
  success: 1
file_date_updated: 2026-06-02T07:23:12Z
has_accepted_license: '1'
intvolume: '        35'
issue: '6'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '06'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: bdb9578d-d553-11ed-ba76-ed5d39fce6f0
  grant_number: I06223
  name: Structure and mechanism of the mitochondrial MIM insertase
publication: Protein Science
publication_identifier:
  eissn:
  - 1469-896X
  issn:
  - 0961-8368
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Dynamic disorder is crucial for mitochondrial protein import
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2026'
...
---
OA_place: publisher
OA_type: hybrid
PlanS_conform: '1'
_id: '20538'
abstract:
- lang: eng
  text: In this study, we describe an integrated approach for methyl group assignment
    comprising precursor-based selective methyl group labeling, a novel pulse sequence
    for methyl to backbone coherence transfer and chemical shift predictions using
    UCBShift 2.0. The utility of this novel α-ketoacid isotopologue is shown by the
    adaptation of an HMBC-HMQC pulse sequence that simultaneously connects geminal
    methyl groups of leucine and valine residues to each other and to the protein
    backbone. By additional 13C,2H-labeling of residues other than valine and leucine
    residues of the protein, important chemical shift information about neighboring
    residues (following valine and leucine residues) can be achieved. Thus, different
    valine and leucine residues in a protein can be characterized as a specific chemical
    shift vector. Frequency matching with predicted chemical shifts via UCBShift 2.0
    using experimental data taken from a subset of the BMRB database revealed a correct
    assignment performance of about 90%. With applications to proteins of 60.2 kDa
    and 134 kDa (4 × 33.5 kDa) in size, we demonstrate that the approach provides
    valuable information even for very large proteins.
acknowledged_ssus:
- _id: NMR
- _id: LifeSc
acknowledgement: A.L.P and G.T were funded by the “New Ideas” program by Vienna Doctoral
  School in Chemistry. S.K. was funded by the Austrian Science Fund FWF P35098-B.
  This work was supported financially by the Austrian Science Fund (FWF, grant numbers
  I06223 and I5812-B, “AlloSpace”). This research was supported by the Scientific
  Service Units (SSU) of Institute of Science and Technology Austria (ISTA) through
  resources provided by the Nuclear Magnetic Resonance Facility and the Lab Support
  Facility (LSF). We thank Celina Sailer for assistance with the analysis of the NMR
  spectrum of HsTom70.
article_number: '169465'
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Sonja
  full_name: Knödlstorfer, Sonja
  last_name: Knödlstorfer
- first_name: Giorgia
  full_name: Toscano, Giorgia
  id: 334a5e40-8747-11f0-b671-ba1f5154b4b4
  last_name: Toscano
- first_name: Aleksandra L.
  full_name: Ptaszek, Aleksandra L.
  last_name: Ptaszek
- first_name: Georg
  full_name: Kontaxis, Georg
  last_name: Kontaxis
- first_name: Federico
  full_name: Napoli, Federico
  id: d42e08e7-f4fc-11eb-af0a-d71e26138f1b
  last_name: Napoli
  orcid: 0000-0002-9043-136X
- first_name: Jakob
  full_name: Schneider, Jakob
  id: 64368429-eb97-11eb-a6c2-c980b1f44415
  last_name: Schneider
- first_name: Katharina
  full_name: Maier, Katharina
  last_name: Maier
- first_name: Anna
  full_name: Kapitonova, Anna
  id: 9fb2a840-89e1-11ee-a8b7-cc5c7ba62471
  last_name: Kapitonova
- first_name: Roman J.
  full_name: Lichtenecker, Roman J.
  last_name: Lichtenecker
- first_name: Paul
  full_name: Schanda, Paul
  id: 7B541462-FAF6-11E9-A490-E8DFE5697425
  last_name: Schanda
  orcid: 0000-0002-9350-7606
- first_name: Robert
  full_name: Konrat, Robert
  last_name: Konrat
citation:
  ama: Knödlstorfer S, Toscano G, Ptaszek AL, et al. A novel HMBC-CC-HMQC NMR strategy
    for methyl assignment using triple-13C-labeled α-ketoisovalerate integrated with
    UCBShift 2.0. <i>Journal of Molecular Biology</i>. 2025;437(23). doi:<a href="https://doi.org/10.1016/j.jmb.2025.169465">10.1016/j.jmb.2025.169465</a>
  apa: Knödlstorfer, S., Toscano, G., Ptaszek, A. L., Kontaxis, G., Napoli, F., Schneider,
    J., … Konrat, R. (2025). A novel HMBC-CC-HMQC NMR strategy for methyl assignment
    using triple-13C-labeled α-ketoisovalerate integrated with UCBShift 2.0. <i>Journal
    of Molecular Biology</i>. Elsevier. <a href="https://doi.org/10.1016/j.jmb.2025.169465">https://doi.org/10.1016/j.jmb.2025.169465</a>
  chicago: Knödlstorfer, Sonja, Giorgia Toscano, Aleksandra L. Ptaszek, Georg Kontaxis,
    Federico Napoli, Jakob Schneider, Katharina Maier, et al. “A Novel HMBC-CC-HMQC
    NMR Strategy for Methyl Assignment Using Triple-13C-Labeled α-Ketoisovalerate
    Integrated with UCBShift 2.0.” <i>Journal of Molecular Biology</i>. Elsevier,
    2025. <a href="https://doi.org/10.1016/j.jmb.2025.169465">https://doi.org/10.1016/j.jmb.2025.169465</a>.
  ieee: S. Knödlstorfer <i>et al.</i>, “A novel HMBC-CC-HMQC NMR strategy for methyl
    assignment using triple-13C-labeled α-ketoisovalerate integrated with UCBShift
    2.0,” <i>Journal of Molecular Biology</i>, vol. 437, no. 23. Elsevier, 2025.
  ista: Knödlstorfer S, Toscano G, Ptaszek AL, Kontaxis G, Napoli F, Schneider J,
    Maier K, Kapitonova A, Lichtenecker RJ, Schanda P, Konrat R. 2025. A novel HMBC-CC-HMQC
    NMR strategy for methyl assignment using triple-13C-labeled α-ketoisovalerate
    integrated with UCBShift 2.0. Journal of Molecular Biology. 437(23), 169465.
  mla: Knödlstorfer, Sonja, et al. “A Novel HMBC-CC-HMQC NMR Strategy for Methyl Assignment
    Using Triple-13C-Labeled α-Ketoisovalerate Integrated with UCBShift 2.0.” <i>Journal
    of Molecular Biology</i>, vol. 437, no. 23, 169465, Elsevier, 2025, doi:<a href="https://doi.org/10.1016/j.jmb.2025.169465">10.1016/j.jmb.2025.169465</a>.
  short: S. Knödlstorfer, G. Toscano, A.L. Ptaszek, G. Kontaxis, F. Napoli, J. Schneider,
    K. Maier, A. Kapitonova, R.J. Lichtenecker, P. Schanda, R. Konrat, Journal of
    Molecular Biology 437 (2025).
date_created: 2025-10-26T23:01:35Z
date_published: 2025-12-01T00:00:00Z
date_updated: 2025-12-30T10:29:20Z
day: '01'
ddc:
- '540'
department:
- _id: PaSc
- _id: GradSch
doi: 10.1016/j.jmb.2025.169465
external_id:
  pmid:
  - '41016549'
file:
- access_level: open_access
  checksum: feb92f9c79032c261165f4ca573f444a
  content_type: application/pdf
  creator: dernst
  date_created: 2025-12-30T10:29:08Z
  date_updated: 2025-12-30T10:29:08Z
  file_id: '20915'
  file_name: 2025_JourMolecularBiology_Knoedlstorfer.pdf
  file_size: 3076611
  relation: main_file
  success: 1
file_date_updated: 2025-12-30T10:29:08Z
has_accepted_license: '1'
intvolume: '       437'
issue: '23'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: bdb9578d-d553-11ed-ba76-ed5d39fce6f0
  grant_number: I06223
  name: Structure and mechanism of the mitochondrial MIM insertase
- _id: eb9c82eb-77a9-11ec-83b8-aadd536561cf
  grant_number: I05812
  name: AlloSpace. The emergence and mechanisms of allostery
publication: Journal of Molecular Biology
publication_identifier:
  eissn:
  - 1089-8638
  issn:
  - 0022-2836
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: A novel HMBC-CC-HMQC NMR strategy for methyl assignment using triple-13C-labeled
  α-ketoisovalerate integrated with UCBShift 2.0
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 437
year: '2025'
...
---
OA_place: publisher
OA_type: gold
_id: '21327'
abstract:
- lang: eng
  text: Proteins exist as a dynamic ensemble of multiple conformations, and these
    motions are often crucial for their functions. However, current structure prediction
    methods predominantly yield a single conformation, overlooking the conformational
    heterogeneity revealed by diverse experimental modalities. Here, we present a
    framework for building experiment-grounded protein structure generative models
    that infer conformational ensembles consistent with measured experimental data.
    The key idea is to treat stateof-the-art protein structure predictors (e.g., AlphaFold3)
    as sequence-conditioned structural priors, and cast ensemble modeling as posterior
    inference of protein structures given experimental measurements. Through extensive
    real-data experiments, we demonstrate the generality of our method to incorporate
    a variety of experimental measurements. In particular, our framework uncovers
    previously unmodeled conformational heterogeneity from crystallographic densities,
    and generates high-accuracy NMR ensembles orders of magnitude faster than the
    status quo. Notably, we demonstrate that our ensembles outperform AlphaFold3 (Abramson
    et al., 2024) and sometimes better fit experimental data than publicly deposited
    structures to the Protein Data Bank (PDB, Burley et al. (2017)). We believe that
    this approach will unlock building predictive models that fully embrace experimentally
    observed conformational diversity.
acknowledged_ssus:
- _id: ScienComp
acknowledgement: 'This work was supported by the Israeli Science Foundation (ISF)
  grant number 1834/24. We acknowledge support from the Austrian Science Fund (FWF,
  grant numbers I5812-B and I6223) and the financial support of the Helmsley Fellowships
  Program for Sustainability and Health. This research uses resources of the Institute
  of Science and Technology Austria’s scientific computing cluster. '
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Sai A
  full_name: Maddipatla, Sai A
  id: e957f5e5-91c9-11f0-a95f-e090f66ecb4d
  last_name: Maddipatla
- first_name: Nadav E
  full_name: Sellam, Nadav E
  id: ef280fe0-91c9-11f0-a95f-8dea3f5bc513
  last_name: Sellam
- first_name: Meital I
  full_name: Bojan, Meital I
  id: 11d88cf5-91ca-11f0-a95f-edf9f08f47b7
  last_name: Bojan
- first_name: Sanketh
  full_name: Vedula, Sanketh
  id: 94f2fe44-70fa-11f0-b76b-92922c09452b
  last_name: Vedula
- first_name: Paul
  full_name: Schanda, Paul
  id: 7B541462-FAF6-11E9-A490-E8DFE5697425
  last_name: Schanda
  orcid: 0000-0002-9350-7606
- first_name: Ailie
  full_name: Marx, Ailie
  last_name: Marx
- first_name: Alexander
  full_name: Bronstein, Alexander
  id: 58f3726e-7cba-11ef-ad8b-e6e8cb3904e6
  last_name: Bronstein
  orcid: 0000-0001-9699-8730
citation:
  ama: 'Maddipatla SA, Sellam NE, Bojan MI, et al. Inverse problems with experiment-guided
    AlphaFold. In: <i>Proceedings of the 42nd International Conference on Machine
    Learning</i>. Vol 267. ML Research Press; 2025:42366-42393.'
  apa: 'Maddipatla, S. A., Sellam, N. E., Bojan, M. I., Vedula, S., Schanda, P., Marx,
    A., &#38; Bronstein, A. M. (2025). Inverse problems with experiment-guided AlphaFold.
    In <i>Proceedings of the 42nd International Conference on Machine Learning</i>
    (Vol. 267, pp. 42366–42393). Vancouver, Canada: ML Research Press.'
  chicago: Maddipatla, Sai A, Nadav E Sellam, Meital I Bojan, Sanketh Vedula, Paul
    Schanda, Ailie Marx, and Alex M. Bronstein. “Inverse Problems with Experiment-Guided
    AlphaFold.” In <i>Proceedings of the 42nd International Conference on Machine
    Learning</i>, 267:42366–93. ML Research Press, 2025.
  ieee: S. A. Maddipatla <i>et al.</i>, “Inverse problems with experiment-guided AlphaFold,”
    in <i>Proceedings of the 42nd International Conference on Machine Learning</i>,
    Vancouver, Canada, 2025, vol. 267, pp. 42366–42393.
  ista: 'Maddipatla SA, Sellam NE, Bojan MI, Vedula S, Schanda P, Marx A, Bronstein
    AM. 2025. Inverse problems with experiment-guided AlphaFold. Proceedings of the
    42nd International Conference on Machine Learning. ICML: International Conference
    on Machine Learning, PMLR, vol. 267, 42366–42393.'
  mla: Maddipatla, Sai A., et al. “Inverse Problems with Experiment-Guided AlphaFold.”
    <i>Proceedings of the 42nd International Conference on Machine Learning</i>, vol.
    267, ML Research Press, 2025, pp. 42366–93.
  short: S.A. Maddipatla, N.E. Sellam, M.I. Bojan, S. Vedula, P. Schanda, A. Marx,
    A.M. Bronstein, in:, Proceedings of the 42nd International Conference on Machine
    Learning, ML Research Press, 2025, pp. 42366–42393.
conference:
  end_date: 2025-07-19
  location: Vancouver, Canada
  name: 'ICML: International Conference on Machine Learning'
  start_date: 2025-07-13
corr_author: '1'
date_created: 2026-02-18T12:11:17Z
date_published: 2025-07-30T00:00:00Z
date_updated: 2026-02-19T08:56:43Z
day: '30'
ddc:
- '000'
- '540'
department:
- _id: PaSc
- _id: AlBr
- _id: GradSch
external_id:
  arxiv:
  - '2502.09372'
file:
- access_level: open_access
  checksum: f33230a6d59b7978d4cd72795e4e9059
  content_type: application/pdf
  creator: dernst
  date_created: 2026-02-19T08:56:10Z
  date_updated: 2026-02-19T08:56:10Z
  file_id: '21338'
  file_name: 2025_ICML_Maddipatla.pdf
  file_size: 1924177
  relation: main_file
  success: 1
file_date_updated: 2026-02-19T08:56:10Z
has_accepted_license: '1'
intvolume: '       267'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 42366 - 42393
project:
- _id: eb9c82eb-77a9-11ec-83b8-aadd536561cf
  grant_number: I05812
  name: AlloSpace. The emergence and mechanisms of allostery
- _id: bdb9578d-d553-11ed-ba76-ed5d39fce6f0
  grant_number: I06223
  name: Structure and mechanism of the mitochondrial MIM insertase
publication: Proceedings of the 42nd International Conference on Machine Learning
publication_identifier:
  eissn:
  - 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
status: public
title: Inverse problems with experiment-guided AlphaFold
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 267
year: '2025'
...