Biophysics

Opening and closing of a cryptic pocket in VP35 toggles it between two different RNA-binding modes

1. Upasana L Mallimadugula
2. Matthew A Cruz
3. Neha Vithani
4. Maxwell I Zimmerman
5. Gregory R Bowman

• Curated by eLife

  eLife Assessment

  This study provides important insights into how cryptic pockets play a role in shaping binding preferences of protein-nucleic acid interactions. By combining biochemical assays and state-of-the-art molecular dynamics simulations, mechanism underlying viral protein 35 (VP35) homologs to bind the backbone of double stranded RNA is presented. The evidence is compelling for molecular determinants that suggest two different dsRNA binding modes for VP35 and also underscores the evolutionary importance of these pockets.

Reviewed by eLife

Mechanical imbalance between normal and transformed cells drives epithelial homeostasis through cell competition

1. Praver Gupta
2. Sayantani Kayal
3. Nobuyuki Tanimura
4. Shilpa P Pothapragada
5. Harish K Senapati
6. Padmashree Devendran
7. Yasuyuki Fujita
8. Dapeng Bi
9. Tamal Das

• Curated by eLife

  eLife Assessment

  In this important study, the authors combine innovative experimental approaches, including direct compressibility measurements and traction force analyses, with theoretical modeling to propose that wild-type cells exert compressive forces on softer HRasV12-transformed cells, influencing competition outcomes. The data generally provide solid evidence that transformed epithelial cells exhibit higher compressibility than wild-type cells, a property linked to their compaction during mechanical cell competition. However, the study would benefit from further characterization of how compression affects the behavior of HRasV12 cells and clearer causal links between compressibility and competition outcomes.

Reviewed by eLife

Cluster size determines morphology of transcription factories in human cells

1. Massimiliano Semeraro
2. Giuseppe Negro
3. Giada Forte
4. Antonio Suma
5. Giuseppe Gonnella
6. Peter R Cook
7. Davide Marenduzzo

• Curated by eLife

  eLife Assessment

  This is a valuable polymer model that provides insight into the origin of macromolecular mixed and demixed states within transcription clusters. The well-performed and clearly presented simulations will be of interest to those studying gene expression in the context of chromatin. While the study is generally solid, it could benefit from a more direct comparison with existing experimental data sets as well as further discussion of the limits of the underlying model assumptions.

Reviewed by eLife

De novo identification of universal cell mechanics gene signatures

1. Marta Urbanska
2. Yan Ge
3. Maria Winzi
4. Shada Abuhattum
5. Syed Shafat Ali
6. Maik Herbig
7. Martin Kräter
8. Nicole Toepfner
9. Joanne Durgan
10. Oliver Florey
11. Martina Dori
12. Federico Calegari
13. Fidel-Nicolás Lolo
14. Miguel Ángel del Pozo
15. Anna Taubenberger
16. Carlo Vittorio Cannistraci
17. Jochen Guck

• Curated by eLife

  eLife Assessment

  This important study uses machine learning-based network analysis on transcriptomic data from different tissue cell types to identify a small set of conserved (pan-tissue) genes associated with changes in cell mechanics. The new method, which provides a new type of approach for mechanobiology, is accessible, compelling, and well-validated using in silico and experimental approaches. The study provides motivation for researchers to test hypotheses concerning the identified five-gene network, and the method will be strengthened over time with expanded sets of validations, such as testing genes with hitherto unknown roles and different perturbation techniques.

Reviewed by eLife

Harnessing AlphaFold to reveal hERG channel conformational state secrets

1. Khoa Ngo
2. Pei-Chi Yang
3. Vladimir Yarov-Yarovoy
4. Colleen E. Clancy
5. Igor Vorobyov

• Curated by eLife

  eLife Assessment

  This valuable study uses AlphaFold2 to guide the structural modelling of different states of the human voltage-gated potassium channel KV11.1, a key pharmacological drug target. Follow-up molecular dynamics and drug-docking simulations, combined with experimental comparisons, offer convincing evidence supporting the models, showing that drugs bind more effectively to the inactivated state. The work shows potential for improving drug potency predictions in ion channel pharmacology, though its applicability to other systems remains uncertain.

Reviewed by eLife

Effects of residue substitutions on the cellular abundance of proteins

1. Thea K Schulze
2. Kresten Lindorff-Larsen

• Curated by eLife

  eLife Assessment

  This valuable study presents a thorough analysis of protein abundance changes caused by amino acid substitutions, using structural context to improve predictive accuracy. By deriving substitution response matrices based on solvent accessibility, the authors demonstrate that simple structural features can predict abundance effects with accuracy comparable to complex methods such as free energy calculations. The strength of the evidence is solid, supported by robust experimental design and comprehensive analyses. This work is expected to be of interest to broad audiences as it offers practical tools for analyzing mutational effects and insights into the structural basis of proteostasis.

Reviewed by eLife, PREreview

Structure and function of the human mitochondrial MRS2 channel

1. Zhihui He
2. Yung-Chi Tu
3. Chen-Wei Tsai
4. Jonathan Mount
5. Jingying Zhang
6. Ming-Feng Tsai
7. Peng Yuan

• Curated by Biophysics Colab

  Evaluation Statement (14 June 2024)

  The study by He et al. explores the structure and mechanisms of the human mitochondrial RNA splicing 2 (MRS2) protein, predicted to form Mg2+-selective channels in the mitochondrial inner membrane based on homology to the CorA family of prokaryotic Mg2+ channels. The authors use an innovative biochemical strategy to express MRS2 and perform single particle reconstructions in the absence and presence of key divalent cations. High resolution reconstructions of the pentameric channel reveal binding sites for Mg2+ and Ca2+, and electrophysiological investigations suggest that MRS2 is a Ca2+-regulated, cation-selective, Mg2+-permeable channel, in contrast to the Mg2+-regulated, Mg2+-selective CorA channel. This is an important study with interesting structural and functional observations, which will motivate further investigations of a potential role for MRS2 in mitochondrial Ca2+ signaling.

  Biophysics Colab recommends this study to scientists interested in the structure, function and regulation of cation channels as well as those working on mitochondrial transport.

  Biophysics Colab has evaluated this study as one that meets the following criteria:

  - Rigorous methodology

  - Transparent reporting

  - Appropriate interpretation

  (This evaluation refers to the version of record for this work, which is linked to and has been revised from the original preprint following peer review.)

Reviewed by Biophysics Colab

Prospective evaluation of structure-based simulations reveal their ability to predict the impact of kinase mutations on inhibitor binding

1. Sukrit Singh
2. Vytautas Gapsys
3. Matteo Aldeghi
4. David Schaller
5. Aziz M. Rangwala
6. Jessica B. White
7. Joseph P. Bluck
8. Jenke Scheen
9. William G. Glass
10. Jiaye Guo
11. Sikander Hayat
12. Bert L. de Groot
13. Andrea Volkamer
14. Clara D. Christ
15. Markus A. Seeliger
16. John D. Chodera

Reviewed by PREreview

Torsion is a Dynamic Regulator of DNA Replication Stalling and Reactivation

1. Xiaomeng Jia
2. Xiang Gao
3. Shuming Zhang
4. James T. Inman
5. Yifeng Hong
6. Anupam Singh
7. Smita Patel
8. Michelle D. Wang

Reviewed by PREreview

Physical constraints and biological regulations underlie universal osmoresponses

1. Yiyang Ye
2. Qirun Wang
3. Jie Lin

• Curated by eLife

  eLife Assessment

  This manuscript develops a theoretical model of osmotic pressure adaptation in microbes by osmolyte production and wall synthesis. The prediction of a rapid increase in growth rate on osmotic shock is experimentally validated using fission yeast. By using phenomenological rules rather than detailed molecular mechanisms, the model can potentially apply to a wide range of microbes, providing important insights that would be of interest to the wider community studying the regulation of cell size and mechanics. However, because the core assumptions of the model have not been tested across a range of microbial organisms, the evidence for the universality of the model remains incomplete.

Reviewed by eLife