Protein Structure and Dynamics

This study evaluates AlphaFold2's ability to predict apo and holo protein conformations using randomized alanine masking and subsampling, finding it effective for minor changes but less so for large domain movements.

This study uses high-resolution molecular dynamics simulations to analyze PKM1 and PKM2 structural dynamics, revealing new cryptic pockets for antitumoral drug design.

The paper investigates the role of stereochemistry in disordered protein-protein interactions, finding that chirality is inconsequential in fully disordered complexes but essential when folding and binding are coupled.

The paper uses simulations to study the FXR-RXR heterodimer's structure and shows the hinge's role in DNA binding and interdomain allostery.

The paper provides proteome-wide structure predictions for all human herpesviruses and identifies new protein families and potential functions through structural analysis.

This study improves agreement between smFRET experiments and molecular dynamics simulations by accounting for time-averaging, revealing hidden conformational states in proteins.

This study shows that reducing the stability of a nanobody does not affect its binding affinity, suggesting stability and affinity can be decoupled in therapeutic proteins.

The paper investigates the structural robustness of Escherichia coli TpiA by introducing amino acid insertions and shows that some variants retain wild-type activity despite structural perturbations.

This paper introduces Rosetta-MPDock, a membrane protein docking method that improves prediction accuracy by capturing conformational changes and integrating AlphaFold2-multimer, achieving better success rates in predicting membrane protein complex structures.

This paper introduces TransPross, a transformer-based model for protein secondary structure prediction that outperforms existing methods by leveraging attention mechanisms and deep learning.

This paper introduces EVOLVEpro, a few-shot learning framework using protein language models to rapidly improve protein activity with minimal experimental data.

ESM-Scan uses ESM zero-shot prediction to identify amino acid substitutions in proteins, showing effectiveness in predicting stability and function changes through benchmarking and experimental validation.

The paper calculates protein conformations using local stereochemistry knowledge and the interval Branch-and-Prune algorithm, showing that stereochemistry variations improve computational efficiency.

This study uses molecular dynamics simulations to investigate viscosity and diffusion in crowded protein solutions, showing that diffusion reduction exceeds viscosity effects due to cluster formation.

PredIDR accurately predicts protein intrinsic disorder regions using a deep convolutional neural network, achieving performance comparable to top state-of-the-art methods in the CAID assessment.

This study investigates folding pathways and degradation signals in yeast small GTPases, revealing heterogeneous folding landscapes and predetermined breaking points.

This paper characterizes the disordered structure of the PHL4 transcription factor's effector domain and shows it forms a tetramer with a central folded region.

This study evaluates five coarse-grained protein models for predicting phase diagrams of hnRNPA1 LCD mutants, finding that only three accurately reproduce experimental data, highlighting the need to balance single-molecule and collective properties.

The paper introduces a framework to describe viral capsid subunit shapes using spherical tiling theory, revealing distinct interface groups and potential assembly pathways in T = 1 capsids.

STRPsearch detects structured tandem repeat proteins by aligning protein structures to a curated database and mapping repeat units efficiently.

This study uses all-atom simulations to model phosphorylation effects on intrinsically disordered proteins, showing agreement with experimental data on conformational changes.

MDRepo provides an open repository for storing and analyzing molecular dynamics simulations to support drug discovery and structural biology research.

This study evaluates force field limitations in constant pH molecular dynamics simulations of a mini-protein, showing significant pKa errors due to force field and water model choices.

The paper introduces a Python package to map protein conformational landscapes using crystallographic drug fragment screens and applies it to PTP-1B and SARS-CoV-2 MPro.

This study uses molecular dynamics simulations to analyze the conformational behavior of SARS-CoV-2 Mpro loops and their relationship with substrate binding and allosteric communication.

This study refines the Martini force field to better model glycoprotein interactions by aligning simulations with experimental data on sugar-protein interactions.

The paper describes the structural arrangement of F-keratin in Pavo cristatus, focusing on the N-block and C-block organization and their role in forming composite fibers.

This study uses biophysical and computational methods to characterize the structure of human Cdt1, revealing 'folded over' conformations that suggest a scaffold function.

The paper develops a structure-aware method to annotate Leucine-rich Repeat (LRR) domains by integrating geometric properties of protein structures, improving accuracy over sequence-based approaches.

The paper introduces SOP-MULTI, a coarse-grained force field for simulating multi-domain and intrinsically disordered proteins, validated against experimental scattering data.