Protein Structure and Dynamics

The paper uses solution scattering and simulations to show that Dhh1's modular architecture allows structural heterogeneity while maintaining functional specificity.

This study uses a refined coarse-grained model to predict the viscosity of high-concentration antibody solutions, showing improved accuracy over existing models.

JAAG simplifies creating AlphaFold 3 JSON input files for glycan and macromolecule modeling by providing a web-based interface to reduce manual errors.

This paper designs small single domain proteins that present three distinct viral epitopes using deep learning, showing improved immunogenicity compared to single-epitope designs.

This study uses molecular dynamics to analyze conformational changes in surfactant protein B at the alveolar air/liquid interface, revealing stability of the closed conformation and hydrophobic-driven changes in the open conformation.

This paper designs novel solenoid proteins using in silico evolution, achieving successful folding for alpha-solenoids and improved results for beta-solenoids with refinements.

This paper introduces Riff-Diff, a machine learning and atomistic modeling method for designing enzymes with high catalytic activity and stereoselectivity, demonstrating its effectiveness for two chemical reactions.

RFdiffusion2 scaffolds unindexed atom-level catalytic active sites via flow matching without inverse rotamer enumeration, solving all 41 in silico benchmark cases and yielding active de novo enzymes across four reactions.

BAGEL enables flexible protein design by exploring an energy landscape through a modular framework, supporting diverse design goals and integrating deep learning models.

This paper designs highly active metallohydrolases using a new generative AI method, achieving kcat/KM values up to 53,000 M-1 s-1 without experimental optimization.

This study improves nanobody structure prediction by using synthetic data and a classifier to filter structural accuracy, achieving better results than existing methods with lower computational cost.

The paper identifies and characterizes a unique C2H2 zinc finger domain in Drosophila that mediates dimerization through a conserved CGEx motif, revealing its structural and evolutionary significance.

This study shows that the pKa values of buried ionizable amino acids in proteins correlate with the thermodynamic stability of the protein, indicating that they reflect conformational transition energetics rather than local electrostatic properties.

This paper introduces a protein embedding model that captures both global and local structural similarity, outperforming existing methods in structural comparison tasks.

This paper introduces a discrete diffusion model for protein sequence design using all-atom representations, showing improved novelty and diversity compared to amino acid-based models.

This study shows AlphaFold2 can learn some protein folding principles without MSAs or templates, revealing intermediate structures and a 'local first, global later' mechanism.

This paper introduces a D-NEMD method to identify allosteric positions in proteins by analyzing long-range structural responses to alanine substitutions, validated on KPC-2 beta-lactamase.

This study investigates how lipid membrane interactions affect the conformational dynamics and energy landscape of membrane-bound TNF, showing that membrane association stabilizes the symmetric state over asymmetric conformations.

This paper examines whether diffusion models can extract physics-like energies for protein docking, finding they can recover energy funnels comparable to Rosetta in 9 out of 25 cases.

This study identifies the structural basis of allosteric regulation in the human cis-prenyltransferase complex using a combination of experimental and computational methods.

The paper combines NMR data with AlphaFlow to identify excited state conformers of pro-IL-18, revealing structural insights from transient states.

The paper identifies that AlphaFold has a higher false-positive rate for homodimers than heterodimers and improves detection using a logistic regression model incorporating structural and homology data.

This study uses cryo-EM and molecular dynamics to analyze conformational transitions in AE1 and shows how PIP2 lipids inhibit transport by stabilizing the outward-facing state.

FuzzAletheia maps dynamic interaction patterns of IDP-ligand complexes to guide hit-to-lead optimization, achieving a 10-fold activity enhancement in a p53 ligand.

The paper introduces mTM-align2, a method for rapid and accurate protein structure database search that uses inverse folding models and contrastive learning, achieving high precision in seconds.

The paper uses Weighted Ensemble simulations to study Hepatitis B virus capsid assembly, revealing new conformations and modulator effects not accessible via standard MD simulations.

This paper designs twistless alpha-helical repeat proteins that inhibit ice recrystallization with activity comparable to native ice-binding proteins.

The paper introduces a computational method to calculate minimum energy pathways in transport proteins, providing mechanistic insights into conformational changes in three membrane transporter superfamilies.

This paper uses molecular dynamics simulations at 310 K to analyze cryo-EM reconstructions of actin filaments, revealing conformational differences from physiological conditions and explaining functional properties.

The paper uses crystallographic ensembles to quantify conformational entropy changes in SARS-CoV-2 Macrodomain upon ligand binding, linking structural heterogeneity to binding thermodynamics.