Protein Structure and Dynamics

Folddisco efficiently searches for similar protein structural motifs in large databases using a geometric feature index and rarity-based scoring, achieving faster query times and better storage efficiency than existing methods.

This study compares the structural stability and proton-exchange dynamics of two closely related superoxide dismutase isozymes in Staphylococcus aureus, showing that the neofunctionalised camSOD is more stable than the ancestral MnSOD.

The paper decodes energetic blueprints of conserved protein folds to explain functional diversity and enables engineered transcription factors with ligand-driven responses.

This paper introduces ProtHMSO, a heuristic multi-site optimization framework using masked protein language models to design functional protein sequences more efficiently than existing methods.

This paper introduces a Bayesian method to interpret time-resolved experiments using molecular simulations, demonstrating its application to protein unfolding studies.

This paper introduces FlashABB, a model that predicts antibody structures faster than sequence embedding models, enabling efficient access to 3D information for antibody stability and developability prediction.

This study uses molecular dynamics simulations to investigate how the intrinsically disordered regions of FUS recognize U1 snRNA, revealing distinct interaction mechanisms and structural changes upon RNA binding.

This paper identifies specific interfacial residues in IGPS that modulate allosteric regulation through structural and dynamic changes induced by targeted mutations.

The paper uses language modeling to create a comprehensive representation of protein biology, enabling structure prediction and discovery of high-affinity protein interactions.

AI-IDP predicts conformational ensembles of disordered proteins by combining deep learning with physical restraints, revealing common structural features across proteomes.

This study investigates how anionic and cationic surfactants affect the conformational stability of a cationic protein using molecular dynamics simulations.

The paper maps structural coverage of Arabidopsis thaliana developmental proteins using experimental data and AlphaFold predictions, finding higher structural coverage in plants than in humans.

The paper investigates how intramolecular interactions between folded and disordered regions of ubiquilin proteins influence their structure and function across different species.

This paper designs intrinsically disordered proteins using a physics-guided machine learning framework to encode complex signal processing and condensate properties.

This study models the structure of LRP1 using homology and neural network-based methods, revealing glycan-mediated dimerization and its role in stabilizing the protein's quaternary structure.

The paper determines the atomic structure of insect chorion amyloid filaments and reveals their assembly principles, showing functional amyloids can operate in a regulated biological context.

DeepRank-Ab improves scoring of antibody-antigen complexes using geometric deep learning, outperforming existing methods in accuracy and ranking.

This study uses a combined experimental platform to analyze the conformational dynamics of EAAT1, revealing that multimodal dynamics regulate its function and identifying a mutation that inhibits transport by stabilizing a paused conformation.

This paper develops a hierarchical sequence-based framework to infer distributed protein organization, identifies novel ciliary proteins, and enables synthetic protein design.

This paper uses pressure and temperature to study how TMV coat protein assembly changes, revealing localized structural dynamics and epitope masking under high pressure.

The paper reports a spontaneous structural transition in the insulin receptor during molecular dynamics simulation, revealing a conformation compatible with hybrid insulin binding sites.

This study structures two co-translational folding intermediates of an immunoglobulin-like domain using NMR and MD simulations, revealing parallel folding pathways conserved within the domain family.

This study uses molecular dynamics simulations to show that antibody maturation increases rigidity in protein-contacting regions and flexibility at glycan interfaces.

This study compares AI tools for predicting protein structural ensembles, finding they generate diverse but distinct conformational distributions, with limited coverage of experimental structures and minimal response to known mutations.

The paper shows that neutral evolution can lead to increased structure in unstructured proteins and loss of structure in structured proteins, suggesting a diffuse sequence-structure landscape.

TAMALE identifies functional residues across the human proteome using structure models and variant effect predictions, validated through case studies and experimental validation.

AlphaInterp analyzes AlphaFold 3's internal mechanisms to show how evolutionary data influences protein structure prediction, revealing dependencies on comparative context and phylogenetic diversity.

This paper introduces OCDesign, a curriculum-guided framework for multi-property protein design, showing that staged objective introduction improves success rates compared to one-shot optimization.

This study uses MD simulations to show that preorganized thumb-subdomain motions in SARS-CoV-2 polymerase drive functional transitions through structurally coupled regulatory regions.

ProtXAI combines molecular dynamics and explainable AI to identify residue-level determinants of protein conformational changes across diverse systems.