Protein Structure and Dynamics

The Geometry of Allostery: A Laplacian Minor Hierarchy for Many-Body Protein Communication

This paper introduces a mathematical framework to analyze allostery in proteins, showing how mutations affect pathway correlations and communication through intermediary residues.

Amino acid repeat mosaics shape protein functional landscape

The paper investigates how amino acid homorepeats (HRs) in proteins influence molecular outcomes through different mosaic configurations and identifies their functional implications.

ProMiSE: Protein Multi-State Evaluation Benchmark in Biological Contexts

ProMiSE evaluates protein multi-state prediction models using a curated dataset of biological conformational changes, revealing limitations in capturing functionally relevant dynamics.

XL-MS-Guided Structure Prediction of Disordered Encephalitozoon hellem Proteins

The paper develops a structure prediction method using XL-MS data for disordered microsporidian proteins with no homologs, successfully modeling two spore wall proteins.

MAHLER: Integrating Metadynamics and Inverse Folding to Predict Antibody-Antigen Kinetics

MAHLER predicts antibody-antigen dissociation kinetics using a hybrid machine learning and physics approach, achieving screening-grade accuracy and fast computation.

Validation of MHPC512: A Publicly Available Special-Purpose Supercomputer for Molecular Dynamics Simulations of Biomolecular Systems

The paper validates MHPC512, a special-purpose supercomputer for molecular dynamics simulations, showing it produces results consistent with established software.

EditorForge: An Active-Site-Aware Framework for Inverse-Folding-Based Protein Redesign

EditorForge refines inverse-folded protein sequences for enzyme and genome-editor domains by applying constraints and audits to ensure structural integrity and active-site protection.

CGRig: a rigid-body protein model with residue-level interaction sites for long-time and large-scale protein assembly simulation

CGRig is a rigid-body protein model that enables efficient simulation of large-scale protein assembly while preserving residue-level interaction specificity.

Not All Charges Are Equal: Side-Chain Chemistry Reshapes the Disordered Ensemble of α-synuclein

This paper shows that arginine substitutions, despite similar charge, compact α-synuclein more than lysine, accelerating amyloid formation and reshaping its disordered ensemble.

Accelerated sampling of protein dynamics using BioEmu augmented molecular simulation

This study introduces BioEmu, a workflow combining generative AI with molecular simulations to sample protein conformations, showing both broad coverage and specific limitations in capturing conformational heterogeneity.

Context-Aware Hydrophobicity Modeling: HydroMap and FastHydroMap

This paper introduces HydroMap and FastHydroMap models to predict hydrophobicity from water features, enabling rapid and accurate computation of dewetting free energy for proteins and surfaces.

Structural Evidence for Occupancy-Dependent Inter-Site Coupling in Human Glutathione Synthetase

This study uses atomistic simulations to show how ligand binding in one subunit of hGS alters the geometry and solvent environment of the opposite active site, revealing a distributed allosteric network underlying negative cooperativity.

Aromatic Ring Flips Reveal Reshaping of Protein Dynamics in Crystals and Complexes

The paper compares aromatic ring flip kinetics in GB1 protein across crystals, IgG complexes, and solution, showing reduced flipping in crystals and revealing how crystal environments restrain motion.

Comparative Molecular Dynamics Characterization of Hair Keratin Unfolding Mechanics

This study uses molecular dynamics simulations to compare unfolding mechanics of 51 keratin proteins, revealing rate-dependent nanomechanical responses and correlations with molecular descriptors.

SLiMNet: a deep learning model to detect short linear motifs using protein large language model representations and paired inputs

SLiMNet detects functional similarity in SLiM pairs using deep learning and protein LLM embeddings, identifying new motifs and providing functional annotations.

Promera: a unified model for biomolecular structure prediction, filtering, and design

Promera is a generative model for biomolecular structure prediction, filtering, and design that improves binder filtering and controllable design compared to existing methods.

Changes in biophysical characteristics of YghA from E. coli due to variation in pH

This study examines how pH changes affect the biophysical properties of YghA from E. coli, revealing structural instability at acidic pH and altered interactions with NADH.

Learning Protein-Protein Interaction Interfaces from Multimodal Representations

The paper develops ESM3-PPISites, a model that identifies protein-protein interaction interfaces using multimodal representations, outperforming existing methods and improving docking accuracy.

D-Retro-Inverso Peptide Candidates for Inhibiting SAA Cardiac Amyloidosis

The paper designs and evaluates D-amino acid-based peptides to inhibit SAA3 fibril formation in a mouse model of cardiac amyloidosis.

Biomolecular Condensates Act as Distinct Solvation Environments that Reshape Amino Acid pK Values

The paper investigates how biomolecular condensates alter amino acid pKa values through simulations, finding protonated states are favored in condensates.

Do AI Structure Predictors Capture Bound-State Disorder? A Benchmark on Fuzzy Protein Complexes

This paper benchmarks AI structure predictors on fuzzy protein complexes, finding they consistently violate 30% of NOE restraints and show poor helicity correlation with thermodynamic expectations.

DDI_single: Single-Sequence-Based Protein Domain Assembly

DDI_single improves multi-domain protein structure prediction by accurately assembling domains using a single sequence and a novel gated cross-attention module.

ProtGPT3: an Open-source family of Promptable and Aligned Protein Language Models

ProtGPT3 is an open-source family of protein language models that enables controlled protein generation through alignment and prompting, showing effectiveness in generating functional proteins.

Generalizing the Gaussian Network Model: Spanning-TreeThermodynamics Shows Entropy-Driven KRAS Activation

This paper generalizes the Gaussian Network Model using spanning-tree thermodynamics to show that KRAS activation is driven by entropy-enthalpy compensation.

SNAC-DB: An ML-Ready Database for Antibody and NANOBODY(R) VHH-Antigen Complexes with Expanded Structural Diversity and Real-World Benchmarking

The paper introduces SNAC-DB, a database with expanded structural diversity for antibody and NANOBODY VHH-antigen complexes, and benchmarks seven models showing limited accuracy and ranking issues.

VelocityFM: Short-Horizon Protein Trajectory Prediction via Flow Matching in Velocity Space

VelocityFM predicts short-horizon protein trajectories using flow matching in velocity space, achieving high TM-scores and geometric validity on unseen proteins.

EnzOracle: Mechanism-aware prediction of enzyme environmental adaptation via a classification-guided mixture-of-experts framework

EnzOracle predicts enzyme environmental adaptation traits from sequence using a mixture-of-experts framework, showing strong accuracy and mechanism-aware validation.

Divergent Loop Architecture Shapes Pocket2 Variation in Shark Legumains

The paper compares legumain structures across vertebrates, identifying Pocket 2 as a conserved yet variable region with species-specific structural and ligand-binding differences.

pLM-Guided Inverse Folding for Antibody Sequence Design

The paper improves antibody sequence design by combining a general inverse folding model with an antibody-specific language model, achieving better amino acid recovery and sequence diversity.

Structural motif search across the protein-universe with Folddisco

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.