Protein Structure and Dynamics

Folding scFv--Antigen Complexes at Scale

The paper benchmarks structure prediction models for scFv-Ag complexes using a large-scale dataset and evaluates confidence metrics for selecting high-quality predictions.

A generalizable interface-seeded framework for de novo design of functional oligomers

This paper introduces an AI-based framework for designing responsive protein oligomers that assemble in response to chemical or phosphorylation triggers, validated through experimental testing.

zsasa: a Zig-based engine for high-throughput solvent accessible surface area at proteome scale

zsasa calculates solvent accessible surface area at proteome scale with high throughput, low memory use, and exact or approximate modes.

A Comprehensive Evaluation of Protein Structure Prediction Models for Short Peptides

This study benchmarks five protein structure prediction models on short peptides, finding accuracy improves with length and models perform better on helical structures.

Location dependence of protein intrinsic disorder in Drosophila melanogaster

The paper investigates the location dependence of protein intrinsic disorder in Drosophila melanogaster, finding that disorder is more common at terminals and linked to specific functions like protein-binding.

Extending the MARTINI 3 Coarse-Grained Forcefield to Polypeptoids

This paper develops a MARTINI 3 compatible coarse-grained forcefield for polypeptoids, enabling efficient simulation of their structure and self-assembly.

Beyond native sequence recovery: Improved modeling of thesequence-energy landscape of protein structures

This paper introduces PottsMPNN, a model trained to generate Potts energy functions for protein design, showing improved sequence generation and energy prediction over native sequence recovery.

ConformFlow: scalable normalizing flow for protein conformational ensemble generation

ConformFlow generates protein conformational ensembles using a scalable normalizing flow framework, outperforming diffusion-based methods in speed and generalization.

Calcium Dependent Conformational Changes in Human Transglutaminase 2 and its Implications in Celiac Disease

This study investigates calcium-dependent conformational changes in TG2 and their role in celiac disease using molecular dynamics and nsSNP analysis.

A discrete-to-continuous mathematical model for ensemble distributions of a ligand-interacting macromolecular species across milieux-dependent conformational states may offer insights into the genesis and progression of cooperative binding

The paper introduces a discrete-to-continuous mathematical model to study cooperative binding by analyzing ensemble distributions of macromolecular conformational states across different environments.

Collective fluctuations underlying nanobody inhibitory activity targeting B. anthracis S-layers revealed by multiscale simulations

This study uses multiscale simulations and machine learning to show that nanobodies induce local fluctuations in B. anthracis S-layer proteins, leading to lattice-scale disassembly and pathogenicity inhibition.

USP-ddG: A Unified Structural Paradigm with Data Efficacy and Mixture-of-Experts for Predicting Mutational Effects on Protein-Protein Interactions

USP-ddG predicts mutational effects on protein-protein interactions by improving data efficiency and modeling conformational dynamics, outperforming existing methods on benchmark datasets.

Exploring the Structural Lexicon of the Proteome via Metric Geometry

This paper introduces GWProt, a framework using metric geometry to analyze protein structures, identifying conformational switches and shared functional domains across proteins.

Structural Bioinformatics of Four Human Aquaporins and Their Water-Soluble QTY Analogs

The paper applies the QTY code with AlphaFold 3 to design water-soluble analogs of four human aquaporins while preserving their structure and function.

The Emergence of Novel Versus Known Three-Dimensional Structures from Random Sequences.

This study shows that random sequences repeated in tandem are more likely to fold into stable structures than fully random sequences, with some structures being novel and experimentally confirmed.

Coupled Binding and Folding of NS2B/NS3 Protease and Linker Effects Revealed by Topology-based Modeling

This paper uses topology-based modeling to study the binding and folding of WNV NS2B/NS3 protease and shows how the G4SG4 linker affects its stability and folding pathways.

Resolving Local and Global Conformational Heterogeneity of the Human Intrinsically Disordered Proteome

This paper introduces a framework to resolve conformational heterogeneity in human intrinsically disordered regions (IDRs) using polymer physics descriptors, revealing local and global structural differences linked to function.

Incorporating Surfaced-Induced Dissociation Mass Spectrometry Data into an AlphaFold-derived deep learning network improves protein structure prediction

The paper develops SIDFold, a deep learning model that integrates SID-nMS data with AlphaFold to improve protein complex structure prediction accuracy.

Benchmarking and behavioral characterization of LLM agents for protein design

This paper benchmarks LLM agents in protein design tasks, finding they outperform hardcoded pipelines but underperform expert practice due to limited evaluation depth.

Loop-Directed Cofactor Binding Enables Programmable Multico-factor Protein Design

This paper designs proteins with multiple cofactor binding sites by placing histidine ligands in loop regions, enabling precise control over cofactor positioning and function.

Exploring the large-scale properties of a protein secondary structure genotype-to-phenotype map

The paper characterizes the robustness and complexity of a protein secondary structure genotype-to-phenotype map using a plant pathogen effector domain.

A Chromatin Biology Assessment of AlphaFold3

This paper benchmarks AlphaFold3's ability to predict structures of chromatin complexes, finding it excels at histone interactions but struggles with DNA-binding factors.

Prosculpt: Lowering the Barrier to Computational Protein Design

Prosculpt is a protein design pipeline that simplifies the use of multiple tools for protein design, enabling users to perform complex tasks without coding.

The Gompertz curve for estimating growth rates of Protein Data Bank and protein folds

The paper fits the Gompertz curve to PDB growth data to estimate future PDB entries and protein folds, revealing a deceleration in growth.

Geometry-Constrained Prediction of Catalytically Competent Kinase Domains Across the Human Kinome

This paper introduces AFEX, a geometry-constrained framework for predicting active kinase domains, achieving high accuracy across the human kinome.

Exploiting NMR Ensemble Heterogeneity Enables Small Molecule Discovery Against Dynamic Protein-Protein Interfaces

This paper introduces AtlasNMR, a framework using NMR ensembles to identify small molecules targeting dynamic protein-protein interfaces, demonstrating its effectiveness with the nNOS PDZ domain.

HyRes: Accurate Physics-Based Simulation of Dynamic Protein Structures and Interactions in Complex Environments at Scale

HyRes simulates dynamic protein structures and interactions for IDPs, showing high accuracy across environments and generating ensembles for thousands of human IDPs.

Computational Redesign of an Antifreeze Protein Using Deep Learning

This study uses deep learning to redesign an antifreeze protein, identifying variants with improved properties but not surpassing wild-type activity.

ComplexDesign: sequence-hallucination design of protein binders bridging multiple proteins

ComplexDesign is a method for designing multichain protein complexes by optimizing sequences to fold proteins and form inter-chain interactions, achieving high success rates in designing dimers, trimers, and tetramers.

Zero-shot design of drug-binding proteins via neural selection-expansion

This paper introduces a method using two neural networks to design drug-binding proteins with high affinity, surpassing current state-of-the-art methods.