protein sequence

Amino acid clustering and epistasis guide sequence-based prediction of phenotype modulation

The paper develops a method to predict phenotype modulation by analyzing amino acid clustering and epistasis in protein sequences, showing that these factors improve prediction accuracy.

Generative design of de novo AAV vectors with unique serological profiles

This paper designs de novo AAV vectors with unique serological profiles using a variational autoencoder, achieving transduction efficiency and nAb avoidance in human sera.

RabbitCD-HIT: Distributed High-Sensitivity Greedy Incremental Clustering for Billion-Scale Protein Sequences in Hours

RabbitCD-HIT clusters billion-scale protein sequences efficiently, achieving faster performance than CD-HIT on large datasets.

StableProt: Structure-Aware Deep Learning for Protein Thermostability (Tm) and Environmental Adaptation (OGT) Prediction

StableProt predicts protein thermostability and organismal optimal growth temperature using a structure-aware deep learning framework, achieving high accuracy and robustness across temperature regimes.

pLM-bVAE: protein language model-enhanced binary representation improves quantum annealing-based protein sequence design

This paper introduces pLM-bVAE, a binary variational autoencoder enhanced with protein language model representations, showing improved sequence reconstruction and design performance in quantum annealing-based protein sequence design.

RPFace: From biased structural benchmarks to generalizable RNA-protein interface prediction

RPFace predicts RNA-protein interfaces directly from sequence, outperforming existing methods on RNA interfaces and generalizing to in vivo data without pretraining.

Protify: A Benchmarking Platform Revealing Task Dependence and Homology Leakage in Protein Language Model Evaluation

Protify benchmarks protein language models across tasks and evaluation settings, revealing task dependence and homology leakage in model performance.

Language-guided domain adaptation improves protein sequence rep-resentations for antimicrobial resistance analysis

BacLLM improves protein sequence representations for antimicrobial resistance analysis by integrating functional knowledge and enhancing resistance gene identification and mechanism prediction.

Translating chemical reactions into enzyme sequences enables formate dehydrogenase engineering

This paper introduces REXzyme, a model translating chemical reactions into enzyme sequences, and demonstrates its ability to generate active formate dehydrogenases for CO2 reduction.

A protein language model for domain, functional site, and variant effect prediction

PALM, a protein language model, predicts domain, functional site, and variant effects with high accuracy using curated sequence data and outperforms existing models in multiple benchmarks.

PartiDesign: A structure-sequence co-design paradigm for practical all-to-all biomolecules design

PartiDesign is a structure-sequence co-design model that generates molecular structures and sequences for proteins, nucleic acids, and small molecules, achieving high design throughput across benchmarks.

Error-Controlled Discovery of Protein Interactions via Conformal Calibration

PPI-Caliper controls false discovery rate in protein interaction prediction using conformal calibration without retraining models.

Autonomous generalizability auditing of scientific foundation models

This paper introduces AutoSPECTRA, a protocol for auditing generalizability of scientific foundation models across biological domains.

Peptorama: Structure creation and exploratory data analysis for non-ribosomal peptides

Peptorama provides tools for creating and analyzing non-ribosomal peptide structures, enabling efficient comparison of known and predicted peptides to aid in biodiscovery.

CARTnet: Template-guided B-cell Epitope Prediction with Contact-aware Attention

CARTnet improves B-cell epitope prediction using a contact-aware deep learning framework, outperforming existing methods on internal and external datasets.

Omics-scale decoding of protein N-glycosylation using protein language model embeddings

The paper decodes protein N-glycosylation sites from protein language model embeddings using a zero-shot framework, revealing biological insights and disease associations.

Direct Bioconjugations of Diverse Payloads using an Extraordinarily Donor-Promiscuous Flavin Transferase

This paper introduces a direct enzymatic bioconjugation platform using the flavin transferase ApbE, enabling site-specific conjugation of diverse payloads without intermediate chemical steps.

Mapping and Probing the Substrate Scope of a Ketoamide-Forming Splicease by Computational Design

The paper uses computational methods to design and evaluate splicease variants for generating diverse ketoamide substrates, finding that top-scoring peptides are spliced more efficiently than single-point mutants.

Parameter-Efficient Adaptation of Protein Language Models for Dual-Target Antimicrobial Peptide Discovery Under Strict Homology Constraints

This paper develops a parameter-efficient transfer learning framework to discover antimicrobial peptides with high potency and low cytotoxicity using protein language models.

Target Specific Conformational Flexibility and Electrostatic Complementarity Modulate LTNF10 Peptide Binding to Phospholipase A2 Variants from Snake Venoms

This study investigates how charge and conformational changes in a peptide affect its binding to different snake venom PLA2 variants, revealing structural and electrostatic factors influencing affinity.

Machine learning guided design of strong transcriptional activation domains

The paper designs functional transcriptional activation domains using machine learning and experimental validation, finding that over 90% of predicted sequences work in yeast.

Coding region changes in the Hippo pathway component YAP1 contribute to body size differences among mammalian species

This study identifies coding region changes in YAP1 that contribute to body size differences among rodents by showing increased growth-promoting activity in capybara YAP1 compared to mouse and vole YAP1.

Minimal requirements and evolution of polar membrane targeting in the land plant SOSEKI protein family

This study identifies a polar targeting peptide in plants and reveals its evolutionary conservation and diversification within the SOSEKI protein family.

Predicted condensation-related signatures localize to two C-terminal regions of the prion protein across cervid PRNP variants associated with chronic wasting disease

De novo design of mini-proteins as specific binders to PACAP-38, a key mediator of migraine

This study designs mini-proteins that bind PACAP-38 with high affinity, showing improved potency and stability compared to earlier versions.

The Quagmire of Immunogenicity-Guided Antibody Design: Labels Limit Progress

The paper evaluates antibody design methods using immunogenicity labels and finds that format-based approaches outperform sequence-based predictors, but label inaccuracies limit progress.

Gene Embedding Hub: a standardized resource for human gene representations

The paper introduces a standardized resource of human gene embeddings derived from diverse biological data sources, enabling comparison and use across modalities.

GLOM TGITO: multiscale protein modelling and multiview landscape-guided sequence discovery

The paper introduces GLOM-TGITO, a method for protein design that combines multiscale modeling with multiview landscape-guided optimization, achieving high accuracy and novel sequence discovery.

Bioactivity foundation model for hit identification and hit-to-lead optimization from sequence data

PSICHIC+ is a bioactivity foundation model that predicts binding affinities from sequence data, improving hit identification and hit-to-lead optimization using heterogeneous bioactivity data.

EverGreen: A Calcium Sensing Fluorescent Protein with Ultra-Slow Response Properties

The paper introduces a fluorescent calcium biosensor with ultra-slow response kinetics, useful for applications where delayed signal detection is advantageous.