Artificial intelligence-aided protein engineering: from topological data analysis to deep protein language models
Protein engineering is an emerging field in biotechnology that has the potential to
revolutionize various areas, such as antibody design, drug discovery, food security, ecology …
revolutionize various areas, such as antibody design, drug discovery, food security, ecology …
Easy and accurate protein structure prediction using ColabFold
Since its public release in 2021, AlphaFold2 (AF2) has made investigating biological
questions, by using predicted protein structures of single monomers or full complexes, a …
questions, by using predicted protein structures of single monomers or full complexes, a …
ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a language diffusion model
Through evolution, nature has presented a set of remarkable protein materials, including
elastins, silks, keratins and collagens with superior mechanical performances that play …
elastins, silks, keratins and collagens with superior mechanical performances that play …
Large Language Models Can Be Contextual Privacy Protection Learners
Abstract The proliferation of Large Language Models (LLMs) has driven considerable
interest in fine-tuning them with domain-specific data to create specialized language …
interest in fine-tuning them with domain-specific data to create specialized language …
Improving antibody language models with native pairing
SM Burbach, B Briney - Patterns, 2024 - cell.com
Existing antibody language models are limited by their use of unpaired antibody sequence
data. A recently published dataset of∼ 1.6× 10 6 natively paired human antibody sequences …
data. A recently published dataset of∼ 1.6× 10 6 natively paired human antibody sequences …
End-to-end protein–ligand complex structure generation with diffusion-based generative models
Background Three-dimensional structures of protein–ligand complexes provide valuable
insights into their interactions and are crucial for molecular biological studies and drug …
insights into their interactions and are crucial for molecular biological studies and drug …
Recent advances and challenges in protein structure prediction
Artificial intelligence has made significant advances in the field of protein structure prediction
in recent years. In particular, DeepMind's end-to-end model, AlphaFold2, has demonstrated …
in recent years. In particular, DeepMind's end-to-end model, AlphaFold2, has demonstrated …
[HTML][HTML] Machine learning methods for predicting protein structure from single sequences
Recent breakthroughs in protein structure prediction have increasingly relied on the use of
deep neural networks. These recent methods are notable in that they produce 3-D atomic …
deep neural networks. These recent methods are notable in that they produce 3-D atomic …
Improved structure-related prediction for insufficient homologous proteins using MSA enhancement and pre-trained language model
Q Meng, F Guo, J Tang - Briefings in Bioinformatics, 2023 - academic.oup.com
In recent years, protein structure problems have become a hotspot for understanding protein
folding and function mechanisms. It has been observed that most of the protein structure …
folding and function mechanisms. It has been observed that most of the protein structure …
Metaenzyme: Meta pan-enzyme learning for task-adaptive redesign
Enzyme design plays a crucial role in both industrial production and biology. However, this
field faces challenges due to the lack of comprehensive benchmarks and the complexity of …
field faces challenges due to the lack of comprehensive benchmarks and the complexity of …