The process of designing biomolecules, in particular proteins, is witnessing a rapid change
in available tooling and approaches, moving from design through physicochemical force …

Protein inverse folding has attracted increasing attention in recent years. However, we
observe that current methods are usually limited to the CATH dataset and the recovery …

In recent years, generative protein sequence models have been developed to sample novel
sequences. However, predicting whether generated proteins will fold and function remains …

While DeepMind has tentatively solved protein folding, its inverse problem--protein design
which predicts protein sequences from their 3D structures--still faces significant challenges …

Recent studies have shown competitive performance in protein inverse folding, while most
of them disregard the importance of predictive confidence, fail to cover the vast protein …

Advances in deep learning models have revolutionized the study of biomolecule systems
and their mechanisms. Graph representation learning, in particular, is important for …

Proteins serve as the foundation of life, and numerous diseases and challenges in the field
of life sciences are intimately linked to the molecular dynamics laws that are concealed …

There is strong interest in accurate methods for predicting changes in protein stability
resulting from amino acid mutations to the protein sequence. Recombinant proteins must …

摘要蛋白质是各类生命活动不可缺少的承担者, 其序列决定了折叠后的三维结构和功能.
这些具有特定功能的蛋白质在生物医学等多个领域具有重要的应用价值. 计算蛋白质设计可以 …

Proteins are essential to life as they carry out a great variety of biological functions. Protein
sequences determine their three-dimensional structures, and therefore physiological …