Into the Unknown: From Structure to Disorder in Protein Function Prediction
원문 초록
Intrinsically disordered regions (IDRs) account for one-third of the human proteome and play essential biological roles. However, predicting the functions of IDRs remains a major challenge due to their lack of stable structures, rapid sequence evolution, and context-dependent behavior. Many predictors of protein function neglect or underperform on IDRs. Recent advances in computational biology and machine learning, including protein language models, alignment-free approaches, and IDR-specific methods, have revealed conserved bulk features and local motifs within IDRs that are linked to function. This review highlights emerging computational methods that map the sequence-function relationship in IDRs, outlines critical challenges in IDR function annotation, and proposes a community-driven framework to accelerate interpretable functional predictions for IDRs.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
AnnoDPO: Protein Functional Annotation Learning with Direct Preference Optimization
MSNGO: multi-species protein function annotation based on 3D protein structure and network propagation
evoBPE: Evolutionary Protein Sequence Tokenization
A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges
ProtBoost: protein function prediction with Py-Boost and Graph Neural Networks -- CAFA5 top2 solution
A Survey on LLM-as-a-Judge
토론
이 논문과 연결된 포럼 글이 아직 없습니다.