ProQ3: Improved model quality assessments using Rosetta energy terms
Motivation: To assess the quality of a protein model, i.e. to estimate how close it is to its native structure, using no other information than the structure of the model has been shown to be useful for structure prediction. The state of the art method, ProQ2, is based on a machine learning approach that uses a number of features calculated from a protein model. Here, we examine if these features can be exchanged with energy terms calculated from Rosetta and if a combination of these terms can improve the quality assessment. Results: When using the full atom energy function from Rosetta in ProQRosFA the QA is on par with our previous state-of-the-art method, ProQ2. The method based on the low-resolution centroid scoring function, ProQRosCen, performs almost as well and the combination of all the three methods, ProQ2, ProQRosFA and ProQCenFA into ProQ3 show superior performance over ProQ2. Availability: ProQ3 is freely available on BitBucket at https://bitbucket.org/ElofssonLab/proq3
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
ProQ3D: Improved model quality assessments using Deep Learning
Summary: Protein quality assessment is a long-standing problem in bioinformatics. For more than a decade we have developed state-of-art predictors by carefully selecting and optimising inputs to a machine learning method…
Deep LearningmodelLiTransProQA: an LLM-based Literary Translation evaluation metric with Professional Question Answering
The impact of Large Language Models (LLMs) has extended into literary domains. However, existing evaluation metrics prioritize mechanical accuracy over artistic expression and tend to overrate machine translation (MT) as…
Machine TranslationQuestion AnsweringTranslationDProQ: A Gated-Graph Transformer for Protein Complex Structure Assessment
Proteins interact to form complexes to carry out essential biological functions. Computational methods have been developed to predict the structures of protein complexes. However, an important challenge in protein comple…
Drug DiscoveryProQA: Structural Prompt-based Pre-training for Unified Question Answering
Question Answering (QA) is a longstanding challenge in natural language processing. Existing QA works mostly focus on specific question types, knowledge domains, or reasoning skills. The specialty in QA research hinders …
Continual LearningFew-Shot LearningQuestion AnsweringTransfer LearningProQA: Structural Prompt-based Pre-training for Unified Question Answering
Question Answering (QA) is a longstanding challenge in natural language processing. Existing QA works mostly focus on specific question types, knowledge domains, or reasoning skills. The specialty in QA research hinders …
Continual LearningFew-Shot LearningQuestion AnsweringTransfer Learning