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Amino Acid Sequence

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PANDA: Predicting the change in proteins binding affinity upon mutations by finding a signal in primary structures.

Journal of bioinformatics and computational biology
Accurately determining a change in protein binding affinity upon mutations is important to find novel therapeutics and to assist mutagenesis studies. Determination of change in binding affinity upon mutations requires sophisticated, expensive, and ti...

Prediction of African Swine Fever Virus Inhibitors by Molecular Docking-Driven Machine Learning Models.

Molecules (Basel, Switzerland)
African swine fever virus (ASFV) causes a highly contagious and severe hemorrhagic viral disease with high mortality in domestic pigs of all ages. Although the virus is harmless to humans, the ongoing ASFV epidemic could have severe economic conseque...

Machine learning analyses of antibody somatic mutations predict immunoglobulin light chain toxicity.

Nature communications
In systemic light chain amyloidosis (AL), pathogenic monoclonal immunoglobulin light chains (LC) form toxic aggregates and amyloid fibrils in target organs. Prompt diagnosis is crucial to avoid permanent organ damage, but delayed diagnosis is common ...

How Deep Learning Tools Can Help Protein Engineers Find Good Sequences.

The journal of physical chemistry. B
The deep learning revolution introduced a new and efficacious way to address computational challenges in a wide range of fields, relying on large data sets and powerful computational resources. In protein engineering, we consider the challenge of com...

Recent Applications of Deep Learning Methods on Evolution- and Contact-Based Protein Structure Prediction.

International journal of molecular sciences
The new advances in deep learning methods have influenced many aspects of scientific research, including the study of the protein system. The prediction of proteins' 3D structural components is now heavily dependent on machine learning techniques tha...

Protein sequence design with deep generative models.

Current opinion in chemical biology
Protein engineering seeks to identify protein sequences with optimized properties. When guided by machine learning, protein sequence generation methods can draw on prior knowledge and experimental efforts to improve this process. In this review, we h...

Prediction of Anticancer Peptides with High Efficacy and Low Toxicity by Hybrid Model Based on 3D Structure of Peptides.

International journal of molecular sciences
Recently, anticancer peptides (ACPs) have emerged as unique and promising therapeutic agents for cancer treatment compared with antibody and small molecule drugs. In addition to experimental methods of ACPs discovery, it is also necessary to develop ...

Structure-based protein function prediction using graph convolutional networks.

Nature communications
The rapid increase in the number of proteins in sequence databases and the diversity of their functions challenge computational approaches for automated function prediction. Here, we introduce DeepFRI, a Graph Convolutional Network for predicting pro...

Improvement of Neoantigen Identification Through Convolution Neural Network.

Frontiers in immunology
Accurate prediction of neoantigens and the subsequent elicited protective anti-tumor response are particularly important for the development of cancer vaccine and adoptive T-cell therapy. However, current algorithms for predicting neoantigens are lim...

Deep Learning-Based Advances in Protein Structure Prediction.

International journal of molecular sciences
Obtaining an accurate description of protein structure is a fundamental step toward understanding the underpinning of biology. Although recent advances in experimental approaches have greatly enhanced our capabilities to experimentally determine prot...