AIMC Topic: Amino Acid Sequence

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ProtPlat: an efficient pre-training platform for protein classification based on FastText.

BMC bioinformatics Feb 11, 2022
BACKGROUND: For the past decades, benefitting from the rapid growth of protein sequence data in public databases, a lot of machine learning methods have been developed to predict physicochemical properties or functions of proteins using amino acid se...
Amino Acid Sequence Natural Language Processing Neural Networks, Computer Machine Learning Proteins
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Machine learning modeling of family wide enzyme-substrate specificity screens.

PLoS computational biology Feb 10, 2022
Biocatalysis is a promising approach to sustainably synthesize pharmaceuticals, complex natural products, and commodity chemicals at scale. However, the adoption of biocatalysis is limited by our ability to select enzymes that will catalyze their nat...
Drug Discovery Proteins Amino Acid Sequence Substrate Specificity Machine Learning
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A backbone-centred energy function of neural networks for protein design.

Nature Feb 9, 2022
A protein backbone structure is designable if a substantial number of amino acid sequences exist that autonomously fold into it. It has been suggested that the designability of backbones is governed mainly by side chain-independent or side chain type...
Models, Molecular Amino Acid Sequence Neural Networks, Computer Proteins Protein Conformation
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Protein sequence design with a learned potential.

Nature communications Feb 8, 2022
The task of protein sequence design is central to nearly all rational protein engineering problems, and enormous effort has gone into the development of energy functions to guide design. Here, we investigate the capability of a deep neural network mo...
Deep Learning Models, Molecular Computer Simulation Protein Engineering Amino Acid Sequence Protein Folding Crystallography, X-Ray Protein Domains
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End-to-End Deep Learning Model to Predict and Design Secondary Structure Content of Structural Proteins.

ACS biomaterials science & engineering Feb 7, 2022
Structural proteins are the basis of many biomaterials and key construction and functional components of all life. Further, it is well-known that the diversity of proteins' function relies on their local structures derived from their primary amino ac...
Amino Acid Sequence Protein Structure, Secondary Deep Learning Proteins
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A deep learning model to detect novel pore-forming proteins.

Scientific reports Feb 7, 2022
Many pore-forming proteins originating from pathogenic bacteria are toxic against agricultural pests. They are the key ingredients in several pesticidal products for agricultural use, including transgenic crops. There is an urgent need to identify no...
Pesticides Deep Learning Amino Acid Sequence Bacteria Pore Forming Cytotoxic Proteins Crops, Agricultural
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A Transfer-Learning-Based Deep Convolutional Neural Network for Predicting Leukemia-Related Phosphorylation Sites from Protein Primary Sequences.

International journal of molecular sciences Feb 3, 2022
As one of the most important post-translational modifications (PTMs), phosphorylation refers to the binding of a phosphate group with amino acid residues like Ser (S), Thr (T) and Tyr (Y) thus resulting in diverse functions at the molecular level. Ab...
Cluster Analysis Neoplasm Proteins Phosphorylation Phosphoproteins Deep Learning ROC Curve Peptides Learning Curve Entropy Leukemia Amino Acid Sequence Databases as Topic Humans Neural Networks, Computer
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AMP: Species-Specific Prediction of Anti-microbial Peptides Using Zero and Few Shot Learning.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2022
Evolution of drug-resistant microbial species is one of the major challenges to global health. Development of new antimicrobial treatments such as antimicrobial peptides needs to be accelerated to combat this threat. However, the discovery of novel a...
Peptides Amino Acid Sequence Machine Learning Anti-Bacterial Agents
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Boltzmann Machine Learning and Regularization Methods for Inferring Evolutionary Fields and Couplings From a Multiple Sequence Alignment.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2022
The inverse Potts problem to infer a Boltzmann distribution for homologous protein sequences from their single-site and pairwise amino acid frequencies recently attracts a great deal of attention in the studies of protein structure and evolution. We ...
Machine Learning Proteins Amino Acid Sequence Sequence Alignment
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A two-step ensemble learning for predicting protein hot spot residues from whole protein sequence.

Amino acids Jan 30, 2022
Protein hot spot residues are functional sites in protein-protein interactions. Biological experimental methods are traditionally used to identify hot spot residues, which is laborious and time-consuming. Thus a variety of computational methods were ...
Databases, Protein Amino Acid Sequence Protein Binding Machine Learning Proteins
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