AIMC Topic: Amino Acid Sequence

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A Machine Learning Approach for Drug-target Interaction Prediction using Wrapper Feature Selection and Class Balancing.

Molecular informatics Feb 11, 2020
Drug-Target interaction (DTI) plays a crucial role in drug discovery, drug repositioning and understanding the drug side effects which helps to identify new therapeutic profiles for various diseases. However, the exponential growth in the genomic and...
Drug Discovery Drug Development Databases, Protein Machine Learning Algorithms Computer Simulation Databases, Chemical Receptors, Cytoplasmic and Nuclear Enzymes Ion Channels Receptors, G-Protein-Coupled Pharmaceutical Preparations Amino Acid Sequence
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Prediction of Contact Residues in Anti-HIV Neutralizing Antibody by Deep Learning.

Japanese journal of infectious diseases Jan 31, 2020
The monoclonal antibody 1C10 targets the V3 loop of HIV-1 and neutralizes a broad range of clade B viruses. However, the mode of interaction between 1C10 and the V3 loop remains unclear because crystallization of 1C10 and the V3 peptide was unsuccess...
HIV Antibodies HIV Envelope Protein gp120 Binding Sites, Antibody Humans Antibodies, Neutralizing Deep Learning Molecular Docking Simulation Amino Acid Sequence Antibodies, Monoclonal Amino Acid Substitution Peptide Fragments
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Prediction of peptide binding to MHC using machine learning with sequence and structure-based feature sets.

Biochimica et biophysica acta. General subjects Jan 16, 2020
Selecting peptides that bind strongly to the major histocompatibility complex (MHC) for inclusion in a vaccine has therapeutic potential for infections and tumors. Machine learning models trained on sequence data exist for peptide:MHC (p:MHC) binding...
Peptides Protein Binding Mice Alleles Histocompatibility Antigens Class I Amino Acid Sequence Machine Learning Algorithms Animals Protein Conformation
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Machine Learning Classifies Core and Outer Fucosylation of N-Glycoproteins Using Mass Spectrometry.

Scientific reports Jan 15, 2020
Protein glycosylation is known to be involved in biological progresses such as cell recognition, growth, differentiation, and apoptosis. Fucosylation of glycoproteins plays an important role for structural stability and function of N-linked glycoprot...
Immunoglobulin gamma-Chains Carbohydrate Sequence Glycopeptides Fucose Amino Acid Sequence Chromatography, High Pressure Liquid Tandem Mass Spectrometry Machine Learning Glycosylation Humans
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Improved protein structure prediction using potentials from deep learning.

Nature Jan 15, 2020
Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence. This problem is of fundamental importance as the structure of a protein largely determines its function; however, protein str...
Caspases Proteins Models, Molecular Datasets as Topic Protein Folding Software Amino Acid Sequence Protein Conformation Deep Learning
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Using Weighted Extreme Learning Machine Combined With Scale-Invariant Feature Transform to Predict Protein-Protein Interactions From Protein Evolutionary Information.

IEEE/ACM transactions on computational biology and bioinformatics Jan 10, 2020
Protein-Protein Interactions (PPIs) play an irreplaceable role in biological activities of organisms. Although many high-throughput methods are used to identify PPIs from different kinds of organisms, they have some shortcomings, such as high cost an...
Helicobacter pylori Amino Acid Sequence Protein Interaction Mapping Evolution, Molecular Proteins Databases, Protein Saccharomyces cerevisiae Proteins Sequence Analysis, Protein Humans Machine Learning Animals Protein Interaction Maps Computational Biology
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DeepECA: an end-to-end learning framework for protein contact prediction from a multiple sequence alignment.

BMC bioinformatics Jan 9, 2020
BACKGROUND: Recently developed methods of protein contact prediction, a crucially important step for protein structure prediction, depend heavily on deep neural networks (DNNs) and multiple sequence alignments (MSAs) of target proteins. Protein seque...
Deep Learning User-Computer Interface Proteins Amino Acid Sequence Neural Networks, Computer Protein Structure, Secondary Sequence Alignment Protein Structure, Tertiary
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ProDCoNN: Protein design using a convolutional neural network.

Proteins Jan 6, 2020
Designing protein sequences that fold to a given three-dimensional (3D) structure has long been a challenging problem in computational structural biology with significant theoretical and practical implications. In this study, we first formulated this...
Databases, Protein Neural Networks, Computer Software Amino Acid Sequence Proteins Datasets as Topic Protein Engineering Protein Structure, Secondary Sequence Alignment
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iProDNA-CapsNet: identifying protein-DNA binding residues using capsule neural networks.

BMC bioinformatics Dec 27, 2019
BACKGROUND: Since protein-DNA interactions are highly essential to diverse biological events, accurately positioning the location of the DNA-binding residues is necessary. This biological issue, however, is currently a challenging task in the age of ...
Position-Specific Scoring Matrices Neural Networks, Computer Software Algorithms Amino Acids Reproducibility of Results Humans DNA-Binding Proteins ROC Curve Amino Acid Sequence DNA
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Discovering nuclear targeting signal sequence through protein language learning and multivariate analysis.

Analytical biochemistry Dec 26, 2019
Nuclear localization signals (NLSs) are peptides that target proteins to the nucleus by binding to carrier proteins in the cytoplasm that transport their cargo across the nuclear membrane. Accurate identification of NLSs can help elucidate the functi...
Amino Acid Sequence Machine Learning Nuclear Localization Signals Databases, Protein Natural Language Processing
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