AIMC Topic: Protein Binding

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A Novel Protein Mapping Method for Predicting the Protein Interactions in COVID-19 Disease by Deep Learning.

Interdisciplinary sciences, computational life sciences Jan 12, 2021
The new type of corona virus (SARS-COV-2) emerging in Wuhan, China has spread rapidly to the world and has become a pandemic. In addition to having a significant impact on daily life, it also shows its effect in different areas, including public heal...
Humans SARS-CoV-2 Deep Learning ROC Curve COVID-19 Algorithms Reproducibility of Results Genome, Viral Protein Interaction Mapping Protein Binding Amino Acids
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Prediction of kinase inhibitors binding modes with machine learning and reduced descriptor sets.

Scientific reports Jan 12, 2021
Protein kinases are receiving wide research interest, from drug perspective, due to their important roles in human body. Available kinase-inhibitor data, including crystallized structures, revealed many details about the mechanism of inhibition and b...
Protein Conformation Protein Kinase Inhibitors Models, Molecular Protein Kinases Humans Machine Learning Protein Binding Support Vector Machine
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An interpretable bimodal neural network characterizes the sequence and preexisting chromatin predictors of induced transcription factor binding.

Genome biology Jan 7, 2021
BACKGROUND: Transcription factor (TF) binding specificity is determined via a complex interplay between the transcription factor's DNA binding preference and cell type-specific chromatin environments. The chromatin features that correlate with transc...
Chromatin Histones Neural Networks, Computer Binding Sites Protein Binding Genome Transcription Factors Basic Helix-Loop-Helix Transcription Factors Humans DNA-Binding Proteins Gene Expression Regulation
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MATHLA: a robust framework for HLA-peptide binding prediction integrating bidirectional LSTM and multiple head attention mechanism.

BMC bioinformatics Jan 6, 2021
BACKGROUND: Accurate prediction of binding between class I human leukocyte antigen (HLA) and neoepitope is critical for target identification within personalized T-cell based immunotherapy. Many recent prediction tools developed upon the deep learnin...
Humans Neural Networks, Computer Computational Biology Models, Statistical Histocompatibility Antigens Class I Algorithms Peptides Protein Binding
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Artificial intelligence in the early stages of drug discovery.

Archives of biochemistry and biophysics Dec 19, 2020
Although the use of computational methods within the pharmaceutical industry is well established, there is an urgent need for new approaches that can improve and optimize the pipeline of drug discovery and development. In spite of the fact that there...
Cell Line Pharmaceutical Preparations Proteins Humans Ligands Animals Drug Repositioning Drug Discovery Deep Learning Protein Binding
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Deep neural networks for inferring binding sites of RNA-binding proteins by using distributed representations of RNA primary sequence and secondary structure.

BMC genomics Dec 17, 2020
BACKGROUND: RNA binding proteins (RBPs) play a vital role in post-transcriptional processes in all eukaryotes, such as splicing regulation, mRNA transport, and modulation of mRNA translation and decay. The identification of RBP binding sites is a cru...
RNA Neural Networks, Computer Binding Sites Protein Binding RNA-Binding Proteins
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Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning.

Cell Dec 16, 2020
Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which ha...
Linear Models Humans HEK293 Cells Behavior, Animal Photons Animals Amino Acid Sequence Amygdala Binding Sites Protein Binding Serotonin Plasma Membrane Transport Proteins Wakefulness Machine Learning Directed Molecular Evolution Mice Sleep Mice, Inbred C57BL Algorithms Serotonin Brain Kinetics
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ChemBoost: A Chemical Language Based Approach for Protein - Ligand Binding Affinity Prediction.

Molecular informatics Dec 14, 2020
Identification of high affinity drug-target interactions is a major research question in drug discovery. Proteins are generally represented by their structures or sequences. However, structures are available only for a small subset of biomolecules an...
Ligands Computational Chemistry Drug Discovery Protein Binding Computational Biology Machine Learning
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RBPsuite: RNA-protein binding sites prediction suite based on deep learning.

BMC genomics Dec 9, 2020
BACKGROUND: RNA-binding proteins (RBPs) play crucial roles in various biological processes. Deep learning-based methods have been demonstrated powerful on predicting RBP sites on RNAs. However, the training of deep learning models is very time-intens...
RNA Binding Sites Deep Learning Protein Binding RNA-Binding Proteins
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DeepA-RBPBS: A hybrid convolution and recurrent neural network combined with attention mechanism for predicting RBP binding site.

Journal of biomolecular structure & dynamics Dec 4, 2020
It's important to infer the binding site of RNA-binding proteins (RBP) for understanding the interaction between RBP and its RNA targets and decipher the mechanisms of transcriptional regulation. However, experimental detection of RBP binding sites i...
Binding Sites Neural Networks, Computer Protein Binding RNA-Binding Proteins RNA
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