AIMC Topic: Binding Sites

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DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks.

BMC bioinformatics Feb 1, 2021
BACKGROUND: Due to the complexity of the biological systems, the prediction of the potential DNA binding sites for transcription factors remains a difficult problem in computational biology. Genomic DNA sequences and experimental results from paralle...
Computational Biology Transcription Factors Binding Sites Chromatin Neural Networks, Computer Protein Binding
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SSnet: A Deep Learning Approach for Protein-Ligand Interaction Prediction.

International journal of molecular sciences Jan 30, 2021
Computational prediction of Protein-Ligand Interaction (PLI) is an important step in the modern drug discovery pipeline as it mitigates the cost, time, and resources required to screen novel therapeutics. Deep Neural Networks (DNN) have recently show...
Caenorhabditis elegans Protein Structure, Secondary Ligands Datasets as Topic Binding Sites Deep Learning Protein Binding Protein Domains Animals Drug Discovery Humans
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Systematic analysis of binding of transcription factors to noncoding variants.

Nature Jan 27, 2021
Many sequence variants have been linked to complex human traits and diseases, but deciphering their biological functions remains challenging, as most of them reside in noncoding DNA. Here we have systematically assessed the binding of 270 human trans...
Disease Binding Sites SELEX Aptamer Technique Support Vector Machine Ligands Genome, Human Humans Protein Binding Polymorphism, Single Nucleotide Transcription Factors
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Classification and prediction of protein-protein interaction interface using machine learning algorithm.

Scientific reports Jan 19, 2021
Structural insight of the protein-protein interaction (PPI) interface can provide knowledge about the kinetics, thermodynamics and molecular functions of the complex while elucidating its role in diseases and further enabling it as a potential therap...
Support Vector Machine Proteins Databases, Protein Models, Molecular Molecular Docking Simulation Protein Interaction Maps Protein Binding Binding Sites Thermodynamics Protein Interaction Mapping
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TargetDBP+: Enhancing the Performance of Identifying DNA-Binding Proteins via Weighted Convolutional Features.

Journal of chemical information and modeling Jan 7, 2021
Protein-DNA interactions exist ubiquitously and play important roles in the life cycles of living cells. The accurate identification of DNA-binding proteins (DBPs) is one of the key steps to understand the mechanisms of protein-DNA interactions. Alth...
Databases, Protein DNA-Binding Proteins Binding Sites Algorithms Support Vector Machine Position-Specific Scoring Matrices
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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...
Transcription Factors Humans Chromatin Neural Networks, Computer Basic Helix-Loop-Helix Transcription Factors Binding Sites Gene Expression Regulation Protein Binding DNA-Binding Proteins Genome Histones
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Repurposing potential of FDA-approved and investigational drugs for COVID-19 targeting SARS-CoV-2 spike and main protease and validation by machine learning algorithm.

Chemical biology & drug design Dec 22, 2020
The present study aimed to assess the repurposing potential of existing antiviral drug candidates (FDA-approved and investigational) against SARS-CoV-2 target proteins that facilitates viral entry and replication into the host body. To evaluate molec...
Humans Machine Learning COVID-19 SARS-CoV-2 Molecular Docking Simulation Antiviral Agents Binding Sites Spike Glycoprotein, Coronavirus Protease Inhibitors Drug Repositioning Viral Matrix Proteins Cell Line Deoxyadenosines Structure-Activity Relationship Cell Survival COVID-19 Drug Treatment
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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...
Serotonin Plasma Membrane Transport Proteins Wakefulness Machine Learning Sleep Algorithms Animals Humans Directed Molecular Evolution Brain Linear Models HEK293 Cells Protein Binding Photons Serotonin Behavior, Animal Mice Amygdala Mice, Inbred C57BL Binding Sites Kinetics Amino Acid Sequence
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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 Proteins RNA Binding Sites Deep Learning Protein Binding
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