AIMC Topic: Binding Sites

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Representation learning of genomic sequence motifs with convolutional neural networks.

PLoS computational biology Dec 19, 2019
Although convolutional neural networks (CNNs) have been applied to a variety of computational genomics problems, there remains a large gap in our understanding of how they build representations of regulatory genomic sequences. Here we perform systema...
Humans Neural Networks, Computer Computer Simulation Deep Learning DNA Genome, Human Binding Sites Amino Acid Motifs Genomics Computational Biology Transcription Factors Databases, Genetic
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Latest trends in structure based drug design with protein targets.

Advances in protein chemistry and structural biology Dec 18, 2019
Structure based drug designing is an important endeavor in the field of structural bioinformatics. Previously the entire process was dependent on the wet-lab experiments to build libraries of ligand molecules. And the molecules used to be tested to d...
Anti-HIV Agents Binding Sites Protein Binding Proteins Thermodynamics Anti-Bacterial Agents Computational Biology Structure-Activity Relationship Drugs, Investigational Molecular Docking Simulation Neuroprotective Agents Drug Design Molecular Dynamics Simulation Humans Antineoplastic Agents Ligands Machine Learning
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MathDL: mathematical deep learning for D3R Grand Challenge 4.

Journal of computer-aided molecular design Nov 16, 2019
We present the performances of our mathematical deep learning (MathDL) models for D3R Grand Challenge 4 (GC4). This challenge involves pose prediction, affinity ranking, and free energy estimation for beta secretase 1 (BACE) as well as affinity ranki...
Cathepsins Aspartic Acid Endopeptidases Binding Sites Thermodynamics Small Molecule Libraries Protein Binding Humans Ligands Molecular Docking Simulation Amyloid Precursor Protein Secretases Drug Design Deep Learning
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Exploring fragment-based target-specific ranking protocol with machine learning on cathepsin S.

Journal of computer-aided molecular design Nov 15, 2019
Cathepsin S (CatS), a member of cysteine cathepsin proteases, has been well studied due to its significant role in many pathological processes, including arthritis, cancer and cardiovascular diseases. CatS inhibitors have been included in D3R-GC3 for...
Binding Sites Thermodynamics Cathepsins Ligands Crystallography, X-Ray Protein Conformation Humans Machine Learning Molecular Docking Simulation Computer-Aided Design Protein Binding Databases, Protein
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Identifying Cancer-Specific circRNA-RBP Binding Sites Based on Deep Learning.

Molecules (Basel, Switzerland) Nov 7, 2019
Circular RNAs (circRNAs) are extensively expressed in cells and tissues, and play crucial roles in human diseases and biological processes. Recent studies have reported that circRNAs could function as RNA binding protein (RBP) sponges, meanwhile RBPs...
Humans Neoplasm Proteins Binding Sites Sequence Analysis, Protein RNA, Neoplasm Neoplasms Deep Learning RNA-Binding Proteins Databases, Protein RNA, Circular
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Recognizing five molecular ligand-binding sites with similar chemical structure.

Journal of computational chemistry Oct 23, 2019
Accurate identification of ligand-binding sites and discovering the protein-ligand interaction mechanism are important for understanding proteins' functions and designing new drugs. Meanwhile, accurate computational prediction and mechanism research ...
Support Vector Machine Ligands Proteins Adenosine Diphosphate Binding Sites NAD Guanosine Diphosphate Adenosine Triphosphate Guanosine Triphosphate
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Graph Convolutional Neural Networks for Predicting Drug-Target Interactions.

Journal of chemical information and modeling Oct 16, 2019
Accurate determination of target-ligand interactions is crucial in the drug discovery process. In this paper, we propose a graph-convolutional (Graph-CNN) framework for predicting protein-ligand interactions. First, we built an unsupervised graph-aut...
Ligands Databases, Chemical Protein Conformation Binding Sites Neural Networks, Computer Drug Discovery Protein Binding Drug Development Proteins
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econvRBP: Improved ensemble convolutional neural networks for RNA binding protein prediction directly from sequence.

Methods (San Diego, Calif.) Sep 9, 2019
RNA binding proteins (RBPs) determine RNA process from synthesis to decay, which play a key role in RNA transport, translation and degradation. Therefore, exploring RBPs' function from the amino acid sequence using computational methods has become on...
Deep Learning Computational Biology RNA-Binding Proteins Sequence Analysis, Protein Amino Acid Sequence RNA Datasets as Topic Binding Sites
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Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints.

Nature communications Sep 4, 2019
The inapplicability of amino acid covariation methods to small protein families has limited their use for structural annotation of whole genomes. Recently, deep learning has shown promise in allowing accurate residue-residue contact prediction even f...
Binding Sites Proteomics Proteome Models, Molecular Protein Conformation Animals Humans Deep Learning Computational Biology Algorithms Reproducibility of Results
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Boosting phosphorylation site prediction with sequence feature-based machine learning.

Proteins Aug 22, 2019
Protein phosphorylation is one of the essential posttranslation modifications playing a vital role in the regulation of many fundamental cellular processes. We propose a LightGBM-based computational approach that uses evolutionary, geometric, sequenc...
Threonine Binding Sites Serine Sequence Analysis, Protein Proteins Models, Molecular Humans Reproducibility of Results Databases, Protein Protein Conformation Animals Machine Learning Phosphorylation Species Specificity Computational Biology Algorithms Tyrosine Protein Processing, Post-Translational
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