AIMC Topic: Proteins

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Protein-Protein Interface Topology as a Predictor of Secondary Structure and Molecular Function Using Convolutional Deep Learning.

Journal of chemical information and modeling Jul 6, 2021
To power the specific recognition and binding of protein partners into functional complexes, a wealth of information about the structure and function of the partners is necessarily encoded into the global shape of protein-protein interfaces and their...
Deep Learning Proteins Protein Structure, Secondary Neural Networks, Computer
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Physics-based protein structure refinement in the era of artificial intelligence.

Proteins Jun 29, 2021
Protein structure refinement is the last step in protein structure prediction pipelines. Physics-based refinement via molecular dynamics (MD) simulations has made significant progress during recent years. During CASP14, we tested a new refinement pro...
Artificial Intelligence Computational Biology Proteins Software Protein Conformation Molecular Dynamics Simulation Physical Phenomena Markov Chains
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Predicting aptamer sequences that interact with target proteins using an aptamer-protein interaction classifier and a Monte Carlo tree search approach.

PloS one Jun 25, 2021
Oligonucleotide-based aptamers, which have a three-dimensional structure with a single-stranded fragment, feature various characteristics with respect to size, toxicity, and permeability. Accordingly, aptamers are advantageous in terms of diagnosis a...
Sequence Analysis, RNA Molecular Docking Simulation Proteins Monte Carlo Method Machine Learning Models, Chemical Aptamers, Nucleotide Computer Simulation
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TopDomain: Exhaustive Protein Domain Boundary Metaprediction Combining Multisource Information and Deep Learning.

Journal of chemical theory and computation Jun 23, 2021
Protein domains are independent, functional, and stable structural units of proteins. Accurate protein domain boundary prediction plays an important role in understanding protein structure and evolution, as well as for protein structure prediction. C...
Protein Conformation Algorithms Proteins Protein Domains Deep Learning Computational Biology
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Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations.

Cell reports methods Jun 21, 2021
Structure prediction for proteins lacking homologous templates in the Protein Data Bank (PDB) remains a significant unsolved problem. We developed a protocol, C-I-TASSER, to integrate interresidue contact maps from deep neural-network learning with t...
Models, Molecular Humans Computational Biology SARS-CoV-2 COVID-19 Protein Conformation Proteins Algorithms Deep Learning
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Predicting Drug-Target Interactions with Deep-Embedding Learning of Graphs and Sequences.

The journal of physical chemistry. A Jun 18, 2021
Computational approaches for predicting drug-target interactions (DTIs) play an important role in drug discovery since conventional screening experiments are time-consuming and expensive. In this study, we proposed end-to-end representation learning ...
Computer Graphics Deep Learning Computational Biology Drug Discovery Pharmaceutical Preparations Proteins Amino Acid Sequence
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Prediction of drug efficacy from transcriptional profiles with deep learning.

Nature biotechnology Jun 17, 2021
Drug discovery focused on target proteins has been a successful strategy, but many diseases and biological processes lack obvious targets to enable such approaches. Here, to overcome this challenge, we describe a deep learning-based efficacy predicti...
Deep Learning Mice Drug Repositioning Proteins Drug Discovery Transcriptome Animals
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Multi-labelled proteins recognition for high-throughput microscopy images using deep convolutional neural networks.

BMC bioinformatics Jun 15, 2021
BACKGROUND: Proteins are of extremely vital importance in the human body, and no movement or activity can be performed without proteins. Currently, microscopy imaging technologies developed rapidly are employed to observe proteins in various cells an...
Proteins Microscopy Neural Networks, Computer Image Processing, Computer-Assisted Humans
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PANDA: Predicting the change in proteins binding affinity upon mutations by finding a signal in primary structures.

Journal of bioinformatics and computational biology Jun 11, 2021
Accurately determining a change in protein binding affinity upon mutations is important to find novel therapeutics and to assist mutagenesis studies. Determination of change in binding affinity upon mutations requires sophisticated, expensive, and ti...
Machine Learning Mutation Amino Acid Sequence Protein Binding Proteins
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Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review.

Molecular diversity Jun 10, 2021
Artificial intelligence (AI) renders cutting-edge applications in diverse sectors of society. Due to substantial progress in high-performance computing, the development of superior algorithms, and the accumulation of huge biological and chemical data...
Humans Data Mining Protein Interaction Mapping Protein Folding Models, Molecular Workflow Big Data Databases, Pharmaceutical Protein Binding Proteins Structure-Activity Relationship Models, Theoretical Artificial Intelligence Drug Design Algorithms Drug Discovery
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