AIMC Topic: Amino Acid Sequence

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An interpretable deep learning model for classifying adaptor protein complexes from sequence information.

Methods (San Diego, Calif.) Sep 26, 2022
Adaptor proteins (APs) are a family of proteins that aids in intracellular membrane trafficking, and their impairments or defects are closely related to various disorders. Traditional methods to identify and classify APs require time and complex tech...
Machine Learning Algorithms Neural Networks, Computer Amino Acid Sequence Deep Learning Proteins
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Discovering design principles of collagen molecular stability using a genetic algorithm, deep learning, and experimental validation.

Proceedings of the National Academy of Sciences of the United States of America Sep 26, 2022
Collagen is the most abundant structural protein in humans, providing crucial mechanical properties, including high strength and toughness, in tissues. Collagen-based biomaterials are, therefore, used for tissue repair and regeneration. Utilizing col...
Humans Biocompatible Materials Molecular Dynamics Simulation Deep Learning Amino Acid Sequence Collagen
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Graph Neural Network for Protein-Protein Interaction Prediction: A Comparative Study.

Molecules (Basel, Switzerland) Sep 19, 2022
Proteins are the fundamental biological macromolecules which underline practically all biological activities. Protein-protein interactions (PPIs), as they are known, are how proteins interact with other proteins in their environment to perform biolog...
Amino Acid Sequence Neural Networks, Computer Proteins
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Robust deep learning-based protein sequence design using ProteinMPNN.

Science (New York, N.Y.) Sep 15, 2022
Although deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here, we describe a deep learning-based pro...
Proteins Amino Acid Sequence Deep Learning Protein Engineering Crystallography, X-Ray Cryoelectron Microscopy Protein Conformation
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Protein secondary structure assignment using residual networks.

Journal of molecular modeling Aug 23, 2022
Proteins are constructed from amino acid sequences. Their structural classifications include primary, secondary, tertiary, and quaternary, with tertiary and quaternary structures influencing protein function. Because a protein's structure is inextric...
Neural Networks, Computer Amino Acid Sequence Computational Biology Humans Protein Structure, Secondary Algorithms Proteins
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A deep learning method for predicting molecular properties and compound-protein interactions.

Journal of molecular graphics & modelling Aug 17, 2022
Predicting molecular properties and compound-protein interactions (CPIs) are two important areas of drug design and discovery. They are also an essential way to discover lead compounds in virtual screening. Recently, in silico methods based on deep l...
Amino Acid Sequence Tumor Suppressor Protein p53 Animals Caenorhabditis elegans Humans Deep Learning
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NanoNet: Rapid and accurate end-to-end nanobody modeling by deep learning.

Frontiers in immunology Aug 12, 2022
Antibodies are a rapidly growing class of therapeutics. Recently, single domain camelid VHH antibodies, and their recognition nanobody domain (Nb) appeared as a cost-effective highly stable alternative to full-length antibodies. There is a growing ne...
Antibodies Amino Acid Sequence Single-Domain Antibodies Complementarity Determining Regions Deep Learning
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Transformer Neural Networks for Protein Family and Interaction Prediction Tasks.

Journal of computational biology : a journal of computational molecular cell biology Aug 10, 2022
The scientific community is rapidly generating protein sequence information, but only a fraction of these proteins can be experimentally characterized. While promising deep learning approaches for protein prediction tasks have emerged, they have comp...
Amino Acid Sequence Proteins Neural Networks, Computer
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IDRBP-PPCT: Identifying Nucleic Acid-Binding Proteins Based on Position-Specific Score Matrix and Position-Specific Frequency Matrix Cross Transformation.

IEEE/ACM transactions on computational biology and bioinformatics Aug 8, 2022
DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) are two important nucleic acid-binding proteins (NABPs), which play important roles in biological processes such as replication, translation and transcription of genetic material. Some prote...
Support Vector Machine Databases, Protein RNA-Binding Proteins Amino Acid Sequence Position-Specific Scoring Matrices Algorithms DNA Computational Biology DNA-Binding Proteins
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ppdx: Automated modeling of protein-protein interaction descriptors for use with machine learning.

Journal of computational chemistry Aug 5, 2022
This paper describes ppdx, a python workflow tool that combines protein sequence alignment, homology modeling, and structural refinement, to compute a broad array of descriptors for characterizing protein-protein interactions. The descriptors can be ...
Software Protein Binding Proteins Amino Acid Sequence Machine Learning
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