AIMC Topic: Protein Domains

Clear Filters Showing 21 to 30 of 77 articles

Protein sequence design with a learned potential.

Nature communications Feb 8, 2022
The task of protein sequence design is central to nearly all rational protein engineering problems, and enormous effort has gone into the development of energy functions to guide design. Here, we investigate the capability of a deep neural network mo...
Computer Simulation Deep Learning Crystallography, X-Ray Protein Engineering Protein Folding Models, Molecular Protein Domains Amino Acid Sequence
View on PubMed DOI

Protein Design with Deep Learning.

International journal of molecular sciences Oct 29, 2021
Computational Protein Design (CPD) has produced impressive results for engineering new proteins, resulting in a wide variety of applications. In the past few years, various efforts have aimed at replacing or improving existing design methods using De...
Proteins Protein Domains Protein Engineering Deep Learning Computational Biology
View on PubMed DOI

iMPT-FDNPL: Identification of Membrane Protein Types with Functional Domains and a Natural Language Processing Approach.

Computational and mathematical methods in medicine Oct 11, 2021
Membrane protein is an important kind of proteins. It plays essential roles in several cellular processes. Based on the intramolecular arrangements and positions in a cell, membrane proteins can be divided into several types. It is reported that the ...
Databases, Protein Computational Biology Humans Natural Language Processing Membrane Proteins Protein Domains Support Vector Machine Algorithms
View on PubMed DOI

MANORAA: A machine learning platform to guide protein-ligand design by anchors and influential distances.

Structure (London, England : 1993) Oct 5, 2021
The MANORAA platform uses structure-based approaches to provide information on drug design originally derived from mapping tens of thousands of amino acids on a grid. In-depth analyses of the pockets, frequently occurring atoms, influential distances...
Tetrahydrofolate Dehydrogenase Ligands Crystallography, X-Ray Protein Binding Trimethoprim Computational Biology Proteins Databases, Protein COVID-19 Models, Molecular SARS-CoV-2 Humans Protein Domains Drug Design Machine Learning Pandemics
View on PubMed DOI

A deep-learning framework for multi-level peptide-protein interaction prediction.

Nature communications Sep 15, 2021
Peptide-protein interactions are involved in various fundamental cellular functions and their identification is crucial for designing efficacious peptide therapeutics. Recently, a number of computational methods have been developed to predict peptide...
Proteins Models, Molecular Protein Domains Deep Learning Protein Binding Computational Biology Binding Sites Algorithms Reproducibility of Results Peptides
View on PubMed DOI

Prediction of Protein Solubility Based on Sequence Feature Fusion and DDcCNN.

Interdisciplinary sciences, computational life sciences Jul 8, 2021
BACKGROUND: Prediction of protein solubility is an indispensable prerequisite for pharmaceutical research and production. The general and specific objective of this work is to design a new model for predicting protein solubility by using protein sequ...
Protein Domains Amino Acid Sequence Solubility Neural Networks, Computer Proteins
View on PubMed DOI

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 Proteins Algorithms Protein Domains Deep Learning Computational Biology
View on PubMed DOI

Improving protein domain classification for third-generation sequencing reads using deep learning.

BMC genomics Apr 9, 2021
BACKGROUND: With the development of third-generation sequencing (TGS) technologies, people are able to obtain DNA sequences with lengths from 10s to 100s of kb. These long reads allow protein domain annotation without assembly, thus can produce impor...
Sequence Analysis, DNA Protein Domains High-Throughput Nucleotide Sequencing Humans Software Algorithms Deep Learning
View on PubMed DOI

Characterizing the function of domain linkers in regulating the dynamics of multi-domain fusion proteins by microsecond molecular dynamics simulations and artificial intelligence.

Proteins Mar 27, 2021
Multi-domain proteins are not only formed through natural evolution but can also be generated by recombinant DNA technology. Because many fusion proteins can enhance the selectivity of cell targeting, these artificially produced molecules, called mul...
Protein Domains Amino Acids Benchmarking Molecular Dynamics Simulation Recombinant Fusion Proteins Protein Engineering Artificial Intelligence Computational Biology Gene Expression Humans Pliability Mutagenesis, Insertional
View on PubMed DOI

DeepCys: Structure-based multiple cysteine function prediction method trained on deep neural network: Case study on domains of unknown functions belonging to COX2 domains.

Proteins Feb 22, 2021
Cysteine (Cys) is the most reactive amino acid participating in a wide range of biological functions. In-silico predictions complement the experiments to meet the need of functional characterization. Multiple Cys function prediction algorithm is scar...
Amino Acid Sequence Sulfides Glutathione Structure-Activity Relationship Models, Molecular Nitroso Compounds Protein Domains Cations, Divalent Software Sulfinic Acids Disulfides Protein Structure, Secondary Deep Learning Sulfonic Acids Electron Transport Complex IV Protein Processing, Post-Translational Cysteine
View on PubMed DOI
Popular Topics
Recent Journals