AIMC Topic: Protein Conformation

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MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

Journal of molecular biology Mar 10, 2018
Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO,...
Sequence Homology, Amino Acid Sequence Analysis, Protein Amino Acid Sequence Protein Conformation Gene Ontology Protein Interaction Mapping Software Algorithms Reproducibility of Results Protein Interaction Maps Computational Biology Proteins Models, Molecular Internet
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Probing light chain mutation effects on thrombin via molecular dynamics simulations and machine learning.

Journal of biomolecular structure & dynamics Mar 2, 2018
Thrombin is a key component for chemotherapeutic and antithrombotic therapy development. As the physiologic and pathologic roles of the light chain still remain vague, here, we continue previous efforts to understand the impacts of the disease-associ...
Humans Machine Learning Protein Conformation Hydrogen Bonding Thrombin Allosteric Regulation Protein Binding Mutation Molecular Dynamics Simulation Sodium
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Using Chou's general PseAAC to analyze the evolutionary relationship of receptor associated proteins (RAP) with various folding patterns of protein domains.

Journal of theoretical biology Feb 22, 2018
The receptor-associated protein (RAP) is an inhibitor of endocytic receptors that belong to the lipoprotein receptor gene family. In this study, a computational approach was tried to find the evolutionarily related fold of the RAP proteins. Through t...
Databases, Protein Structure-Activity Relationship Models, Molecular Protein Conformation Computational Biology Support Vector Machine Carrier Proteins Evolution, Molecular
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Gene-Specific Variant Classifier (DPYD-Varifier) to Identify Deleterious Alleles of Dihydropyrimidine Dehydrogenase.

Clinical pharmacology and therapeutics Feb 2, 2018
Deleterious variants in dihydropyrimidine dehydrogenase (DPD, DPYD gene) can be highly predictive of clinical toxicity to the widely prescribed chemotherapeutic 5-fluorouracil (5-FU). However, there are very limited data pertaining to the functional ...
Computer Simulation Risk Assessment Pharmacogenetics Genotype Humans Machine Learning Models, Molecular Fluorouracil Inhibitory Concentration 50 HCT116 Cells Dose-Response Relationship, Drug Cell Survival Predictive Value of Tests Structure-Activity Relationship Mutation, Missense Dihydrouracil Dehydrogenase (NADP) Pharmacogenomic Testing Pharmacogenomic Variants HEK293 Cells Gene Frequency Protein Conformation Antimetabolites, Antineoplastic
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PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

Journal of theoretical biology Feb 1, 2018
Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been s...
Protein Conformation Sequence Analysis, Protein Machine Learning Software Databases, Protein Catalysis
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Predicting the Effect of Single and Multiple Mutations on Protein Structural Stability.

Molecules (Basel, Switzerland) Jan 27, 2018
Predicting how a point mutation alters a protein's stability can guide pharmaceutical drug design initiatives which aim to counter the effects of serious diseases. Conducting mutagenesis studies in physical proteins can give insights about the effect...
Amino Acid Substitution Thermodynamics Proteins Mutation Protein Stability Protein Conformation Neural Networks, Computer Computer Simulation Support Vector Machine Decision Trees
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Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition.

Journal of chemical information and modeling Jan 10, 2018
Inspired by natural language processing techniques, we here introduce Mol2vec, which is an unsupervised machine learning approach to learn vector representations of molecular substructures. Like the Word2vec models, where vectors of closely related w...
Models, Chemical Datasets as Topic Protein Conformation Algorithms Reproducibility of Results Proteins Unsupervised Machine Learning Natural Language Processing Molecular Structure
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New insights into the efficiency of thymol synergistic effect with p-cymene in inhibiting advanced glycation end products: A multi-way analysis based on spectroscopic and electrochemical methods in combination with molecular docking study.

Journal of pharmaceutical and biomedical analysis Dec 24, 2017
Protein glycation in the body is one of the main reasons of diabetes complications. The electrochemical studies on the inhibitory mechanism of glycation are rather scarce. Thus, it is important to investigate the role of electrochemistry in the glyca...
Kinetics Hypoglycemic Agents Drug Synergism Protein Processing, Post-Translational Monoterpenes Structure-Activity Relationship Arginine Electrochemical Techniques Spectrophotometry, Ultraviolet Protein Conformation Molecular Docking Simulation Lysine Cymenes Protein Binding Serum Albumin, Bovine Glycosylation Glycation End Products, Advanced Thymol Binding Sites
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Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks.

Cell systems Dec 20, 2017
While genes are defined by sequence, in biological systems a protein's function is largely determined by its three-dimensional structure. Evolutionary information embedded within multiple sequence alignments provides a rich source of data for inferri...
Protein Folding Sequence Alignment Humans Neural Networks, Computer Machine Learning Algorithms Databases, Protein Models, Molecular Probability Protein Conformation Forecasting Animals Computational Biology Proteins
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Protein structure modeling and refinement by global optimization in CASP12.

Proteins Dec 5, 2017
For protein structure modeling in the CASP12 experiment, we have developed a new protocol based on our previous CASP11 approach. The global optimization method of conformational space annealing (CSA) was applied to 3 stages of modeling: multiple sequ...
Proteins Models, Molecular Molecular Dynamics Simulation Crystallography, X-Ray Protein Conformation Protein Folding Sequence Analysis, Protein Protein Interaction Domains and Motifs Algorithms Computational Biology Support Vector Machine Models, Statistical Humans Machine Learning
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