AIMC Topic: Protein Conformation

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Machine learning and docking models for Mycobacterium tuberculosis topoisomerase I.

Tuberculosis (Edinburgh, Scotland) Jan 20, 2017
There is a shortage of compounds that are directed towards new targets apart from those targeted by the FDA approved drugs used against Mycobacterium tuberculosis. Topoisomerase I (Mttopo I) is an essential mycobacterial enzyme and a promising target...
Drug Design Dose-Response Relationship, Drug Structure-Activity Relationship Bayes Theorem Humans Machine Learning Molecular Docking Simulation Computer-Aided Design Topoisomerase I Inhibitors Molecular Targeted Therapy Protein Conformation Mycobacterium smegmatis DNA Topoisomerases, Type I Antitubercular Agents Tuberculosis Mycobacterium tuberculosis
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A machine learning approach for ranking clusters of docked protein-protein complexes by pairwise cluster comparison.

Proteins Jan 20, 2017
Reliable identification of near-native poses of docked protein-protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein-protein interactions is challenging for traditional biophysical or knowledge based potentials and th...
Research Design Molecular Docking Simulation Protein Binding Computational Biology Machine Learning Software Binding Sites Thermodynamics Protein Interaction Mapping Structural Homology, Protein Cluster Analysis Proteins Benchmarking Protein Conformation
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Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.

PLoS computational biology Jan 5, 2017
MOTIVATION: Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predict...
Sequence Analysis, Protein Neural Networks, Computer Machine Learning Algorithms Computational Biology Proteins Databases, Protein Protein Conformation
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Prediction of HIV-1 protease cleavage site using a combination of sequence, structural, and physicochemical features.

BMC bioinformatics Dec 23, 2016
BACKGROUND: The human immunodeficiency virus type 1 (HIV-1) aspartic protease is an important enzyme owing to its imperative part in viral development and a causative agent of deadliest disease known as acquired immune deficiency syndrome (AIDS). Dev...
Data Accuracy HIV Protease Protein Conformation Substrate Specificity Neural Networks, Computer Humans Decision Trees Algorithms Amino Acid Sequence HIV Infections Computational Biology HIV-1
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Predicting protein conformational changes for unbound and homology docking: learning from intrinsic and induced flexibility.

Proteins Dec 5, 2016
Predicting protein conformational changes from unbound structures or even homology models to bound structures remains a critical challenge for protein docking. Here we present a study directly addressing the challenge by reducing the dimensionality a...
Binding Sites Thermodynamics Protein Multimerization Structural Homology, Protein Benchmarking Protein Conformation Dimensional Measurement Accuracy Software Research Design Molecular Docking Simulation Protein Binding Computational Biology Models, Statistical Proteins Machine Learning
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A Graph Approach to Mining Biological Patterns in the Binding Interfaces.

Journal of computational biology : a journal of computational molecular cell biology Nov 28, 2016
Protein-RNA interactions play important roles in the biological systems. Searching for regular patterns in the Protein-RNA binding interfaces is important for understanding how protein and RNA recognize each other and bind to form a complex. Herein, ...
Computer Graphics Amino Acid Motifs Protein Interaction Domains and Motifs RNA Protein Conformation Binding Sites Animals Molecular Docking Simulation Protein Binding Humans RNA-Binding Proteins Computational Biology Support Vector Machine Proteins Data Mining
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Machine Learning Approaches for Predicting Protein Complex Similarity.

Journal of computational biology : a journal of computational molecular cell biology Oct 17, 2016
Discriminating native-like structures from false positives with high accuracy is one of the biggest challenges in protein-protein docking. While there is an agreement on the existence of a relationship between various favorable intermolecular interac...
Humans Neural Networks, Computer Protein Binding Machine Learning Proteins Protein Conformation Animals Molecular Docking Simulation
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Correcting the impact of docking pose generation error on binding affinity prediction.

BMC bioinformatics Sep 22, 2016
BACKGROUND: Pose generation error is usually quantified as the difference between the geometry of the pose generated by the docking software and that of the same molecule co-crystallised with the considered protein. Surprisingly, the impact of this e...
Ligands Protein Conformation Protein Binding Humans Nuclear Proteins Software Transcription Factors Molecular Docking Simulation Pyrazines
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Molecular Properties of Drugs Interacting with SLC22 Transporters OAT1, OAT3, OCT1, and OCT2: A Machine-Learning Approach.

The Journal of pharmacology and experimental therapeutics Aug 3, 2016
Statistical analysis was performed on physicochemical descriptors of ∼250 drugs known to interact with one or more SLC22 "drug" transporters (i.e., SLC22A6 or OAT1, SLC22A8 or OAT3, SLC22A1 or OCT1, and SLC22A2 or OCT2), followed by application of ma...
Protein Conformation Models, Molecular Substrate Specificity Machine Learning Organic Anion Transporters, Sodium-Independent Organic Anion Transport Protein 1 Protein Binding Pharmaceutical Preparations Organic Cation Transporter 1 Computational Biology Hydrogen-Ion Concentration Membrane Transport Proteins
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Adaptive local learning in sampling based motion planning for protein folding.

BMC systems biology Aug 1, 2016
BACKGROUND: Simulating protein folding motions is an important problem in computational biology. Motion planning algorithms, such as Probabilistic Roadmap Methods, have been successful in modeling the folding landscape. Probabilistic Roadmap Methods ...
Machine Learning Protein Conformation Computational Biology Thermodynamics Proteins Movement Models, Molecular Protein Folding
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