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Molecular Docking Simulation

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Deep Learning and Random Forest Approach for Finding the Optimal Traditional Chinese Medicine Formula for Treatment of Alzheimer's Disease.

Journal of chemical information and modeling Apr 2, 2019
It has demonstrated that glycogen synthase kinase 3β (GSK3β) is related to Alzheimer's disease (AD). On the basis of the world largest traditional Chinese medicine (TCM) database, a network-pharmacology-based approach was utilized to investigate TCM ...
Molecular Docking Simulation Support Vector Machine Medicine, Chinese Traditional Deep Learning Protein Interaction Maps Molecular Dynamics Simulation Protein Conformation Alzheimer Disease Computational Biology Databases, Pharmaceutical Drug Compounding Glycogen Synthase Kinase 3 Quantitative Structure-Activity Relationship
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Automated discovery of GPCR bioactive ligands.

Current opinion in structural biology Mar 23, 2019
While G-protein-coupled receptors (GPCRs) constitute the largest class of membrane proteins, structures and endogenous ligands of a large portion of GPCRs remain unknown. Because of the involvement of GPCRs in various signaling pathways and physiolog...
Molecular Dynamics Simulation Ligands Protein Conformation Drug Design Humans Drug Discovery Machine Learning Receptors, G-Protein-Coupled Molecular Docking Simulation
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IVS2vec: A tool of Inverse Virtual Screening based on word2vec and deep learning techniques.

Methods (San Diego, Calif.) Mar 22, 2019
Inverse Virtual Screening is a powerful technique in the early stage of drug discovery process. This technique can provide important clues for biologically active molecules, which is useful in the following researches of durg discovery. In this work,...
User-Computer Interface Proteins Protein Conformation Databases, Factual Molecular Docking Simulation Deep Learning Software Algorithms
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Improved Method of Structure-Based Virtual Screening via Interaction-Energy-Based Learning.

Journal of chemical information and modeling Mar 18, 2019
Virtual screening is a promising method for obtaining novel hit compounds in drug discovery. It aims to enrich potentially active compounds from a large chemical library for further biological experiments. However, the accuracy of current virtual scr...
Ligands User-Computer Interface Protein Conformation Cheminformatics Proteins Thermodynamics Drug Evaluation, Preclinical Machine Learning Molecular Docking Simulation
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The Development of Target-Specific Machine Learning Models as Scoring Functions for Docking-Based Target Prediction.

Journal of chemical information and modeling Mar 18, 2019
The identification of possible targets for a known bioactive compound is of the utmost importance for drug design and development. Molecular docking is one possible approach for in-silico protein target prediction, whereas a molecule is docked into s...
Protein Conformation Molecular Docking Simulation Computational Biology Support Vector Machine Neural Networks, Computer Machine Learning
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Predicting protein-peptide interaction sites using distant protein complexes as structural templates.

Scientific reports Mar 12, 2019
Protein-peptide interactions play an important role in major cellular processes, and are associated with several human diseases. To understand and potentially regulate these cellular function and diseases it is important to know the molecular details...
Peptides Molecular Docking Simulation Protein Binding Computational Biology Humans Amino Acid Sequence Cluster Analysis Protein Interaction Mapping Datasets as Topic Machine Learning Proteins Binding Sites Software
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A combined drug discovery strategy based on machine learning and molecular docking.

Chemical biology & drug design Mar 7, 2019
Data mining methods based on machine learning play an increasingly important role in drug design and discovery. In the current work, eight machine learning methods including decision trees, k-Nearest neighbor, support vector machines, random forests,...
Area Under Curve Inhibitory Concentration 50 Crystallography, X-Ray Binding Sites Protein Structure, Tertiary Machine Learning Drug Discovery Databases, Factual ROC Curve Molecular Docking Simulation Principal Component Analysis
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In Need of Bias Control: Evaluating Chemical Data for Machine Learning in Structure-Based Virtual Screening.

Journal of chemical information and modeling Mar 5, 2019
Reports of successful applications of machine learning (ML) methods in structure-based virtual screening (SBVS) are increasing. ML methods such as convolutional neural networks show promising results and often outperform traditional methods such as e...
Retrospective Studies Ligands Molecular Docking Simulation Machine Learning Structure-Activity Relationship Molecular Structure Databases, Factual Bias Benchmarking
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De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping.

Journal of chemical information and modeling Mar 5, 2019
Here we show that Generative Topographic Mapping (GTM) can be used to explore the latent space of the SMILES-based autoencoders and generate focused molecular libraries of interest. We have built a sequence-to-sequence neural network with Bidirection...
Molecular Docking Simulation Drug Design Catalytic Domain Small Molecule Libraries Receptor, Adenosine A2A Deep Learning Drug Evaluation, Preclinical Ligands
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Machine Learning Consensus To Predict the Binding to the Androgen Receptor within the CoMPARA Project.

Journal of chemical information and modeling Feb 11, 2019
The nuclear androgen receptor (AR) is one of the most relevant biological targets of Endocrine Disrupting Chemicals (EDCs), which produce adverse effects by interfering with hormonal regulation and endocrine system functioning. This paper describes n...
Humans Androgen Receptor Antagonists Molecular Docking Simulation Machine Learning Drug Discovery Software Receptors, Androgen Protein Binding Endocrine Disruptors Androgens
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