AI Medical Compendium Journal:
Journal of molecular graphics & modelling

Showing 31 to 40 of 42 articles

OctSurf: Efficient hierarchical voxel-based molecular surface representation for protein-ligand affinity prediction.

Journal of molecular graphics & modelling Feb 9, 2021
Voxel-based 3D convolutional neural networks (CNNs) have been applied to predict protein-ligand binding affinity. However, the memory usage and computation cost of these voxel-based approaches increase cubically with respect to spatial resolution and...
Protein Binding Proteins Ligands Neural Networks, Computer
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Machine learning transition temperatures from 2D structure.

Journal of molecular graphics & modelling Jan 29, 2021
A priori knowledge of physicochemical properties such as melting and boiling could expedite materials discovery. However, theoretical modeling from first principles poses a challenge for efficient virtual screening of potential candidates. As an alte...
Machine Learning Software Quantitative Structure-Activity Relationship Transition Temperature Thermodynamics
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Performance comparison of wavelet neural network and adaptive neuro-fuzzy inference system with small data sets.

Journal of molecular graphics & modelling Jul 24, 2020
In this work, performance of wavelet neural network (WNN) and adaptive neuro-fuzzy inference system (ANFIS) models were compared with small data sets by different criteria such as second order corrected Akaike information criterion (AICc), Bayesian i...
Fuzzy Logic Bayes Theorem Neural Networks, Computer
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Learning-to-rank technique based on ignoring meaningless ranking orders between compounds.

Journal of molecular graphics & modelling Jul 24, 2019
Learning-to-rank, which is a machine-learning technique for information retrieval, was recently introduced to ligand-based virtual screening to reduce the costs of developing a new drug. The quality of a rank prediction model depends on experimental ...
Machine Learning Algorithms Drug Discovery Humans Models, Theoretical
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Prediction of ATP-binding sites in membrane proteins using a two-dimensional convolutional neural network.

Journal of molecular graphics & modelling Jul 15, 2019
Membrane proteins, the most important drug targets, account for around 30% of total proteins encoded by the genome of living organisms. An important role of these proteins is to bind adenosine triphosphate (ATP), facilitating crucial biological proce...
Algorithms Reproducibility of Results ROC Curve Neural Networks, Computer Machine Learning Adenosine Triphosphate Binding Sites Amino Acid Motifs Web Browser Models, Theoretical Position-Specific Scoring Matrices Databases, Protein Amino Acid Sequence Computational Biology Membrane Proteins
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Discovery of small molecule binders of human FSHR(TMD) with novel structural scaffolds by integrating structural bioinformatics and machine learning algorithms.

Journal of molecular graphics & modelling Mar 5, 2019
BACKGROUND: The activation of follicle stimulating hormone receptor (FSHR) by FSH and the consequent downstream signaling activities are crucial for reproductive health. The role of FSHR in tumor progression as well as osteoporosis advancement has al...
Computers, Molecular Ligands Hydrophobic and Hydrophilic Interactions Quantitative Structure-Activity Relationship Receptors, FSH Binding Sites Humans Computational Biology Machine Learning Drug Design Cell Line Models, Molecular Protein Binding
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Visualizing convolutional neural network protein-ligand scoring.

Journal of molecular graphics & modelling Jun 18, 2018
Protein-ligand scoring is an important step in a structure-based drug design pipeline. Selecting a correct binding pose and predicting the binding affinity of a protein-ligand complex enables effective virtual screening. Machine learning techniques c...
Proteins Models, Molecular Deep Learning Ligands Neural Networks, Computer Molecular Conformation ROC Curve Algorithms Protein Binding
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Prediction of lysine propionylation sites using biased SVM and incorporating four different sequence features into Chou's PseAAC.

Journal of molecular graphics & modelling Jul 25, 2017
Lysine propionylation is an important and common protein acylation modification in both prokaryotes and eukaryotes. To better understand the molecular mechanism of propionylation, it is important to identify propionylated substrates and their corresp...
Amino Acids Amino Acid Sequence Acetylation Lysine Position-Specific Scoring Matrices Computational Biology Support Vector Machine Protein Processing, Post-Translational Reproducibility of Results Peptides Algorithms
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Chemogenomics knowledgebase and systems pharmacology for hallucinogen target identification-Salvinorin A as a case study.

Journal of molecular graphics & modelling Aug 8, 2016
Drug abuse is a serious problem worldwide. Recently, hallucinogens have been reported as a potential preventative and auxiliary therapy for substance abuse. However, the use of hallucinogens as a drug abuse treatment has potential risks, as the funda...
Reproducibility of Results Genomics Databases, Chemical Diterpenes, Clerodane Models, Molecular Knowledge Bases Hallucinogens
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Highly predictive support vector machine (SVM) models for anthrax toxin lethal factor (LF) inhibitors.

Journal of molecular graphics & modelling Nov 17, 2015
Anthrax is a highly lethal, acute infectious disease caused by the rod-shaped, Gram-positive bacterium Bacillus anthracis. The anthrax toxin lethal factor (LF), a zinc metalloprotease secreted by the bacilli, plays a key role in anthrax pathogenesis ...
Bacillus anthracis Small Molecule Libraries Antidotes Models, Chemical Models, Statistical User-Computer Interface Databases, Chemical High-Throughput Screening Assays Predictive Value of Tests Support Vector Machine Bacterial Toxins Structure-Activity Relationship Antigens, Bacterial
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