AIMC Topic: Molecular Conformation

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Deep Learning for Novel Antimicrobial Peptide Design.

Biomolecules Mar 22, 2021
Antimicrobial resistance is an increasing issue in healthcare as the overuse of antibacterial agents rises during the COVID-19 pandemic. The need for new antibiotics is high, while the arsenal of available agents is decreasing, especially for the tre...
ROC Curve Escherichia coli Area Under Curve Machine Learning Deep Learning Molecular Conformation Protein Conformation, alpha-Helical Pore Forming Cytotoxic Proteins Bayes Theorem Amino Acid Sequence
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In silico design of novel aptamers utilizing a hybrid method of machine learning and genetic algorithm.

Molecular diversity Feb 7, 2021
Aptamers can be regarded as efficient substitutes for monoclonal antibodies in many diagnostic and therapeutic applications. Due to the tedious and prohibitive nature of SELEX (systematic evolution of ligands by exponential enrichment), the in silico...
Machine Learning Algorithms Biomarkers Molecular Dynamics Simulation Aptamers, Nucleotide Molecular Conformation Molecular Docking Simulation RNA Proteins Ligands CD13 Antigens Drug Design
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Prediction of pharmacological activities from chemical structures with graph convolutional neural networks.

Scientific reports Jan 12, 2021
Many therapeutic drugs are compounds that can be represented by simple chemical structures, which contain important determinants of affinity at the site of action. Recently, graph convolutional neural network (GCN) models have exhibited excellent res...
Amino Acid Sequence Pharmacology Molecular Conformation Pharmaceutical Preparations Drug Evaluation, Preclinical Antidepressive Agents Selective Serotonin Reuptake Inhibitors Humans Neural Networks, Computer
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Combining Data with Predictions for Modeling Hepatic Steatosis by Using Stratified Bagging and Conformal Prediction.

Chemical research in toxicology Dec 21, 2020
Hepatic steatosis (fatty liver) is a severe liver disease induced by the excessive accumulation of fatty acids in hepatocytes. In this study, we developed reliable models for predicting hepatic steatosis on the basis of an data set of 1041 compound...
Molecular Conformation Hydrocarbons, Aromatic Hydrocarbons, Acyclic Fatty Liver Models, Molecular Databases, Factual Computer Simulation Humans Machine Learning
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Predicting With Confidence: Using Conformal Prediction in Drug Discovery.

Journal of pharmaceutical sciences Oct 17, 2020
One of the challenges with predictive modeling is how to quantify the reliability of the models' predictions on new objects. In this work we give an introduction to conformal prediction, a framework that sits on top of traditional machine learning al...
Machine Learning Algorithms Reproducibility of Results Molecular Conformation Quantitative Structure-Activity Relationship Drug Discovery
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Integrated Variational Approach to Conformational Dynamics: A Robust Strategy for Identifying Eigenfunctions of Dynamical Operators.

The journal of physical chemistry. B Oct 9, 2020
One approach to analyzing the dynamics of a physical system is to search for long-lived patterns in its motions. This approach has been particularly successful for molecular dynamics data, where slowly decorrelating patterns can indicate large-scale ...
Molecular Dynamics Simulation Neural Networks, Computer Nonlinear Dynamics Molecular Conformation
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Reverse graph self-attention for target-directed atomic importance estimation.

Neural networks : the official journal of the International Neural Network Society Oct 8, 2020
Estimating the importance of each atom in a molecule is one of the most appealing and challenging problems in chemistry, physics, and materials science. The most common way to estimate the atomic importance is to compute the electronic structure usin...
Attention Molecular Conformation Nuclear Energy Machine Learning Humans Electronics Neural Networks, Computer
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Can One Hear the Shape of a Molecule (from its Coulomb Matrix Eigenvalues)?

Journal of chemical information and modeling Jul 29, 2020
Coulomb matrix eigenvalues (CMEs) are global 3D representations of molecular structure, which have been previously used to predict atomization energies, prioritize geometry searches, and interpret rotational spectra. The properties of the CME represe...
Molecular Structure Algorithms Isomerism Unsupervised Machine Learning Molecular Conformation
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Cov_FB3D: A De Novo Covalent Drug Design Protocol Integrating the BA-SAMP Strategy and Machine-Learning-Based Synthetic Tractability Evaluation.

Journal of chemical information and modeling Apr 9, 2020
drug design actively seeks to use sets of chemical rules for the fast and efficient identification of structurally new chemotypes with the desired set of biological properties. Fragment-based design tools have been successfully applied in the disco...
Enzyme Inhibitors Molecular Conformation Drug Design Machine Learning Humans Models, Molecular Computer Simulation
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Flexible Fitting of Small Molecules into Electron Microscopy Maps Using Molecular Dynamics Simulations with Neural Network Potentials.

Journal of chemical information and modeling Mar 30, 2020
Despite significant advances in resolution, the potential for cryo-electron microscopy (EM) to be used in determining the structures of protein-drug complexes remains unrealized. Determination of accurate structures and coordination of bound ligands ...
Protein Conformation Neural Networks, Computer Molecular Conformation Cryoelectron Microscopy Molecular Dynamics Simulation Microscopy, Electron
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