AIMC Topic: Ligands

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Machine Learning on DNA-Encoded Libraries: A New Paradigm for Hit Finding.

Journal of medicinal chemistry Jun 11, 2020
DNA-encoded small molecule libraries (DELs) have enabled discovery of novel inhibitors for many distinct protein targets of therapeutic value. We demonstrate a new approach applying machine learning to DEL selection data by identifying active molecul...
Estrogen Receptor alpha Epoxide Hydrolases Protein Kinase Inhibitors Small Molecule Libraries Proto-Oncogene Proteins c-kit DNA Ligands Neural Networks, Computer Drug Discovery
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Combining Machine Learning and Enhanced Sampling Techniques for Efficient and Accurate Calculation of Absolute Binding Free Energies.

Journal of chemical theory and computation Jun 4, 2020
Calculating absolute binding free energies is challenging and important. In this paper, we test some recently developed metadynamics-based methods and develop a new combination with a Hamiltonian replica-exchange approach. The methods were tested on ...
Machine Learning Algorithms Drug Design Humans Thermodynamics Protein Structure, Tertiary Epoxide Hydrolases Protein Binding Molecular Dynamics Simulation Ligands
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Deep Learning Based Drug Screening for Novel Coronavirus 2019-nCov.

Interdisciplinary sciences, computational life sciences Jun 1, 2020
A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the world. Although there are some drugs to treat 2019-nCoV, there is no proper scientific evidence abou...
Deep Learning User-Computer Interface Antiviral Agents SARS-CoV-2 Drug Design Amino Acid Sequence Coronavirus Infections Ligands Models, Molecular Molecular Dynamics Simulation Drug Evaluation, Preclinical Coronavirus 3C Proteases Humans Pandemics Cysteine Endopeptidases COVID-19 Databases, Pharmaceutical Structural Homology, Protein Betacoronavirus Pneumonia, Viral Viral Nonstructural Proteins Databases, Nucleic Acid Sequence Alignment Catalytic Domain Oligopeptides
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TF3P: Three-Dimensional Force Fields Fingerprint Learned by Deep Capsular Network.

Journal of chemical information and modeling May 28, 2020
Molecular fingerprints are the workhorse in ligand-based drug discovery. In recent years, an increasing number of research papers reported fascinating results on using deep neural networks to learn 2D molecular representations as fingerprints. It is ...
Neural Networks, Computer Machine Learning Drug Discovery Ligands
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Using machine learning to improve ensemble docking for drug discovery.

Proteins May 25, 2020
Ensemble docking has provided an inexpensive method to account for receptor flexibility in molecular docking for virtual screening. Unfortunately, as there is no rigorous theory to connect the docking scores from multiple structures to measured activ...
User-Computer Interface Protein Binding Support Vector Machine Bayes Theorem Ligands Humans Molecular Docking Simulation Drug Discovery Binding Sites Protein Structure, Secondary ErbB Receptors Protein Kinase Inhibitors
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Improving Docking-Based Virtual Screening Ability by Integrating Multiple Energy Auxiliary Terms from Molecular Docking Scoring.

Journal of chemical information and modeling May 11, 2020
Virtual Screening (VS) based on molecular docking is an efficient method used for retrieving novel hit compounds in drug discovery. However, the accuracy of the current docking scoring function (SF) is usually insufficient. In this study, in order to...
Molecular Docking Simulation Protein Binding Proteins Machine Learning Ligands
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Binding Affinity Prediction by Pairwise Function Based on Neural Network.

Journal of chemical information and modeling May 11, 2020
We present a new approach to estimate the binding affinity from given three-dimensional poses of protein-ligand complexes. In this scheme, every protein-ligand atom pair makes an additive free-energy contribution. The sum of these pairwise contributi...
Protein Binding Ligands Neural Networks, Computer Molecular Docking Simulation Drug Design
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LIT-PCBA: An Unbiased Data Set for Machine Learning and Virtual Screening.

Journal of chemical information and modeling Apr 23, 2020
Comparative evaluation of virtual screening methods requires a rigorous benchmarking procedure on diverse, realistic, and unbiased data sets. Recent investigations from numerous research groups unambiguously demonstrate that artificially constructed ...
Machine Learning Ligands Molecular Docking Simulation Proteins
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Ranking Molecules with Vanishing Kernels and a Single Parameter: Active Applicability Domain .

Journal of chemical information and modeling Apr 23, 2020
In ligand-based virtual screening, high-throughput screening (HTS) data sets can be exploited to train classification models. Such models can be used to prioritize yet untested molecules, from the most likely active (against a protein target of inter...
Software Ligands Neural Networks, Computer
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The power of deep learning to ligand-based novel drug discovery.

Expert opinion on drug discovery Mar 31, 2020
INTRODUCTION: Deep discriminative and generative neural-network models are becoming an integral part of the modern approach to ligand-based novel drug discovery. The variety of different architectures of neural networks, the methods of their training...
Deep Learning Ligands Algorithms Humans Drug Design Neural Networks, Computer Drug Discovery
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