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ARTIFICIAL INTELLIGENCE FOR THE REAL WORLD
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Generative Adversarial Networks
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A new synthetic approach for pyrazolo[1,5-a]pyrazine-4(5H)-one derivatives and their antiproliferative effects on lung adenocarcinoma cell line
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Artificial Intelligence-Based Application to Explore Inhibitors of Neurodegenerative Diseases
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Artificial intelligence in the early stages of drug discovery.
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Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets
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Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
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IDDkin: network-based influence deep diffusion model for enhancing prediction of kinase inhibitors
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DeepPurpose: a deep learning library for drug–target interaction prediction
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Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects
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Non-Steroidal Anti-Inflammatory Drugs Increase Cisplatin, Paclitaxel, and Doxorubicin Efficacy against Human Cervix Cancer Cells
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Exploring nature’s bounty: identification of Withania somnifera as a promising source of therapeutic agents against COVID-19 by virtual screening and in silico evaluation
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PROMISCUOUS 2.0: a resource for drug-repositioning
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LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates
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DeepDrug: A general graph-based deep learning framework for drug-drug interactions and drug-target interactions prediction
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PubChem in 2021: new data content and improved web interfaces
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Activity Prediction of Small Molecule Inhibitors for Antirheumatoid Arthritis Targets Based on Artificial Intelligence.
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Cloud 3D-QSAR: a web tool for the development of quantitative structure-activity relationship models in drug discovery
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SNF-CVAE: Computational method to predict drug-disease interactions using similarity network fusion and collective variational autoencoder
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Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells.
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MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery
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Machine learning-guided discovery and design of non-hemolytic peptides
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DeepACP: A Novel Computational Approach for Accurate Identification of Anticancer Peptides by Deep Learning Algorithm
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A multimodal deep learning-based drug repurposing approach for treatment of COVID-19
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Discovery of Potential Flavonoid Inhibitors Against COVID-19 3CL Proteinase Based on Virtual Screening Strategy
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IAMPE: NMR-Assisted Computational Prediction of Antimicrobial Peptides
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DeepH-DTA: Deep Learning for Predicting Drug-Target Interactions: A Case Study of COVID-19 Drug Repurposing
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A computational framework of host-based drug repositioning for broad-spectrum antivirals against RNA viruses
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De Novo Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization
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Automated In Silico Identification of Drug Candidates for Coronavirus Through a Novel Programmatic Tool and Extensive Computational (MD, DFT) Studies of Select Drug Candidates
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Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning
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SNF-NN: computational method to predict drug-disease interactions using similarity network fusion and neural networks
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MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm
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Structure-Activity relationship of Quercetin and its Tumor Necrosis Factor Alpha inhibition activity by computational and machine learning methods
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Functional fine-mapping of noncoding risk variants in amyotrophic lateral sclerosis utilizing convolutional neural network
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Structure-Based Virtual Screening to Discover Potential Lead Molecules for the SARS-CoV-2 Main Protease
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iDrug: Integration of drug repositioning and drug-target prediction via cross-network embedding
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Ligand and structure-based virtual screening applied to the SARS-CoV-2 main protease: an in silico repurposing study
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Drug discovery with explainable artificial intelligence
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Toward heterogeneous information fusion: bipartite graph convolutional networks for in silico drug repurposing
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MGATRx: Discovering Drug Repositioning Candidates Using Multi-view Graph Attention
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Chemical-informatics approach to COVID-19 drug discovery: Monte Carlo based QSAR, virtual screening and molecular docking study of some in-house molecules as papain-like protease (PLpro) inhibitors
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Structure-based virtual screening and molecular dynamics simulation of SARS-CoV-2 Guanine-N7 methyltransferase (nsp14) for identifying antiviral inhibitors against COVID-19
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The application of machine learning techniques to innovative antibacterial discovery and development
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AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning
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A novel drug repurposing approach for non-small cell lung cancer using deep learning
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Protein Binding Pocket Optimization for Virtual High-Throughput Screening (vHTS) Drug Discovery
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Identification of novel class I and class IIb histone deacetylase inhibitor for Alzheimer's disease therapeutics.
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Artificial intelligence in chemistry and drug design
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PaccMannRL on SARS-CoV-2: Designing antiviral candidates with conditional generative models
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EasyVS: a user-friendly web-based tool for molecule library selection and structure-based virtual screening
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Deep-AmPEP30: Improve Short Antimicrobial Peptides Prediction with Deep Learning
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RosENet: Improving Binding Affinity Prediction by Leveraging Molecular Mechanics Energies with an Ensemble of 3D Convolutional Neural Networks
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A deep neural network for molecular wave functions in quasi-atomic minimal basis representation.
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Repurposing Zileuton as a Depression Drug Using an AI and In Vitro Approach
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Drug repurposing against Parkinson's disease by text mining the scientific literature
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AutoGrow4: an open-source genetic algorithm for de novo drug design and lead optimization
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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
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PSBP-SVM: A Machine Learning-Based Computational Identifier for Predicting Polystyrene Binding Peptides
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Dr AFC: drug repositioning through anti-fibrosis characteristic
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Predicting commercially available antiviral drugs that may act on the novel coronavirus (SARS-CoV-2) through a drug-target interaction deep learning model
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Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks
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Focusing on the Unfolded Protein Response and Autophagy Related Pathways to Reposition Common Approved Drugs against COVID-19
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Identification of SARS-CoV-2 Cell Entry Inhibitors by Drug Repurposing Using in silico Structure-Based Virtual Screening Approach
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Transformer-CNN: Swiss knife for QSAR modeling and interpretation
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SAEROF: an ensemble approach for large-scale drug-disease association prediction by incorporating rotation forest and sparse autoencoder deep neural network
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Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2
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VISAR: an interactive tool for dissecting chemical features learned by deep neural network QSAR models
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Accelerated Discovery of Novel Ponatinib Analogs with Improved Properties for the Treatment of Parkinson's Disease.
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D3Similarity: A Ligand-Based Approach for Predicting Drug Targets and for Virtual Screening of Active Compounds Against COVID-19
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A novel artificial intelligence protocol to investigate potential leads for Parkinson's disease
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An Introduction to Machine Learning
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HNet-DNN: Inferring New Drug-Disease Associations with Deep Neural Network Based on Heterogeneous Network Features
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LigBuilder V3: A Multi-Target de novo Drug Design Approach
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FL-QSAR: a federated learning based QSAR prototype for collaborative drug discovery
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ChemGrapher: Optical Graph Recognition of Chemical Compounds by Deep Learning
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In silico screening of Chinese herbal medicines with the potential to directly inhibit 2019 novel coronavirus
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OntoQSAR: an Ontology for Interpreting Chemical and Biological Data in Quantitative Structure-Activity Relationship Studies
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A Deep Learning Approach to Antibiotic Discovery
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Machine learning on DNA-encoded libraries: A new paradigm for hit-finding
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DRIMC: an improved drug repositioning approach using Bayesian inductive matrix completion
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Virtual Screening of DPP-4 Inhibitors Using QSAR-Based Artificial Intelligence and Molecular Docking of Hit Compounds to DPP-8 and DPP-9 Enzymes
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NegStacking: Drug−Target Interaction Prediction Based on Ensemble Learning and Logistic Regression
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Will Artificial Intelligence for Drug Discovery Impact Clinical Pharmacology?
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Quantitative structure-activity relationship (QSAR) models and their applicability domain analysis on HIV-1 protease inhibitors by machine learning methods
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DeepMalaria: Artificial Intelligence Driven Discovery of Potent Antiplasmodials
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Vienna LiverTox Workspace—A Set of Machine Learning Models for Prediction of Interactions Profiles of Small Molecules With Transporters Relevant for Regulatory Agencies
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Design, synthesis and ADMET prediction of bis-benzimidazole as anticancer agent.
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A New Algorithm Optimized for Initial Dose Settings of Vancomycin Using Machine Learning.
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Improved protein structure prediction using potentials from deep learning
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Artificial Intelligence
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DTI-CDF: a cascade deep forest model towards the prediction of drug-target interactions based on hybrid features
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BIOPHYSICAL PREDICTION OF PROTEIN-PEPTIDE INTERACTIONS AND SIGNALING NETWORKS USING MACHINE LEARNING
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Rethinking drug design in the artificial intelligence era
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Combined quantum mechanics/molecular mechanics (QM/MM) methods to understand the charge density distribution of estrogens in the active site of estrogen receptors
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Artificial Intelligence in Nephrology: Core Concepts, Clinical Applications, and Perspectives.
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Prediction of Adverse Drug Reactions by Combining Biomedical Tripartite Network and Graph Representation Model.
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Identifying cancer-related molecular targets of Nandina domestica Thunb. by network pharmacology-based analysis in combination with chemical profiling and molecular docking studies.
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Turning genome-wide association study findings into opportunities for drug repositioning
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Harnessing Artificial Intelligence to Optimize Long‐Term Maintenance Dosing for Antiretroviral‐Naive Adults with HIV‐1 Infection
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HeteroDualNet: A Dual Convolutional Neural Network With Heterogeneous Layers for Drug-Disease Association Prediction via Chou’s Five-Step Rule
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Prediction of K562 cells functional inhibitors based on machine learning approaches.
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Advances and Perspectives in Applying Deep Learning for Drug Design and Discovery
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BiRWDDA: A Novel Drug Repositioning Method Based on Multisimilarity Fusion
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The significance of artificial intelligence in drug delivery system design.
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Discovery of novel potential selective HDAC8 inhibitors by combine ligand-based, structure-based virtual screening and in-vitro biological evaluation
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GWAS for systemic sclerosis identifies multiple risk loci and highlights fibrotic and vasculopathy pathways
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RepCOOL: computational drug repositioning via integrating heterogeneous biological networks
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Multi-Target Chemometric Modelling, Fragment Analysis and Virtual Screening with ERK Inhibitors as Potential Anticancer Agents
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dendPoint: a web resource for dendrimer pharmacokinetics investigation and prediction
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Comprehensive ensemble in QSAR prediction for drug discovery
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StackCBPred: A stacking based prediction of protein-carbohydrate binding sites from sequence.
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Inductive transfer learning for molecular activity prediction: Next-Gen QSAR Models with MolPMoFiT
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The impact of artificial intelligence in medicine on the future role of the physician
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Investigation of Machine Intelligence in Compound Cell Activity Classification.
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A Computational Toxicology Approach to Screen the Hepatotoxic Ingredients in Traditional Chinese Medicines: Polygonum multiflorum Thunb as a Case Study
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Toxicity prediction of small drug molecules of androgen receptor using multilevel ensemble model
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A novel protein descriptor for the prediction of drug binding sites
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Associating 197 Chinese herbal medicine with drug targets and diseases using the similarity ensemble approach
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Artificial Intelligence-Based Drug Design and Discovery
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PTPD: predicting therapeutic peptides by deep learning and word2vec
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Molecular Docking: Shifting Paradigms in Drug Discovery
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A Free Web-Based Protocol to Assist Structure-Based Virtual Screening Experiments
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Deep learning enables rapid identification of potent DDR1 kinase inhibitors
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A machine learning and network framework to discover new indications for small molecules
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Development of Multi-Target Chemometric Models for the Inhibition of Class I PI3K Enzyme Isoforms: A Case Study Using QSAR-Co Tool
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Predicting Drug-Disease Associations via Using Gaussian Interaction Profile and Kernel-Based Autoencoder
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Looking beyond the hype: Applied AI and machine learning in translational medicine
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IVS2vec: A tool of Inverse Virtual Screening based on word2vec and deep learning techniques.
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DLIGAND2: an improved knowledge-based energy function for protein–ligand interactions using the distance-scaled, finite, ideal-gas reference state
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Comparison of Target Features for Predicting Drug-Target Interactions by Deep Neural Network Based on Large-Scale Drug-Induced Transcriptome Data
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Artificial Intelligence for Clinical Trial Design.
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Advancing Drug Discovery via Artificial Intelligence.
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Herb-Induced Liver Injury: Phylogenetic Relationship, Structure-Toxicity Relationship, and Herb-Ingredient Network Analysis
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Machine Learning From Molecular Dynamics Trajectories to Predict Caspase-8 Inhibitors Against Alzheimer’s Disease
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Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery.
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Targeting HIV/HCV Coinfection Using a Machine Learning-Based Multiple Quantitative Structure-Activity Relationships (Multiple QSAR) Method
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In Silico Prediction of PAMPA Effective Permeability Using a Two-QSAR Approach
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Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions
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QSAR Classification Models for Predicting the Activity of Inhibitors of Beta-Secretase (BACE1) Associated with Alzheimer’s Disease
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Discovery of novel glycogen synthase kinase-3α inhibitors: Structure-based virtual screening, preliminary SAR and biological evaluation for treatment of acute myeloid leukemia.
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Using artificial intelligence methods to speed up drug discovery
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Gypsum-DL: an open-source program for preparing small-molecule libraries for structure-based virtual screening
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Performance Evaluation of cuDNN Convolution Algorithms on NVIDIA Volta GPUs
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deepDR: a network-based deep learning approach to in silico drug repositioning
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Ligity: A Non-Superpositional, Knowledge-Based Approach to Virtual Screening
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QSAR-Co: An Open Source Software for Developing Robust Multitasking or Multitarget Classification-Based QSAR Models
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A network pharmacology approach to investigate the blood enriching mechanism of Danggui buxue Decoction.
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ACP-DL: A Deep Learning Long Short-Term Memory Model to Predict Anticancer Peptides Using High-Efficiency Feature Representation
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BRUSELAS: HPC Generic and Customizable Software Architecture for 3D Ligand-Based Virtual Screening of Large Molecular Databases
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Governance of automated image analysis and artificial intelligence analytics in healthcare.
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Exploiting machine learning for end-to-end drug discovery and development
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Applications of machine learning in drug discovery and development
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Predicting Parkinson's Disease Genes Based on Node2vec and Autoencoder
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Identification of Target Genes at Juvenile Idiopathic Arthritis GWAS Loci in Human Neutrophils
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Deep Learning and Random Forest Approach for Finding the Optimal Traditional Chinese Medicine Formula for Treatment of Alzheimer's Disease
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Interpretable Deep Learning in Drug Discovery
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Combating Diseases with Computational Strategies Used for Drug Design and Discovery.
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AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions
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Artificial intelligence in drug development: present status and future prospects.
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Pharmacogenomics, biomarker network, and allele frequencies in colorectal cancer
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DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies
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CompScore: boosting structure-based virtual screening performance by incorporating docking scoring functions components into consensus scoring
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GCAC: galaxy workflow system for predictive model building for virtual screening
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RCDR: A Recommender Based Method for Computational Drug Repurposing
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Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas
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LSA: a local-weighted structural alignment tool for pharmaceutical virtual screening
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Structure-Based Virtual Screening for the Identification of High Affinity Compounds as Potent VEGFR2 Inhibitors for the Treatment of Renal Cell Carcinoma.
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eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates
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DrPOCS: Drug Repositioning Based on Projection Onto Convex Sets
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A Drug-Target Network-Based Supervised Machine Learning Repurposing Method Allowing the Use of Multiple Heterogeneous Information Sources.
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PyQSAR: A Fast QSAR Modeling Platform Using Machine Learning and Jupyter Notebook
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DEEPScreen: high performance drug–target interaction prediction with convolutional neural networks using 2-D structural compound representations
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Identifying Lysophosphatidic Acid Acyltransferase β (LPAAT‐β) as the Target of a Nanomolar Angiogenesis Inhibitor from a Phenotypic Screen Using the Polypharmacology Browser PPB2
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STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets
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Open Targets Platform: new developments and updates two years on
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The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019
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QSAR-Based Virtual Screening: Advances and Applications in Drug Discovery
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DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences
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ChEMBL: towards direct deposition of bioassay data
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ChemBoost: A Chemical Language Based Approach for Protein – Ligand Binding Affinity Prediction
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Novel drug candidates for treating esophageal carcinoma: A study on differentially expressed genes, using connectivity mapping and molecular docking
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Artificial Intelligence in Drug Design-The Storm Before the Calm?
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A chemical language based approach for protein - ligand interaction prediction
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METADOCK: A parallel metaheuristic schema for virtual screening methods
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PISTON: Predicting drug indications and side effects using topic modeling and natural language processing
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How CUDA Powers the Machine Learning Revolution
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PubChem 2019 update: improved access to chemical data
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An integrative machine learning approach for prediction of toxicity-related drug safety
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RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy
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Drug repurposing: progress, challenges and recommendations
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Homology modeling in drug discovery: Overview, current applications, and future perspectives
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Transforming Computational Drug Discovery with Machine Learning and AI.
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Deep learning and virtual drug screening
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DTI-RCNN: New Efficient Hybrid Neural Network Model to Predict Drug-Target Interactions
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MDCKpred: a web-tool to calculate MDCK permeability coefficient of small molecule using membrane-interaction chemical features
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Screening Strategies and Methods for Better Off-Target Liability Prediction and Identification of Small-Molecule Pharmaceuticals
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Neurodegenerative Diseases: Regenerative Mechanisms and Novel Therapeutic Approaches
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PlayMolecule BindScope: large scale CNN-based virtual screening on the web
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Modulating BET Bromodomain Inhibitor ZEN‐3694 and Enzalutamide Combination Dosing in a Metastatic Prostate Cancer Patient Using CURATE.AI, an Artificial Intelligence Platform
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Ambit-SMIRKS: a software module for reaction representation, reaction search and structure transformation
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Improvement of Adequate Digoxin Dosage: An Application of Machine Learning Approach
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Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review
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Machine Learning-based Virtual Screening and Its Applications to Alzheimer’s Drug Discovery: A Review
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PADME: A Deep Learning-based Framework for Drug-Target Interaction Prediction
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A decision theoretic approach to model evaluation in computational drug discovery
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Polypharmacology by Design: A Medicinal Chemist's Perspective on Multitargeting Compounds.
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Artificial intelligence in drug design
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Machine intelligence decrypts β-lapachone as an allosteric 5-lipoxygenase inhibitor† †Electronic supplementary information (ESI) available: Supplementary figures, data and methods. See DOI: 10.1039/c8sc02634c
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Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility
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Bioactive molecule prediction using majority voting-based ensemble method
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QEX: target-specific druglikeness filter enhances ligand-based virtual screening
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WDL‐RF: predicting bioactivities of ligand molecules acting with G protein‐coupled receptors by combining weighted deep learning and random forest
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LS‐align: an atom‐level, flexible ligand structural alignment algorithm for high‐throughput virtual screening
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QSAR Modeling of ToxCast Assays Relevant to the Molecular Initiating Events of AOPs Leading to Hepatic Steatosis
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Learning with multiple pairwise kernels for drug bioactivity prediction
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ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database
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DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural Networks
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Interpretation of ANN‐based QSAR models for prediction of antioxidant activity of flavonoids
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DPubChem: a web tool for QSAR modeling and high-throughput virtual screening
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Development of Ligand‐based Big Data Deep Neural Network Models for Virtual Screening of Large Compound Libraries
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GRTR: Drug-Disease Association Prediction Based on Graph Regularized Transductive Regression on Heterogeneous Network
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Computational drug repositioning using low-rank matrix approximation and randomized algorithms
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Computational prediction of chemical reactions: current status and outlook.
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The rise of deep learning in drug discovery.
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PKRank: a novel learning-to-rank method for ligand-based virtual screening using pairwise kernel and RankSVM
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How artificial intelligence is changing drug discovery
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Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.
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ProTox-II: a webserver for the prediction of toxicity of chemicals
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Identification of potent and selective small molecule inhibitors of the cation channel TRPM4
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Artificial Intelligence in Drug Design
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SPIDR: small-molecule peptide-influenced drug repurposing
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Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era
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Current Concepts of Neurodegenerative Mechanisms in Alzheimer's Disease
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Chematica: A Story of Computer Code That Started to Think like a Chemist
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Identification of a Novel Protein Arginine Methyltransferase 5 Inhibitor in Non-small Cell Lung Cancer by Structure-Based Virtual Screening
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End-to-end differentiable learning of protein structure
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A Network Pharmacology Approach to Uncover the Multiple Mechanisms of Hedyotis diffusa Willd. on Colorectal Cancer
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Identification of Novel Protein Kinase Receptor Type 2 Inhibitors Using Pharmacophore and Structure-Based Virtual Screening
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Estimation of clinical trial success rates and related parameters
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DeepDTA: deep drug–target binding affinity prediction
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Recurrent Neural Network Model for Constructive Peptide Design
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Discovery of new GSK-3β inhibitors through structure-based virtual screening.
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Applying machine learning techniques to predict the properties of energetic materials
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Uncovering the anticancer mechanism of Compound Kushen Injection against HCC by integrating quantitative analysis, network analysis and experimental validation
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Ensemble learning method for the prediction of new bioactive molecules
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Discovering new PI3Kα inhibitors with a strategy of combining ligand-based and structure-based virtual screening
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Discovery of indolylpiperazinylpyrimidines with dual-target profiles at adenosine A2A and dopamine D2 receptors for Parkinson's disease treatment
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De Novo Design of Bioactive Small Molecules by Artificial Intelligence
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Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks
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Identification of Novel Aurora Kinase A (AURKA) Inhibitors via Hierarchical Ligand-Based Virtual Screening
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DeepSynergy: predicting anti-cancer drug synergy with Deep Learning
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SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties
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vNN Web Server for ADMET Predictions
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Deep reinforcement learning for de novo drug design
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The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations.
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Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization
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Application of Generative Autoencoder in De Novo Molecular Design
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DrugBank 5.0: a major update to the DrugBank database for 2018
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Drug discovery and development: Role of basic biological research
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From machine learning to deep learning: progress in machine intelligence for rational drug discovery.
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Targeting Dengue Virus NS-3 Helicase by Ligand based Pharmacophore Modeling and Structure based Virtual Screening
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ADMET Evaluation in Drug Discovery. 18. Reliable Prediction of Chemical-Induced Urinary Tract Toxicity by Boosting Machine Learning Approaches.
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System Pharmacology-Based Dissection of the Synergistic Mechanism of Huangqi and Huanglian for Diabetes Mellitus
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Discovery of a Low Toxicity O-GlcNAc Transferase (OGT) Inhibitor by Structure-based Virtual Screening of Natural Products
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Meta-QSAR: a large-scale application of meta-learning to drug design and discovery
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PyGOLD: a python based API for docking based virtual screening workflow generation
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Planning chemical syntheses with deep neural networks and symbolic AI
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Is Multitask Deep Learning Practical for Pharma?
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Identification of potent inhibitors of DNA methyltransferase 1 (DNMT1) through a pharmacophore-based virtual screening approach.
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The NCI Genomic Data Commons as an engine for precision medicine.
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When less is more – efficacy with less toxicity at the ED50
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ADMET Evaluation in Drug Discovery. Part 17: Development of Quantitative and Qualitative Prediction Models for Chemical-Induced Respiratory Toxicity.
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Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models
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Machine learning workflow to enhance predictions of Adverse Drug Reactions (ADRs) through drug-gene interactions: application to drugs for cutaneous diseases
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Structure-based virtual screening and molecular docking for the identification of potential multi-targeted inhibitors against breast cancer
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Chromatin interactions reveal novel gene targets for drug repositioning in rheumatic diseases
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3D Pharmacophore-Based Virtual Screening and Docking Approaches toward the Discovery of Novel HPPD Inhibitors
281
DeepPPI: Boosting Prediction of Protein-Protein Interactions with Deep Neural Networks
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When Will AI Exceed Human Performance? Evidence from AI Experts
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LimTox: a web tool for applied text mining of adverse event and toxicity associations of compounds, drugs and genes
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ChemSAR: an online pipelining platform for molecular SAR modeling
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ENRI: A tool for selecting structure‐based virtual screening target conformations
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Tandem application of ligand-based virtual screening and G4-OAS assay to identify novel G-quadruplex-targeting chemotypes.
287
Neurodegenerative disease: models, mechanisms, and a new hope
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A novel framework for the identification of drug target proteins: Combining stacked auto-encoders with a biased support vector machine
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Performance of machine-learning scoring functions in structure-based virtual screening
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Molecular de-novo design through deep reinforcement learning
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Deep Learning Based Regression and Multiclass Models for Acute Oral Toxicity Prediction with Automatic Chemical Feature Extraction
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SPOT‐ligand 2: improving structure‐based virtual screening by binding‐homology search on an expanded structural template library
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Predicting neurological Adverse Drug Reactions based on biological, chemical and phenotypic properties of drugs using machine learning models
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DrugPathSeeker: Interactive UI for exploring drug-ADR relation via pathways
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Google DeepMind and healthcare in an age of algorithms
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SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules
297
Computational Multitarget Drug Design
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The polypharmacology browser: a web-based multi-fingerprint target prediction tool using ChEMBL bioactivity data
299
Application of Machine-Learning Models to Predict Tacrolimus Stable Dose in Renal Transplant Recipients
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Chembench: A Publicly Accessible, Integrated Cheminformatics Portal
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Deep learning for computational chemistry
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Profiling Prediction of Kinase Inhibitors: Toward the Virtual Assay.
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In Silico Prediction of Physicochemical Properties of Environmental Chemicals Using Molecular Fingerprints and Machine Learning
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The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology
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RADER: a RApid DEcoy Retriever to facilitate decoy based assessment of virtual screening
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Matched Molecular Pair Analysis in Short: Algorithms, Applications and Limitations
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Low Data Drug Discovery with One-Shot Learning
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DPDR-CPI, a server that predicts Drug Positioning and Drug Repositioning via Chemical-Protein Interactome
309
The RCSB protein data bank: integrative view of protein, gene and 3D structural information
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Discovery of a VHL and HIF1α interaction inhibitor with in vivo angiogenic activity via structure-based virtual screening.
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Learning Deep Architectures for Interaction Prediction in Structure-based Virtual Screening
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A Data-Driven Approach to Predicting Successes and Failures of Clinical Trials.
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DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants
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PL-PatchSurfer2: Improved Local Surface Matching-Based Virtual Screening Method That Is Tolerant to Target and Ligand Structure Variation
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L1000CDS2: LINCS L1000 characteristic direction signatures search engine
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Optimal medication dosing from suboptimal clinical examples: A deep reinforcement learning approach
317
Bioactive Molecule Prediction Using Extreme Gradient Boosting
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SwissSimilarity: A Web Tool for Low to Ultra High Throughput Ligand-Based Virtual Screening
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GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing
320
mCSM-lig: quantifying the effects of mutations on protein-small molecule affinity in genetic disease and emergence of drug resistance
321
Deep learning for computational biology
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Discovery of New Chemical Entities for Old Targets: Insights on the Lead Optimization of Chromone-Based Monoamine Oxidase B (MAO-B) Inhibitors.
323
Enhancing the Enrichment of Pharmacophore-Based Target Prediction for the Polypharmacological Profiles of Drugs
324
mCSM-AB: a web server for predicting antibody–antigen affinity changes upon mutation with graph-based signatures
325
TargetNet: a web service for predicting potential drug–target interaction profiling via multi-target SAR models
326
In silico clinical trials: how computer simulation will transform the biomedical industry
327
CSM-lig: a web server for assessing and comparing protein–small molecule affinities
328
Innovation in the pharmaceutical industry: New estimates of R&D costs.
329
3-D structural interactions and quantitative structural toxicity studies of tyrosine derivatives intended for safe potent inflammation treatment
330
Improving chemical similarity ensemble approach in target prediction
331
USR-VS: a web server for large-scale prospective virtual screening using ultrafast shape recognition techniques
332
Predicting Protein-Protein Interactions from the Molecular to the Proteome Level.
333
Predicting cancer-relevant proteins using an improved molecular similarity ensemble approach
334
In silico Prediction of Drug Induced Liver Toxicity Using Substructure Pattern Recognition Method
335
Applications of Deep Learning in Biomedicine.
336
SDTNBI: an integrated network and chemoinformatics tool for systematic prediction of drug–target interactions and drug repositioning
337
Pred-binding: large-scale protein–ligand binding affinity prediction
338
De Novo Design at the Edge of Chaos.
339
Role of Molecular Dynamics and Related Methods in Drug Discovery.
340
DeepTox: Toxicity Prediction using Deep Learning
341
ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modeling
342
In silico methods to address polypharmacology: current status, applications and future perspectives.
343
Modelling the Tox21 10 K chemical profiles for in vivo toxicity prediction and mechanism characterization
344
A multiple kernel learning algorithm for drug-target interaction prediction
345
ChemDes: an integrated web-based platform for molecular descriptor and fingerprint computation
346
Inhibition of human copper trafficking by a small molecule significantly attenuates cancer cell proliferation.
347
STITCH 5: augmenting protein–chemical interaction networks with tissue and affinity data
348
ZINC 15 – Ligand Discovery for Everyone
349
PhenoPredict: A disease phenome-wide drug repositioning approach towards schizophrenia drug discovery
350
TarPred: a web application for predicting therapeutic and side effect targets of chemical compounds
351
Revisiting Warfarin Dosing Using Machine Learning Techniques
352
Applying DEKOIS 2.0 in structure-based virtual screening to probe the impact of preparation procedures and score normalization
353
C5.0 Algorithm to Improved Decision Tree with Feature Selection and Reduced Error Pruning
354
Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets
355
pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures
356
MTiOpenScreen: a web server for structure-based virtual screening
357
Beyond the hype: Big data concepts, methods, and analytics
358
Machine-learning approaches in drug discovery: methods and applications.
359
Route Design in the 21st Century: The ICSYNTH Software Tool as an Idea Generator for Synthesis Prediction
360
Discovery of Multitarget-Directed Ligands against Alzheimer's Disease through Systematic Prediction of Chemical-Protein Interactions
361
A Network-Based Classification Model for Deriving Novel Drug-Disease Associations and Assessing Their Molecular Actions
362
Discovery of Inhibitors of Schistosoma mansoni HDAC8 by Combining Homology Modeling, Virtual Screening, and in Vitro Validation
363
Ligand Efficiency-Based Support Vector Regression Models for Predicting Bioactivities of Ligands to Drug Target Proteins
364
DruGeVar: An Online Resource Triangulating Drugs with Genes and Genomic Biomarkers for Clinical Pharmacogenomics
365
Polypharmacology: challenges and opportunities in drug discovery.
366
DeepFace: Closing the Gap to Human-Level Performance in Face Verification
367
Identification of a natural product-like STAT3 dimerization inhibitor by structure-based virtual screening
368
Improvement of Virtual Screening Results by Docking Data Feature Analysis
369
SwissTargetPrediction: a web server for target prediction of bioactive small molecules
370
Deep learning in neural networks: An overview
371
Emotional and behavioral symptoms in neurodegenerative disease: a model for studying the neural bases of psychopathology.
372
Identifying the macromolecular targets of de novo-designed chemical entities through self-organizing map consensus
373
Artificial intelligence-based classification of breast cancer using cellular images
374
Rapid identification of Keap1-Nrf2 small-molecule inhibitors through structure-based virtual screening and hit-based substructure search.
375
GWAS Central: a comprehensive resource for the comparison and interrogation of genome-wide association studies
376
Basics and recent advances in peptide and protein drug delivery.
377
The ChEMBL bioactivity database: an update
378
SMPDB 2.0: Big Improvements to the Small Molecule Pathway Database
379
Exploring the Pharmacogenomics Knowledge Base (PharmGKB) for Repositioning Breast Cancer Drugs by Leveraging Web Ontology Language (OWL) and Cheminformatics Approaches
380
In Silico Models for Designing and Discovering Novel Anticancer Peptides
381
Discovery of pteridin-7(8H)-one-based irreversible inhibitors targeting the epidermal growth factor receptor (EGFR) kinase T790M/L858R mutant.
382
Discovery of Novel Small-Molecule Inhibitors of BRD4 Using Structure-Based Virtual Screening
383
The Tox21 robotic platform for the assessment of environmental chemicals--from vision to reality.
384
Virtual screening strategies in drug discovery: a critical review.
385
ChemMapper: a versatile web server for exploring pharmacology and chemical structure association based on molecular 3D similarity method
386
Deep Architectures and Deep Learning in Chemoinformatics: The Prediction of Aqueous Solubility for Drug-Like Molecules
387
Open-source platform to benchmark fingerprints for ligand-based virtual screening
388
Discovery of a new small-molecule inhibitor of p53-MDM2 interaction using a yeast-based approach.
389
Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis
390
lazar: a modular predictive toxicology framework
391
Physiological and molecular characterization of Phytophthora infestans isolates from the Central Colombian Andean Region.
392
PubMed: The Bibliographic Database
393
TargetHunter: An In Silico Target Identification Tool for Predicting Therapeutic Potential of Small Organic Molecules Based on Chemogenomic Database
394
ImageNet classification with deep convolutional neural networks
395
Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17
396
admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties
397
Synthesis, in vitro antifungal evaluation and in silico study of 3-azolyl-4-chromanone phenylhydrazones
398
Synthesis, in vitro antifungal evaluation and in silico study of 3-azolyl-4-chromanone phenylhydrazones
399
Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs
400
Merging Systems Biology with Pharmacodynamics
401
Drug development and clinical trials—the path to an approved cancer drug
402
Building high-level features using large scale unsupervised learning
403
Dual modification of Alzheimer’s disease PHF-tau protein by lysine methylation and ubiquitylation: a mass spectrometry approach
404
Enabling future drug discovery by de novo design
405
Control of excitatory CNS synaptogenesis by astrocyte-secreted proteins Hevin and SPARC
406
Old friends in new guise: repositioning of known drugs with structural bioinformatics
407
PPI_SVM: Prediction of protein-protein interactions using machine learning, domain-domain affinities and frequency tables
408
Utilization of a least square support vector machine (LSSVM) for slope stability analysis
409
The Sequence Read Archive
410
Struct2Net: a web service to predict protein–protein interactions using a structure-based approach
411
Gaussian Processes for Classification: QSAR Modeling of ADMET and Target Activity
412
Computational approaches for drug design and discovery: An overview
413
ImageNet: A large-scale hierarchical image database
414
Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions
415
Machine learning in virtual screening.
416
Discovery of Novel HIV Entry Inhibitors for the CXCR4 Receptor by Prospective Virtual Screening
417
Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer
418
Virtual Screening: A Fast Tool for Drug Design
419
Selective structure-based virtual screening for full and partial agonists of the beta2 adrenergic receptor.
420
An evaluation of the implementation of the Cramer classification scheme in the Toxtree software
421
Prodrugs: design and clinical applications
422
Novel paradigms for drug discovery: computational multitarget screening.
423
DrugBank: a knowledgebase for drugs, drug actions and drug targets
424
Gaussian Processes: A Method for Automatic QSAR Modeling of ADME Properties
425
Adaptive neuro-fuzzy inference system (ANFIS): a new approach to predictive modeling in QSAR applications: a study of neuro-fuzzy modeling of PCP-based NMDA receptor antagonists.
426
Artificial intelligence approaches for rational drug design and discovery.
427
A comparison of physical properties, screening procedures and a human efficacy trial for predicting the bioavailability of commercial elemental iron powders used for food fortification.
428
Identification of nonpeptide CCR5 receptor agonists by structure-based virtual screening.
429
TrixX: structure-based molecule indexing for large-scale virtual screening in sublinear time
430
ArrayExpress—a public database of microarray experiments and gene expression profiles
431
Global mapping of pharmacological space
432
The discovery of new 11beta-hydroxysteroid dehydrogenase type 1 inhibitors by common feature pharmacophore modeling and virtual screening.
433
COSMOfrag: A Novel Tool for High-Throughput ADME Property Prediction and Similarity Screening Based on Quantum Chemistry
434
Virtual Computational Chemistry Laboratory – Design and Description
435
Can cell systems biology rescue drug discovery?
436
ProPose: Steered Virtual Screening by Simultaneous Protein-Ligand Docking and Ligand-Ligand Alignment
437
FlexX‐Scan: Fast, structure‐based virtual screening
438
Automatic prediction of protein function
439
Impact of physical properties of formulations on bioavailability of active substance: current and novel drugs with cyclosporine.
440
A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae)
441
MULTIPROSPECTOR: An algorithm for the prediction of protein–protein interactions by multimeric threading
442
Introduction to Neural Networks for Signal Processing
443
Exploiting Generative Models in Discriminative Classifiers
444
Conservation of gene order: a fingerprint of proteins that physically interact.
445
Long Short-Term Memory
446
Some Studies in Machine Learning Using the Game of Checkers
447
Support-Vector Networks
449
Backpropagation Applied to Handwritten Zip Code Recognition
450
Learning representations by back-propagating errors
451
Trends in Pattern Recognition and Machine Learning
452
Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position
454
The numerical solution of variational problems
455
Gradient Theory of Optimal Flight Paths
456
Computing Machinery and Intelligence
457
25:1315–1360 therapeutic targets for soft tissue sarcomas
458
:1315–1360 and Molecular Docking of Hit Compounds to DPP-8 and DPP-9 Enzymes
459
25:1315–1360 on virtual screening strategy
460
WGMFDDA: A Novel Weighted-Based Graph Regularized Matrix Factorization for Predicting Drug-Disease Associations
461
ACP-GCN: The Identification of Anticancer Peptides Based on Graph Convolution Networks
462
7 Ways to Handle Missing Values in Machine Learning | by Satyam Kumar | Towards Data Science
463
Predicting Phase 3 Clinical Trial Results by Modeling Phase 2 Clinical Trial Subject Level Data Using Deep Learning
464
Prediction of active compounds from SMILES codes using backpropagation algorithm
465
Prediction of Human Intestinal Absorption of Compounds Using Artificial Intelligence Techniques.
466
An Introduction to Machine Learning
467
Drug-repositioning opportunities for cancer therapy: novel molecular targets for known compounds.
468
A Practical Guide to The Cancer Genome Atlas (TCGA)
470
DrugNet: Network-based drug-disease prioritization by integrating heterogeneous data
471
Chapter 12 – Future Avenues
472
Identification of a natural product-like STAT3 dimerization inhibitor by structure-based virtual screening
473
Chapter 9 - Newer QSAR Techniques
474
Book Title-Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment (eds)
475
ChemSpider. Search and Share Chemistry
476
Cheminformatics at the interface of medicinal chemistry and proteomics.
477
VEGA-QSAR: AI Inside a Platform for Predictive Toxicology
478
From Experimental Approaches to Computational Techniques: A Review on the Prediction of Protein-Protein Interactions
479
Quantitative structure-activity relationships of antioxidant phenolic compounds.
480
Virtual screening for the discovery of bioactive natural products
481
Data storage and analysis in ArrayExpress.
482
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
483
A logical calculus of the ideas immanent in nervous activity
484
Neocognitron: A hierarchical neural network capable of visual pattern recognition
485
The Perceptron: A Perceiving and Recognizing Automaton
487
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