Papers citing Interpretation of Quantitative Structure–Activity Relationship Models: Past, Present, and Future
Quantitative structure–activity relationships for primary aerobic biodegradation of organic chemicals in pristine surface waters: starting points for predicting biodegradation under acclimatization
Environmental Science Processes & Impacts · 2017
Tom M. Nolte, Kevin Pinto-Gil, A. Jan Hendriks, Ad M.J. Ragas, Manuel Pastor
Read original paper ↗ ·Predictive and mechanistic multivariate linear regression models for reaction development
Chemical Science · 2018
Celine B. Santiago, Jing-Yao Guo, Matthew S. Sigman
Read original paper ↗ ·QSAR: What Else?
Methods in molecular biology · 2018
Giuseppina C. Gini
Read original paper ↗ ·e-Bitter: Bitterant Prediction by the Consensus Voting From the Machine-Learning Methods
Frontiers in Chemistry · 2018
Suqing Zheng, Mengying Jiang, Chengwei Zhao, Rui Zhu, Zhicheng Hu, Yong Xu, Lin Fu
Read original paper ↗ ·Thin-layer chromatography in quantitative structure-activity relationship studies
Journal of Liquid Chromatography & Related Technologies · 2018
Dušanka Milojković‐Opsenica, Filip Lj. Andrić, Sandra B. Šegan, Jelena Trifković, Živoslav Tešić
Read original paper ↗ ·Photoredox‐Catalyzed Decarboxylative Oxidation of Arylacetic Acids
Chemistry - An Asian Journal · 2018
Yota Sakakibara, Phillippa Cooper, Kei Murakami, Kenichiro Itami
Read original paper ↗ ·The Current Limits in Virtual Screening and Property Prediction
Future Medicinal Chemistry · 2018
Michael Christopher Hutter
Read original paper ↗ ·Multiple quantitative structure-activity relationships (QSARs) analysis for orally active trypanocidal N-myristoyltransferase inhibitors
Journal of Molecular Structure · 2018
Vijay Hariram Masand, Nahed N. E. El-Sayed, Mukesh U. Bambole, Vaijant R. Patil, Sumer D. Thakur
Read original paper ↗ ·Optimal Piecewise Linear Regression Algorithm for QSAR Modelling
Molecular Informatics · 2018
Jonathan Cardoso‐Silva, George Papadatos, Lazaros G. Papageorgiou, Sophia Tsoka
Read original paper ↗ ·Comparing quantitative prediction methods for the discovery of small-molecule chiral catalysts
Nature Reviews Chemistry · 2018
Jolene P. Reid, Matthew S. Sigman
Read original paper ↗ ·Deep learning for predicting toxicity of chemicals: a mini review
Journal of Environmental Science and Health Part C · 2018
Weihao Tang, Jingwen Chen, Zhongyu Wang, Hong‐Bin Xie, Huixiao Hong
Read original paper ↗ ·Finding the structural requirements of diverse HIV-1 protease inhibitors using multiple QSAR modelling for lead identification
SAR and QSAR in environmental research · 2018
Amit Kumar Halder
Read original paper ↗ ·Interpretation of QSAR Models: Mining Structural Patterns Taking into Account Molecular Context
Molecular Informatics · 2018
Mariia Matveieva, M Cronin, Павел Геннадьевич Полищук
Read original paper ↗ ·Study of the Applicability Domain of the QSAR Classification Models by Means of the Rivality and Modelability Indexes
Molecules · 2018
Irene Luque Ruiz, Miguel Ángel Gómez‐Nieto
Read original paper ↗ ·In-Silico Extraction of Design Ideas Using MMPA-by-QSAR and its Application on ADME Endpoints
Journal of Chemical Information and Modeling · 2018
Alexios Koutsoukas, George Chang, Christopher E. Keefer
Read original paper ↗ ·QSAR investigation of acute toxicity of organic compounds during oral administration to mice
Biomeditsinskaya Khimiya · 2019
O.V. Tinkov, Veniamin Y. Grigorev, Павел Геннадьевич Полищук, A. V. Yarkov, Oleg A. Raevsky
Read original paper ↗ ·Predictive Multitask Deep Neural Network Models for ADME-Tox Properties: Learning from Large Data Sets
Journal of Chemical Information and Modeling · 2019
Jan Wenzel, Hans Matter, Friedemann Schmidt
Read original paper ↗ ·Development and design of novel cardiovascular therapeutics based on Rho kinase inhibition—In silico approach
Computational Biology and Chemistry · 2019
S Zdravkovic, Milan Pavlović, Svetlana Apostlović, Goran Pante Koracevic, Sonja Šalinger-Martinović, Dragana Stanojević, Dusan T. Sokolovic, Aleksandar M. Veselinović
Read original paper ↗ ·Predicting Blood–Brain Partitioning of Small Molecules Using a Novel Minimalistic Descriptor-Based Approach via the 3D-RISM-KH Molecular Solvation Theory
ACS Omega · 2019
Dipankar Roy, Vijaya Kumar Hinge, Andriy Kovalenko
Read original paper ↗ ·Interpretation of QSAR Models by Coloring Atoms According to Changes in Predicted Activity: How Robust Is It?
Journal of Chemical Information and Modeling · 2019
Robert P. Sheridan
Read original paper ↗ ·In Need of Bias Control: Evaluating Chemical Data for Machine Learning in Structure-Based Virtual Screening
Journal of Chemical Information and Modeling · 2019
Jochen Sieg, Florian Flachsenberg, Matthias Rarey
Read original paper ↗ ·Optimization of a Deep-Learning Method Based on the Classification of Images Generated by Parameterized Deep Snap a Novel Molecular-Image-Input Technique for Quantitative Structure–Activity Relationship (QSAR) Analysis
Frontiers in Bioengineering and Biotechnology · 2019
Yasunari Matsuzaka, Yoshihiro Uesawa
Read original paper ↗ ·From machine learning to deep learning: Advances in scoring functions for protein–ligand docking
Wiley Interdisciplinary Reviews Computational Molecular Science · 2019
Chao Shen, Junjie Ding, Zhe Wang, Dongsheng Cao, Xiaoqin Ding, Tingjun Hou
Read original paper ↗ ·Contributions of Computer-Based Chemical Modeling Technologies on the Risk Assessment and the Environmental Fate Study of (Nano)pesticides
Springer eBooks · 2019
Juan José Villaverde, Beatriz Sevilla-Morán, Carmen López‐Goti, José Luis Alonso‐Prados, Pilar Sandín‐España
Read original paper ↗ ·Time-Domain Analysis of Molecular Dynamics Trajectories Using Deep Neural Networks: Application to Activity Ranking of Tankyrase Inhibitors
Journal of Chemical Information and Modeling · 2019
Vladimir P. Berishvili, Valentin O. Perkin, Andrew E. Voronkov, Eugene V. Radchenko, Riyaz Syed, Chittireddy Venkata Ramana Reddy, Viness Pillay, Pradeep Kumar, Yahya Essop Choonara, Ähmed Kamal, Vladimir A. Palyulin
Read original paper ↗ ·Effect of pectin on the interactions among phenolic compounds determined by antioxidant capacity
Journal of Molecular Structure · 2019
Gilberto Mercado‐Mercado, Laura Alejandra De la Rosa, Emilio ́Álvarez-Parrilla
Read original paper ↗ ·Artificial Neural Network (ANN) Modeling of Odor Threshold Property of Diverse Chemical Constituents of Black Tea and Coffee
International Journal of Quantitative Structure-Property Relationships · 2019
Gopala Krishna Jillella, Probir Kumar Ojha
Read original paper ↗ ·Interpretation of Compound Activity Predictions from Complex Machine Learning Models Using Local Approximations and Shapley Values
Journal of Medicinal Chemistry · 2019
Raquel Rodríguez-Pérez, Jürgen Bajorath
Read original paper ↗ ·Neural-based approaches to overcome feature selection and applicability domain in drug-related property prediction
Applied Soft Computing · 2019
María Virginia Sabando, Ignacio Ponzoni, Axel J. Soto
Read original paper ↗ ·Autonome Entdeckung in den chemischen Wissenschaften, Teil I: Fortschritt
Angewandte Chemie · 2019
Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen
Read original paper ↗ ·Autonome Entdeckung in den chemischen Wissenschaften, Teil II: Ausblick
Angewandte Chemie · 2019
Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen
Read original paper ↗ ·Autonomous Discovery in the Chemical Sciences Part I: Progress
Angewandte Chemie International Edition · 2019
Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen
Read original paper ↗ ·Autonomous Discovery in the Chemical Sciences Part II: Outlook
Angewandte Chemie International Edition · 2019
Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen
Read original paper ↗ ·Toward Interpretable Machine Learning Models for Materials Discovery
Advanced Intelligent Systems · 2019
Paulius Mikulskis, Morgan R. Alexander, David Alan Winkler
Read original paper ↗ ·A Random Forest Model to Predict the Activity of a Large Set of Soluble Epoxide Hydrolase Inhibitors Solely Based on a Set of Simple Fragmental Descriptors
Combinatorial Chemistry & High Throughput Screening · 2019
Jamal Shamsara
Read original paper ↗ ·Identification of prodigious and under-privileged structural features for RG7834 analogs as Hepatitis B virus expression inhibitor
Medicinal Chemistry Research · 2019
Vijay Hariram Masand, Nahed N. E. El-Sayed, Vesna Rastija, Mithilesh M. Rathore, Maja Karnaš
Read original paper ↗ ·A Comprehensive QSAR Study on Antileishmanial and Antitrypanosomal Cinnamate Ester Analogues
Molecules · 2019
Freddy A. Bernal, Thomas Jürgen Schmidt
Read original paper ↗ ·Exploration of histone deacetylase 8 inhibitors through classification QSAR study: Part II
Journal of Molecular Structure · 2019
Sk. Abdul Amin, Nilanjan Adhikari, Tarun Jha
Read original paper ↗ ·Essential elements regulating HDAC8 inhibition: a classification based structural analysis and enzyme-inhibitor interaction study of hydroxamate based HDAC8 inhibitors
Journal of Biomolecular Structure and Dynamics · 2019
Suvankar Banerjee, Sk. Abdul Amin, Nilanjan Adhikari, Tarun Jha
Read original paper ↗ ·Prospects for Discovering the Secondary Metabolites of Cordyceps Sensu Lato by the Integrated Strategy
Medicinal Chemistry · 2019
Shabana Bibi, Yuanbing Wang, Dexiang Tang, Mohammad Amjad Kamal, Hong Yu
Read original paper ↗ ·Exploring indole derivatives as myeloid cell leukaemia-1 (Mcl-1) inhibitors with multi-QSAR approach: a novel hope in anti-cancer drug discovery
New Journal of Chemistry · 2020
Sk. Abdul Amin, Kalyan Ghosh, Dipayan Mondal, Tarun Jha, Shovanlal Gayen
Read original paper ↗ ·QSAR without borders
Chemical Society Reviews · 2020
Eugene N. Muratov, Jürgen Bajorath, Robert P. Sheridan, Igor V. Tetko, Dmitry A. Filimonov, Vladimir Poroikov, Tudor Ionel Oprea, Igor I. Baskin, Alexandre A. Varnek, Adrián E. Roitberg, Olexandr Isayev, Stefano Curtalolo, Denis Fourches, Yoram Cohen, Alán Aspuru‐Guzik, David Alan Winkler, Dimitris K. Agrafiotis, Artem R Cherkasov, Alexander Tropsha
Read original paper ↗ ·The Cross-Interpretation of QSAR Toxicological Models
Lecture notes in computer science · 2020
O.V. Tinkov, Павел Геннадьевич Полищук, Veniamin Y. Grigorev, Yuri B. Porozov
Read original paper ↗ ·Quantum chemical predictions of water–octanol partition coefficients applied to the SAMPL6 logP blind challenge
Journal of Computer-Aided Molecular Design · 2020
Michael R. Jones, Bernard R. Brooks
Read original paper ↗ ·QSAR studies on benzothiophene derivatives as Plasmodium falciparum N‐myristoyltransferase inhibitors: Molecular insights into affinity and selectivity
Drug Development Research · 2020
Mariana Lopes Garcia, Andrew Albert de Oliveira, Renata Vieira Bueno, Victor H. R. Nogueira, Guilherme E. de Souza, Rafael V. C. Guido
Read original paper ↗ ·Discriminations of active from inactive HDAC8 inhibitors Part II: Bayesian classification study to find molecular fingerprints
SAR and QSAR in environmental research · 2020
Sk. Abdul Amin, Suvankar Banerjee, Nilanjan Adhikari, Tarun Jha
Read original paper ↗ ·A self-attention based message passing neural network for predicting molecular lipophilicity and aqueous solubility
Journal of Cheminformatics · 2020
Bowen Tang, Skyler T. Kramer, Meijuan Fang, Ying‐Kun Qiu, Zhen Wu, Dong He Xu
Read original paper ↗ ·VISAR: an interactive tool for dissecting chemical features learned by deep neural network QSAR models
Bioinformatics · 2020
Qingyang Ding, Siyu Hou, Songpeng Zu, Yonghui Zhang, Shao Li
Read original paper ↗ ·In silico toxicology: From structure–activity relationships towards deep learning and adverse outcome pathways
Wiley Interdisciplinary Reviews Computational Molecular Science · 2020
Jennifer Hemmerich, Gerhard Franz Ecker
Read original paper ↗ ·Discriminant models on mitochondrial toxicity improved by consensus modeling and resolving imbalance in training
Chemosphere · 2020
Weihao Tang, Jingwen Chen, Huixiao Hong
Read original paper ↗ ·