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RESEARCH PAPER · Nature Communications · 2021

Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias

Dávid Péter Kovács, William McCorkindale, Alpha A. Lee

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Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers biasOriginalA transferable active-learning strategy for reactive molecular force fields91Linear Atomic Cluster Expansion Force Fields for Organic Molecules: beyond RMSE0Linear Atomic Cluster Expansion Force Fields for Organic Molecules: beyond RMSE6Linear Atomic Cluster Expansion Force Fields for Organic Molecules: beyond RMSE1Machine Learning in Chemical Engineering: Strengths, Weaknesses, Opportunities, and Threats323Predicting scalar coupling constants by graph angle-attention neural network10Linear Atomic Cluster Expansion Force Fields for Organic Molecules: beyond RMSE6Linear Atomic Cluster Expansion Force Fields for Organic Molecules: Beyond RMSE121Artificial Intelligence based Approach for Rapid Material Discovery: From Chemical Synthesis to Quantum Materials0Beyond structural insight: a deep neural network for the prediction of Pt L 2/3 -edge X-ray absorption spectra12Providing direction for mechanistic inferences in radical cascade cyclization using a Transformer model8Reproducing the invention of a named reaction: zero-shot prediction of unseen chemical reactions17Scientific Overconfidence in High-Performing Materials AI Systems0RetroTRAE: retrosynthetic translation of atomic environments with Transformer0Machine Learning at the Interface of Polymer Science and Biology: How Far Can We Go?21Retrosynthetic reaction pathway prediction through neural machine translation of atomic environments99Machine intelligence for chemical reaction space124Autonomous design of new chemical reactions using a variational autoencoder27Accurate, affordable, and generalizable machine learning simulations of transition metal x-ray absorption spectra using the XANESNET deep neural network43Machine learning in medical applications: A review of state-of-the-art methods541Machine-learning-guided reaction kinetics prediction towards solvent identification for chemical absorption of carbonyl sulfide29Chemical property prediction under experimental biases5Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels10Developing green and sustainable concrete in integrating with different urban wastes92Extended Connectivity Fingerprints as a Chemical Reaction Representation for Enantioselective Organophosphorus-Catalyzed Asymmetric Reaction Prediction25Z-number-based AQI in rough set theoretic framework for interpretation of air quality for different thresholds of PM2.5 and PM109Concepts and applications of chemical fingerprint for hit and lead screening139Explainable machine learning in materials science501Explainable Solvation Free Energy Prediction Combining Graph Neural Networks with Chemical Intuition43Standardization of chemical compounds using language modeling1Machine-learned digital phase switch for sustainable chemical production9Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery138Prediction and interpretation of antibiotic-resistance genes occurrence at recreational beaches using machine learning models31Quantum chemical data generation as fill-in for reliability enhancement of machine-learning reaction and retrosynthesis planning14Evolution of design approaches in asymmetric organocatalysis over the last decade5Spatiotemporal pattern of greenhouse gas emissions in China’s wastewater sector and pathways towards carbon neutrality254Global reactivity models are impactful in industrial synthesis applications15Reconstruction of lossless molecular representations from fingerprints33Interpretable Machine Learning Model for Predicting Interaction Energies between Dimethyl Sulfide and Potential Absorbing Solvents8Reaction Impurity Prediction using a Data Mining Approach**9Reproducing the color with reformulated recipe0Retrosynthesis prediction using an end-to-end graph generative architecture for molecular graph editing81Machine learning-aided prediction of nitrogen heterocycles in bio-oil from the pyrolysis of biomass48RetroRanker: leveraging reaction changes to improve retrosynthesis prediction through re-ranking10Characterizing Uncertainty in Machine Learning for Chemistry111Machine Learning for Bridging the Gap between Density Functional Theory and Coupled Cluster Energies23Making sense of mineral trace-element data – How to avoid common pitfalls in statistical analysis and interpretation38Standardizing chemical compounds with language models4A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges8Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction6Scientific discovery in the age of artificial intelligence1779Four-Dimensional-Spacetime Atomistic Artificial Intelligence Models19A Graph Neural Network Model with a Transparent Decision-Making Process Defines the Applicability Domain for Environmental Estrogen Screening16Retrosynthesis prediction with an interpretable deep-learning framework based on molecular assembly tasks121Comment on ‘Physics-based representations for machine learning properties of chemical reactions’10A machine learning approach for predicting the reactivity power of hypervalent iodine compounds7Accelerated chemical science with AI86Thermodynamics of Water and Ice from a Fast and Scalable First-Principles Neuroevolution Potential35Application of machine learning in chemical engineering: outlook and perspectives31Unveiling the Quantitative Relationships between Electron Distribution and Steric Hindrance of Organic Amines and Their Reaction Rates with Carbonyl Sulfur: A Theoretical Calculation Investigation8Autonomous generation of single photon emitting materials1Investigating the reliability and interpretability of machine learning frameworks for chemical retrosynthesis15Machine learning for catalyst design: data matters3Advances in machine learning with chemical language models in molecular property and reaction outcome predictions29Generalizability Improvement of Interpretable Symbolic Regression Models for Quantitative Structure–Activity Relationships5Application of machine learning in tax prediction: A review with practical approaches18Exploring Chemical Reaction Space with Machine Learning Models: Representation and Feature Perspective26RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction5Machine Learning-Based Yield Prediction for First-Row Transition Metal Catalyzed Cross-Coupling Reactions0Do Chemformers Dream of Organic Matter? Evaluating a Transformer Model for Multistep Retrosynthesis33Transfer learning for Heterocycle Synthesis Prediction0Data Analytics for Catalysis Predictions: Are We Ready Yet?5DrugGym: A testbed for the economics of autonomous drug discovery7A novel coupling interpretable machine learning framework for water quality prediction and environmental effect understanding in different flow discharge regulations of hydro-projects19Accurately Predicting Barrier Heights for Radical Reactions in Solution Using Deep Graph Networks17Leveraging graph neural networks to predict Hammett’s constants for benzoic acid derivatives7A comprehensive study of cytosine-ZnO interactions: Theoretical and experimental insights26BUSClean: Open-source software for breast ultrasound image pre-processing and knowledge extraction for medical AI7Integrating machine learning to uncover homogeneous catalytic mechanisms in N‐vinyl‐pyrrolidone synthesis1ChemTransGNN + +: from Reactants to Products via Multiscale Graph-Transformer Modeling of Reaction Pathways0Computational tools for the prediction of site- and regioselectivity of organic reactions33Performance assessment of various graph neural network architectures for predicting yields in cross-coupling reactions2Inorganic Chemical Reaction Predictor Using Random Forest and Support Vector Machine2Graph-Theory Algorithm for Prediction of Electrolyte Degradation Reactions in Lithium- and Sodium-Ion Batteries1Challenging Reaction Prediction Models to Generalize to Novel Chemistry23In Silico Exploration of Metabolite-Derived Soft Materials Using a Chemical Reaction Network0Interpreting surface adsorption with band data: a machine learning perspective on quantum orientation1RadicalRetro: A Deep Learning-Based Retrosynthesis Model for Radical Reactions1Optimizing Vanadium-Catalyzed Epoxidation Reactions: Machine-Learning-Driven Yield Predictions and Data Augmentation6Exploration of Quinolone Amides as Promising Candidates for the Treatment of Human African Trypanosomiasis: In Silico Virtual Screening and Molecular Docking3Transfer Learning for Heterocycle Retrosynthesis3Inter‐Hammett: Enhancing Interpretability in Hammett‘s Constant Prediction via Extracting Rules1Hybrid 2-Quinolone–1,2,3-triazole Compounds: Rational Design, In Silico Optimization, Synthesis, Characterization, and Antibacterial Evaluation3Deep learning in chemical synthesis and retrosynthesis0Kinetic predictions for S N 2 reactions using the BERT architecture: comparison and interpretation0An exploration of dataset bias in single-step retrosynthesis prediction1AI-powered medicinal chemistry and translational drug development0Bayesian optimization- and high-throughput-guided synthesis of monofluoroalkenes via defluorinative C–C bond formation0Case studies: Breakthroughs at the intersection of ML and chemical engineering0Data-Driven Synergistic Optimization of Biomass-Plastic Co-Pyrolysis: Predicting Dynamic Activation Energy via Transfer Learning0Quantum-Informed Molecular Learning for Natural Product Chemical Space Through Electronic Structure, Reactivity, Intermolecular Forces, and Data-Efficient Property Prediction0Reaction Prediction Can Change How Natural Product Scaffolds Are Optimized by Connecting Biosynthetic Logic, Semisynthesis, and Medicinal Chemistry Search0Transfer learning for reaction optimisation: overview of its applications and limits0Collision-free morgan fingerprints: a principled approach to enhance machine learning performance and interpretability in chemistry4Explainable AI methods for drug discovery: A survey of interpretability, metrics and mechanistic insight13Substrate Scope in Organic Reactions: Comparison of Fingerprint-Based and Reactivity-Based Similarity Metrics1MolXProt: A Cross-Attention Transformer-Based Graph Neural Network for Protein-Ligand Binding Affinity Prediction1Chemical Language Model Applications in Medicinal Chemistry0Reaction-Center-Guided Reranking of Transformer Product Predictions with a Product-Conditioned Graph Neural Network0AI-assisted molecular and materials discovery in chemistry and chemical engineering: A methodological and bibliometric review0

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