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RESEARCH PAPER · Chemical Communications · 2022

Modern machine learning for tackling inverse problems in chemistry: molecular design to realization

Bhuvanesh Sridharan, Manan Goel, U. Deva Priyakumar

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Modern machine learning for tackling inverse problems in chemistry: molecular design to realizationOriginalDeep Reinforcement Learning for Molecular Inverse Problem of Nuclear Magnetic Resonance Spectra to Molecular Structure36Efficient and enhanced sampling of drug‐like chemical space for virtual screening and molecular design using modern machine learning methods26An Improved Model for Predicting Compound Retrosynthesizability Using Machine Learning3MatFlow: A System for Knowledge-based Novel Materials Design using Machine Learning5Application of SMILES to Cheminformatics and Generation of Optimum SMILES Descriptors Using CORAL Software2Designing hexaphyrins for high-potential NLO switches: the synergy of core-modifications and meso -substitutions15High-throughput transient photoluminescence spectrometer for deep learning of thermally activated delayed fluorescence materials11Computational Design and Manufacturing of Sustainable Materials through First-Principles and Materiomics73Computer-aided multi-objective optimization in small molecule discovery128Conditional Molecular Generation Net Enables Automated Structure Elucidation Based on 13 C NMR Spectra and Prior Knowledge34CMGN: a conditional molecular generation net to design target-specific molecules with desired properties21Data-Driven Inverse Problem for Optimizing the Induction Hardening Process of C45 Spur-Gear8Identifying potential drug-target interactions based on ensemble deep learning12Machine Learning Methods for Small Data Challenges in Molecular Science499GIDnets: Generative Neural Networks for Solving Inverse Design Problems via Latent Space Exploration0Advances in the Application of Artificial Intelligence-Based Spectral Data Interpretation: A Perspective64Recent Progresses in Neural Networks for Alzheimer's Disease Detection1Machine learning for rapid inference of critical dimensions in optical metrology of nanopatterned surfaces9Rational design of antimicrobial peptides: an optimization approach14Exploring the Intersection of Geophysics and Diagnostic Imaging in the Health Sciences5An extensive review on lung cancer therapeutics using machine learning techniques: state-of-the-art and perspectives65Understanding predictions of drug profiles using explainable machine learning models24Hit me with your best shot: Integrated hit discovery for the next generation of drug targets15A review of large language models and autonomous agents in chemistry269Predicting Rate Constants of Hydrogen Abstraction Reactions between OH/HO2 and Alkanes by Machine Learning Models5Generation of Rational Drug-like Molecular Structures Through a Multiple-Objective Reinforcement Learning Framework4Guided multi-objective generative AI to enhance structure-based drug design20Transition metal phosphide/ molybdenum disulfide heterostructures towards advanced electrochemical energy storage: recent progress and challenges40Using machine learning to map simulated noisy and laser-limited multidimensional spectra to molecular electronic couplings6Chemically Informed Deep Learning for Interpretable Radical Reaction Prediction5In silico modeling of targeted protein degradation22Database of Nonaqueous Proton-Conducting Materials1Discovery, design, and engineering of enzymes based on molecular retrobiosynthesis10Druggability Studies of Benzene Sulfonamide Substituted Diarylamide (E3) as a Novel Diuretic2Artificial Intelligence in Molecular Optimization: Current Paradigms and Future Frontiers4Optimization of Catalysts Using Computational Chemistry, Machine Learning, and Cheminformatics0Integrating AI into OLED material design: a comprehensive review of computational frameworks, challenges, and opportunities16Self-driving laboratories with artificial intelligence: An overview of process systems engineering perspective14Towards self-driving/autonomous material discovery lab1Inverse ligand design: a generative data-driven model for optimizing vanadyl-based epoxidation catalysts5Recent trends and the need for organic semiconductors for a sustainable future0LaMGen: LLM-based 3D molecular generation for multi-target drug design2Back to the Electrofuture: Named Reactions Powered by Electroorganic Syntheses1Design of Multifunctional Bioactive Peptides for Potential Application in Food Packaging: A Machine-Learning-Integrated Optimization Framework1Enhancing Conditional Molecular Generation With Pretrained SMILES Transformer and Contrastive Representation Learning0Advanced representations and generative artificial intelligence for polyolefins0Inverting Non-injective Functions with Twin Neural Network Regression1From molecular descriptors to data-driven design: Multiscale modelling and machine learning for shape memory polymers0Toward autonomous chemical discovery: agentic AI in organic synthesis and nanochemistry0

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  1. Deep Reinforcement Learning for Molecular Inverse Problem of Nuclear Magnetic Resonance Spectra to Molecular Structure

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  2. Efficient and enhanced sampling of drug‐like chemical space for virtual screening and molecular design using modern machine learning methods

    Wiley Interdisciplinary Reviews Computational Molecular Science · 2022-09-16

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  3. An Improved Model for Predicting Compound Retrosynthesizability Using Machine Learning

    IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · 2022-11-01

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  4. MatFlow: A System for Knowledge-based Novel Materials Design using Machine Learning

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  5. Application of SMILES to Cheminformatics and Generation of Optimum SMILES Descriptors Using CORAL Software

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  6. Designing hexaphyrins for high-potential NLO switches: the synergy of core-modifications and meso -substitutions

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    Eline Desmedt, David Smets, Tatiana Marianne Woller, Mercedes Alonso, Freija De Vleeschouwer

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  7. High-throughput transient photoluminescence spectrometer for deep learning of thermally activated delayed fluorescence materials

    Journal of Materials Chemistry C · 2023-01-01

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  8. Computational Design and Manufacturing of Sustainable Materials through First-Principles and Materiomics

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  9. Computer-aided multi-objective optimization in small molecule discovery

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  10. Conditional Molecular Generation Net Enables Automated Structure Elucidation Based on 13 C NMR Spectra and Prior Knowledge

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  11. CMGN: a conditional molecular generation net to design target-specific molecules with desired properties

    Briefings in Bioinformatics · 2023-05-16

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  12. Data-Driven Inverse Problem for Optimizing the Induction Hardening Process of C45 Spur-Gear

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  13. Identifying potential drug-target interactions based on ensemble deep learning

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  14. Machine Learning Methods for Small Data Challenges in Molecular Science

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  15. GIDnets: Generative Neural Networks for Solving Inverse Design Problems via Latent Space Exploration

    International Joint Conference on Artificial Intelligence · 2023-08-01

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  16. Advances in the Application of Artificial Intelligence-Based Spectral Data Interpretation: A Perspective

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  17. Recent Progresses in Neural Networks for Alzheimer's Disease Detection

    Preprints.org · 2023-10-12

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  18. Machine learning for rapid inference of critical dimensions in optical metrology of nanopatterned surfaces

    CIRP journal of manufacturing science and technology · 2023-10-20

    Ramin Sabbagh, Alec Stothert, Dragan Djurdjanović

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  19. Rational design of antimicrobial peptides: an optimization approach

    Molecular Systems Design & Engineering · 2023-12-12

    Danush Sadasivam, Pranav Nambiar, Arnab Dutta, Debirupa Mitra

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  20. Exploring the Intersection of Geophysics and Diagnostic Imaging in the Health Sciences

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  21. An extensive review on lung cancer therapeutics using machine learning techniques: state-of-the-art and perspectives

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  22. Understanding predictions of drug profiles using explainable machine learning models

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  23. Hit me with your best shot: Integrated hit discovery for the next generation of drug targets

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  24. A review of large language models and autonomous agents in chemistry

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  25. Predicting Rate Constants of Hydrogen Abstraction Reactions between OH/HO2 and Alkanes by Machine Learning Models

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  26. Generation of Rational Drug-like Molecular Structures Through a Multiple-Objective Reinforcement Learning Framework

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  27. Guided multi-objective generative AI to enhance structure-based drug design

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  30. Chemically Informed Deep Learning for Interpretable Radical Reaction Prediction

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  36. Optimization of Catalysts Using Computational Chemistry, Machine Learning, and Cheminformatics

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  39. Towards self-driving/autonomous material discovery lab

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  40. Inverse ligand design: a generative data-driven model for optimizing vanadyl-based epoxidation catalysts

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