Papers Retrosynthesis
“Retrosynthesis” 태그가 달린 논문 110편 · 필터 해제
DeepRetro: Retrosynthetic Pathway Discovery using Iterative LLM Reasoning
Retrosynthesis, the identification of precursor molecules for a target compound, is pivotal for synthesizing complex molecules, but faces challenges in discovering novel pathways beyond predefined templates. Recent large…
HallucinationLarge Language ModelRetrosynthesisRETRO SYNFLOW: Discrete Flow Matching for Accurate and Diverse Single-Step Retrosynthesis
A fundamental problem in organic chemistry is identifying and predicting the series of reactions that synthesize a desired target product molecule. Due to the combinatorial nature of the chemical search space, single-ste…
RetrosynthesisSingle-step retrosynthesisDiffER: Categorical Diffusion for Chemical Retrosynthesis
Methods for automatic chemical retrosynthesis have found recent success through the application of models traditionally built for natural language processing, primarily through transformer neural networks. These models h…
RetrosynthesisLLM-Augmented Chemical Synthesis and Design Decision Programs
Retrosynthesis, the process of breaking down a target molecule into simpler precursors through a series of valid reactions, stands at the core of organic chemistry and drug development. Although recent machine learning (…
Decision MakingMulti-step retrosynthesisNavigateRetrosynthesis+1Leveraging Large Language Models for enzymatic reaction prediction and characterization
Predicting enzymatic reactions is crucial for applications in biocatalysis, metabolic engineering, and drug discovery, yet it remains a complex and resource-intensive task. Large Language Models (LLMs) have recently demo…
Drug DiscoveryIn-Context Learningparameter-efficient fine-tuningRetrosynthesisEnhancing Chemical Reaction and Retrosynthesis Prediction with Large Language Model and Dual-task Learning
Chemical reaction and retrosynthesis prediction are fundamental tasks in drug discovery. Recently, large language models (LLMs) have shown potential in many domains. However, directly applying LLMs to these tasks faces t…
Drug DesignDrug DiscoveryLanguage ModelingLanguage Modelling+3Chemical knowledge-informed framework for privacy-aware retrosynthesis learning
Chemical reaction data is a pivotal asset, driving advances in competitive fields such as pharmaceuticals, materials science, and industrial chemistry. Its proprietary nature renders it sensitive, as it often includes co…
Privacy PreservingRetrosynthesisNatureLM: Deciphering the Language of Nature for Scientific Discovery
Foundation models have revolutionized natural language processing and artificial intelligence, significantly enhancing how machines comprehend and generate human languages. Inspired by the success of these foundation mod…
Drug DiscoveryRetrosynthesisscientific discoveryRetro-Rank-In: A Ranking-Based Approach for Inorganic Materials Synthesis Planning
Retrosynthesis strategically plans the synthesis of a chemical target compound from simpler, readily available precursor compounds. This process is critical for synthesizing novel inorganic materials, yet traditional met…
Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATIONOut-of-Distribution GeneralizationRetrosynthesisEnhancing Retrosynthesis with Conformer: A Template-Free Method
Retrosynthesis plays a crucial role in the fields of organic synthesis and drug development, where the goal is to identify suitable reactants that can yield a target product molecule. Although existing methods have achie…
RetrosynthesisLeveraging Large Language Models as Knowledge-Driven Agents for Reliable Retrosynthesis Planning
Identifying reliable synthesis pathways in materials chemistry is a complex task, particularly in polymer science, due to the intricate and often non-unique nomenclature of macromolecules. To address this challenge, we p…
Knowledge GraphsRetrievalRetrosynthesisGDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation
Retrosynthesis prediction focuses on identifying reactants capable of synthesizing a target product. Typically, the retrosynthesis prediction involves two phases: Reaction Center Identification and Reactant Generation. H…
molecular representationRetrosynthesisASKCOS: an open source software suite for synthesis planning
The advancement of machine learning and the availability of large-scale reaction datasets have accelerated the development of data-driven models for computer-aided synthesis planning (CASP) in the past decade. Here, we d…
Decision MakingPredictionRetrosynthesisChimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases
Planning and conducting chemical syntheses remains a major bottleneck in the discovery of functional small molecules, and prevents fully leveraging generative AI for molecular inverse design. While early work has shown t…
RetrosynthesisSuitability of Large Language Models for Extraction of High-Quality Chemical Reaction Dataset from Patent Literature
With the advent of artificial intelligence (AI), it is now possible to design diverse and novel molecules from previously unexplored chemical space. However, a challenge for chemists is the synthesis of such molecules. R…
RetrosynthesisRetrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert Knowledge
While inorganic retrosynthesis planning is essential in the field of chemical science, the application of machine learning in this area has been notably less explored compared to organic retrosynthesis planning. In this …
RetrievalRetrosynthesisBatGPT-Chem: A Foundation Large Model For Retrosynthesis Prediction
Retrosynthesis analysis is pivotal yet challenging in drug discovery and organic chemistry. Despite the proliferation of computational tools over the past decade, AI-based systems often fall short in generalizing across …
Drug DiscoveryLanguage ModellingLarge Language ModelRetrosynthesisDirectly Optimizing for Synthesizability in Generative Molecular Design using Retrosynthesis Models
Synthesizability in generative molecular design remains a pressing challenge. Existing methods to assess synthesizability span heuristics-based methods, retrosynthesis models, and synthesizability-constrained molecular g…
Drug DiscoveryRetrosynthesisAccelerating the inference of string generation-based chemical reaction models for industrial applications
Template-free SMILES-to-SMILES translation models for reaction prediction and single-step retrosynthesis are of interest for industrial applications in computer-aided synthesis planning systems due to their state-of-the-…
PredictionRetrosynthesisSingle-step retrosynthesisTranslationDouble-Ended Synthesis Planning with Goal-Constrained Bidirectional Search
Computer-aided synthesis planning (CASP) algorithms have demonstrated expert-level abilities in planning retrosynthetic routes to molecules of low to moderate complexity. However, current search methods assume the suffic…
Retrosynthesisvalid