Precision fragment addition: domain-specific DeepFrag2 models for smarter lead optimization [0.03%]
精准片段替换：药物分子领域专用DeepFrag2模型助力更智能的先导化合物优化
César R García-Jacas,Harrison Green,Shayne D Wierbowski et al.
César R García-Jacas et al.
This study introduces a series of machine-learning models based on DeepFrag, our previously published tool designed to guide small-molecule lead optimization through fragment addition. We demonstrate enhanced accuracy by training new DeepFr...
Scientific knowledge graph and ontology generation using open large language models [0.03%]
基于开源大规模语言模型的科学知识图和本体生成
Alexandru Oarga,Matthew Hart,Andres M Bran et al.
Alexandru Oarga et al.
Knowledge graphs (KGs) are powerful tools for structured information modeling, increasingly recognized for their potential to enhance the factuality and reasoning capabilities of Large Language Models (LLMs). However, in scientific domains,...
MC3D: the materials cloud computational database of experimentally known stoichiometric inorganics [0.03%]
材料云：已知化学式的无机物计算数据库
Sebastiaan P Huber,Michail Minotakis,Marnik Bercx et al.
Sebastiaan P Huber et al.
Density-functional theory (DFT) is a widely used method to compute properties of materials, which are often collected in databases and serve as valuable starting points for further studies. In this article, we present the Materials Cloud Th...
A simple compound prioritization method for drug discovery considering multi-target binding [0.03%]
一种用于药物发现的基于多靶点结合的简便化合物优先级确定方法
Alžbeta Kubincová,David L Mobley
Alžbeta Kubincová
Active learning is an emerging paradigm used to help accelerating drug discovery, but most prior applications seek solely to optimize potency, whereas multiple properties influence a compound's utility as a drug candidate. We introduce a me...
Data augmentation in a triple transformer loop retrosynthesis model [0.03%]
基于三重变压器循环的 retrosynthesis 模型中的数据增强方法
Yves Grandjean,David Kreutter,Jean-Louis Reymond
Yves Grandjean
Reactions in the US Patent Office (USPTO) are biased towards a few over-represented reaction types, which potentially limits their usefulness for computer-assisted synthesis planning (CASP). To obtain an equilibrated dataset, we applied ret...
Assessing the performance of quantum-mechanical descriptors in physicochemical and biological property prediction [0.03%]
评估量子力学描述符在物理化学和生物属性预测中的性能
Alejandra Hinostroza Caldas,Artem Kokorin,Alexandre Tkatchenko et al.
Alejandra Hinostroza Caldas et al.
Machine learning (ML) approaches have drastically advanced the exploration of structure-property and property-property relationships in computer-aided drug discovery. A central challenge in this field is the identification of molecular desc...
Artem Mishchenko,Anupam Bhattacharya,Xiangwen Wang et al.
Artem Mishchenko et al.
This review explores the impact of deep learning (DL) techniques on understanding and predicting electronic structures in two-dimensional (2D) materials. We highlight unique computational challenges posed by 2D materials and discuss how DL ...
Mol2Raman: a graph neural network model for predicting Raman spectra from SMILES representations [0.03%]
Mol2Raman：一种从SMILES表示预测拉曼光谱的图神经网络模型
Salvatore Sorrentino,Alessandro Gussoni,Francesco Calcagno et al.
Salvatore Sorrentino et al.
Raman spectroscopy is a powerful technique for probing molecular vibrations, yet the computational prediction of Raman spectra remains challenging due to the high cost of quantum chemical methods and the complexity of structure-spectrum rel...
Active learning meets metadynamics: automated workflow for reactive machine learning interatomic potentials [0.03%]
主动学习与元动力学的结合：用于反应型机器学习相互原子势的自动化工作流程
Valdas Vitartas,Hanwen Zhang,Veronika Juraskova et al.
Valdas Vitartas et al.
Atomistic simulations driven by machine-learned interatomic potentials (MLIPs) are a cost-effective alternative to ab initio molecular dynamics (AIMD). Yet, their broad applicability in reaction modelling remains hindered, in part, by the n...
MaskTerial: a foundation model for automated 2D material flake detection [0.03%]
MaskTerial：二维材料碎片检测的预训练模型
Jan-Lucas Uslu,Alexey Nekrasov,Alexander Hermans et al.
Jan-Lucas Uslu et al.
The detection and classification of exfoliated two-dimensional (2D) material flakes from optical microscope images can be automated using computer vision algorithms. This has the potential to increase the accuracy and objectivity of classif...