NSTL国家科技图书文献中心

1. GCLmf: A Novel Molecular Graph Contrastive Learning Framework Based on Hard Negatives and Application in Toxicity Prediction** NSTL国家科技图书文献中心

Xinxin Yu | Yuanting Chen ... - 《Molecular informatics.》 - 2025,44(1) - e202400169～e202400169 - 共13页

摘要：Abstract In silico methods for prediction of | chemical toxicity can decrease the cost and increase the | efficiency in the early stage of drug discovery. However | , due to low accessibility of sufficient and reliable | toxicity data, constructing robust and accurate

关键词： chemical toxicity | graph contrastive learning | GNN | hard negatives | molecular representation | self-supervised learning

2. Predicting the Price of Molecules Using Their Predicted Synthetic Pathways NSTL国家科技图书文献中心

Massina Abderrahmane | Hamza Tajmouati ... - 《Molecular informatics.》 - 2025,44(2) - e202400039～e202400039 - 共13页

摘要：Currently, numerous metrics allow chemists and | computational chemists to refine and filter libraries of | virtual molecules in order to prioritize their synthesis | . Some of the most commonly used metrics and models are | QSAR models, docking scores, diverse druggability

关键词： deep learning; molecular price prediction; retrosynthesis; synthetic accessibility.

3. An Integrated Fuzzy Neural Network and Topological Data Analysis for Molecular Graph Representation Learning and Property Forecasting NSTL国家科技图书文献中心

Pham, Phu - 《Molecular informatics.》 - 2025,44(3) - e202400335～e202400335 - 共15页

摘要：Within a recent decade, graph neural network | (GNN) has emerged as a powerful neural architecture | for various graph-structured data modelling and task | -driven representation learning problems. Recent studies | have highlighted the remarkable capabilities of GNNs

关键词： topological data analysis | graph neural network | neuro-fuzzy network | molecular graph | toxicity

4. CoLiNN: A Tool for Fast Chemical Space Visualization of Combinatorial Libraries Without Enumeration NSTL国家科技图书文献中心

Pikalyova, Regina | Akhmetshin, Tagir ... - 《Molecular informatics.》 - 2025,44(3) - e202400263～e202400263 - 共13页

摘要：Visualization of the combinatorial library | chemical space provides a comprehensive overview of | available compound classes, their diversity, and | physicochemical property distribution - key factors in drug | discovery. Typically, this visualization requires time

关键词： chemical space | combinatorial library | compound enumeration | DNA-encoded libraries (DELs) | GTM

5. Interpret Gaussian Process Models by Using Integrated Gradients NSTL国家科技图书文献中心

Fan Zhang | Naoaki Ono ... - 《Molecular informatics.》 - 2025,44(1) - e202400051～e202400051 - 共12页

摘要：Abstract Gaussian process regression (GPR) is | a nonparametric probabilistic model capable of | computing not only the predicted mean but also the | predicted standard deviation, which represents the | confidence level of predictions. It offers great

关键词： explainable AI | gaussian process | integrated gradients

6. Discovery of New HER2 Inhibitors via Computational Docking, Pharmacophore Modeling, and Machine Learning NSTL国家科技图书文献中心

Aseel Yasin Matrouk | Haneen Mohammad ... - 《Molecular informatics.》 - 2025,44(2) - e202400336～e202400336 - 共18页

摘要：The human epidermal growth factor receptor 2 | (HER2) is a critical oncogene implicated in the | development of various aggressive cancers, particularly | breast cancer. Discovering novel HER2 inhibitors is | crucial for expanding therapeutic options for HER2

关键词： Bagging; HER2; J48Graft; ML-QSAR; flexible docking.

7. Modeling Carbon Basicity NSTL国家科技图书文献中心

Fraczkiewicz, Robert | Waldman, Marvin - 《Molecular informatics.》 - 2025,44(3) - e202400296～e202400296 - 共10页

摘要：This work presents a predictive model of | aqueous ionization constants (pKa) of protonatable | carbons in certain aromatic rings. The phenomenon of | carbon atoms sometimes acting as a stable and | reversible base accepting a proton in water solution is

关键词： carbon basicity | ionization constant | machine learning | pKa | prediction | pK(a)

8. Active learning approaches in molecule pKi prediction NSTL国家科技图书文献中心

Kashafutdinova, I. M... | Poyezzhayeva, A.... - 《Molecular informatics.》 - 2025,44(1) - e202400154～e202400154 - 共14页

摘要：During the early stages of drug design | , identifying compounds with suitable bioactivities is crucial | . Given the vast array of potential drug databases, it | ' s feasible to assay only a limited subset of | candidates. The optimal method for selecting the candidates

关键词： active learning | bioactivity | ChEMBL datasets

9. MAYA (Multiple ActivitY Analyzer): An Open Access Tool to Explore Structure-Multiple Activity Relationships in the Chemical Universe NSTL国家科技图书文献中心

J. Israel Espinoza-C... | José L. Medina-Franc... - 《Molecular informatics.》 - 2025,44(2) - e202400306～e202400306 - 共7页

摘要：Herein, we introduce MAYA (Multiple Activity | Analyzer), a tool designed to automatically construct a | chemical multiverse, generating multiple visualizations | of chemical spaces of a compound data set described | by structural descriptors of different nature such

关键词： automatic data visualization; chemical multiverse; chemical space; chemoinformatics; open

10. Deep Modeling of Gain-of-Function Mutations on Androgen Receptor NSTL国家科技图书文献中心

You, Jiaying | Foo, Jane ... - 《Molecular informatics.》 - 2025,44(4) - e202500018～e202500018 - 共10页

摘要：The efficiency of Androgen Receptor (AR | ) pathway inhibitors for prostate cancer (PCa) is on | decline due to resistance mechanisms including the | occurrence of gain-of-function mutations on human androgen | receptor (AR). Hence, understanding and predicting such