José L Medina-Franco
José L Medina-Franco
Ligand B-Factor Index: A Metric for Prioritizing Protein-Ligand Complexes in Docking [0.03%]
配体B因子指标：对接中优先处理蛋白质-配体复合物的一种度量标准
Liliana Halip,Cristian Neanu,Sorin Avram
Liliana Halip
Docking is a structure-based cheminformatics tool broadly employed in early drug discovery. Based on the tridimensional structure of the protein target, docking is used to predict the binding interactions between the protein and a ligand, e...
LiProS: Findable, Accessible, Interoperable, and Reusable Data Simulation Workflow to Predict Accurate Lipophilicity Profiles for Small Molecules [0.03%]
LiProS：用于预测小分子准确的亲脂性谱图的可查找、可访问、互操作和可重复的数据模拟工作流
Esteban Bertsch-Aguilar,Antonio Piedra,Daniel Acuña et al.
Esteban Bertsch-Aguilar et al.
Lipophilicity is a fundamental physicochemical property widely used to evaluate key parameters in drug design, materials science, and food engineering. It plays a critical role in predicting membrane permeability, absorption, and distributi...
Machine Learning-Based Identification of Petroleum Distillates and Gasoline Traces Using Measured and Synthetic GC Spectra from Collected Samples [0.03%]
基于机器学习的石油馏分和汽油痕迹识别方法及其仿真与实验研究
Omer Kaspi,Yaniv Y Avissar,Arnon Grafit et al.
Omer Kaspi et al.
Ignition cases involving arsons are typically handled by forensic experts who examine spectra of samples collected from scenes of fire to test for the existence or absence of ignitable liquids. This is tedious work, since many cases do not ...
Integrating Generative Pretrained Transformer and Genetic Algorithms for Efficient and Diverse Molecular Generation [0.03%]
基于生成性预训练变换器和遗传算法的高效多样化分子生成方法研究
Chengcheng Xu,Chen Zeng,Xi Yang et al.
Chengcheng Xu et al.
In computer-aided drug design, molecular generation models play a crucial role in accelerating the drug development process. Current models mainly fall into two categories: deep learning models with high performance but poor interpretabilit...
Rapid Assessment of Virtually Synthesizable Chemical Structures via Support Vector Machine Models [0.03%]
基于支持向量机模型的虚拟合成化学结构的快速评价方法研究
Yuto Iwasaki,Tomoyuki Miyao
Yuto Iwasaki
Support vector machine (SVM) and support vector regression (SVR) are widely used for building quantitative structure-activity relationship models for small- and medium-sized datasets. Although SVM and SVR models can efficiently predict comp...
Network Analysis of the Organic Chemistry in Patents, Literature, and Pharmaceutical Industry [0.03%]
基于专利、文献和制药企业的有机化学网络分析
Emma Svensson,Emma Granqvist,Tomas Bastys et al.
Emma Svensson et al.
Chemical reactions can be connected in large networks such as knowledge graphs. In this way, prior work has been able to draw meaningful conclusions about the properties and structures involved in organic chemistry reactions. However, the r...
Structural Flexibility and Shape Similarity Contribute to Exclusive Functions of Certain Atg8 Isoforms in the Autophagy Process [0.03%]
自噬过程中某些Atg8同工型独有功能的产生源于其结构灵活性和形状相似性
Alexey Rayevsky,Eliah Bulgakov,Mariia Stykhylias et al.
Alexey Rayevsky et al.
Despite the abundance of systematically collected experimental data and facts, the multistep process of autophagy still contains many dark spots. One concerns the background selectivity of interactions between certain autophagy-related prot...
Neural Network Models for Prediction of Biological Activity using Molecular Dynamics Data: A Case of Photoswitchable Peptides [0.03%]
基于分子动力学数据预测生物活性的神经网络模型及其光控多肽的例子
Anton Cherednichenko,Sergii Afonin,Oleg Babii et al.
Anton Cherednichenko et al.
Prediction of biological activities of chemical compounds by the machine learning techniques in general and the neural networks (NNs) in particular, is usually based on the analysis of their binding to the target of interest. If such affini...
Drug Search and Design Considering Cell Specificity of Chemically Induced Gene Expression Profiles for Disease-Associated Tissues [0.03%]
基于化学诱导的基因表达谱细胞特异性的疾病组织相关药物筛选与设计
Chikashige Yamanaka,Michio Iwata,Kazuma Kaitoh et al.
Chikashige Yamanaka et al.
The use of omics data, including gene expression profiles, has recently gained increasing attention in drug discovery. Omics-based drug searches and designs are often based on the correlations between chemically induced and disease-induced ...