Computation sparks chemical discovery

A bibliometric analysis of the Cheminformatics/QSAR literature (2000-2023) for predictive modeling in data science using the SCOPUS database

A bibliometric analysis of the Cheminformatics/QSAR articles published in the present century (2000-2023) is presented based on a SCOPUS search made in October 2024 using a given set of search criteria. The obtained results of 52,415 documents against the specific query are analyzed based on the number of documents per year, contributions of different countries and Institutes in Cheminformatics/QSAR publications, the contributions of researchers based on the number of documents, appearance in the top-cited articles, h-index, composite c-score (ns), and the newly introduced q-score. Finally, a list of the top 50 Cheminformatics/QSAR researchers is presented. An analysis is also made for the content of the top-cited articles during the period 2000-2023 in comparison to those before 2000 to capture the trend of changes in the Cheminformatics/QSAR research. The limiting factors of any bibliometric analysis are also briefly presented.

Prediction of Nanoparticle Sizes for Arbitrary Methacrylates Using Artificial Neuronal Networks

Particle sizes represent one of the key factors influencing the usability and specific targeting of nanoparticles in medical applications such as vectors for drug or gene therapy. A multi-layered graph convolutional network combined with a fully connected neuronal network is presented for the prediction of the size of nanoparticles based only on the polymer structure, the degree of polymerization, and the formulation parameters. The model is capable of predicting particle sizes obtained by nanoprecipitation of different poly(methacrylates). This includes polymers the network has not been trained with, indicating the high potential for generalizability of the model. By utilizing this model, a significant amount of time and resources can be saved in formulation optimization without extensive primary testing of material properties.