Moisés Domínguez, Verónica A. Jiménez, Gökcen Savasci, Rocío Araya-Osorio, Janne Pesonen, Raúl Mera-Adasme
{"title":"goChem: A Composable Library for Multi-Scale Computational Chemistry Data Analysis","authors":"Moisés Domínguez, Verónica A. Jiménez, Gökcen Savasci, Rocío Araya-Osorio, Janne Pesonen, Raúl Mera-Adasme","doi":"10.1002/jcc.70004","DOIUrl":"10.1002/jcc.70004","url":null,"abstract":"<div>\u0000 \u0000 <p>Data analysis is a major task for Computational Chemists. The diversity of modeling tools currently available in Computational Chemistry requires the development of flexible analysis tools that can adapt to different systems and output formats. As a contribution to this need, we report the implementation of goChem, a versatile open-source library for multiscale analysis of computational chemistry data. The library, written in and for the Go programming language, allows for easy integration of different levels of theory, in an easy-to-use API, allowing the development of both one-use and complex analysis programs in Go. We describe the library and detail some selected applications that illustrate the capabilities and potential of this tool. The library is available at http://gochem.org.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142961534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"COX-2 Inhibitor Prediction With KNIME: A Codeless Automated Machine Learning-Based Virtual Screening Workflow","authors":"Powsali Ghosh, Ashok Kumar, Sushil Kumar Singh","doi":"10.1002/jcc.70030","DOIUrl":"10.1002/jcc.70030","url":null,"abstract":"<div>\u0000 \u0000 <p>Cyclooxygenase-2 (COX-2) is an enzyme that plays a crucial role in inflammation by converting arachidonic acid into prostaglandins. The overexpression of enzyme is associated with conditions such as cancer, arthritis, and Alzheimer's disease (AD), where it contributes to neuroinflammation. In silico virtual screening is pivotal in early-stage drug discovery; however, the absence of coding or machine learning expertise can impede the development of reliable computational models capable of accurately predicting inhibitor compounds based on their chemical structure. In this study, we developed an automated KNIME workflow for predicting the COX-2 inhibitory potential of novel molecules by building a multi-level ensemble model constructed with five machine learning algorithms (i.e., Logistic Regression, K-Nearest Neighbors, Decision Tree, Random Forest, and Extreme Gradient Boosting) and various molecular and fingerprint descriptors (i.e., AtomPair, Avalon, MACCS, Morgan, RDKit, and Pattern). Post-applicability domain filtering, the final majority voting-based ensemble model achieved 90.0% balanced accuracy, 87.7% precision, and 86.4% recall on the external validation set. The freely accessible workflow empowers users to swiftly and effortlessly predict COX-2 inhibitors, eliminating the need for any prior knowledge in machine learning, coding, or statistical modeling, significantly broadening its accessibility. While beginners can seamlessly use the tool as is, experienced KNIME users can leverage it as a foundation to build advanced workflows, driving further research and innovation.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142961946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Photodissociation of \u0000 \u0000 \u0000 \u0000 \u0000 Cr(CO)\u0000 \u0000 \u0000 4\u0000 \u0000 \u0000 bpy\u0000 \u0000 $$ mathrm{Cr}{left(mathrm{CO}right)}_4mathrm{bpy} $$\u0000 : A Non-Adiabatic Dynamics Investigation","authors":"Bartosz Ciborowski, Morgane Vacher","doi":"10.1002/jcc.70021","DOIUrl":"10.1002/jcc.70021","url":null,"abstract":"<p>Carbonyl complexes of <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mrow>\u0000 <mi>d</mi>\u0000 </mrow>\u0000 <mrow>\u0000 <mn>6</mn>\u0000 </mrow>\u0000 </msup>\u0000 </mrow>\u0000 <annotation>$$ {d}^6 $$</annotation>\u0000 </semantics></math> metals with an α-diimine ligand exhibit both emission and ligand-selective photodissociation from MLCT states. Studying this photodissociative mechanism is challenging for experimental approaches due to an ultrafast femtosecond timescale and spectral overlap of multiple photoproducts. The photochemistry of a prototypical system <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mrow>\u0000 <mtext>Cr(CO)</mtext>\u0000 </mrow>\u0000 <mrow>\u0000 <mn>4</mn>\u0000 </mrow>\u0000 </msub>\u0000 <mtext>bpy</mtext>\u0000 </mrow>\u0000 <annotation>$$ mathrm{Cr}{left(mathrm{CO}right)}_4mathrm{bpy} $$</annotation>\u0000 </semantics></math> is investigated with non-adiabatic dynamic simulations. Obtained 86 fs lifetime of the bright <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mrow>\u0000 <mi>S</mi>\u0000 </mrow>\u0000 <mrow>\u0000 <mn>3</mn>\u0000 </mrow>\u0000 </msub>\u0000 </mrow>\u0000 <annotation>$$ {S}_3 $$</annotation>\u0000 </semantics></math> state and 13% quantum yield are in good agreement with experimental data. The present simulations suggest a ballistic mechanism of photodissociation, which is irrespective of the occupied electronic state. This is in contrast to the previously established mechanism of competitive intersystem crossing and dissociation. Selectivity of axial photodissociation is shown to be caused by the absence of an avoided crossing in the equatorial direction.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142961947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}