Molecular Informatics最新文献_第2页

Cover Picture: (Mol. Inf. 7/2024) 封面图片：（Mol.Inf. 7/2024）

IF 3.6 4区医学

Molecular Informatics Pub Date : 2024-07-12 DOI: 10.1002/minf.202480701

引用次数: 0

DIGEP-Pred 2.0: A web application for predicting drug-induced cell signaling and gene expression changes. DIGEP-Pred 2.0：用于预测药物诱导的细胞信号传导和基因表达变化的网络应用程序。

IF 2.8 4区医学

Molecular Informatics Pub Date : 2024-07-09 DOI: 10.1002/minf.202400032

Sergey M Ivanov, Anastasia V Rudik, Alexey A Lagunin, Dmitry A Filimonov, Vladimir V Poroikov

{"title":"DIGEP-Pred 2.0: A web application for predicting drug-induced cell signaling and gene expression changes.","authors":"Sergey M Ivanov, Anastasia V Rudik, Alexey A Lagunin, Dmitry A Filimonov, Vladimir V Poroikov","doi":"10.1002/minf.202400032","DOIUrl":"https://doi.org/10.1002/minf.202400032","url":null,"abstract":"The analysis of drug-induced gene expression profiles (DIGEP) is widely used to estimate the potential therapeutic and adverse drug effects as well as the molecular mechanisms of drug action. However, the corresponding experimental data is absent for many existing drugs and drug-like compounds. To solve this problem, we created the DIGEP-Pred 2.0 web application, which allows predicting DIGEP and potential drug targets by structural formula of drug-like compounds. It is based on the combined use of structure-activity relationships (SARs) and network analysis. SAR models were created using PASS (Prediction of Activity Spectra for Substances) technology for data from the Comparative Toxicogenomics Database (CTD), the Connectivity Map (CMap) for the prediction of DIGEP, and PubChem and ChEMBL for the prediction of molecular mechanisms of action (MoA). Using only the structural formula of a compound, the user can obtain information on potential gene expression changes in several cell lines and drug targets, which are potential master regulators responsible for the observed DIGEP. The mean accuracy of prediction calculated by leave-one-out cross validation was 86.5 % for 13377 genes and 94.8 % for 2932 proteins (CTD data), and it was 97.9 % for 2170 MoAs. SAR models (mean accuracy-87.5 %) were also created for CMap data given on MCF7, PC3, and HL60 cell lines with different threshold values for the logarithm of fold changes: 0.5, 0.7, 1, 1.5, and 2. Additionally, the data on pathways (KEGG, Reactome), biological processes of Gene Ontology, and diseases (DisGeNet) enriched by the predicted genes, together with the estimation of target-master regulators based on OmniPath data, is also provided. DIGEP-Pred 2.0 web application is freely available at https://www.way2drug.com/digep-pred.","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141559261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Cumulative phylogenetic, sequence and structural analysis of Insulin superfamily proteins provide unique structure-function insights. 对胰岛素超家族蛋白的系统发育、序列和结构的累积分析提供了独特的结构-功能见解。

IF 2.8 4区医学

Molecular Informatics Pub Date : 2024-07-08 DOI: 10.1002/minf.202300160

Shrilakshmi Sheshagiri Rao, Shankar V Kundapura, Debayan Dey, Chandrasekaran Palaniappan, Kanagaraj Sekar, Ananda Kulal, Udupi A Ramagopal

{"title":"Cumulative phylogenetic, sequence and structural analysis of Insulin superfamily proteins provide unique structure-function insights.","authors":"Shrilakshmi Sheshagiri Rao, Shankar V Kundapura, Debayan Dey, Chandrasekaran Palaniappan, Kanagaraj Sekar, Ananda Kulal, Udupi A Ramagopal","doi":"10.1002/minf.202300160","DOIUrl":"https://doi.org/10.1002/minf.202300160","url":null,"abstract":"The insulin superfamily proteins (ISPs), in particular, insulin, IGFs and relaxin proteins are key modulators of animal physiology. They are known to have evolved from the same ancestral gene and have diverged into proteins with varied sequences and distinct functions, but maintain a similar structural architecture stabilized by highly conserved disulphide bridges. The recent surge of sequence data and the structures of these proteins prompted a need for a comprehensive analysis, which connects the evolution of these sequences (427 sequences) in the light of available functional and structural information including representative complex structures of ISPs with their cognate receptors. This study reveals (a) unusually high sequence conservation of IGFs (>90 % conservation in 184 sequences) and provides a possible structure-based rationale for such high sequence conservation; (b) provides an updated definition of the receptor-binding signature motif of the functionally diverse relaxin family members (c) provides a probable non-canonical C-peptide cleavage site in a few insulin sequences. The high conservation of IGFs appears to represent a classic case of resistance to sequence diversity exerted by physiologically important interactions with multiple partners. We also propose a probable mechanism for C-peptide cleavage in a few distinct insulin sequences and redefine the receptor-binding signature motif of the relaxin family. Lastly, we provide a basis for minimally modified insulin mutants with potential therapeutic application, inspired by concomitant changes observed in other insulin superfamily protein members supported by molecular dynamics simulation.","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141555195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-Task ADME/PK prediction at industrial scale: leveraging large and diverse experimentaldatasets. 工业规模的多任务 ADME/PK 预测：利用大型多样的实验数据集。

IF 2.8 4区医学

Molecular Informatics Pub Date : 2024-07-08 DOI: 10.1002/minf.202400079

Moritz Walter, Jens M Borghardt, Lina Humbeck, Miha Skalic

{"title":"Multi-Task ADME/PK prediction at industrial scale: leveraging large and diverse experimentaldatasets.","authors":"Moritz Walter, Jens M Borghardt, Lina Humbeck, Miha Skalic","doi":"10.1002/minf.202400079","DOIUrl":"https://doi.org/10.1002/minf.202400079","url":null,"abstract":"ADME (Absorption, Distribution, Metabolism, Excretion) properties are key parameters to judge whether a drug candidate exhibits a desired pharmacokinetic (PK) profile. In this study, we tested multi-task machine learning (ML) models to predict ADME and animal PK endpoints trained on in-house data generated at Boehringer Ingelheim. Models were evaluated both at the design stage of a compound (i. e., no experimental data of test compounds available) and at testing stage when a particular assay would be conducted (i. e., experimental data of earlier conducted assays may be available). Using realistic time-splits, we found a clear benefit in performance of multi-task graph-based neural network models over single-task model, which was even stronger when experimental data of earlier assays is available. In an attempt to explain the success of multi-task models, we found that especially endpoints with the largest numbers of data points (physicochemical endpoints, clearance in microsomes) are responsible for increased predictivity in more complex ADME and PK endpoints. In summary, our study provides insight into how data for multiple ADME/PK endpoints in a pharmaceutical company can be best leveraged to optimize predictivity of ML models.","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141555197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Chemoinformatic regression methods and their applicability domain. 化学信息回归方法及其适用领域。

IF 2.8 4区医学

Molecular Informatics Pub Date : 2024-07-01 Epub Date: 2024-05-28 DOI: 10.1002/minf.202400018

Thomas-Martin Dutschmann, Valerie Schlenker, Knut Baumann

引用次数: 0

Structural analysis of neomycin B and kanamycin A binding Aminoglycosides Modifying Enzymes (AME) and bacterial ribosomal RNA. 新霉素 B 和卡那霉素 A 与氨基糖苷类药物修饰酶 (AME) 和细菌核糖体 RNA 结合的结构分析。

IF 2.8 4区医学

Molecular Informatics Pub Date : 2024-07-01 Epub Date: 2024-06-10 DOI: 10.1002/minf.202300339

Julia Revillo Imbernon, Jean-Marc Weibel, Eric Ennifar, Gilles Prévost, Esther Kellenberger

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Comparing search algorithms on the retrosynthesis problem. 比较逆合成问题的搜索算法。

IF 2.8 4区医学

Molecular Informatics Pub Date : 2024-07-01 Epub Date: 2024-06-12 DOI: 10.1002/minf.202300259

Milo Roucairol, Tristan Cazenave

引用次数: 0

Best of both worlds: An expansion of the state of the art pKa model with data from three industrial partners 两全其美：利用三个工业合作伙伴提供的数据扩展最先进的 pKa 模型

IF 3.6 4区医学

Molecular Informatics Pub Date : 2024-06-21 DOI: 10.1002/minf.202400088

Robert Fraczkiewicz, Huy Quoc Nguyen, Newton Wu, Nina Kausch‐Busies, Sergio Grimbs, Kai Sommer, Antonius ter Laak, Judith Günther, Björn Wagner, Michael Reutlinger

{"title":"Best of both worlds: An expansion of the state of the art pKa model with data from three industrial partners","authors":"Robert Fraczkiewicz, Huy Quoc Nguyen, Newton Wu, Nina Kausch‐Busies, Sergio Grimbs, Kai Sommer, Antonius ter Laak, Judith Günther, Björn Wagner, Michael Reutlinger","doi":"10.1002/minf.202400088","DOIUrl":"https://doi.org/10.1002/minf.202400088","url":null,"abstract":"In a unique collaboration between Simulations Plus and several industrial partners, we were able to develop a new version 11.0 of the previously published in silico pKa model, S+pKa, with considerably improved prediction accuracy. The model's training set was vastly expanded by large amounts of experimental data obtained from F. Hoffmann‐La Roche AG, Genentech Inc., and the Crop Science division of Bayer AG. The previous v7.0 of S+pKa was trained on data from public sources and the Pharmaceutical division of Bayer AG. The model has shown dramatic improvements in predictive accuracy when externally validated on three new contributor compound sets. Less expected was v11.0’s improvement in prediction on new compounds developed at Bayer Pharma after v7.0 was released (2013–2023), even without contributing additional data to v11.0. We illustrate chemical space coverage by chemistries encountered in the five domains, public and industrial, outline model construction, and discuss factors contributing to model's success.","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141504470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring drug repositioning possibilities of kinase inhibitors via molecular simulation** 通过分子模拟探索激酶抑制剂药物重新定位的可能性**

IF 3.6 4区医学

Molecular Informatics Pub Date : 2024-06-21 DOI: 10.1002/minf.202300336

Qing‐Xin Wang, Jiao Cai, Zi‐Jun Chen, Jia‐Chuan Liu, Jing‐Jing Wang, Hai Zhou, Qing‐Qing Li, Zi‐Xuan Wang, Yi‐Bo Wang, Zhen‐Jiang Tong, Jin Yang, Tian‐Hua Wei, Meng‐Yuan Zhang, Yun Zhou, Wei‐Chen Dai, Ning Ding, Xue‐Jiao Leng, Xiao‐Ying Yin, Shan‐Liang Sun, Yan‐Cheng Yu, Nian‐Guang Li, Zhi‐Hao Shi

{"title":"Exploring drug repositioning possibilities of kinase inhibitors via molecular simulation**","authors":"Qing‐Xin Wang, Jiao Cai, Zi‐Jun Chen, Jia‐Chuan Liu, Jing‐Jing Wang, Hai Zhou, Qing‐Qing Li, Zi‐Xuan Wang, Yi‐Bo Wang, Zhen‐Jiang Tong, Jin Yang, Tian‐Hua Wei, Meng‐Yuan Zhang, Yun Zhou, Wei‐Chen Dai, Ning Ding, Xue‐Jiao Leng, Xiao‐Ying Yin, Shan‐Liang Sun, Yan‐Cheng Yu, Nian‐Guang Li, Zhi‐Hao Shi","doi":"10.1002/minf.202300336","DOIUrl":"https://doi.org/10.1002/minf.202300336","url":null,"abstract":"Kinases, a class of enzymes controlling various substrates phosphorylation, are pivotal in both physiological and pathological processes. Although their conserved ATP binding pockets pose challenges for achieving selectivity, this feature offers opportunities for drug repositioning of kinase inhibitors (KIs). This study presents a cost‐effective in silico prediction of KIs drug repositioning via analyzing cross‐docking results. We established the KIs database (278 unique KIs, 1834 bioactivity data points) and kinases database (357 kinase structures categorized by the DFG motif) for carrying out cross‐docking. Comparative analysis of the docking scores and reported experimental bioactivity revealed that the Atypical, TK, and TKL superfamilies are suitable for drug repositioning. Among these kinase superfamilies, Olverematinib, Lapatinib, and Abemaciclib displayed enzymatic activity in our focused AKT‐PI3K‐mTOR pathway with IC50 values of 3.3, 3.2 and 5.8 μM. Further cell assays showed IC50 values of 0.2, 1.2 and 0.6 μM in tumor cells. The consistent result between prediction and validation demonstrated that repositioning KIs via in silico method is feasible.","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141504468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Updating and profiling the natural product‐likeness of Latin American compound libraries 更新和剖析拉丁美洲化合物库的天然产品相似性

IF 3.6 4区医学

Molecular Informatics Pub Date : 2024-06-21 DOI: 10.1002/minf.202400052

Alejandro Gómez‐García, Ann‐Kathrin Prinz, Daniel A. Acuña Jiménez, William J. Zamora, Haruna L. Barazorda‐Ccahuana, Miguel Á. Chávez‐Fumagalli, Marilia Valli, Adriano D. Andricopulo, Vanderlan da S. Bolzani, Dionisio A. Olmedo, Pablo N. Solís, Marvin J. Núñez, Johny R. Rodríguez Pérez, Hoover A. Valencia Sánchez, Héctor F. Cortés Hernández, Oscar M. Mosquera Martinez, Oliver Koch, José L. Medina‐Franco

{"title":"Updating and profiling the natural product‐likeness of Latin American compound libraries","authors":"Alejandro Gómez‐García, Ann‐Kathrin Prinz, Daniel A. Acuña Jiménez, William J. Zamora, Haruna L. Barazorda‐Ccahuana, Miguel Á. Chávez‐Fumagalli, Marilia Valli, Adriano D. Andricopulo, Vanderlan da S. Bolzani, Dionisio A. Olmedo, Pablo N. Solís, Marvin J. Núñez, Johny R. Rodríguez Pérez, Hoover A. Valencia Sánchez, Héctor F. Cortés Hernández, Oscar M. Mosquera Martinez, Oliver Koch, José L. Medina‐Franco","doi":"10.1002/minf.202400052","DOIUrl":"https://doi.org/10.1002/minf.202400052","url":null,"abstract":"Compound databases of natural products play a crucial role in drug discovery and development projects and have implications in other areas, such as food chemical research, ecology and metabolomics. Recently, we put together the first version of the Latin American Natural Product database (LANaPDB) as a collective effort of researchers from six countries to ensemble a public and representative library of natural products in a geographical region with a large biodiversity. The present work aims to conduct a comparative and extensive profiling of the natural product‐likeness of an updated version of LANaPDB and the individual ten compound databases that form part of LANaPDB. The natural product‐likeness profile of the Latin American compound databases is contrasted with the profile of other major natural product databases in the public domain and a set of small‐molecule drugs approved for clinical use. As part of the extensive characterization, we employed several chemoinformatics metrics of natural product likeness. The results of this study will capture the attention of the global community engaged in natural product databases, not only in Latin America but across the world.","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141504469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0