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Virtual screening of natural products to enhance melanogenosis. 虚拟筛选提高黑色素生成的天然产品。
IF 2.8 4区 医学
Molecular Informatics Pub Date : 2024-09-01 Epub Date: 2024-06-12 DOI: 10.1002/minf.202300335
Colin Bournez, José-Manuel Gally, Samia Aci-Sèche, Philippe Bernard, Pascal Bonnet
{"title":"Virtual screening of natural products to enhance melanogenosis.","authors":"Colin Bournez, José-Manuel Gally, Samia Aci-Sèche, Philippe Bernard, Pascal Bonnet","doi":"10.1002/minf.202300335","DOIUrl":"10.1002/minf.202300335","url":null,"abstract":"<p><p>Natural products have long been an important source of inspiration for medicinal chemistry and drug discovery. In the cosmetic field, they remain the major elements of the composition and serve as marketing asset. Recent research showed the implication of salt-inducible kinases on the melanin production in skin via MITF regulation. Finding new potent modulators on such target could open the way to several cosmetic applications to attenuate visible signs of photoaging and improve the tan without sun. Since virtual screening can be a powerful tool for detecting hit compounds in the early stages of a drug discovery process, we applied this method on salt-inducible kinase 2 to discover potential interesting compounds. Here, we present the different steps from the construction of a database of natural products, to the validation of a docking protocol and the results of the virtual screening. Hits from the screening were tested in vitro to confirm their efficiency and results are discussed.</p>","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":" ","pages":"e202300335"},"PeriodicalIF":2.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141306333","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
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 : 2024-09-01 Epub 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":"10.1002/minf.202300160","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":" ","pages":"e202300160"},"PeriodicalIF":2.8,"publicationDate":"2024-09-01","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
Prediction of blood-brain barrier permeability using machine learning approaches based on various molecular representation. 利用基于各种分子表征的机器学习方法预测血脑屏障通透性。
IF 2.8 4区 医学
Molecular Informatics Pub Date : 2024-09-01 Epub Date: 2024-06-12 DOI: 10.1002/minf.202300327
Li Liang, Zhiwen Liu, Xinyi Yang, Yanmin Zhang, Haichun Liu, Yadong Chen
{"title":"Prediction of blood-brain barrier permeability using machine learning approaches based on various molecular representation.","authors":"Li Liang, Zhiwen Liu, Xinyi Yang, Yanmin Zhang, Haichun Liu, Yadong Chen","doi":"10.1002/minf.202300327","DOIUrl":"10.1002/minf.202300327","url":null,"abstract":"<p><p>The assessment of compound blood-brain barrier (BBB) permeability poses a significant challenge in the discovery of drugs targeting the central nervous system. Conventional experimental approaches to measure BBB permeability are labor-intensive, cost-ineffective, and time-consuming. In this study, we constructed six machine learning classification models by combining various machine learning algorithms and molecular representations. The model based on ExtraTree algorithm and random partitioning strategy obtains the best prediction result, with AUC value of 0.932±0.004 and balanced accuracy (BA) of 0.837±0.010 for the test set. We employed the SHAP method to identify important features associated with BBB permeability. In addition, matched molecular pair (MMP) analysis and representative substructure derivation method were utilized to uncover the transformation rules and distinctive structural features of BBB permeable compounds. The machine learning models proposed in this work can serve as an effective tool for assessing BBB permeability in the drug discovery for central nervous system disease.</p>","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":" ","pages":"e202300327"},"PeriodicalIF":2.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141306332","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
Cover Picture: (Mol. Inf. 8/2024) 封面图片：（Mol.Inf. 8/2024）
IF 3.6 4区 医学
Molecular Informatics Pub Date : 2024-08-12 DOI: 10.1002/minf.202480801
{"title":"Cover Picture: (Mol. Inf. 8/2024)","authors":"","doi":"10.1002/minf.202480801","DOIUrl":"https://doi.org/10.1002/minf.202480801","url":null,"abstract":"","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":"73 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212171","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
Ensemble docking based virtual screening of SARS-CoV-2 main protease inhibitors. 基于组合对接的 SARS-CoV-2 主要蛋白酶抑制剂虚拟筛选。
IF 2.8 4区 医学
Molecular Informatics Pub Date : 2024-08-01 Epub Date: 2024-07-08 DOI: 10.1002/minf.202300279
Anastasia D Fomina, Victoria I Uvarova, Liubov I Kozlovskaya, Vladimir A Palyulin, Dmitry I Osolodkin, Aydar A Ishmukhametov
{"title":"Ensemble docking based virtual screening of SARS-CoV-2 main protease inhibitors.","authors":"Anastasia D Fomina, Victoria I Uvarova, Liubov I Kozlovskaya, Vladimir A Palyulin, Dmitry I Osolodkin, Aydar A Ishmukhametov","doi":"10.1002/minf.202300279","DOIUrl":"10.1002/minf.202300279","url":null,"abstract":"<p><p>During the first years of COVID-19 pandemic, X-ray structures of the coronavirus drug targets were acquired at an unprecedented rate, giving hundreds of PDB depositions in less than a year. The main protease (Mpro) of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) is the primary validated target of direct-acting antivirals. The selection of the optimal ensemble of structures of Mpro for the docking-driven virtual screening campaign was thus non-trivial and required a systematic and automated approach. Here we report a semi-automated active site RMSD based procedure of ensemble selection from the SARS-CoV-2 Mpro crystallographic data and virtual screening of its inhibitors. The procedure was compared with other approaches to ensemble selection and validated with the help of hand-picked and peer-reviewed activity-annotated libraries. Prospective virtual screening of non-covalent Mpro inhibitors resulted in a new chemotype of thienopyrimidinone derivatives with experimentally confirmed enzyme inhibition.</p>","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":" ","pages":"e202300279"},"PeriodicalIF":2.8,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141555196","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
Chemical space exploration with Molpher: Generating and assessing a glucocorticoid receptor ligand library. 利用 Molpher 探索化学空间：生成并评估糖皮质激素受体配体库。
IF 2.8 4区 医学
Molecular Informatics Pub Date : 2024-08-01 Epub Date: 2024-07-09 DOI: 10.1002/minf.202300316
M Isabel Agea, Ivan Čmelo, Wim Dehaen, Ya Chen, Johannes Kirchmair, David Sedlák, Petr Bartůněk, Martin Šícho, Daniel Svozil
{"title":"Chemical space exploration with Molpher: Generating and assessing a glucocorticoid receptor ligand library.","authors":"M Isabel Agea, Ivan Čmelo, Wim Dehaen, Ya Chen, Johannes Kirchmair, David Sedlák, Petr Bartůněk, Martin Šícho, Daniel Svozil","doi":"10.1002/minf.202300316","DOIUrl":"10.1002/minf.202300316","url":null,"abstract":"<p><p>Computational exploration of chemical space is crucial in modern cheminformatics research for accelerating the discovery of new biologically active compounds. In this study, we present a detailed analysis of the chemical library of potential glucocorticoid receptor (GR) ligands generated by the molecular generator, Molpher. To generate the targeted GR library and construct the classification models, structures from the ChEMBL database as well as from the internal IMG library, which was experimentally screened for biological activity in the primary luciferase reporter cell assay, were utilized. The composition of the targeted GR ligand library was compared with a reference library that randomly samples chemical space. A random forest model was used to determine the biological activity of ligands, incorporating its applicability domain using conformal prediction. It was demonstrated that the GR library is significantly enriched with GR ligands compared to the random library. Furthermore, a prospective analysis demonstrated that Molpher successfully designed compounds, which were subsequently experimentally confirmed to be active on the GR. A collection of 34 potential new GR ligands was also identified. Moreover, an important contribution of this study is the establishment of a comprehensive workflow for evaluating computationally generated ligands, particularly those with potential activity against targets that are challenging to dock.</p>","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":" ","pages":"e202300316"},"PeriodicalIF":2.8,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141559260","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
Navigating pharmacophore space to identify activity discontinuities: A case study with BCR-ABL. 浏览药理空间以识别活性不连续性：BCR-ABL 案例研究。
IF 2.8 4区 医学
Molecular Informatics Pub Date : 2024-08-01 Epub Date: 2024-07-09 DOI: 10.1002/minf.202400050
Maroua Lejmi, Damien Geslin, Ronan Bureau, Bertrand Cuissart, Ilef Ben Slima, Nida Meddouri, Amel Borgi, Jean-Luc Lamotte, Alban Lepailleur
{"title":"Navigating pharmacophore space to identify activity discontinuities: A case study with BCR-ABL.","authors":"Maroua Lejmi, Damien Geslin, Ronan Bureau, Bertrand Cuissart, Ilef Ben Slima, Nida Meddouri, Amel Borgi, Jean-Luc Lamotte, Alban Lepailleur","doi":"10.1002/minf.202400050","DOIUrl":"10.1002/minf.202400050","url":null,"abstract":"<p><p>The exploration of chemical space is a fundamental aspect of chemoinformatics, particularly when one explores a large compound data set to relate chemical structures with molecular properties. In this study, we extend our previous work on chemical space visualization at the pharmacophoric level. Instead of using conventional binary classification of affinity (active vs inactive), we introduce a refined approach that categorizes compounds into four distinct classes based on their activity levels: super active, very active, active, and inactive. This classification enriches the color scheme applied to pharmacophore space, where the color representation of a pharmacophore hypothesis is driven by the associated compounds. Using the BCR-ABL tyrosine kinase as a case study, we identified intriguing regions corresponding to pharmacophore activity discontinuities, providing valuable insights for structure-activity relationships analysis.</p>","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":" ","pages":"e202400050"},"PeriodicalIF":2.8,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141559262","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
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
{"title":"Cover Picture: (Mol. Inf. 7/2024)","authors":"","doi":"10.1002/minf.202480701","DOIUrl":"https://doi.org/10.1002/minf.202480701","url":null,"abstract":"","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":"243 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141609429","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
{"title":"Chemoinformatic regression methods and their applicability domain.","authors":"Thomas-Martin Dutschmann, Valerie Schlenker, Knut Baumann","doi":"10.1002/minf.202400018","DOIUrl":"10.1002/minf.202400018","url":null,"abstract":"<p><p>The growing interest in chemoinformatic model uncertainty calls for a summary of the most widely used regression techniques and how to estimate their reliability. Regression models learn a mapping from the space of explanatory variables to the space of continuous output values. Among other limitations, the predictive performance of the model is restricted by the training data used for model fitting. Identification of unusual objects by outlier detection methods can improve model performance. Additionally, proper model evaluation necessitates defining the limitations of the model, often called the applicability domain. Comparable to certain classifiers, some regression techniques come with built-in methods or augmentations to quantify their (un)certainty, while others rely on generic procedures. The theoretical background of their working principles and how to deduce specific and general definitions for their domain of applicability shall be explained.</p>","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":" ","pages":"e202400018"},"PeriodicalIF":2.8,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141158308","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
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
{"title":"Structural analysis of neomycin B and kanamycin A binding Aminoglycosides Modifying Enzymes (AME) and bacterial ribosomal RNA.","authors":"Julia Revillo Imbernon, Jean-Marc Weibel, Eric Ennifar, Gilles Prévost, Esther Kellenberger","doi":"10.1002/minf.202300339","DOIUrl":"10.1002/minf.202300339","url":null,"abstract":"<p><p>Aminoglycosides are crucial antibiotics facing challenges from bacterial resistance. This study addresses the importance of aminoglycoside modifying enzymes in the context of escalating resistance. Drawing upon over two decades of structural data in the Protein Data Bank, we focused on two key antibiotics, neomycin B and kanamycin A, to explore how the aminoglycoside structure is exploited by this family of enzymes. A systematic comparison across diverse enzymes and the RNA A-site target identified common characteristics in the recognition mode, while assessing the adaptability of neomycin B and kanamycin A in various environments.</p>","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":" ","pages":"e202300339"},"PeriodicalIF":2.8,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141296441","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
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