ACS Publications最新文献

{"title":"Prediction and Interpretation Microglia Cytotoxicity by Machine Learning.","authors":"Qing Liu, Dakuo He, Mengmeng Fan, Jinpeng Wang, Zeyu Cui, Hao Wang, Yan Mi, Ning Li, Qingqi Meng, Yue Hou","doi":"10.1021/acs.jcim.4c00366","DOIUrl":"10.1021/acs.jcim.4c00366","url":null,"abstract":"<p><p>Ameliorating microglia-mediated neuroinflammation is a crucial strategy in developing new drugs for neurodegenerative diseases. Plant compounds are an important screening target for the discovery of drugs for the treatment of neurodegenerative diseases. However, due to the spatial complexity of phytochemicals, it becomes particularly important to evaluate the effectiveness of compounds while avoiding the mixing of cytotoxic substances in the early stages of compound screening. Traditional high-throughput screening methods suffer from high cost and low efficiency. A computational model based on machine learning provides a novel avenue for cytotoxicity determination. In this study, a microglia cytotoxicity classifier was developed using a machine learning approach. First, we proposed a data splitting strategy based on the molecule murcko generic scaffold, under this condition, three machine learning approaches were coupled with three kinds of molecular representation methods to construct microglia cytotoxicity classifier, which were then compared and assessed by the predictive accuracy, balanced accuracy, F₁-score, and Matthews Correlation Coefficient. Then, the recursive feature elimination integrated with support vector machine (RFE-SVC) dimension reduction method was introduced to molecular fingerprints with high dimensions to further improve the model performance. Among all the microglial cytotoxicity classifiers, the SVM coupled with ECFP4 fingerprint after feature selection (ECFP4-RFE-SVM) obtained the most accurate classification for the test set (ACC of 0.99, BA of 0.99, F₁-score of 0.99, MCC of 0.97). Finally, the Shapley additive explanations (SHAP) method was used in interpreting the microglia cytotoxicity classifier and key substructure smart identified as structural alerts. Experimental results show that ECFP4-RFE-SVM have reliable classification capability for microglia cytotoxicity, and SHAP can not only provide a rational explanation for microglia cytotoxicity predictions, but also offer a guideline for subsequent molecular cytotoxicity modifications.</p>","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":" ","pages":"9306-9326"},"PeriodicalIF":5.6,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141464275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PEGylated ATP-Independent Luciferins for Noninvasive High-Sensitivity High-Speed Bioluminescence Imaging.","authors":"Xiaodong Tian, Yiyu Zhang, Hui-Wang Ai","doi":"10.1021/acschembio.4c00601","DOIUrl":"https://doi.org/10.1021/acschembio.4c00601","url":null,"abstract":"<p><p>Bioluminescence imaging (BLI) is a powerful, noninvasive imaging method for animal studies. NanoLuc luciferase and its derivatives are attractive bioluminescent reporters recognized for their efficient photon production and ATP independence. However, utilizing them for animal imaging poses notable challenges. Low substrate solubility has been a prominent problem, limiting <i>in vivo</i> brightness, while the susceptibility of luciferins to auto-oxidation by molecular oxygen in air increases handling complexity and poses an obstacle to obtaining consistent results. To address these issues, we developed a range of caged PEGylated luciferins with increased auto-oxidation resistance and water solubility of up to 25 mM, resulting in substantial <i>in vivo</i> bioluminescence increases in mouse models. This advancement has created the brightest and most sensitive luciferase-luciferin combination, enabling high-speed video-rate imaging of freely moving mice with brain-expressed luciferase. These innovative substrates offer new possibilities for investigating a wide range of biological processes and are poised to become invaluable resources for chemical, biological, and biomedical fields.</p>","PeriodicalId":11,"journal":{"name":"ACS Chemical Biology","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142875325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Peptide Nanocarriers for Targeted Delivery of Nucleic Acids for Cancer Therapy.","authors":"Chunli Song, Leying Jiang, Xinrui Sha, Zijun Jiao, Yun Xing, Xi Li, Xinyu Li, Zhiyong Yao, Zigang Li, Dongyuan Wang, Lixiang Zhang, Yaping Zhang, Feng Yin","doi":"10.1021/acs.bioconjchem.4c00324","DOIUrl":"https://doi.org/10.1021/acs.bioconjchem.4c00324","url":null,"abstract":"<p><p>Peptides have been extensively studied in nanomedicine with great bioactivity and biocompatibility; however, their poor cell-membrane-penetrating properties and nonselectivity greatly limit their clinical applications. In this study, tumor-targeting therapy was achieved by modifying our previously developed efficient peptide vector with the cancer-targeting peptide RGD, enabling it to specifically target tumor cells with a high expression of RGD-binding receptors. B-cell lymphoma-2 antisense oligonucleotides were selected as the target model to validate the effectiveness of the delivery carriers. Results demonstrated that this delivery system can be efficiently and selectively taken up by RGD receptor-positive cells (α_vβ₃ integrin receptor), further inducing effective target gene knockdown. Overall, this system provided a promising strategy for the targeted delivery of nucleic acid drugs.</p>","PeriodicalId":29,"journal":{"name":"Bioconjugate Chemistry","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142875479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>Pothos</i>: A Python Package for Polymer Chain Orientation and Microstructure Evolution Monitoring.","authors":"Thomas J Barrett, Marilyn L Minus","doi":"10.1021/acs.jctc.4c01216","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01216","url":null,"abstract":"<p><p>In the pursuit of informing experimental techniques with in silico optimizations, we propose a pip deployable Python package, <i>pothos</i>, to easily determine polymer crystallites within molecular dynamic melts and the chain orientation parameters of atomistic and coarse-grained simulations. The package supports the commonly used ⟨<i>P</i>₂⟩, ⟨<i>P</i>₄⟩, and ⟨<i>P</i>₆⟩ order parameters based on the chain chord vector and utilizes a modified DBSCAN algorithm to determine crystalline regions. The results of analysis are written to text and LAMMPS dump files for visualization and analysis.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142875487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Iodide Enhances the Production of Pseurotin D over Pseurotin A by Inverting the Preference for the S_N2 versus the S_N2' Product in the Final Nonenzymatic Step.","authors":"Yukyung Choi, Yeongseo Kim, Jin Wook Cha, Gyu Sung Lee, Huong T Pham, Men Thi Ngo, Saegun Kim, Chung Sub Kim, Kyo Bin Kang","doi":"10.1021/acs.jnatprod.4c01128","DOIUrl":"https://doi.org/10.1021/acs.jnatprod.4c01128","url":null,"abstract":"<p><p>Nonenzymatic reactions, though critical in natural product biosynthesis, are significantly challenging to control. Adding 3% NaI to the culture medium of <i>Penicillium janczewskii</i> significantly increased pseurotin D (<b>1</b>) production and decreased pseurotin A (<b>2</b>) production. Previously, <b>1</b> and <b>2</b> were suggested to be produced via a nonenzymatic reaction, where the epoxide at C-10 undergoes S_N2 (<b>2</b>) or S_N2' (<b>1</b>) reactions. We confirmed that <b>1</b> was isolated as a 1:1 mixture of C-13 epimers by spectral elucidation via CP3 analysis aided by selective excitation NMR methods, which supported that <b>1</b> was produced through a nonenzymatic S_N2' reaction. We propose that NaI increased the ratio of <b>1</b> by causing steric hindrance at the C-11 position of the transient intermediate, which makes C-13 more preferred in the S_N2/S_N2' competition.</p>","PeriodicalId":47,"journal":{"name":"Journal of Natural Products ","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142875488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Infrared Spectroscopy of Isocyano-Polycyclic Aromatic Hydrocarbons: The NC Stretch.","authors":"Vincent J Esposito, Ryan C Fortenberry, Christiaan Boersma, Louis J Allamandola","doi":"10.1021/acs.jpca.4c07416","DOIUrl":"https://doi.org/10.1021/acs.jpca.4c07416","url":null,"abstract":"<p><p>Anharmonic computations reveal an intense, narrow (20 cm^-1, 0.043 μm) absorption feature at approximately 2160 cm^-1 (4.63 μm) in the vibrational spectra of 14 prototypical singly isocyano-substituted polycyclic aromatic hydrocarbons (NC-PAHs) attributed to the NC stretching mode. The intrinsically bright NC stretching mode and strong anharmonic coupling to other states in this region of the spectrum, along with the presence of multiple isomers of each NC-PAH, creates a complex, intense band for each molecule alone, and for the group of molecules as a whole. The NC stretching feature is shifted approximately 130 cm^-1 to lower frequency compared to the CN stretching feature of cyano-substituted PAHs. This shift is due to the weaker NC bond as a result of the zwitterionic character of the NC-PAHs. Advanced resonance polyad matrices are utilized in the second order vibrational perturbation treatment, providing in-depth understanding of the spectroscopic characteristics of each vibrational transition. These detailed spectroscopic data are provided for use in analysis of future laboratory experiments and the search for NC-PAHs in astronomical observations. Such data will be vital to the continued benchmarking of computational methodologies for use in exotic, substituted PAHs that have never been studied before.</p>","PeriodicalId":59,"journal":{"name":"The Journal of Physical Chemistry A","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142875490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generating Multistate Conformations of P-type ATPases with a Conditional Diffusion Model.","authors":"Jingtian Xu, Yong Wang","doi":"10.1021/acs.jcim.4c01519","DOIUrl":"10.1021/acs.jcim.4c01519","url":null,"abstract":"<p><p>Understanding and predicting the diverse conformational states of membrane proteins is essential for elucidating their biological functions. Despite advancements in computational methods, accurately capturing these complex structural changes remains a significant challenge. Here, we introduce a computational approach to generate diverse and biologically relevant conformations of membrane proteins using a conditional diffusion model. Our approach integrates forward and backward diffusion processes, incorporating state classifiers and additional conditioners to control the generation gradient of conformational states. We specifically targeted the P-type ATPases, a critical family of membrane transporters, and constructed a comprehensive data set through a combination of experimental structures and molecular dynamics simulations. Our model, incorporating a graph neural network with specialized membrane constraints, demonstrates exceptional accuracy in generating a wide range of P-type ATPase conformations associated with different functional states. This approach represents a meaningful step forward in the computational generation of membrane protein conformations using AI and holds promise for studying the dynamics of other membrane proteins.</p>","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":" ","pages":"9227-9239"},"PeriodicalIF":5.6,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142542870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potency Prediction of Covalent Inhibitors against SARS-CoV-2 3CL-like Protease and Multiple Mutants by Multiscale Simulations.","authors":"Muya Xiong, Tianqing Nie, Zhewen Li, Meiyi Hu, Haixia Su, Hangchen Hu, Yechun Xu, Qiang Shao","doi":"10.1021/acs.jcim.4c01594","DOIUrl":"10.1021/acs.jcim.4c01594","url":null,"abstract":"<p><p>3-Chymotrypsin-like protease (3CL^pro) is a prominent target against pathogenic coronaviruses. Expert knowledge of the cysteine-targeted covalent reaction mechanism is crucial to predict the inhibitory potency of approved inhibitors against 3CL^pros of SARS-CoV-2 variants and perform structure-based drug design against newly emerging coronaviruses. We carried out an extensive array of classical and hybrid QM/MM molecular dynamics simulations to explore covalent inhibition mechanisms of five well-characterized inhibitors toward SARS-CoV-2 3CL^pro and its mutants. The calculated binding affinity and reactivity of the inhibitors are highly consistent with experimental data, and the predicted inhibitory potency of the inhibitors against 3CL^pro with L167F, E166V, or T21I/E166V mutant is in full agreement with IC₅₀s determined by the accompanying enzymatic assays. The explored mechanisms unveil the impact of residue mutagenesis on structural dynamics that communicates to change not only noncovalent binding strength but also covalent reaction free energy. Such a change is inhibitor dependent, corresponding to varied levels of drug resistance of these 3CL^pro mutants against nirmatrelvir and simnotrelvir and no resistance to the <b>11a</b> compound. These results together suggest that the present simulations with a suitable protocol can efficiently evaluate the reactivity and potency of covalent inhibitors along with the elucidated molecular mechanisms of covalent inhibition.</p>","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":" ","pages":"9501-9516"},"PeriodicalIF":5.6,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142737777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Good are Current Pocket-Based 3D Generative Models?: The Benchmark Set and Evaluation of Protein Pocket-Based 3D Molecular Generative Models.","authors":"Haoyang Liu, Yifei Qin, Zhangming Niu, Mingyuan Xu, Jiaqiang Wu, Xianglu Xiao, Jinping Lei, Ting Ran, Hongming Chen","doi":"10.1021/acs.jcim.4c01598","DOIUrl":"10.1021/acs.jcim.4c01598","url":null,"abstract":"<p><p>The development of a three-dimensional (3D) molecular generative model based on protein pockets has recently attracted a lot of attention. This type of model aims to achieve the simultaneous generation of molecular graphs and 3D binding conformation under the constraint of protein binding. Various pocket-based generative models have been proposed; however, currently, there is a lack of systematic and objective evaluation metrics for these models. To address this issue, a comprehensive benchmark data set, named POKMOL-3D, is proposed to evaluate protein pocket-based 3D molecular generative models. It includes 32 protein targets together with their known active compounds as a test set to evaluate the versatility of generation models to mimic the real-world scenario. Additionally, a series of two-dimensional (2D) and 3D evaluation metrics with some newly created ones was integrated to assess the quality of generated molecular structures and their binding conformations. It is expected that this work can enhance our comprehension of the effectiveness and weakness of current 3D generative models and stimulate the discussion on challenges and useful guidance for developing the next wave of molecular generative models.</p>","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":" ","pages":"9260-9275"},"PeriodicalIF":5.6,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142764596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kinase-Bench: Comprehensive Benchmarking Tools and Guidance for Achieving Selectivity in Kinase Drug Discovery.","authors":"Tian-Hua Wei, Shuang-Shuang Zhou, Xiao-Long Jing, Jia-Chuan Liu, Meng Sun, Zong-Hao Zhao, Qing-Qing Li, Zi-Xuan Wang, Jin Yang, Yun Zhou, Xue Wang, Cheng-Xiao Ling, Ning Ding, Xin Xue, Yan-Cheng Yu, Xiao-Long Wang, Xiao-Ying Yin, Shan-Liang Sun, Peng Cao, Nian-Guang Li, Zhi-Hao Shi","doi":"10.1021/acs.jcim.4c01830","DOIUrl":"10.1021/acs.jcim.4c01830","url":null,"abstract":"<p><p>Developing selective kinase inhibitors remains a formidable challenge in drug discovery because of the highly conserved structural information on adenosine triphosphate (ATP) binding sites across the kinase family. Tailoring docking protocols to identify promising kinase inhibitor candidates for optimization has long been a substantial obstacle to drug discovery. Therefore, we introduced \"Kinase-Bench,\" a pioneering benchmark suite designed for an advanced virtual screen, to improve the selectivity and efficacy of kinase inhibitors. Our comprehensive data set includes 6875 selective ligands and 422,799 decoys for 75 kinases, using extensive bioactivity and structural data from the ChEMBL database and decoys generated by the Directory of Useful Decoys-Enhanced version. Our benchmarking sets and retrospective case studies were designed to provide useful guidance in discovering selective kinase inhibitors. We employed a Glide High-Throughput Virtual Screen and Standard Precision complemented by three scoring functions and customized protein-ligand interaction filters that target specific kinase residue interactions. These innovations were successfully implemented in our virtual screen efforts targeting JAK1 inhibitors, achieving selectivity against its family member, TYK2. Consequently, we identified novel potential hits: Compound <b>2</b> (JAK1 IC₅₀: 980.5 nM, TYK2 IC₅₀: 4.5 μM) and the approved pan-AKT inhibitor Capivasertib (JAK1 IC₅₀: 275.9 nM, TYK2 IC₅₀: 10.9 μM). Using the Kinase-Bench protocol, both compounds demonstrated substantial JAK1 selectivity, making them strong candidates for further investigation. Our pharmaceutical results underscore the utility of tailored virtual screen protocols in identifying selective kinase inhibitors with substantial implications for rational drug design. Kinase-Bench offers a robust toolset for selective kinase drug discovery with the potential to effectively guide future therapeutic strategies effectively.</p>","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":" ","pages":"9528-9550"},"PeriodicalIF":5.6,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142764599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}