Literature DB >> 26525350

Computer-aided design of carbon nanotubes with the desired bioactivity and safety profiles.

Denis Fourches1, Dongqiuye Pu2, Liwen Li3, Hongyu Zhou3, Qingxin Mu3, Gaoxing Su3, Bing Yan3, Alexander Tropsha2.   

Abstract

Growing experimental evidences suggest the existence of direct relationships between the surface chemistry of nanomaterials and their biological effects. Herein, we have employed computational approaches to design a set of biologically active carbon nanotubes (CNTs) with controlled protein binding and cytotoxicity. Quantitative structure-activity relationship (QSAR) models were built and validated using a dataset of 83 surface-modified CNTs. A subset of a combinatorial virtual library of 240 000 ligands potentially attachable to CNTs was selected to include molecules that were within the chemical similarity threshold with respect to the modeling set compounds. QSAR models were then employed to virtually screen this subset and prioritize CNTs for chemical synthesis and biological evaluation. Ten putatively active and 10 putatively inactive CNTs decorated with the ligands prioritized by virtual screening for either protein-binding or cytotoxicity assay were synthesized and tested. We found that all 10 putatively inactive and 7 of 10 putatively active CNTs were confirmed in the protein-binding assay, whereas all 10 putatively inactive and 6 of 10 putatively active CNTs were confirmed in the cytotoxicity assay. This proof-of-concept study shows that computational models can be employed to guide the design of surface-modified nanomaterials with the desired biological and safety profiles.

Entities:  

Keywords:  Carbon nanotubes; QSAR; cheminformatics; nanotoxicity; virtual screening

Mesh:

Substances:

Year:  2015        PMID: 26525350      PMCID: PMC4959546          DOI: 10.3109/17435390.2015.1073397

Source DB:  PubMed          Journal:  Nanotoxicology        ISSN: 1743-5390            Impact factor:   5.913


  42 in total

1.  Novel variable selection quantitative structure--property relationship approach based on the k-nearest-neighbor principle

Authors: 
Journal:  J Chem Inf Comput Sci       Date:  2000-01

Review 2.  Toxic potential of materials at the nanolevel.

Authors:  Andre Nel; Tian Xia; Lutz Mädler; Ning Li
Journal:  Science       Date:  2006-02-03       Impact factor: 47.728

3.  Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis.

Authors:  Hao Zhu; Alexander Tropsha; Denis Fourches; Alexandre Varnek; Ester Papa; Paola Gramatica; Tomas Oberg; Phuong Dao; Artem Cherkasov; Igor V Tetko
Journal:  J Chem Inf Model       Date:  2008-03-01       Impact factor: 4.956

4.  Towards understanding mechanisms governing cytotoxicity of metal oxides nanoparticles: hints from nano-QSAR studies.

Authors:  Agnieszka Gajewicz; Nicole Schaeublin; Bakhtiyor Rasulev; Saber Hussain; Danuta Leszczynska; Tomasz Puzyn; Jerzy Leszczynski
Journal:  Nanotoxicology       Date:  2014-07-01       Impact factor: 5.913

5.  Modeling biological activities of nanoparticles.

Authors:  V Chandana Epa; Frank R Burden; Carlos Tassa; Ralph Weissleder; Stanley Shaw; David A Winkler
Journal:  Nano Lett       Date:  2012-10-09       Impact factor: 11.189

6.  QSAR as a random event: modeling of nanoparticles uptake in PaCa2 cancer cells.

Authors:  Andrey A Toropov; Alla P Toropova; Tomasz Puzyn; Emilio Benfenati; Giuseppina Gini; Danuta Leszczynska; Jerzy Leszczynski
Journal:  Chemosphere       Date:  2013-04-06       Impact factor: 7.086

7.  Trust, but verify: on the importance of chemical structure curation in cheminformatics and QSAR modeling research.

Authors:  Denis Fourches; Eugene Muratov; Alexander Tropsha
Journal:  J Chem Inf Model       Date:  2010-07-26       Impact factor: 4.956

8.  Reducing nanotube cytotoxicity using a nano-combinatorial library approach.

Authors:  Qiu Zhang; Hongyu Zhou; Bing Yan
Journal:  Methods Mol Biol       Date:  2010

9.  Protein binding modulates the cellular uptake of silver nanoparticles into human cells: implications for in vitro to in vivo extrapolations?

Authors:  Nancy A Monteiro-Riviere; Meghan E Samberg; Steven J Oldenburg; Jim E Riviere
Journal:  Toxicol Lett       Date:  2013-05-06       Impact factor: 4.372

10.  Recent advances in graphene family materials toxicity investigations.

Authors:  Agnieszka Maria Jastrzębska; Patrycja Kurtycz; Andrzej Roman Olszyna
Journal:  J Nanopart Res       Date:  2012-11-29       Impact factor: 2.253

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  10 in total

Review 1.  QSAR without borders.

Authors:  Eugene N Muratov; Jürgen Bajorath; Robert P Sheridan; Igor V Tetko; Dmitry Filimonov; Vladimir Poroikov; Tudor I Oprea; Igor I Baskin; Alexandre Varnek; Adrian Roitberg; Olexandr Isayev; Stefano Curtarolo; Denis Fourches; Yoram Cohen; Alan Aspuru-Guzik; David A Winkler; Dimitris Agrafiotis; Artem Cherkasov; Alexander Tropsha
Journal:  Chem Soc Rev       Date:  2020-05-01       Impact factor: 54.564

Review 2.  Toward a systematic exploration of nano-bio interactions.

Authors:  Xue Bai; Fang Liu; Yin Liu; Cong Li; Shenqing Wang; Hongyu Zhou; Wenyi Wang; Hao Zhu; David A Winkler; Bing Yan
Journal:  Toxicol Appl Pharmacol       Date:  2017-03-24       Impact factor: 4.219

3.  Predicting Nano-Bio Interactions by Integrating Nanoparticle Libraries and Quantitative Nanostructure Activity Relationship Modeling.

Authors:  Wenyi Wang; Alexander Sedykh; Hainan Sun; Linlin Zhao; Daniel P Russo; Hongyu Zhou; Bing Yan; Hao Zhu
Journal:  ACS Nano       Date:  2017-11-22       Impact factor: 15.881

4.  Elucidation of the Molecular Determinants for Optimal Perfluorooctanesulfonate Adsorption Using a Combinatorial Nanoparticle Library Approach.

Authors:  Yin Liu; Gaoxing Su; Fei Wang; Jianbo Jia; Shuhuan Li; Linlin Zhao; Yali Shi; Yaqi Cai; Hao Zhu; Bin Zhao; Guibin Jiang; Hongyu Zhou; Bing Yan
Journal:  Environ Sci Technol       Date:  2017-06-06       Impact factor: 9.028

5.  Evaluating the cytotoxicity of a large pool of metal oxide nanoparticles to Escherichia coli: Mechanistic understanding through In Vitro and In Silico studies.

Authors:  Supratik Kar; Kavitha Pathakoti; Paul B Tchounwou; Danuta Leszczynska; Jerzy Leszczynski
Journal:  Chemosphere       Date:  2020-09-25       Impact factor: 7.086

Review 6.  Trust, but Verify II: A Practical Guide to Chemogenomics Data Curation.

Authors:  Denis Fourches; Eugene Muratov; Alexander Tropsha
Journal:  J Chem Inf Model       Date:  2016-06-22       Impact factor: 4.956

Review 7.  Reproducibility, sharing and progress in nanomaterial databases.

Authors:  Alexander Tropsha; Karmann C Mills; Anthony J Hickey
Journal:  Nat Nanotechnol       Date:  2017-12-06       Impact factor: 40.523

Review 8.  Practices and Trends of Machine Learning Application in Nanotoxicology.

Authors:  Irini Furxhi; Finbarr Murphy; Martin Mullins; Athanasios Arvanitis; Craig A Poland
Journal:  Nanomaterials (Basel)       Date:  2020-01-08       Impact factor: 5.076

9.  Computational Indicator Approach for Assessment of Nanotoxicity of Two-Dimensional Nanomaterials.

Authors:  Alexey A Tsukanov; Boris Turk; Olga Vasiljeva; Sergey G Psakhie
Journal:  Nanomaterials (Basel)       Date:  2022-02-15       Impact factor: 5.076

10.  A safe-by-design tool for functionalised nanomaterials through the Enalos Nanoinformatics Cloud platform.

Authors:  Dimitra-Danai Varsou; Antreas Afantitis; Andreas Tsoumanis; Georgia Melagraki; Haralambos Sarimveis; Eugenia Valsami-Jones; Iseult Lynch
Journal:  Nanoscale Adv       Date:  2018-11-05
  10 in total

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