QSAR modeling of nanomaterials.

A thorough understanding of the relationships between the physicochemical properties and the behavior of nanomaterials in biological systems is mandatory for designing safe and efficacious nanomedicines. Quantitative structure-activity relationship (QSAR) methods help to establish such relationships, although their application to model the behavior of nanomaterials requires new ideas and applications to account for the novel properties of this class of compounds. This review presents and discusses a number of recent inspiring applications of QSAR modeling and descriptors for nanomaterials with a focus on approaches that attempt to describe the interactions that take place at the nano/bio-interface. The paradigm shift from classic to nano-QSAR currently relies on both theoretically and experimentally derived descriptors, and the solutions adopted for modeling are diverse, mirroring the structural and behavioral heterogeneity of nanomaterials. Research should focus on both aspects of a QSAR study: the generation of nanospecific theoretical descriptors and experimental test data.

[1]  T. Puzyn,et al.  Toward the development of "nano-QSARs": advances and challenges. , 2009, Small.

[2]  Miquel Solà,et al.  Modeling the structure‐property relationships of nanoneedles: A journey toward nanomedicine , 2009, J. Comput. Chem..

[3]  E. Nakamura,et al.  Fullerene–Oligonucleotide Conjugates: Photoinduced Sequence‐Specific DNA Cleavage , 1995 .

[4]  Takashi Yumura,et al.  End-cap effects on vibrational structures of finite-length carbon nanotubes. , 2005, Journal of the American Chemical Society.

[5]  Judith Klein-Seetharaman,et al.  Carbon nanotubes degraded by neutrophil myeloperoxidase induce less pulmonary inflammation. , 2010, Nature nanotechnology.

[6]  T. Xia,et al.  Understanding biophysicochemical interactions at the nano-bio interface. , 2009, Nature materials.

[7]  Parag Aggarwal,et al.  Nanoparticle interaction with plasma proteins as it relates to particle biodistribution, biocompatibility and therapeutic efficacy. , 2009, Advanced drug delivery reviews.

[8]  J. Nagy,et al.  Application of the Hansen solubility Parameters theory to carbon nanotubes. , 2008, Journal of nanoscience and nanotechnology.

[9]  Andrew P Worth,et al.  A theoretical framework for predicting the oxidative stress potential of oxide nanoparticles , 2011, Nanotoxicology.

[10]  Paul G. Mezey,et al.  The Electronic Structures and Properties of Open-Ended and Capped Carbon Nanoneedles , 2006, J. Chem. Inf. Model..

[11]  R. Bernstein,et al.  On the Mechanism of DNA Cleavage by Fullerenes Investigated in Model Systems: Electron Transfer from Guanosine and 8-Oxo-Guanosine Derivatives to C60 , 1999 .

[12]  Robert G. Parr,et al.  Density Functional Theory of Electronic Structure , 1996 .

[13]  Hideki Yamamoto,et al.  Dispersion and Flocculation Behavior of Fine Metal Oxide Particles in Various Solvents [Translated]† , 2002 .

[14]  Jianzhong Liu,et al.  Identification of possible sources of nanotoxicity from carbon nanotubes inserted into membrane bilayers using membrane interaction quantitative structure--activity relationship analysis. , 2008, Chemical research in toxicology.

[15]  Maurizio Prato,et al.  CELL-PENETRATING CNTS FOR DELIVERY OF THERAPEUTICS , 2007 .

[16]  Jerzy Leszczynski,et al.  A density functional theory study on the effect of shape and size on the ionization potential and electron affinity of different carbon nanostructures , 2006 .

[17]  M. Prato,et al.  Applications of carbon nanotubes in drug delivery. , 2005, Current opinion in chemical biology.

[18]  C. Teng,et al.  Neuroprotective effect of hexasulfobutylated C60 on rats subjected to focal cerebral ischemia. , 2001, Free radical biology & medicine.

[19]  Kenneth A. Dawson,et al.  Nanoparticle size and surface properties determine the protein corona with possible implications for biological impacts , 2008, Proceedings of the National Academy of Sciences.

[20]  A. Tropsha,et al.  Quantitative nanostructure-activity relationship modeling. , 2010, ACS nano.

[21]  Sabina Passamonti,et al.  Hemolytic effects of water-soluble fullerene derivatives. , 2004, Journal of medicinal chemistry.

[22]  Yang Yang,et al.  Data flow modeling, data mining and QSAR in high-throughput discovery of functional nanomaterials , 2011, Comput. Chem. Eng..

[23]  M. Dobrovolskaia,et al.  Immunological properties of engineered nanomaterials , 2007, Nature Nanotechnology.

[24]  D. Choi,et al.  Buckminsterfullerenol Free Radical Scavengers Reduce Excitotoxic and Apoptotic Death of Cultured Cortical Neurons , 1996, Neurobiology of Disease.

[25]  Masataka Mochizuki,et al.  Antibacterial and antiproliferative activity of cationic fullerene derivatives. , 2003, Bioorganic & medicinal chemistry letters.

[26]  Susanna Bosi,et al.  Antimycobacterial Activity of Ionic Fullerene Derivatives , 2000 .

[27]  Jim E Riviere,et al.  An index for characterization of nanomaterials in biological systems. , 2010, Nature nanotechnology.

[28]  Hongyu Zhou,et al.  A nano-combinatorial library strategy for the discovery of nanotubes with reduced protein-binding, cytotoxicity, and immune response. , 2008, Nano letters.

[29]  Sara Linse,et al.  Understanding the nanoparticle–protein corona using methods to quantify exchange rates and affinities of proteins for nanoparticles , 2007, Proceedings of the National Academy of Sciences.