Publications, Classified by Research Category

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Conformational search

  • A. Vajdi and N. Haspel. Clustering Protein Conformations Using a Dynamic Programming Based Similarity Measurement Proc. of BICoB (8th international conference on bioinformatics and computational biology), Las Vegas, NV, March, 2016. BibTeX
  • Luo D. and N. Haspel. Multi-resolution rigidity-based sampling of protein confor- mational paths. In CSBW (Computational Structural Bioinformatics Workshop), in proc. of ACM-BCB, 787-793, 2013. BibTeX  
  • N. Haspel, D. Luo and E. Gonzalez. Detecting Intermediate Structures in Protein Conformational Pathways. Proc. of BICoB (5th international conference on bioinformatics and computational biology), Honolulu, HI, March 5-7, 2013. BibTeX  
  • D. Luo and N. Haspel. Efficient Coarse-Grained Geometry-Based Sampling of Protein Conformational Paths. Proc. of BICoB (5th international conference on bioinformatics and computational biology), Honolulu, HI, March 5-7, 2013. BibTeX  
  • N. Haspel and E. Gonzalez. Topological Properties of the Configuration Spaces of Proteins. Proc. of BICoB (4th international conference on bioinformatics and computational biology), Las Vegas, NV, March 12-14, 2012. BibTeX  
  • R. Vetro, N. Haspel and D. Simovici. Characterizing intermediate conformations in protein conformational space. Proc. of the Ninth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics , Houston, TX, July 2012. BibTeX  
  • N., Haspel. Tracing conformational changes in proteins represented at a coarse level. proc. of BIONETICS 2010, Dec. 1-3 2010, Boston MA, USA. BibTeX
  • N., Haspel, M., Moll, M.L., Baker, W., Chiu and L.E. Kavraki. Tracing conformational changes in proteins.BMC Structural Biology, 10 Suppl 1 (S1), 2010. BibTeX  
  • N., Haspel, M., Moll, M.L., Baker, W., Chiu and L.E. Kavraki. Tracing conformational changes in proteins. proceedings of the Computational Structural Biology Workshop (CSBW '09), in conjunction with IEEE international conference on Bioinformatics and Biomedicine (BIBM 09), Washington DC, Nov. 2009. BibTeX pdf  

Docking

  • R. Farhoodi, B. Akbal-Delibas and N. Haspel. Machine Learning Approaches for Predicting Protein Structure Similarity. Journal of Computational Biology, 24(1), pages 40-51 2017. BibTeX
  • B. Akbal-Delibas, R. Farhoodi, M. Pomplun and N. Haspel. Accurate refinement of docked protein complexes using evolutionary information and deep learning. J. Bioinf. Comp. Biol., 14(3):1642002, 2016. BibTeX
  • R. Farhoodi, B. Akbal-Delibas and N. Haspel. Accurate prediction of docked protein structure similarity using neural networks and restricted boltzmann machines. CSBW (Computational Structural Bioinformatics Workshop), in conjunction with IEEE-BIBM, Washington DC 2015. BibTeX
  • Haspel N. Methods for Detecting Protein Binding Interfaces. Methods in Pharmacology and Toxicology, volume on Computer-aided Drug Discovery, pages 133-152. Editor: Wei Zhang, Publisher: Springer 2015. BibTeX
  • B. Akbal-Delibas, M. Pomplun and N. Haspel. Accurate prediction of docked protein structure similarity. J. Comp. Biol., 22(9):892-904, 2015. BibTeX
  • N. Haspel Methods for Detecting Protein Binding Interfaces. Methods in Pharmacology and Toxicology, volume on Computer-aided Drug Discovery, pages 1-21. Editor: Wei Zhang, Publisher: Springer, 2015. BibTeX
  • B. Akbal-Delibas, M. Pomplun and N. Haspel. AccuRMSD: A Machine Learning Approach to Predicting Structure Similarity of Docked Protein Complexes proc. of ACM-BCB (5th ACM International conference on Bioinformatics and Computational Biology), Newport Beach, CA, September 2014. BibTeX
  • Akbal-Delibas, B. and N. Haspel. A conservation and biophysics guided stochastic approach to refining docked multimeric proteins. BMC Struct. Biol., 13(Suppl 1):S7, 2013. BibTeX
  • B. Akbal-Delibas, I. Hashmi, A. Shehu and N. Haspel. An Evolutionary Conservation Based Method for Refining and Reranking Protein Complex Structures. Journal of Bioinformatics and Computational Biology (JBCB),10(3):1242008, 2012. BibTeX
  • I. Hashmi, B. Akbal-Delibas, N. Haspel and A. Shehu. Guiding protein docking with geometric and evolutionary information. Journal of Bioinformatics and Computational Biology (JBCB),10(3):1242002, 2012. BibTeX
  • B. Akbal, I. Hashmi, A. Shehu and N. Haspel. Refinement of protein complex structures using evolutionary traces.Proc. of the Computational Structural Biology Workshop (CSBW), in conjunction with IEEE BIBM '11, 400-405, 2011. BibTeX
  • I. Hashmi, B. Akbal, N. Haspel and A. Shehu. Protein docking with information on evilutionary conserved interfaces.Proc. of the Computational Structural Biology Workshop (CSBW), in conjunction with IEEE BIBM '11, 358-365, 2011. BibTeX
  • D. Schneidman-Duhovny, Y. Inbar, V. Polak, M. Shatsky, I. Halperin, H. Benyamini, A. Barzilai, O. Dror, N. Haspel, R. Nussinov, and H.J. Wolfson. Taking geometry to its edge: Fast unbound rigid (and hinge-bent) docking. Proteins, 52(1):107–112, 2003. BibTeX pdf  

Critical Residues

  • E. Andersson, R. Hsieh, H. Szeto, R. Farhoodi, F. Jagodzinski and N. Haspel. Assessing how multiple mutations affect protein stability using rigid cluster size distributions. In proc. of IEEE-ICCABS (International Conference on Computational Advances in Bio and Medical Sciences), Atlanta, GA, October 13-15, 2016. BibTeX
  • N. Haspel and F. Jagodzinski, Methods for detecting critical residues in proteins. In Methods Mol. Biol., volume on In Vitro Mutagenesis, pages 227-242. Editor: A. Reeves, Publisher: Springer, NY, USA, 2016. BibTeX
  • B. Akbal-Delibas, F. Jagodzinski, and N. Haspel. A conservation and rigidity based method for detecting critical protein residues. BMC Struct. Biol., 13(Suppl 1):S6, 2013. BibTeX
  • F. Jagodzinski, B. Akbal-Delibas and N. Haspel. An evolutionary conservation & rigidity analysis machine learning approach for detecting critical protein residues. In CSBW (Computational Structural Bioinformatics Workshop), in proc. of ACM-BCB, 780-786,2013. BibTeX
  • B. Akbal, F. Jagodzinski and N. Haspel. Towards a Hybrid Method for Detecting Critical Protein Residues. Proc. of the Computational Structural Biology Workshop (CSBW), in conjunction with IEEE BIBM, 82-85, Philadelphia, PA, Oct. 2012. BibTeX

Molecular Modeling

  • N. Haspel, J. Zheng, D. Zanuy, C. Aleman and R. Nussinov. A protocol for the design of protein and peptide nanostructure self- assemblies exploiting synthetic amino acids. In Methods Mol. Biol., volume 1529 (on Computational Drug Design), pages 323-352. Editor: I. Samish, Publisher: Springer, NY, USA, 2017. BibTeX
  • Sara K. Murase, Nurit Haspel, Luis J. del Vallea, Eric A. Perpète, Catherine Michaux, Ruth Nussinov, Jordi Puiggalí and Carlos Alemán. Molecular characterization of l-phenylalanine terminated poly(l-lactide) conjugates. RSC Advances, 4(44):23231-23241, 2014. BibTeX  
  • Zanuy D., Kotla R., Nussinov R., Teesalu T., Sugahara K. N., Aleman C. and N. Haspel. Sequence dependence of C-End Rule peptides in binding and activation of Neuropilin -1 Receptor. J. Struct. Bio, 182(2):78-86, 2013. BibTeX  
  • Haspel N., Laurent A. D., Zanuy D., Nussinov R., Aleman C., Puiggali J. and Revilla-López G. Conformational Exploration of Two Peptides and Their Hybrid Polymer Conjugates: Potentialities as Self-Aggregating Materials. J. Chem. Phys. B , 116(48):13941-52, 2012. BibTeX  
  • N., Haspel, D., Zanuy, R., Nussinov, T., Teesalu, E., Ruoslahti and C. Aleman. Binding of a C-end rule peptide to the neuropilin-1 receptor: a molecular modeling approach.Biomacromolecules, 50(10):1755-1762, 2011. BibTeX
  • N., Haspel, B., Geisbrecht, J.D., Lambris, and L.E. Kavraki. Multi-scale Characterization of the Energy Landscape of Proteins with Application to the C3d/Efb-C Complex. Proteins: Structure, Function and Bioinformatics, 78(4):1004-1014, 2010. BibTeX
  • D., Zanuy, G., Ballano, A.I., Jimenez AI, J., Casanovas, N., Haspel, C., Cativiela, D., Curco, R., Nussinov and C., Aleman. Protein Segments with Conformationally Restricted Amino Acids Can Control Supramolecular Organization at the Nanoscale. Journal of Chemical Information and Modeling, 49(7):1623–1629, 2009. BibTeX pdf  
  • N., Haspel, D., Ricklin, B., Geisbrecht, J., Lambris, and L.E., Kavraki . Electrostatic Contributions Drive the Interaction Between Staphylococcus aureus Protein Efb-C and its Complement Target C3d. Prot. Sci., 17(11):1894–1906, 2008. BibTeX pdf  
  • N., Haspel, D., Zanuy, J., Zheng, C., Aleman, H., Wolfson, and R. Nussinov. Changing the charge distribution of beta-helical based nanostructures can provide the conditions for charge transfer. Biophys. J., 93:245–253, 2007. BibTeX pdf  
  • J.,Zheng, D., Zanuy, N., Haspel, C.J., Tsai, C., Aleman, and R., Nussinov. Nanostructure design using protein building blocks enhanced by conformationally constrained synthetic residues.. Biochemistry, 46(5):1205–1218, 2007.BibTeX pdf  
  • D. Zanuy, F. Rodriguez-Ropero, N. Haspel, J. Zheng, R. Nussinov, and C. Aleman. Stability of tubular structures based on beta-helical proteins: self-assembled versus polymerized nanoconstructs and wild-type versus mutated sequences. . Biomacromolecules, 8(10):3135–3146, 2007. BibTeX
  • C.J., Tsai, J.,Zheng, D., Zanuy, N., Haspel, and R., Nussinov. Principles of nanostructure design with protein building blocks. Proteins, 68, 2007. BibTeX pdf  
  • C., Aleman, D., Zanuy, A.I., Jimenez, C., Cativiela, N., Haspel, J., Zheng, J., Casanovas, H., Wolfson, and R., Nussinov. Concepts and schemes for the re-engineering of physical protein modules: generating nanodevices via targeted replacements with constrained amino acids.. Phys. Biol., 3(1):S54–62, 2006. BibTeX pdf  
  • N., Haspel, D., Zanuy, C., Aleman, H., Wolfson, and Nussinov R.. De-novo tubular nanostructure design based on self-assembly of beta-helical protein motifs. Structure, 14:1137–1148, 2006. BibTeX pdf  

Protein folding

  • N., Haspel, G., Wainreb, Y., Inbar, H.H., Tsai, C.J., Tsai, H.J., Wolfson, and R., Nussinov. A hierarchical protein folding scheme based on the building block folding model. Methods Mol. Biol., 350:189–204, 2007. BibTeX
  • G., Wainreb, N., Haspel, H., Wolfson, and R., Nussinov. A permissive secondary structure-guided superposition tool for clustering of protein fragments toward protein structure prediction via fragment assembly. Bioinformatics, 22:1343–1352, 2006. BibTeX pdf  
  • N., Haspel, C.J., Tsai, H., Wolfson, and R., Nussinov. Hierarchical protein folding pathways: A computational study of protein fragments.. Proteins, 51:203–215, 2003. BibTeX pdf  
  • N., Haspel, C.J., Tsai, H., Wolfson, and R., Nussinov. Reducing the computational complexity of protein folding via fragment folding and assembly.. Prot. Sci., 12:1177–1187, 2003. BibTeX pdf  
  • N., Haspel, C.J., Tsai, H., Wolfson, and R., Nussinov. From the building blocks folding model to protein structure prediction. In Protein Structure Prediction: Bioinformatics approach, pp. 201–226, Ed. Tsigelny I., 2002. BibTeX
  • S., Kumar, A., Barzilai, N., Haspel, Y.Y., Sham, C.J., Tsai, H., Wolfson, and R., Nussinov. Critical building blocks in proteins: a common theme in folding and binding. In Recent Research Developments in Protein Folding, Stability and Design., Gromiha, M. KH. and Selvarage, S., Trivadrum, India, 2002. BibTeX

Amyloids

  • N., Haspel, D., Zanuy, B., Ma, H., Wolfson, and R., Nussinov. A comparative study of amyloid fibril formation by residues 15-19 of the human calcitonin hormone: A single beta-sheet model with a small hydrohpobic core. J Mol Biol., 345(5):1213–1227, 2005. BibTeX pdf 
  • N., Haspel, D., Zanuy, H.H., Tsai, B., Ma, H., Wolfson, and R., Nussinov. Computational approaches and tools for establishing structural models for short amyloid-forming peptides.. In Amyloid Proteins, pp. 301–318, Ed. Jean D. Sipe.Wiley-VCH, 2005.BibTeX
  • H.H., Tsai, D., Zanuy, N., Haspel, K., Gunasekaran, B., Ma, C.J., Tsai, and R. Nussinov. The stability and dynamic of the human Calcitonin amyloid peptide DFNKF.. Biophys. J., 87(1):146–158, 2004. BibTeX pdf  
  • D., Zanuy, N., Haspel, H.H., Tsai, B., Ma, G., Kannan, H., Wolfson, and R. Nussinov. Side chain interactions determine the amyloid organization: A single layer beta-sheet molecular structure of the calcitonin peptide segment 15-19.. Phys. Biol., 1:89–99, 2004. BibTeX pdf  

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