Accurate and efficient gp120 V3 loop structure based models for the determination of HIV-1 co-receptor usage
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[1] David A. Price,et al. Maraviroc (UK-427,857), a Potent, Orally Bioavailable, and Selective Small-Molecule Inhibitor of Chemokine Receptor CCR5 with Broad-Spectrum Anti-Human Immunodeficiency Virus Type 1 Activity , 2005, Antimicrobial Agents and Chemotherapy.
[2] Andrew J. Low,et al. Predicting HIV Coreceptor Usage on the Basis of Genetic and Clinical Covariates , 2007, Antiviral therapy.
[3] J. Sleasman,et al. Envelope V3 amino acid sequence predicts HIV-1 phenotype (co-receptor usage and tropism for macrophages). , 2000, AIDS.
[4] H. Schuitemaker,et al. Biological phenotype of human immunodeficiency virus type 1 clones at different stages of infection: progression of disease is associated with a shift from monocytotropic to T-cell-tropic virus population , 1992, Journal of virology.
[5] M. Quiñones-Mateu,et al. Current tests to evaluate HIV-1 coreceptor tropism , 2009, Current opinion in HIV and AIDS.
[6] Iosif I. Vaisman,et al. Compositional preferences in quadruplets of nearest neighbor residues in protein structures: statistical geometry analysis , 1998, Proceedings. IEEE International Joint Symposia on Intelligence and Systems (Cat. No.98EX174).
[7] G. Crooks,et al. WebLogo: a sequence logo generator. , 2004, Genome research.
[8] M. Jensen,et al. Predicting HIV-1 coreceptor usage with sequence analysis. , 2003, AIDS reviews.
[9] Majid Masso,et al. Comprehensive mutagenesis of HIV-1 protease: a computational geometry approach. , 2003, Biochemical and biophysical research communications.
[10] B. Korber,et al. A new classification for HIV-1 , 1998, Nature.
[11] Iosif I. Vaisman,et al. A Novel Sequence-Structure Approach for Accurate Prediction of Resistance to HIV-1 Protease Inhibitors , 2007, 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering.
[12] Tobias Sing,et al. Current V3 genotyping algorithms are inadequate for predicting X4 co-receptor usage in clinical isolates , 2007, AIDS.
[13] Majid Masso,et al. Computational mutagenesis studies of protein structure‐function correlations , 2006, Proteins.
[14] Iosif I. Vaisman,et al. Computational Mutagenesis of E. coliLacRepressor: Insight into Structure-Function Relationships and Accurate Prediction of Mutant Activity , 2008, ISBRA.
[15] Iosif I. Vaisman,et al. Accurate prediction of enzyme mutant activity based on a multibody statistical potential , 2007, Bioinform..
[16] T. N. Bhat,et al. The Protein Data Bank , 2000, Nucleic Acids Res..
[17] R. Swanstrom,et al. Improved success of phenotype prediction of the human immunodeficiency virus type 1 from envelope variable loop 3 sequence using neural networks. , 2001, Virology.
[18] Guoli Wang,et al. PISCES: a protein sequence culling server , 2003, Bioinform..
[19] Yuntao Wu. The co-receptor signaling model of HIV-1 pathogenesis in peripheral CD4 T cells , 2009, Retrovirology.
[20] Shungao Xu,et al. Improved prediction of coreceptor usage and phenotype of HIV-1 based on combined features of V3 loop sequence using random forest. , 2007, Journal of microbiology.
[21] D. Kuritzkes. HIV-1 entry inhibitors: an overview , 2009, Current opinion in HIV and AIDS.
[22] Holger Scheib,et al. HIV-1 coreceptor selectivity: structural analogy between HIV-1 V3 regions and chemokine beta-hairpins is not the explanation. , 2006, Structure.
[23] J. Zack,et al. CD4+ NK cells can be productively infected with HIV, leading to downregulation of CD4 expression and changes in function. , 2009, Virology.
[24] David P. Dobkin,et al. The quickhull algorithm for convex hulls , 1996, TOMS.
[25] Michal Sharon,et al. Alternative conformations of HIV-1 V3 loops mimic beta hairpins in chemokines, suggesting a mechanism for coreceptor selectivity. , 2003, Structure.
[26] Ian H. Witten,et al. Data mining in bioinformatics using Weka , 2004, Bioinform..
[27] Teruaki Watabe,et al. Fold Recognition of the Human Immunodeficiency Virus Type 1 V3 Loop and Flexibility of Its Crown Structure During the Course of Adaptation to a Host , 2006, Genetics.
[28] Lynn Morris,et al. A Reliable Phenotype Predictor for Human Immunodeficiency Virus Type 1 Subtype C Based on Envelope V3 Sequences , 2006, Journal of Virology.
[29] J. Goudsmit,et al. Minimal requirements for the human immunodeficiency virus type 1 V3 domain to support the syncytium-inducing phenotype: analysis by single amino acid substitution , 1992, Journal of virology.
[30] D. Eisenberg,et al. A method to identify protein sequences that fold into a known three-dimensional structure. , 1991, Science.
[31] Steven M. Wolinsky,et al. The role of a mutant CCR5 allele in HIV–1 transmission and disease progression , 1996, Nature Medicine.
[32] K. Boulez,et al. The complete Consensus V3 loop peptide of the envelope protein gp120 of HIV‐1 shows pronounced helical character in solution , 1995, FEBS letters.
[33] Iosif I. Vaisman,et al. Accurate prediction of stability changes in protein mutants by combining machine learning with structure based computational mutagenesis , 2008, Bioinform..
[34] G. Ulivi,et al. Robust supervised and unsupervised statistical learning for HIV type 1 coreceptor usage analysis. , 2009, AIDS research and human retroviruses.
[35] Jacques Corbeil,et al. A new perspective on V3 phenotype prediction. , 2003, AIDS research and human retroviruses.
[36] Conrad C. Huang,et al. UCSF Chimera—A visualization system for exploratory research and analysis , 2004, J. Comput. Chem..
[37] J. Albert,et al. Replicative capacity, cytopathic effect and cell tropism of HIV , 1989, AIDS.
[38] Thomas Lengauer,et al. Structural Descriptors of gp120 V3 Loop for the Prediction of HIV-1 Coreceptor Usage , 2007, PLoS Comput. Biol..
[39] Manfred J. Sippl,et al. Boltzmann's principle, knowledge-based mean fields and protein folding. An approach to the computational determination of protein structures , 1993, J. Comput. Aided Mol. Des..