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Lu R-M, Hwang Y-C, Liu IJ, Lee C-C, Tsai H-Z, Li H-J, Wu H-C. Improvement of therapeutic antibodies for the remedy of ailments. J Biomed Sci. 2020;27:1.
Grilo AL, Mantalaris A. The more and more human and worthwhile monoclonal antibody market. Traits Biotechnol. 2019;37:9–16.
Berger M, Shankar V, Vafai A. Therapeutic functions of monoclonal antibodies. Am J Med Sci. 2002;324:14–30.
Hwang WYK, Foote J. Immunogenicity of engineered antibodies. Strategies. 2005;36:3–10.
Strohl W, Strohl L. 8-Monoclonal antibody targets and mechanisms of motion. Thera Antibody Eng. 2012;9:163–96.
Kettleborough CA, Saldanha J, Heath VJ, Morrison CJ, Bendig MM. Humanization of a mouse monoclonal antibody by CDR–grafting: the significance of framework residues on loop conformation. Protein Eng Des Sel. 1991;4:773–83.
Mateo C, Moreno E, Amour Ok, Lombardero J, Harris W. Humanization of a mouse monoclonal antibody that blocks the epidermal progress issue receptor: restoration of antagonistic exercise. Immunotechnology. 1997;3:71–81.
Harding FA, Stickler MM, Razo J, DuBridge R. The immunogenicity of humanized and totally human antibodies: residual immunogenicity resides within the CDR areas. MAbs. 2010;2(3):256–65.
Safdari Y, Farajnia S, Asgharzadeh M, Khalili M. Antibody humanization strategies – a assessment and replace. Biotechnol Genet Eng Rev. 2013;29:175–86.
Khee Hwang WY, Almagro JC, Buss TN, Tan P, Foote J. Use of human germline genes in a CDR homology-based method to antibody humanization. Strategies. 2005;36:35–42.
Pelat T, Thullier P. Non-human primate immune libraries mixed with germline humanization. MAbs. 2009;1:377–81.
Tan P, Mitchell DA, Buss TN, Holmes MA, Anasetti C, Foote J. “Superhumanized” antibodies: discount of immunogenic potential by complementarity-determining area grafting with human germline sequences: Software to an Anti-CD28. J Immunol. 2002;169:1119–25.
Pelat T, Bedouelle H, Rees AR, Crennell SJ, Lefranc M-P, Thullier P. Germline humanization of a non-human primate antibody that neutralizes the anthrax toxin, by in vitro and in silico engineering. J Mol Biol. 2008;384:1400–7.
Sangpheak Ok, Waraho-zhmayev D, Haonoo Ok, Torpaiboon S, Teacharsripaiboon T, Rungrotmongkol T, Poo-arporn RP. Investigation of interactions between binding residues and solubility of grafted humanized anti-VEGF IgG antibodies expressed as full-length format within the cytoplasm of a novel engineered E coli SHuffle pressure. RSC Adv. 2021;11:6035–48.
Olimpieri PP, Marcatili P, Tramontano A. Tabhu: instruments for antibody humanization. Bioinformatics. 2015;31:434–5.
Bujotzek A, Lipsmeier F, Harris SF, Benz J, Kuglstatter A, Georges G. VH-VL orientation prediction for antibody humanization candidate choice: A case examine. MAbs. 2016;8(2):288–305.
Zhao Z, Worthylake D, LeCour L Jr, Maresh GA, Pincus SH. Crystal Construction and Computational Modeling of the Fab Fragment from a Protecting Anti-Ricin Monoclonal Antibody. PLoS ONE. 2012;7:e52613.
Kurella VB, Gali R. Construction guided homology mannequin based mostly design and engineering of mouse antibodies for humanization. Bioinformation. 2014;10:180.
Teplyakov A, Luo J, Obmolova G, Malia TJ, Candy R, Stanfield RL, Kodangattil S, Almagro JC, Gilliland GL. Antibody modeling evaluation II. Buildings and fashions Proteins. 2014;82:1563–82.
Maier JK, Labute P. Evaluation of totally automated antibody homology modeling protocols in molecular working setting. Proteins. 2014;82:1599–610.
Sharma VK, Patapoff TW, Kabakoff B, Pai S, Hilario E, Zhang B, Li C, Borisov O, Kelley RF, Chorny I, et al. In silico choice of therapeutic antibodies for improvement: Viscosity, clearance, and chemical stability. Proc Natl Acad Sci. 2014;111:18601–6.
Kortkhonjia E, Brandman R, Zhou JZ, Voelz VA, Chorny I, Kabakoff B, Patapoff TW, Dill KA, Swartz TE. Probing antibody inner dynamics with fluorescence anisotropy and molecular dynamics simulations. MAbs. 2013;5:306–22.
Margreitter C, Mayrhofer P, Kunert R, Oostenbrink C. Antibody humanization by molecular dynamics simulations—in-silico guided choice of crucial backmutations. J Mol Recognit. 2016;29:266–75.
Wall ME, Phillips GN Jr, Subramaniam S. Protein construction willpower utilizing a database of interatomic distance possibilities. Protein Sci. 1999;8:2720–7.
Maiorov VN, Crippen GM. Significance of root-mean-square deviation in evaluating three-dimensional buildings of globular proteins. J Mol Biol. 1994;235:625–34.
Carugo O. Statistical validation of the root-mean-square-distance, a measure of protein structural proximity. Protein Eng Des Sel. 2007;20:33–7.
Sargsyan Ok. How molecular dimension impacts RMSD functions in molecular dynamics simulations. J Chem Idea Comput. 2017;13:1518–24.
Damm KL, Carlson HA. Gaussian-weighted RMSD superposition of proteins: a structural comparability for versatile proteins and predicted protein buildings. Biophys J. 2006;90:4558–73.
Presta LG, Chen H, O’connor SJ, Chisholm V, Meng YG, Krummen L, Winkler M, Ferrara N. Humanization of an anti-vascular endothelial progress issue monoclonal antibody for the remedy of stable tumors and different problems. Can Res. 1997;57:4593–9.
Zhang Y-F, Ho M. Humanization of high-affinity antibodies focusing on glypican-3 in hepatocellular carcinoma. Sci Rep. 2016;6:1–11.
Hanf KJ, Arndt JW, Chen LL, Jarpe M, Boriack-Sjodin PA, Li Y, van Vlijmen HW, Pepinsky RB, Simon KJ, Lugovskoy A. Antibody humanization by redesign of complementarity-determining area residues proximate to the acceptor framework. Strategies. 2014;65:68–76.
Ye J, Ma N, Madden TL, Ostell JM. IgBLAST: an immunoglobulin variable area sequence evaluation software. Nucleic Acids Res. 2013;41:W34–40.
Ducancel F, Muller BH. Molecular engineering of antibodies for therapeutic and diagnostic functions. MAbs. 2012;4:445–57.
Lonberg N. Human monoclonal antibodies from transgenic mice. Handb Exp Pharmacol. 2008;181(181):69–97.
Tyagi P. Current outcomes and ongoing trials with panitumumab (ABX-EGF), a totally human anti-epidermal progress issue receptor antibody, in metastatic colorectal most cancers. Clin Colorectal Most cancers. 2005;5:21–3.
Antonia S, Goldberg SB, Balmanoukian A, Chaft JE, Sanborn RE, Gupta A, Narwal R, Steele Ok, Gu Y, Karakunnel JJ, Rizvi NA. Security and antitumour exercise of durvalumab plus tremelimumab in non-small cell lung most cancers: a multicentre, part 1b examine. Lancet Oncol. 2016;17:299–308.
Leem J, Dunbar J, Georges G, Shi J, Deane CM. ABodyBuilder: Automated antibody construction prediction with information–pushed accuracy estimation. MAbs. 2016;8(7):1259–68.
Yamashita Ok, Ikeda Ok, Amada Ok, Liang S, Tsuchiya Y, Nakamura H, Shirai H, Standley DM. Kotai Antibody Builder: automated high-resolution structural modeling of antibodies. Bioinformatics. 2014;30:3279–80.
Fernández-Quintero ML, Heiss MC, Liedl KR. Antibody humanization—the Affect of the antibody framework on the CDR-H3 loop ensemble in resolution. Protein Eng Des Sel. 2019;32:411–22.
Payandeh Z, Rajabibazl M, Mortazavi Y, Rahimpour A, Taromchi AH. Ofatumumab monoclonal antibody affinity maturation by means of in silico modeling. Iran Biomed J. 2018;22(3):180–92.
Pantazes RJ, Maranas CD. MAPs: a database of modular antibody components for predicting tertiary buildings and designing affinity matured antibodies. BMC Bioinformatics. 2013;14:168.
Fernández-Quintero ML, Loeffler JR, Bacher LM, Waibl F, Seidler CA, Liedl KR. Native and world rigidification upon antibody affinity maturation. Entrance Mol Biosci. 2020;7:182.
Padlan EA. Anatomy of the antibody molecule. Mol Immunol. 1994;31:169–217.
Regep C, Georges G, Shi J, Popovic B, Deane CM. The H3 loop of antibodies exhibits distinctive structural traits. Proteins. 2017;85:1311–8.
Liang S, Dai J, Hou S, Su L, Zhang D, Guo H, Hu S, Wang H, Rao Z, Guo Y. Structural foundation for treating tumor necrosis issue α (TNFα)-associated ailments with the therapeutic antibody infliximab. J Biol Chem. 2013;288:13799–807.
Cavalli A, Camilloni C, Vendruscolo M. Molecular dynamics simulations with replica-averaged structural restraints generate structural ensembles in response to the utmost entropy precept. J Chem Phys. 2013;138:094112.
Case DA, Aktulga HM, Belfon Ok, Ben-Shalom IY, Brozell SR, Cerutti DS, Cheatham TE, Cisneros GA, Cruzeiro VWD, Darden TA, Duke RE, Giambasu G, Gilson MK, Gohlke H, Goetz AW, Harris R, Izadi S, Izmailov SA, Jin C, Kasavajhala Ok, Kaymak MC, King E, Kovalenko A, Kurtzman T, Lee TS, LeGrand S, Li P, Lin C, Liu J, Luchko T, Luo R, Machado M, Man V, Manathunga M, Merz KM, Miao Y, Mikhailovskii O, Monard G, Nguyen H, O’Hearn KA, Onufriev A, Pan F, Pantano S, Qi R, Rahnamoun A, Roe DR, Roitberg A, Sagui C, Schott-Verdugo S, Shen J, Simmerling CL, Skrynnikov NR, Smith J, Swails J, Walker RC, Wang J, Wei H, Wolf RM, Wu X, Xue Y, York DM, Zhao S, Kollman PA. Amber. San Francisco: College of California; 2021.
Onufriev A, Bashford D, Case DA. Exploring protein native states and large-scale conformational modifications with a modified generalized born mannequin. Proteins. 2004;55:383–94.
Mitternacht S. FreeSASA: An open supply C library for solvent accessible floor space calculations. Analysis. 2016;5:1000.
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