2022
DOI: 10.3390/ijms23073721
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VHH Structural Modelling Approaches: A Critical Review

Abstract: VHH, i.e., VH domains of camelid single-chain antibodies, are very promising therapeutic agents due to their significant physicochemical advantages compared to classical mammalian antibodies. The number of experimentally solved VHH structures has significantly improved recently, which is of great help, because it offers the ability to directly work on 3D structures to humanise or improve them. Unfortunately, most VHHs do not have 3D structures. Thus, it is essential to find alternative ways to get structural i… Show more

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Cited by 10 publications
(8 citation statements)
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References 279 publications
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“…The trRosetta models were shown to fit well with the cryo-electron microscopy experimental data [ 27 , 28 ]. They have been intensively used to understand the structure and function of lipid transporters [ 29 ], protein function deficiency [ 30 ], the Magnaporthe oryzae secretome [ 31 ], the structural characterization of S59L for efficient treatment for ALS and FTD diseases [ 32 ], 3D modeling of antibody domains [ 33 ], predicting vaccine construct [ 34 ], and more. The results of these studies have encouraged researchers and beyond.…”
Section: Introductionmentioning
confidence: 99%
“…The trRosetta models were shown to fit well with the cryo-electron microscopy experimental data [ 27 , 28 ]. They have been intensively used to understand the structure and function of lipid transporters [ 29 ], protein function deficiency [ 30 ], the Magnaporthe oryzae secretome [ 31 ], the structural characterization of S59L for efficient treatment for ALS and FTD diseases [ 32 ], 3D modeling of antibody domains [ 33 ], predicting vaccine construct [ 34 ], and more. The results of these studies have encouraged researchers and beyond.…”
Section: Introductionmentioning
confidence: 99%
“…In the early years, alanine scanning or other experimental methods were used to predict important residues or paratopes for antigen binding ( 61 , 71 , 72 ). While another approach is to analyze the possible binding mode and key amino acids through molecular simulation and docking analysis based on the sequence of antigen and antibody by protein analysis software with different algorithms ( 73 75 ). These methods have become a relatively mainstream and reliable way to analyze the modes of sdAbs-antigen binding.…”
Section: Antigen Binding Modes Of Sdabsmentioning
confidence: 99%
“…Very recently, machine learning and deep learning approaches, such as AlphaFold2 ( 130 ) and trRossetta ( 131 ), make antibody prediction and redesignation to a new level. These approaches are composed of multiple complex neural networks, which could combine very long-distance evolutionary searches and advanced local compositional proposals ( 75 ). These advances are due to the improvement of GPU computing power and better representations of mathematics in the past few years.…”
Section: Systematic Maturation Of Sdabsmentioning
confidence: 99%
“…Today, there is an already established candidate for the role of a fundamentally new human antibody modeling technology: AI-enabled in silico antibody structure prediction [65]. The AlphaFold2 neural network launched in 2021 can predict spatial structure of proteins from their primary sequence with accuracy at the atomic level [66].…”
Section: Prospects Of Artificial Intelligence (Ai) In Further Develop...mentioning
confidence: 99%