VHH Structural Modelling Approaches: A Critical Review

Abstract

V_HH, 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 V_HH 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 V_HHs do not have 3D structures. Thus, it is essential to find alternative ways to get structural information. The methods of structure prediction from the primary amino acid sequence appear essential to bypass this limitation. This review presents the most extensive overview of structure prediction methods applied for the 3D modelling of a given V_HH sequence (a total of 21). Besides the historical overview, it aims at showing how model software programs have been shaping the structural predictions of V_HHs. A brief explanation of each methodology is supplied, and pertinent examples of their usage are provided. Finally, we present a structure prediction case study of a recently solved V_HH structure. According to some recent studies and the present analysis, AlphaFold 2 and NanoNet appear to be the best tools to predict a structural model of V_HH from its sequence.

Keywords: Complementarity Determining Regions; antibodies; deep learning; docking; frameworks; homology and comparative modelling; secondary structure; sequence–structure relationship; single-domain antibody; threading.

Figure A1

Number of V_HH structures deposited in the PDB per year. Structures solved using different experimental methods are colour-coded accordingly (our own analysis) (electron microscopy, solution NMR and X-ray diffraction has been represented in red, green and blue respectively). It differs from Figure 4, as only nonmodified camelid V_HHs were analysed.

Figure 1

Antibody domains. Immunoglobulins are found in mammals such as the dachshund (Canis familiaris) named Snoopy (a) and a Vicuña (d); both pictures were taken in Normandy (France) in August 2021. The immunoglobulins are shown by domains in (b) Classical Immunoglobulin Gamma (IgG) and (e) HCAb (only found in the Camelidae family). (c,f) Antigen-binding domain of IgG and HCAb, namely the VH/VL domain and V_HH domain. The FRs in the VH domain are shown in grey, in the VL domain in dark blue and in the V_HH domain in cyan. The CDRs of the heavy chain are represented as CDRH1, CDRH2 and CDRH3, while CDRL1, CDRL2 and CDRL3 are CDRs of the light chain. The CDRs are represented in red shades: CDR1 (orange), CDR2 (red) and CDR3 (raspberry). Visualisation was performed using PyMOL [1,2,3]. Please notice that Snoopy was not harmed when taking these pictures and received an optimised dose of beef and turkey dog treats that he likes a lot.

Figure 2

Protein structural prediction tools. The above representation is a summary of (a) general protein modelling tools and (b) Antibody and V_HH modelling tools. All the tools are classified according to their availability (standalone and/or online server, academic or commercial) and the methodologies used (comparative/homology modelling, threading, ab initio and deep learning). * The phaser is dedicated to molecular replacement [105].

Figure 3

Superimposition of the V_HH structural models with the X-ray structure of PDB ID: 6XYF. The V_HH structure (in green) is superimposed with a structural model from the (a) Modeller best model for single-template (in yellow, RMSD = 2.28 Å, RMSD CDR3 = 3.80 Å), (b) Modeller best model for multi-template (in red, RMSD = 2.18 Å, RMSD CDR3 = 3.32 Å), (c) ModWeb (in orange, RMSD = 1.92 Å, RMSD CDR3 = 2.05 Å), (d) SwissModel best model with the best sequence identity (in yellow ochre, RMSD = 1.85 Å, RMSD CDR3 = 1.98 Å), (e) SwissModel best model with a GMQE score (in purple, RMSD = 2.05 Å, RMSD CDR3 = 2.75 Å), (f) AlphaFold 2 (in wheat, RMSD = 1.62 Å, RMSD CDR3 = 1.98 Å), (g) RoseTTAfold (in chocolate brown, RMSD = 1.87 Å, RMSD CDR3 = 2.56 Å) and (h) NanoNet (in blue, RMSD = 1.55 Å, RMSD CDR3 = 1.81 Å). Visualisation was performed using PyMOL [1,2,3].

Figure 4

Number of V_HH structures deposited in the PDB per year. Structures solved using different experimental methods are colour-coded accordingly (electron microscopy, solution NMR and X-ray diffraction has been represented in red, green and blue respectively). Data extracted from Reference [159].