ABangle: characterising the VH-VL orientation in antibodies

Dunbar, James B.; Fuchs, Angelika; Shi, Jiye; Deane, Charlotte M.

doi:10.1093/protein/gzt020

Cited by 106 publications

(157 citation statements)

References 39 publications

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“…The V H -V L interface has been shown to have a strong influence on antigen-binding affinity (38,39). Furthermore, the V H -V L torsion angle and flexibility of the V H -V L interface have been reported to vary substantially between the antigen-free and the antigen-bound forms (40,41).…”

Section: Elbow Angle Dynamics Of the G6 Fab Influence The Antigen-binmentioning

confidence: 99%

Mutational landscape of antibody variable domains reveals a switch modulating the interdomain conformational dynamics and antigen binding

Koenig¹,

Lee²,

Walters³

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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Somatic mutations within the antibody variable domains are critical to the immense capacity of the immune repertoire. Here, via a deep mutational scan, we dissect how mutations at all positions of the variable domains of a high-affinity anti-VEGF antibody G6.31 impact its antigen-binding function. The resulting mutational landscape demonstrates that large portions of antibody variable domain positions are open to mutation, and that beneficial mutations can be found throughout the variable domains. We determine the role of one antigen-distal light chain position 83, demonstrating that mutation at this site optimizes both antigen affinity and thermostability by modulating the interdomain conformational dynamics of the antigen-binding fragment. Furthermore, by analyzing a large number of human antibody sequences and structures, we demonstrate that somatic mutations occur frequently at position 83, with corresponding domain conformations observed for G6.31. Therefore, the modulation of interdomain dynamics represents an important mechanism during antibody maturation in vivo. Deciphering the molecular mechanism of SHMs in improving antibodies is critical for understanding the evolution of the immune repertoire. It is well recognized that mutations at the CDRs or FWR structurally adjacent to the CDRs can modulate and optimize the antigen-binding interface (4-7), and several studies have used saturated mutagenesis of CDR position to explore the effect of various mutations on affinity and specificity (8-11).The role of SHM in antigen-distal FWR is less well understood, however. Previous studies have suggested that the antigen-distal FWR contributes primarily to the variable domain structural integrity; thus, mutations at these positions would be either detrimental to or neutral for antigen-binding function (12)(13)(14). Other authors have characterized the potential of antigen-distal framework mutation as beneficial for antigen-binding function. For example, framework mutations can compensate for the destabilizing effect of mutations at CDRs needed for antigen binding (15). In other cases, non-CDR SHMs have been shown to be required for the neutralization activity of broadly neutralizing anti-HIV antibodies (16).Thus far, the roles of SHM have been studied primarily by examining the functional consequences of reverting the somatic mutation of selected antibodies back to the germline sequences (15-21). Although these studies have demonstrated that antibodies depend on somatic mutations to achieve high-affinity antigen binding, the approach is limited to the small set of mutations present in a given antibody.Here we took a systematic approach to assessing the mutability of the whole variable domain for maintaining or improving folding stability and antigen binding. We used a welloptimized anti-vascular endothelial cell growth factor (VEGF), G6.31, with high affinity (K d = 0.4 nM) and excellent thermostability [fragment antigen-binding (Fab) melting temperature (T m ) = 84°C]. G6.31 derives its HC and LC variable domains ...

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Section: Elbow Angle Dynamics Of the G6 Fab Influence The Antigen-binmentioning

confidence: 99%

Mutational landscape of antibody variable domains reveals a switch modulating the interdomain conformational dynamics and antigen binding

Koenig¹,

Lee²,

Walters³

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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“…It was shown that the intrinsic variability in VH-VL orientation of sequence-identical Fv structures is less for antibodies crystallized in the complexed form. 32 As a consequence, the random forest model is able to predict the VH-VL orientation parameters more accurately, which translates into favorable RMSD values.…”

Section: Ama1 and Ama2 Datasetsmentioning

confidence: 98%

“…In this context, we quantify the degrees of freedom of VH-VL orientation in terms of the 6 ABangle parameters derived by Dunbar et al, 32 consisting of one torsion angle, 4 bend angles (2 for each domain) and one distance. Earlier, we were able to show that the ABangle parameters can be predicted reasonably well based on a number of key residues at the interface of the 2 domains.…”

Section: Vh-vl Orientation Adjustmentmentioning

confidence: 99%

“…19 The situation is complicated further because the Fv region is composed of 2 separate immunoglobulin domains, the variable region of the heavy chain and the variable region of the light chain (VH and VL), with 3 CDRs distributed on each of the 2. The relative orientation of the 2 domains exhibits a notable variability over the known repertoire of antibody crystal structures, [30][31][32] and it has been suggested that VH-VL orientation, in addition to length and sequence of the CDRs, is a co-modulator of antigen specificity and affinity. 12 The parameters of VH-VL orientation determine how the CDRs are presented to the antigen, and thus contribute to the shape of the paratope (the antibody counterpart of the antigen's epitope).…”

Section: Introductionmentioning

confidence: 99%

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MoFvAb: Modeling the Fv region of antibodies

Bujotzek

Fuchs

et al. 2015

mAbs

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Knowledge of the 3-dimensional structure of the antigen-binding region of antibodies enables numerous useful applications regarding the design and development of antibody-based drugs. We present a knowledge-based antibody structure prediction methodology that incorporates concepts that have arisen from an applied antibody engineering environment. The protocol exploits the rich and continuously growing supply of experimentally derived antibody structures available to predict CDR loop conformations and the packing of heavy and light chain quickly and without user intervention. The homology models are refined by a novel antibody-specific approach to adapt and rearrange sidechains based on their chemical environment. The method achieves very competitive all-atom root mean square deviation values in the order of 1.5 A on different evaluation datasets consisting of both known and previously unpublished antibody crystal structures.

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“…While these measures encode more orientational information than the Abhinandan-Martin packing angle, both are pairwise difference metrics rather than absolute ones. A geometrically complete, absolute measure of V L -V H orientation, ABangle, was published by Dunbar et al (2013). ABangle is composed of one torsional angle, four plane angles and one distance, representing the six degrees of freedom of the two-body V L -V H complex.…”

Section: Introductionmentioning

confidence: 99%

Improved prediction of antibody V_L–V_Horientation

Marze

Lyskov

Gray

2016

Protein Engineering, Design and Selection

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Antibodies are important immune molecules with high commercial value and therapeutic interest because of their ability to bind diverse antigens. Computational prediction of antibody structure can quickly reveal valuable information about the nature of these antigen-binding interactions, but only if the models are of sufficient quality. To achieve high model quality during complementaritydetermining region (CDR) structural prediction, one must account for the V L -V H orientation. We developed a novel four-metric V L -V H orientation coordinate frame. Additionally, we extended the CDR grafting protocol in RosettaAntibody with a new method that diversifies V L -V H orientation by using 10 V L -V H orientation templates rather than a single one. We tested the multiple-template grafting protocol on two datasets of known antibody crystal structures. During the template-grafting phase, the new protocol improved the fraction of accurate V L -V H orientation predictions from only 26% (12/46) to 72% (33/46) of targets. After the full RosettaAntibody protocol, including CDR H3 remodeling and V L -V H re-orientation, the new protocol produced more candidate structures with accurate V L -V H orientation than the standard protocol in 43/46 targets (93%). The improved ability to predict V L -V H orientation will bolster predictions of other parts of the paratope, including the conformation of CDR H3, a grand challenge of antibody homology modeling.

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ABangle: characterising the VH-VL orientation in antibodies

Cited by 106 publications

References 39 publications

Mutational landscape of antibody variable domains reveals a switch modulating the interdomain conformational dynamics and antigen binding

Mutational landscape of antibody variable domains reveals a switch modulating the interdomain conformational dynamics and antigen binding

MoFvAb: Modeling the Fv region of antibodies

Improved prediction of antibody V_L–V_Horientation

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ABangle: characterising the VH-VL orientation in antibodies

Cited by 106 publications

References 39 publications

Mutational landscape of antibody variable domains reveals a switch modulating the interdomain conformational dynamics and antigen binding

Mutational landscape of antibody variable domains reveals a switch modulating the interdomain conformational dynamics and antigen binding

MoFvAb: Modeling the Fv region of antibodies

Improved prediction of antibody VL–VHorientation

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Resources

About

Improved prediction of antibody V_L–V_Horientation