Exploiting sequence and stability information for directing nanobody stability engineering

Kunz, Patrik; Flock, Tilman; Soler, Nicolas; Zaiß, Moritz; Vincke, Cécile; Sterckx, Yann G.J.; Kastelic, Damjana; Hoheisel, Jörg D.

doi:10.1016/j.bbagen.2017.06.014

Cited by 46 publications

(49 citation statements)

References 69 publications

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“…Previously, we had shown that the introduction of the sequence VE at positions 5 and 6 of an sdAb in combination with 1E or D, and 3Q could lead to an increase in Tm of 5–9 °C [ 32 , 33 ]. Other researchers examined a large repertoire of sdAb sequences and identified the changes 1E and 5V as stabilizing [ 34 ]. Also, prior studies have shown that the addition of negative charges can increase thermal stability and solubility of sdAbs [ 35 , 36 ].…”

Section: Resultsmentioning

confidence: 99%

Selection, characterization, and thermal stabilization of llama single domain antibodies towards Ebola virus glycoprotein

et al. 2017

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BackgroundA key advantage of recombinant antibody technology is the ability to optimize and tailor reagents. Single domain antibodies (sdAbs), the recombinantly produced variable domains derived from camelid and shark heavy chain antibodies, provide advantages of stability and solubility and can be further engineered to enhance their properties. In this study, we generated sdAbs specific for Ebola virus envelope glycoprotein (GP) and increased their stability to expand their utility for use in austere locals. Ebola virus is extremely virulent and causes fatal hemorrhagic fever in ~ 50 percent of the cases. The viral GP binds to host cell receptors to facilitate viral entry and thus plays a critical role in pathogenicity.ResultsAn immune phage display library containing more than 107 unique clones was developed from a llama immunized with a combination of killed Ebola virus and recombinantly produced GP. We panned the library to obtain GP binding sdAbs and isolated sdAbs from 5 distinct sequence families. Three GP binders with dissociation constants ranging from ~ 2 to 20 nM, and melting temperatures from ~ 57 to 72 °C were selected for protein engineering in order to increase their stability through a combination of consensus sequence mutagenesis and the addition of a non-canonical disulfide bond. These changes served to increase the melting temperatures of the sdAbs by 15–17 °C. In addition, fusion of a short positively charged tail to the C-terminus which provided ideal sites for the chemical modification of these sdAbs resulted in improved limits of detection of GP and Ebola virus like particles while serving as tracer antibodies.ConclusionsSdAbs specific for Ebola GP were selected and their stability and functionality were improved utilizing protein engineering. Thermal stability of antibody reagents may be of particular importance when operating in austere locations that lack reliable refrigeration. Future efforts can evaluate the potential of these isolated sdAbs as candidates for diagnostic or therapeutic applications for Ebola.Electronic supplementary materialThe online version of this article (10.1186/s12934-017-0837-z) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Selection, characterization, and thermal stabilization of llama single domain antibodies towards Ebola virus glycoprotein

et al. 2017

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“…Despite the success of these and other approaches [ 47 , 49 , 50 , 51 , 52 ], stabilizing mutations in the CDRs or frameworks would be highly valuable. Fortunately, computational approaches for the design of antibodies with high affinity and thermostability have made significant recent advances [ 53 , 54 , 55 , 56 , 57 , 58 ].…”

Section: Physical and Chemical Stabilitymentioning

confidence: 99%

Toward Drug-Like Multispecific Antibodies by Design

Sawant

Streu

et al. 2020

IJMS

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The success of antibody therapeutics is strongly influenced by their multifunctional nature that couples antigen recognition mediated by their variable regions with effector functions and half-life extension mediated by a subset of their constant regions. Nevertheless, the monospecific IgG format is not optimal for many therapeutic applications, and this has led to the design of a vast number of unique multispecific antibody formats that enable targeting of multiple antigens or multiple epitopes on the same antigen. Despite the diversity of these formats, a common challenge in generating multispecific antibodies is that they display suboptimal physical and chemical properties relative to conventional IgGs and are more difficult to develop into therapeutics. Here we review advances in the design and engineering of multispecific antibodies with drug-like properties, including favorable stability, solubility, viscosity, specificity and pharmacokinetic properties. We also highlight emerging experimental and computational methods for improving the next generation of multispecific antibodies, as well as their constituent antibody fragments, with natural IgG-like properties. Finally, we identify several outstanding challenges that need to be addressed to increase the success of multispecific antibodies in the clinic.

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“…We sought to learn the constraints that characterize functional nanobodies by fitting the autoregressive model to a set of 1.2 million nanobody sequences from the llama immune repertoire (McCoy et al, 2014). Using this model, we find that length-normalized log-probability calculations predict the thermostability of new llama nanobody sequences (ρ=0.53, N=17; Figure 3a; Kunz et al, 2017).…”

Section: Generating An Efficient Library Of Functional Nanobodiesmentioning

confidence: 99%

Protein Design and Variant Prediction Using Autoregressive Generative Models

Shin

Riesselman

Kollasch

et al. 2019

Preprint

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A major biomedical challenge is the interpretation of genetic variation and the ability to design functional novel sequences. Since the space of all possible genetic variation is enormous, there is a concerted effort to develop reliable methods that can capture genotype to phenotype maps. State-of-art computational methods rely on models that leverage evolutionary information and capture complex interactions between residues. However, current methods are not suitable for a large number of important applications because they depend on robust protein or RNA alignments. Such applications include genetic variants with insertions and deletions, disordered proteins, and functional antibodies. Ideally, we need models that do not rely on assumptions made by multiple sequence alignments. Here we borrow from recent advances in natural language processing and speech synthesis to develop a generative deep neural network-powered autoregressive model for biological sequences that captures functional constraints without relying on an explicit alignment structure. Application to unseen experimental measurements of 42 deep mutational scans predicts the effect of insertions and deletions while matching state-of-art missense mutation prediction accuracies. We then test the model on single domain antibodies, or nanobodies, a complex target for alignment-based models due to the highly variable complementarity determining regions. We fit the model to a naïve llama immune repertoire and generate a diverse, optimized library of 10 5 nanobody sequences for experimental validation. Our results demonstrate the power of the 'alignment-free' autoregressive model in mutation effect prediction and design of traditionally challenging sequence families.

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Exploiting sequence and stability information for directing nanobody stability engineering

Cited by 46 publications

References 69 publications

Selection, characterization, and thermal stabilization of llama single domain antibodies towards Ebola virus glycoprotein

Selection, characterization, and thermal stabilization of llama single domain antibodies towards Ebola virus glycoprotein

Toward Drug-Like Multispecific Antibodies by Design

Protein Design and Variant Prediction Using Autoregressive Generative Models

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