The influence of the framework core residues on the biophysical properties of immunoglobulin heavy chain variable domains

Antibody variable domains differ considerably in stability. Single-chain Fv (scFv) fragments derived from natural repertoires frequently lack the high stability needed for therapeutic application, necessitating reengineering not only to humanize their sequence, but also to improve their biophysical properties. The human VH3 domain has been identified as having the best biophysical properties among human subtypes. However, complementarity determining region (CDR) grafts from highly divergent VH domains to huVH3 frequently fail to reach its superior stability. In previous experiments involving a CDR graft from a murine VH9 domain of very poor stability to huVH3, a hybrid VH framework was obtained which combines the lower core residues of muVH9 with the surface residues of huVH3. It resulted in a scFv with far better biophysical properties than the corresponding grafts to the consensus huVH3 framework. To better understand the origin of the superior properties of the hybrid framework, we constructed further hybrids, but now in the context of the consensus CDR-H1 and -H2 of the original human VH3 domain. The new hybrids included elements from either murine VH9, human VH1 or human VH5 domains. From guanidinium chloride-induced equilibrium denaturation measurements, kinetic denaturation experiments, measurements of heat-induced aggregation and comparison of soluble expression yield in Escherichia coli, we conclude that the optimal VH framework is CDR-dependent. The present work pinpoints structural features responsible for this dependency and helps to explain why the immune system uses more than one framework with different structural subtypes in framework 1 to optimally support widely different CDR

The influence of the framework core residues on the biophysical properties of immunoglobulin heavy chain variable domains

Antibody variable domains differ considerably in stability. Single-chain Fv (scFv) fragments derived from natural repertoires frequently lack the high stability needed for therapeutic application, necessitating reengineering not only to humanize their sequence, but also to improve their biophysical properties. The human V(H)3 domain has been identified as having the best biophysical properties among human subtypes. However, complementarity determining region (CDR) grafts from highly divergent V(H) domains to huV(H)3 frequently fail to reach its superior stability. In previous experiments involving a CDR graft from a murine V(H)9 domain of very poor stability to huV(H)3, a hybrid V(H) framework was obtained which combines the lower core residues of muV(H)9 with the surface residues of huV(H)3. It resulted in a scFv with far better biophysical properties than the corresponding grafts to the consensus huV(H)3 framework. To better understand the origin of the superior properties of the hybrid framework, we constructed further hybrids, but now in the context of the consensus CDR-H1 and -H2 of the original human V(H)3 domain. The new hybrids included elements from either murine V(H)9, human V(H)1 or human V(H)5 domains. From guanidinium chloride-induced equilibrium denaturation measurements, kinetic denaturation experiments, measurements of heat-induced aggregation and comparison of soluble expression yield in Escherichia coli, we conclude that the optimal V(H) framework is CDR-dependent. The present work pinpoints structural features responsible for this dependency and helps to explain why the immune system uses more than one framework with different structural subtypes in framework 1 to optimally support widely different CDRs

New algorithms and an in silico benchmark for computational enzyme design

The creation of novel enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Here we describe two new algorithms for enzyme design that employ hashing techniques to allow searching through large numbers of protein scaffolds for optimal catalytic site placement. We also describe an in silico benchmark, based on the recapitulation of the active sites of native enzymes, that allows rapid evaluation and testing of enzyme design methodologies. In the benchmark test, which consists of designing sites for each of 10 different chemical reactions in backbone scaffolds derived from 10 enzymes catalyzing the reactions, the new methods succeed in identifying the native site in the native scaffold and ranking it within the top five designs for six of the 10 reactions. The new methods can be directly applied to the design of new enzymes, and the benchmark provides a powerful in silico test for guiding improvements in computational enzyme design