5nbi

Principles for computational design of antibodies

spinqualitylabelsall models 5nbi, resolution 2.10Å Show:Asymmetric Unit Biological Assembly Drag the structure with the mouse to rotate   Export Animated Image   Print3D Structural highlights 5nbi is a 2 chain structure with sequence from Synthetic construct. Full crystallographic information is available from OCA. For a guided tour on the structure components use FirstGlance. Method: X-ray diffraction, Resolution 2.1Å Resources: FirstGlance, OCA, PDBe, RCSB, PDBsum, ProSAT Publication Abstract from PubMed Natural proteins must both fold into a stable conformation and exert their molecular function. To date, computational design has successfully produced stable and atomically accurate proteins by using so-called "ideal" folds rich in regular secondary structures and almost devoid of loops and destabilizing elements, such as cavities. Molecular function, such as binding and catalysis, however, often demands nonideal features, including large and irregular loops and buried polar interaction networks, which have remained challenging for fold design. Through five design/experiment cycles, we learned principles for designing stable and functional antibody variable fragments (Fvs). Specifically, we (i) used sequence-design constraints derived from antibody multiple-sequence alignments, and (ii) during backbone design, maintained stabilizing interactions observed in natural antibodies between the framework and loops of complementarity-determining regions (CDRs) 1 and 2. Designed Fvs bound their ligands with midnanomolar affinities and were as stable as natural antibodies, despite having >30 mutations from mammalian antibody germlines. Furthermore, crystallographic analysis demonstrated atomic accuracy throughout the framework and in four of six CDRs in one design and atomic accuracy in the entire Fv in another. The principles we learned are general, and can be implemented to design other nonideal folds, generating stable, specific, and precise antibodies and enzymes. Principles for computational design of binding antibodies.,Baran D, Pszolla MG, Lapidoth GD, Norn C, Dym O, Unger T, Albeck S, Tyka MD, Fleishman SJ Proc Natl Acad Sci U S A. 2017 Sep 25. pii: 201707171. doi:, 10.1073/pnas.1707171114. PMID:28973872 From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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