Developability index: a rapid in silico tool for the screening of antibody aggregation propensity.

By Timothy M Lauer, Neeraj J. Agrawal, Naresh Chennamsetty, K. Egodage, B. Helk, B. Trout. 2012

209 citations recorded by the source corpus.

Subfields: Molecular Biology, Radiology, Nuclear Medicine and Imaging

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Citations in the corpus

Addressing polyspecificity of antibodies selected from an in vitro yeast presentation system: a FACS-based, high-throughput selection and analytical tool. (2013, background): “…partial variable domain unfolding; however, the set of antibodies we examined are ostensibly sufficiently thermostable that different attributes, such as surface-exposed hydrophobicity (Lauer et al., 2012), and other weak non-covalent interactions may be the primary cause for polyspecificity.”
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development (2021, unknown): “Previous works have devised accurate developability index based on 3D structures of antibody (Lauer et al. 2012).”
Identifying well-folded de novo proteins in the new era of accurate structure prediction (2022, background): “For example, the top-pLDDT AF model for the toroidal helical repeat dTor_3x33L_2-2 (Figure 4A) and the β-barrel design 10_6_0048 (Figure 4B) have high-confidence scores but present large surface-exposed hydrophobic patches, as captured by SAP score values (>40) higher than the median of successful d”
Five computational developability guidelines for therapeutic antibody profiling (2019, methodology): “One purely structure-based method is the Structural Aggregation Propensity (SAP) metric (5), later included in the Developability Index (6).”
Antibody modeling using the Prediction of ImmunoGlobulin Structure (PIGS) web server (2014, background): “Predicting the structure of antibodies also has implications for the re-design of biotechnologically useful antibodies adopted in a variety of experimental setups 15 .”