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Facile target validation in an animal model with intracellularly expressed monobodies.

ABSTRACT: Rapidly determining the biological effect of perturbing a site within a potential drug target could guide drug discovery efforts, but it remains challenging. Here, we describe a facile target validation approach that exploits monobodies, small synthetic binding proteins that can be fully functionally expressed in cells. We developed a potent and selective monobody to WDR5, a core component of the mixed lineage leukemia (MLL) methyltransferase complex. The monobody bound to the MLL interaction site of WDR5, the same binding site for small-molecule inhibitors whose efficacy has been demonstrated in cells but not in animals. As a genetically encoded reagent, the monobody inhibited proliferation of an MLL-AF9 cell line in vitro, suppressed its leukemogenesis and conferred a survival benefit in an in vivo mouse leukemia model. The capacity of this approach to readily bridge biochemical, structural, cellular characterization and tests in animal models may accelerate discovery and validation of druggable sites.

SUBMITTER: Gupta A

PROVIDER: S-EPMC6103845 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Facile target validation in an animal model with intracellularly expressed monobodies.

Gupta Ankit A Xu Jing J Lee Shirley S Tsai Steven T ST Zhou Bo B Kurosawa Kohei K Werner Michael S MS Koide Akiko A Ruthenburg Alexander J AJ Dou Yali Y Koide Shohei S

Nature chemical biology 20180716 9

Rapidly determining the biological effect of perturbing a site within a potential drug target could guide drug discovery efforts, but it remains challenging. Here, we describe a facile target validation approach that exploits monobodies, small synthetic binding proteins that can be fully functionally expressed in cells. We developed a potent and selective monobody to WDR5, a core component of the mixed lineage leukemia (MLL) methyltransferase complex. The monobody bound to the MLL interaction si ...[more]

PMID: 30013062

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Project description:A stochastic, individual animal systems simulation model describing U.S. beef cow-calf production was developed and parameterized to match typical U.S. Angus genetics under cow-calf production conditions in the Kansas Flint Hills. Model simulation results were compared to available actual, multivariate U.S. cow-calf production data reported according to beef cow-calf standardized performance analysis (SPA) methodology through North Dakota State University's CHAPS program to assess model validity. Individual animal nutrition, reproduction, growth, and health characteristics, as well as production state are determined on a daily time step. Any number of days can be simulated. These capabilities allow for decision analysis and assessment of long-run outcomes of various genetic, management, and economic scenarios regarding multiple metrics simultaneously. Parameterizing the model to match Kansas Flint Hills production conditions for the years 1995 through 2018, 32 different genetic combinations for mature cow weight and peak lactation potential were simulated with 100 iterations each. Sire mature cow weight genetics ranged from 454 to 771 kg in 45 to 46 kg increments. Sire peak lactation genetics were considered at 6.8, 9, 11.3, and 13.6 kg/d for all eight mature cow weights. Utilizing model results for the years 2000 to 2018, raw model results were assessed against actual historical cow-calf production data. Exploratory factor analysis was applied to interpret the underlying factor scores of model output relative to actual cow-calf production data. Comparing modeled herd output with CHAPS herd data, median average calf weaning age, average cow age, percent pregnant per cow exposed, and percent calf mortality per calf born of model output was 3.4 d greater, 0.2 yr greater, 1 percentage point less, and 1.7 percentage points greater, respectively. Subtracting the median CHAPS pre-weaning average daily gain from the median modeled pre-weaning average daily gain for each of the eight respective mature cow weight genetics categories, and then calculating the median of the eight values, the median difference was -0.21 kg/d. Performing the same calculation for birth weight and adjusted 205 d weaning weight, the modeled data was 4.9 and 48.6 kg lighter than the CHAPS data, respectively. Management and genetic details underlying the CHAPS data were unknown.

Dataset Information

Facile target validation in an animal model with intracellularly expressed monobodies.

Publications

Facile target validation in an animal model with intracellularly expressed monobodies.

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