The invention relates to systems and methods for generating a polypeptide library. Specifically, the invention relates to computer-implemented systems and methods for generating a library of polypeptides, for example, antibodies.

The invention utilizes virtual screening strategy to seek for current market drugs as anti-schizophrenia therapy drug repurposing. Drug repurposing strategy finds new uses other than the original medical indications of existing drugs. Finding new indications for such drugs will benefit patients who are in needs for a potential new therapy sooner since known drugs are usually with acceptable safety and pharmacokinetic profiles. In this study, repurposing marketed drugs for DAAO inhibitor as new schizophrenia therapy was performed with virtual screening on marketed drugs and its metabolites. The identified and available drugs and compounds were further confirmed with in vitro DAAO enzymatic inhibitory assay.

The present invention generally relates to methods of rapidly and efficiently searching biologically-related data space. More specifically, the invention includes methods of identifying bio-molecules with desired properties, or which are most suitable for acquiring such properties, from complex bio-molecule libraries or sets of such libraries. The invention also provides methods of modeling sequence-activity relationships. As many of the methods are computer-implemented, the invention additionally provides digital systems and software for performing these methods.

Devices, systems, and methods for strain-specific identification and assessment of susceptibility of microorganisms based on the response of sensors in a colorimetric sensor array to metabolic products of the microorganism.

The present invention provides the use of RNA removal to initiate protein aggregation of a plurality of proteins in a cell or cell lysate. This may be used to create an in vitro model of a disease, such as a neurodegenerative disease. The present invention also provides a method for determining the efficacy of a potential anti-protein aggregation agent comprising the following steps: i) using RNA removal to initiate the aggregation of a protein in a cell or cell lysate, ii) treating the cell or cell lysate with the potential anti-protein aggregation agent before, after or during RNA removal; and iii) comparing protein aggregation in equivalent samples with and without step ii) treatment in which a decrease in protein aggregation associated with step ii) treatment indicates that the potential anti-protein aggregation agent is effective in preventing and/or reversing protein aggregation.

Systems, methods, and devices for generating synthetic genomic datasets and validating bioinformatic pipelines for genomic analysis are disclosed. In preferred embodiments, synthetic maternal and paternal datasets with known variants are used with matched normal synthetic datasets to validate various bioinformatic pipelines. Bioinformatic pipelines are evaluated using the synthetic datasets to assess design changes and improvements. Accuracy, PPV, specificity, sensitivity, reproducibility, and limit of detection of the pipelines in calling variants in synthetic datasets is reported.

A protein composition including TorsinA or TorsinA mutant, LULL1, and a nanobody obtained by immunization using TorsinA and LULL1 is used to grow complex crystals, and three dimensional structures are determined using x-ray data of the crystals. A screening platform is built based on the determined three dimensional structures for designing a drug lead to cure dystonia.

A method for at least one of characterizing, diagnosing, and treating an autoimmune disorder in at least a subject, the method comprising: receiving an aggregate set of biological samples from a population of subjects; generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset for the population of subjects; generating a characterization of the autoimmune condition based upon features extracted from at least one of the microbiome composition dataset and the microbiome functional diversity dataset; based upon the characterization, generating a therapy model configured to correct the autoimmune condition; and at an output device associated with the subject, promoting a therapy to the subject based upon the characterization and the therapy model.

A method for at least one of characterizing, diagnosing, and treating an autoimmune disorder in at least a subject, the method comprising: receiving an aggregate set of biological samples from a population of subjects; generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset for the population of subjects; generating a characterization of the autoimmune condition based upon features extracted from at least one of the microbiome composition dataset and the microbiome functional diversity dataset; based upon the characterization, generating a therapy model configured to correct the autoimmune condition; and at an output device associated with the subject, promoting a therapy to the subject based upon the characterization and the therapy model.

A method for at least one of characterizing, diagnosing, and treating an autoimmune disorder in at least a subject, the method comprising: receiving an aggregate set of biological samples from a population of subjects; generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset for the population of subjects; generating a characterization of the autoimmune condition based upon features extracted from at least one of the microbiome composition dataset and the microbiome functional diversity dataset; based upon the characterization, generating a therapy model configured to correct the autoimmune condition; and at an output device associated with the subject, promoting a therapy to the subject based upon the characterization and the therapy model.