Abstract: A fusion protein comprising a DNA binding domain operably-linked to a dimerization domain, wherein the DNA binding domain specifically binds to a response element.

Abstract: Methods and systems for designing proteins are disclosed, as well as proteins and protein assemblies designed. A computing device can determine a protein repeating unit that includes one or more protein helices and one or more protein loops. The computing device can generate a protein backbone structure with a copy of the protein repeating unit. The computing device can determine whether a distance between a pair of helices of the protein backbone structure is between lower and upper distance thresholds. After determining that the distance between the pair of helices is between the lower and upper distance thresholds, the computing device can: generate a plurality of protein sequences based on the protein backbone structure, select a particular protein sequence of the plurality of protein sequences based on an energy landscape that has information about energy and distance from a target fold of the particular protein sequence, and generate an output based on the particular protein sequence.

Abstract: Disclosed herein are junction polypeptides that can be used, for example, to join together protein building blocks via a rigid fusion to generate a wide range of protein shapes; fusion proteins comprising such junction polypeptides, polymers thereof, and methods for designing such junction polypeptides.

Abstract: The disclosure provides polypeptides as descried herein that including an amino acid sequence at least 50% identical to the amino acid sequence selected from the group consisting of SEQ ID NOS:1-46, oligomers of such polypeptides, methods for using such polypeptides and oligomers, and methods for designing such polypeptides and oligomers.

Abstract: The application of deep machine learning controllers to derive models of phenotypic patient data from primary economic data is disclosed herein. The use of systems and methods of employing the model are disclosed and useful in predicting treatment outcomes and compound efficacy, suggesting treatment plans and compounds, and clinical studies and phenotypical correlation studies in conjunction with medical records, economic data sets or combinations thereof.

Abstract: The present invention provides bi-stable functionalized organic molecule and methods of utilizing these bi-stable functionalized organic molecule.

Abstract: Methods and systems for designing proteins are disclosed, as well as proteins and protein assemblies designed. A comparing device can determine a protein repeating unit that includes one or more protein helices and one or more protein loops. The computing device can generate a protein backbone structure with a copy of the protein repeating unit. The computing device can determine whether a distance between a pair of helices of the protein backbone structure is between lower and upper distance thresholds. After determining that the distance between the pair of helices is between the lower and upper distance thresholds, the computing device can generate a plurality of protein sequences based on the protein backbone structure, select a particular protein sequence of the plurality of protein sequences based on an energy landscape that has information about energy and distance from a target fold of the particular protein sequence, and generate an output based on the particular protein sequence.