Abstract: The present invention relates to a method for predicting three-dimensional structure of a protein from its sequence. Three-dimensional structure may be determined by: (a) generating a multiple sequence alignment for a candidate protein having a known sequence; (b) identifying a covariance matrix between all pairs of sequence positions in the multiple sequence alignment; (c) inverting the covariance matrix and identifying predicted evolutionary constraints using a statistical model of the candidate protein; and (d) simulating folding of an extended chain structure of the candidate protein using the predicted constraints.

Abstract: In order to exploit vulnerabilities of cancer cells on the basis of homozygous deletion, a genomic profile of cancer cells in a biological sample is analyzed to identify homozygous deletions of one or more genes. The homozygous deletions, in turn, are analyzed in view of pathway data (e.g., metabolic, signaling, and/or cell-to-cell communication pathway data obtained from one or more databases) to determine a subset of homozygous deletions performing a function important to the viability of the cell. From this subset of homozygous deletions, cellular pathway data is analyzed to identify one or more partner genes (e.g., synthetic lethals) considered to facilitate or perform the same or similar function as the respective homozygous deletion. Drug annotations, in turn, may be reviewed to identify drugs that inhibit at least one of the synthetic lethal genes and/or gene products.

Abstract: Methods and systems are presented herein for creating and using cell type-specific, quantitative network models of signaling in cells, such as melanoma, to predict cellular response to untested combinational perturbations. The methods involve performing a set of perturbation experiments with cells of a particular type to produce phosphoproteomic and/or phenotypic profiles for the cells; automatically extracting prior pathway information from one or more known databases to build a qualitative prior model; building a signaling pathway model from (i) the phosphoproteomic and/or phenotypic profiles produced from the perturbation experiments and (ii) the qualitative prior model from the known database(s); and performing in silico perturbations using the signaling pathway model to predict responses to a set of perturbation conditions not yet experimentally tested, and identifying one or more candidate drug combinations from the predicted responses.

Abstract: Presented herein are methods of treating cancer, for example, RAFi-resistant melanoma, using a combination of a bromodomain inhibitor such as JQ1, together with either a MEK inhibitor (e.g., MEKi) or a BRAF inhibitor (e.g., RAFi). These combinations were identified from candidate combinations produced by a cell type-specific, quantitative network model of signaling in cells (e.g., melanoma) to predict cellular response to untested combinatorial perturbations.

Abstract: The invention relates to a method for the Cell Type specific labeling with Amino acid Precursors (CTAP). In particular, the disclosed method permits the incorporation of stable isotope-labeled amino acids into the proteome of a vertebrate cell that has been engineered to express an exogenous enzyme that enables the cell to produce an essential amino acid from its amino acid substrate. The method employs stable isotope-labeled amino acid substrate/precursors from which essential amino acids bearing the label are generated. The labeled amino acids generated by the transgenic cell not only supports growth but specifically labels proteins of the transgenic cell. Furthermore, the use of different populations of cells expressing different exogenous amino acid-producing enzymes permits differential labeling of the proteomes of the individual cell populations in multicellular environments.

Abstract: The present invention relates to a method for predicting three-dimensional structure of a protein from its sequence. Three-dimensional structure may be determined by: (a) generating a multiple sequence alignment for a candidate protein having a known sequence; (b) identifying a covariance matrix between all pairs of sequence positions in the multiple sequence alignment; (c) inverting the covariance matrix and identifying predicted evolutionary constraints using a statistical model of the candidate protein; and (d) simulating folding of an extended chain structure of the candidate protein using the predicted constraints.

Abstract: The present invention relates to a method for predicting three-dimensional structure of a protein from its sequence. Three-dimensional structure may be determined by: (a) generating a multiple sequence alignment for a candidate protein having a known sequence; (b) identifying a covariance matrix between all pairs of sequence positions in the multiple sequence alignment; (c) inverting the covariance matrix and identifying predicted evolutionary constraints using a statistical model of the candidate protein; and (d) simulating folding of an extended chain structure of the candidate protein using the predicted constraints.

Abstract: Techniques for modeling living biological systems include receiving constant values for multiple interaction factors wij. A set of initial state values is received for state variables that indicate relevant properties of a living biological system. Also received is a set of trial values for perturbation variables that indicate factors that might affect one or more of the relevant properties of the biological system. A temporal change in a value for a particular state variable is determined based on a non-linear transformation of a sum of the trial value for the perturbation that affects the particular state added to a sum of all non-zero values for a product of wij and a state variable over all state variables. In some embodiments, measurement-based values are received for a measurable subset of the state variables. Values for the constant interaction factors wij are determined based on the measurement-based values.

Abstract: Techniques for modeling living biological systems include receiving constant values for multiple interaction factors wij. A set of initial state values is received for state variables that indicate relevant properties of a living biological system. Also received is a set of trial values for perturbation variables that indicate factors that might affect one or more of the relevant properties of the biological system. A temporal change in a value for a particular state variable is determined based on a non-linear transformation of a sum of the trial value for the perturbation that affects the particular state added to a sum of all non-zero values for a product of wij and a state variable over all state variables. In some embodiments, measurement-based values are received for a measurable subset of the state variables. Values for the constant interaction factors wij are determined based on the measurement-based values.