The technology disclosed describes determination of which elements of a sequence are nearest to uniformly spaced cells in a grid, where the elements have element coordinates, and the cells have dimension-wise cell indices and cell coordinates. The determination includes generating an element-to-cells mapping that maps, to each of the elements, a subset of the cells. The subset of the cells mapped to a particular element in the sequence includes a nearest cell in the grid and one or more neighborhood cells in the grid, and the nearest cell is selected based on matching element coordinates of the particular element to the cell coordinates. The determination further includes generating a cell-to-elements mapping that maps, to each of the cells, a subset of the elements, and using the cell-to-elements mapping to determine, for each of the cells, a nearest element in the sequence.

The present disclosure provides for systems and methods for generating and displaying a three dimensional map of a protein sequence. An exemplary method can provide for using deep learning models to predict protein folding and model protein folding using three dimensional representations. The method more effectively exploits the potential of deep learning approaches. The method approach overall involves three stages—computation, geometry, and assessment.

The invention provides for systems, methods, and compositions for altering expression of target gene sequences and related gene products. Provided are structural information on the Cas protein of the CRISPR-Cas system, use of this information in generating modified components of the CRISPR complex, vectors and vector systems which encode one or more components or modified components of a CRISPR complex, as well as methods for the design and use of such vectors and components. Also provided are methods of directing CRISPR complex formation in eukaryotic cells and methods for utilizing the CRISPR-Cas system. In particular the present invention comprehends optimized functional CRISPR-Cas enzyme systems. In particular the present invention comprehends engineered new guide architectures and enzymes to be used in optimized Staphylococcus aureus CRISPR-Cas enzyme systems.

The invention provides for systems, methods, and compositions for altering expression of target gene sequences and related gene products. Provided are structural information on the Cas protein of the CRISPR-Cas system, use of this information in generating modified components of the CRISPR complex, vectors and vector systems which encode one or more components or modified components of a CRISPR complex, as well as methods for the design and use of such vectors and components. Also provided are methods of directing CRISPR complex formation in eukaryotic cells and methods for utilizing the CRISPR-Cas system. In particular the present invention comprehends optimized functional CRISPR-Cas enzyme systems. In particular the present invention comprehends engineered new guide architectures and enzymes to be used in optimized Staphylococcus aureus CRISPR-Cas enzyme systems.

Exemplary embodiments relate to a protein engineering pipeline configured to optimize or improve proteins for specified functions. The problem space of such a task can grow quickly based on the sequence of the protein being optimized and the functions for which the protein is being designed. The solutions described herein allow the problem space to be efficiently searched by applying a combination of a protein design pipeline and an evaluation procedure performed on a quantum computer. As a result, single or multiple amino acid substitutions at a site of interest may be predicted in order to generate optimized protein variants.

Exemplary embodiments relate to a protein engineering pipeline configured to optimize or improve proteins for specified functions. The problem space of such a task can grow quickly based on the sequence of the protein being optimized and the functions for which the protein is being designed. The solutions described herein allow the problem space to be efficiently searched by applying a combination of a protein design pipeline and an evaluation procedure performed on a quantum computer. As a result, single or multiple amino acid substitutions at a site of interest may be predicted in order to generate optimized protein variants.

Described herein are peptides and variants and mutants thereof capable of interacting with TEAD, disrupting the HIPPO pathway, or modulating the activity or function of TEAD interactions in a cell. Pharmaceutical compositions and uses of peptides, as well as methods of designing and manufacturing such peptides, to treat cancer, tumor, or any other disease/condition associated with a dysregulated HIPPO pathway or uncontrolled cell growth are also described herein.

Described herein are peptides and variants and mutants thereof capable of interacting with TEAD, disrupting the HIPPO pathway, or modulating the activity or function of TEAD interactions in a cell. Pharmaceutical compositions and uses of peptides, as well as methods of designing and manufacturing such peptides, to treat cancer, tumor, or any other disease/condition associated with a dysregulated HIPPO pathway or uncontrolled cell growth are also described herein.

The technology disclosed relates to a variant pathogenicity classifier. The variant pathogenicity classifier comprises memory and runtime logic. The memory stores (i) a reference amino acid sequence of a protein, (ii) an alternative amino acid sequence of the protein that contains a variant amino acid caused by a variant nucleotide, and (iii) a protein contact map of the protein. The runtime logic has access to the memory, and is configured to provide (i) the reference amino acid sequence, (ii) the alternative amino acid sequence, and (iii) the protein contact map as input to a first neural network, and to cause the first neural network to generate a pathogenicity indication of the variant amino acid as output in response to processing (i) the reference amino acid sequence, (ii) the alternative amino acid sequence, and (iii) the protein contact map.

A method for searching for a modification site of a peptide molecule includes: calculating, by a computer, a second steric structure of the peptide molecule by using data of a first steric structure of the peptide molecule, the first steric structure being a steric structure of the peptide molecule in a complex structure of a target molecule and the peptide molecule, the second steric structure being a stable steric structure of the peptide molecule in a state where a steric configuration of a main chain of the peptide molecule in the first steric structure is fixe; and comparing data of the second steric structure with the data of the first steric structure in order to search for a side chain having a difference in steric configuration between the two steric structures.