Molecular interaction predictors
AssigneeMicrosoft Corporation
InventorsNebojsa Jojic, Manuel Jesus Reyes Gomez
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Abstract
Adaptive threading models for predicting an interaction between two or more molecules such as proteins are provided. The adaptive threading models have one or more learnable parameters that can be learned from all or some of the available data. The available data can include data relating to known interactions between the two or more molecules, the composition of the molecules and the geometry of the molecular complex.
Claims8
Computer-executable instructions stored on computer-readable media, the computer-executable instructions encoding a method for evaluating a contact between a protein and a peptide, the method comprising:
- providing an optimized set of weighted contact potentials, the set of optimized weighted contact potentials optimized utilizing one or more machine learning algorithms;
- choosing a set of distances according to a structural template relating to the protein, the set of distances defining a minimum distance of the contact between an amino acid of the protein and an amino acid of the peptide;
- and
- determining a score that rates the contact between the protein and the peptide, the score determined by evaluating protein sequence and peptide sequence data according to the set of distances and the optimized set of weighted contact potentials.
Dependencies are inferred from the claim text.