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.
Claims20
A system for determining binding free energies of protein-protein complexes, the system comprising:
- machine learning means for machine estimating amino acid contact potentials and their corresponding weights from at least some available data;
- and
- machine learning means for determining a binding free energy of one protein to another protein, the machine learning means for determining a binding free energy utilizing an optimized soft step function defining an amino acid distance criterion, the amino acid contact potentials and their corresponding weights to determine the binding free energy of the proteins.
A system for determining a binding free energy between two proteins, the system comprising:
- a prediction component employing an adjusted threading model having one or more learnable parameters, information about the proteins' sequences and a geometry of a protein-protein complex to predict the binding free energy between the two proteins;
- the one or more learnable parameters machine learned at least in part utilizing data relating to known binding energies.
Computer-executable instructions stored on computer-readable media, the computer-executable instructions encoding a method for evaluating a binding energy between two proteins, 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, the set of distances defining a minimum distance of contact between amino acids of the proteins;
- and
- determining a score that rates the contact between the two proteins, the score determined by evaluating sequence data according to the set of distances and the optimized set of weighted contact potentials.
Dependencies are inferred from the claim text.