A method for calculating binding free energy, where the method includes a plurality of steps each including adding a distance restraint potential between a binding calculation target molecule and a target molecule, wherein the method is a method for calculating binding free energy between the binding calculation target molecule and the target molecule using a computer, and wherein anchor points of the binding calculation target molecule in the plurality of the steps are identical anchor points, and anchor points of the target molecule in the plurality of the steps are different anchor points.

Methods and systems are provided to classify or identify a target molecule or its properties from regions of molecular surface of the target molecule. In an implementation, the system identifies patches of the surface, generates a respective latent space ID and a respective real space ID for each of the patches, uses the latent space IDs and the real space IDs to identify at least one candidate item that includes a surface resembling a surface region of the target molecule, wherein the surface region comprises multiple patches in the plurality of surface patches of the target molecule, and uses the at least one candidate item to determine an identification or a classification of the target molecule.

Methods and systems are provided to classify or identify a target molecule or its properties from regions of molecular surface of the target molecule. In an implementation, the system identifies patches of the surface, generates a respective latent space ID and a respective real space ID for each of the patches, uses the latent space IDs and the real space IDs to identify at least one candidate item that includes a surface resembling a surface region of the target molecule, wherein the surface region comprises multiple patches in the plurality of surface patches of the target molecule, and uses the at least one candidate item to determine an identification or a classification of the target molecule.

A system and method for optimizing the latent space in generative machine learning models, and applications of the optimizations for use in the de novo generation of molecules for both ligand-based and pocket-based generation. The ligand-based optimizations comprise a tunable reward system based on a multi-property model and further define new measurable metrics: molecular novelty and uniqueness. The pocket-based optimizations comprise an initial multi-property optimization followed up by either a seed-based optimization or a relaxed-based optimization.

A system and method for optimizing the latent space in generative machine learning models, and applications of the optimizations for use in the de novo generation of molecules for both ligand-based and pocket-based generation. The ligand-based optimizations comprise a tunable reward system based on a multi-property model and further define new measurable metrics: molecular novelty and uniqueness. The pocket-based optimizations comprise an initial multi-property optimization followed up by either a seed-based optimization or a relaxed-based optimization.

The invention provides computational methods for engineering, selecting, and/or identifying proteins with a desired activity. Further provided are automated computational design and screening methods to engineer proteins with desired functional activities including, but not limited to ligand binding, catalytic activity, substrate specificity, regioselectivity and/or stereoselectivity.

The invention provides computational methods for engineering, selecting, and/or identifying proteins with a desired activity. Further provided are automated computational design and screening methods to engineer proteins with desired functional activities including, but not limited to ligand binding, catalytic activity, substrate specificity, regioselectivity and/or stereoselectivity.

The invention provides methods, systems, and computer readable medium for detecting ploidy of chromosome segments or entire chromosomes, for detecting single nucleotide variants and for detecting both ploidy of chromosome segments and single nucleotide variants. In some aspects, the invention provides methods, systems, and computer readable medium for detecting cancer or a chromosomal abnormality in a gestating fetus.

The invention provides methods, systems, and computer readable medium for detecting ploidy of chromosome segments or entire chromosomes, for detecting single nucleotide variants and for detecting both ploidy of chromosome segments and single nucleotide variants. In some aspects, the invention provides methods, systems, and computer readable medium for detecting cancer or a chromosomal abnormality in a gestating fetus.

This disclosure relates to a method and apparatus for training a prediction model. The method includes: obtaining a training sample set; determining a current training sample from the training sample set based on the training sample weights; inputting current target energy characteristics corresponding to the current training sample into a pre-trained prediction model for basic training to obtain a basic prediction model after completing the basic training; updating the training sample weights corresponding to the training samples based on the basic prediction model; and returning to perform the operation of determining the current training sample from the training sample set based on the updated training sample weights until completing model training to obtain a target prediction model.