The present disclosure relates to in vitro experiments and in silico computation and machine-learning based techniques to iteratively improve a process for identifying binders that can bind any given molecular target. Particularly, aspects of the present disclosure are directed to obtaining initial sequence data for aptamers that bind to a target, measuring a first signal to noise ratio within the initial sequence data, provisioning, based on the first signal to noise ratio, a first machine-learning system, generating, by the first machine-learning system, a first set of aptamer sequences, obtaining subsequent sequence data for aptamers that bind to the target, measuring a second signal to noise ratio within the subsequent sequence data, provisioning, based on the second signal to noise ratio, a second machine-learning system, generating, by the second machine-learning system, a second set of aptamer sequences, and outputting the second set of aptamer sequences.

The invention relates to an in silico screening method to identify candidate excipients for reducing aggregation of a protein in a formulation. The method combines computational molecular modeling and molecular dynamics simulations to identify sites on a protein where non-specific self-interaction and interaction of different test excipients may occur, determine the relative binding energies of such interactions, and select one or more test excipients that meet specified interaction criteria for use as candidate excipients in empirical screening studies.

Methods for measuring subpopulations of ribonucleic acid (RNA) molecules are provided. In some embodiments, methods of generating a sequencing library from a plurality of RNA molecules in a test sample obtained from a subject are provided, as well as methods for analyzing the sequencing library to detect, e.g., the presence or absence of a disease.

Methods for measuring subpopulations of ribonucleic acid (RNA) molecules are provided. In some embodiments, methods of generating a sequencing library from a plurality of RNA molecules in a test sample obtained from a subject are provided, as well as methods for analyzing the sequencing library to detect, e.g., the presence or absence of a disease.

The present invention provides a method of manufacturing vectors containing a heterologous gene-editing protein comprising providing (a) transforming a host system with a nucleic acid cassette containing a promoter operably linked to a gene encoding a gene-editing protein, wherein the host system also contains a heterologous inhibitor for the gene-editing protein, (b) incubating the host system for a time sufficient for vector production and to release the recombinant vector, and (c) recovering the recombinant vector. Also provided herein are cell lines for expressing vectors containing a gene-editing protein with an inhibitor of the gene-editing protein to prevent leaky expression of the gene-editing protein comprising constitutive expression of an inhibitor of a gene-editing protein.

The present invention provides a method of manufacturing vectors containing a heterologous gene-editing protein comprising providing (a) transforming a host system with a nucleic acid cassette containing a promoter operably linked to a gene encoding a gene-editing protein, wherein the host system also contains a heterologous inhibitor for the gene-editing protein, (b) incubating the host system for a time sufficient for vector production and to release the recombinant vector, and (c) recovering the recombinant vector. Also provided herein are cell lines for expressing vectors containing a gene-editing protein with an inhibitor of the gene-editing protein to prevent leaky expression of the gene-editing protein comprising constitutive expression of an inhibitor of a gene-editing protein.

Disclosed are methods for identifying bio-molecules with desired properties (or which are most suitable for a round of directed evolution) from complex bio-molecule libraries or sets of such libraries. Some embodiments of the present disclosure provide methods for virtually screening proteins for beneficial properties. Some embodiments of the present disclosure provide methods for virtually screening enzymes for desired activity and/or selectivity for catalytic reactions involving particular substrates. Some embodiments combine screening and directed evolution to design and develop proteins and enzymes having desired properties. Systems and computer program products implementing the methods are also provided.

Disclosed are methods for identifying bio-molecules with desired properties (or which are most suitable for a round of directed evolution) from complex bio-molecule libraries or sets of such libraries. Some embodiments of the present disclosure provide methods for virtually screening proteins for beneficial properties. Some embodiments of the present disclosure provide methods for virtually screening enzymes for desired activity and/or selectivity for catalytic reactions involving particular substrates. Some embodiments combine screening and directed evolution to design and develop proteins and enzymes having desired properties. Systems and computer program products implementing the methods are also provided.

A high-throughput virtual drug screening system based on molecular fingerprints and deep learning, includes a deep-learning model online-modeling subsystem and an online virtual-screening subsystem. The system combines the molecular fingerprints and a deep neural network method to construct a high-throughput virtual drug screening system. The system includes built-in structural-diversity screening libraries and realizes the online automatic construction of deep learning models and virtual screening. The system helps researchers in the drug discovery industry such as medicinal chemistry to conduct rapid screening through their desired targets to obtain potential active compounds and accelerate drug discovery.

Provided herein are methods and compositions relating to libraries of optimized antibodies having nucleic acids encoding for an antibody comprising modified sequences. Libraries described herein include variegated libraries comprising nucleic acids each encoding for a predetermined variant of at least one predetermined reference nucleic acid sequence. Further described herein are protein libraries generated when the nucleic acid libraries are translated. Further described herein are cell libraries expressing variegated nucleic acid libraries described herein.