5 results about "Primary amino acids" patented technology

Methods for predicting the outcome of production of peptides are provided, as well as methods for producing peptides or providing products comprising peptides, which uses said methods. The methods comprise providing a primary amino acid sequence for one or more peptides, and Provide ore or more metrics predicting the outcome of production of the one or more peptides by chemical synthesis using a machine learning model that has been trained to predict one or more metrics characterising the outcome of production of peptides using training data comprising training peptide primary sequences and measured metrics characterising the outcome of production of the training peptides by chemical synthesis. The measured metrics are metrics obtained after completion of the chemical synthesis process. Systems and products for performing the methods are also described.

This invention relates to the field of bioactive peptide technology, and discloses a tetrapeptide with cognitive-improving function and its applications. The primary amino acid sequence of the tetrapeptide is Lys-Gly-Phe-Pro, and its molecular weight is 489.2587 Da. The tetrapeptide of this invention can be chemically synthesized or directionally prepared from sea cucumber protease hydrolysates. The tetrapeptide of this invention exhibits cognitive-improving activity, mainly through inhibiting GABA. B The expression of R activates the cAMP / PKA / CREB signaling pathway, promotes the release of the inhibitory neurotransmitter GABA, reduces oxidative stress damage, increases the gene expression of neurotrophic factors Bdnf and Nt3, and significantly upregulates the gene expression of antioxidant enzymes Sod1 and Gpx1, thereby exerting a neuroprotective effect and improving age-induced cognitive impairment.

A method, computer system, and a computer program product for designing one or more folded structural proteins from at least one raw amino acid sequence is provided. The present invention may include computing one or more character embeddings based on the at least one raw amino acid sequence by utilizing a multi-scale neighborhood-based neural network (MNNN) model. The present invention may then include refining the computed one or more character embeddings with at least one set of sequence neighborhood information. The present invention may further include predicting one or more dihedral angles based on the refined one or more character embeddings.

A protein composition derived from silk fibroin, which composition possesses enhanced solubility and stability in aqueous solutions. The primary amino acid sequence of native fibroin is modified in the SDP such that cysteine disulfide bonds between the fibroin heavy and fibroin light protein chains are reduced or eliminated. Additionally, the composition can have a serine content that is reduced by greater than 40% compared to native fibroin protein, and the average molecular weight of the SDP is less than about 100 kDa.

A protein composition derived from silk fibroin, which composition possesses enhanced solubility and stability in aqueous solutions. The primary amino acid sequence of native fibroin is modified in the SDP such that cysteine disulfide bonds between the fibroin heavy and fibroin light protein chains are reduced or eliminated. Additionally, the composition can have a serine content that is reduced by greater than 40% compared to native fibroin protein, and the average molecular weight of the SDP is less than about 100 kDa.