# How Computers Predict Protein Shapes Faster Using Smart Templates > This patent describes a computer method to quickly predict the 3D shape of proteins by creating and refining "synthetic templates" from existing protein structures, reducing the heavy computational work usually needed. - **Patent:** US 20210280268 - **Original title:** Protein structure prediction system - **Owner:** Dnastar - **Status:** Active - **Times cited:** 1 - **Field:** biotech, software, pharmaceutical ## What it does The patent outlines a multi-step computer method (Claim 1) to predict the 3D structure of a protein, which is an amino acid sequence. It starts by analyzing the protein's sequence to create a "sequence profile matrix" and identify "internal contacts" (Claim 1a-d). These features are then matched ("threaded") against a database of known protein structures, called "original templates" (Claim 1e). The method calculates "normal modes of motion" for these original templates and then "perturbs" them to create many new "synthetic templates" (Claim 1g-h). The system picks the best synthetic templates based on their energy (Claim 1i-j) and combines them with the original ones (Claim 1k). Finally, it runs "Markov Chain Monte Carlo simulations" (Claim 1m) and refines the best resulting shapes through "energy minimization" (Claim 1p) to find the most stable predicted structure (Claim 1q). ## What it does NOT cover - Protein structure prediction methods that do not rely on a database of existing "original templates." - Techniques that do not specifically "perturb" templates using "normal modes of motion" to generate new "synthetic templates." - Prediction systems that do not employ "Markov Chain Monte Carlo simulations" for exploring different protein shapes. - Methods that skip the final "energy minimization" step to refine the predicted protein models. - Protein structure prediction purely based on deep learning or artificial intelligence without the specific template generation and simulation steps outlined. ## The clever bit The novelty lies in creating "synthetic templates" by "perturbing" existing protein structures using their "normal modes of motion." This allows the system to efficiently explore many possible protein shapes without starting from scratch, saving a huge amount of computational time. ## Real-world examples 1. Dnastar Lasergene software suite 2. Protein modeling tools in academic research 3. Drug discovery platforms 4. Biotechnology research software ## Why it matters Predicting protein structures is crucial for understanding how proteins work and for designing new drugs. Traditional methods are very slow and use a lot of computer power. This patent aims to make that process much faster and more efficient by intelligently creating new template structures, which could speed up drug discovery and biological research significantly. ## Frequently asked questions ### What does How Computers Predict Protein Shapes Faster Using Smart Templates cover? This patent describes a computer method to quickly predict the 3D shape of proteins by creating and refining "synthetic templates" from existing protein structures, reducing the heavy computational work usually needed. ### Who owns patent US 20210280268? This patent is owned by Dnastar. ### When does this patent expire? This patent is expected to expire on May 20, 2041, when the invention enters the public domain. ### What is patent US 20210280268 cited by? This patent has been cited by 1 later patents that build on its ideas. ### What problem does this patent solve? Predicting protein structures is crucial for understanding how proteins work and for designing new drugs. Traditional methods are very slow and use a lot of computer power. This patent aims to make that process much faster and more efficient by intelligently creating new template structures, which could speed up drug discovery and biological research significantly. ### What does this patent NOT cover? Protein structure prediction methods that do not rely on a database of existing "original templates." **Full plain-English explainer:** https://patentbrief.org/patent/us/20210280268/protein-structure-prediction-system **Original patent:** https://patents.google.com/patent/US20210280268 --- _Source: PatentBrief — https://patentbrief.org. Patent facts are from public records; the plain-English explanation is PatentBrief's._ ## Related patents Semantically similar inventions in the PatentBrief corpus: - [How to Predict Protein Shapes Better Using Lab Tests and Computers](https://patentbrief.org/patent/us/20210174903/enhanced-protein-structure-prediction-using-protein-homolog-discovery-and-constr) — This patent describes a method to improve predicting a protein's 3D shape by combining computer simulations with actual distance measurements from specific parts of the protein in a lab. - [AI Model Predicts Protein Shapes from Infrared Light Data](https://patentbrief.org/patent/us/10962473/protein-secondary-structure-prediction) — This patent describes a computer method that uses an artificial intelligence model to predict the detailed 3D shapes of proteins within a food ingredient by analyzing how the ingredient absorbs infrared light. - [The Discovery of Aspartame as a Sugar Substitute](https://patentbrief.org/patent/us/3492131/aspartame-sweetener) — This 1966 patent identifies specific chemical compounds, known as aspartylphenylalanine esters, that provide intense sweetness for food and drinks without using sugar. - [How Synthetic Peptides Block Immune System Overreaction](https://patentbrief.org/patent/us/10106579/orkambi-lumacaftor-ivacaftor) — A patent describing specific synthetic peptides designed to stop the body's immune system from attacking healthy cells by blocking a protein called C5. - [How Dynamic Web Applications Use Templates to Fetch Data](https://patentbrief.org/patent/us/7111231/microsoft-word-docx-format) — A method for web applications to use abstract templates that automatically connect to back-end databases based on the user's device or platform.