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34 results about "Binding free energy" patented technology

Protein-ligand binding free energy calculating method based on MM/PBSA model

The invention provides a protein-ligand free energy calculating method based on a MM / PBSA model. The method comprises the following steps of respectively acquiring pdb files of a protein and a ligandmolecule; preprocessing the pdb file of the protein by means of a pdb4amber tool, deleting a hydrogen atom which cannot be read by Amber software; for the pdb file of the ligand molecule, converting the pdb format to a mol2 file format by means of an antechamber tool, and correcting the atom type to the atom type of an amber force field; assigning a GAFF force field parameter of the ligand molecule by means of a tleap command; respectively generating a topological file and a coordinate file of the protein, the ligand micromolecule and a protein-ligand micromolecule composite structure by meansof the tleap command through using an AMBER99SB-ILDN molecule force field parameter, and adding a water box and counter ions in the process; performing energy minimizing, heating and molecular dynamics simulation on a simulation system by means of the Amber software; and performing binding free energy calculation based on a molecular dynamics Poisson-Boltzmann surface area model on a molecular dynamics simulating track in a previous step by means of an MMPBSA.py program.
Owner:JIANGSU UNIV OF TECH

Algorithm for quickly and accurately calculating free affinity between proteinase and drug molecules

The invention belongs to the technical field of pharmacy and relates to an algorithm for quickly and accurately calculating free affinity between proteinase and drug molecules. The algorithm is characterized in that standard chemical potentials of a ligand and receptor in free state and a standard chemical potential of a receptor-ligand complex in bound state are calculated respectively, and differences among the standard chemical potentials are standard binding free energy; wherein in the calculation of the standard chemical potentials, M most steady-state conformations of the molecules are found first, j refers to energy wells corresponding to the most steady-state conformations, with j equal to 1...N, conformation integral zj of the corresponding energy well j of each most steady-state conformation is calculated, corresponding Boltzmann factor RT is calculated accordingly, and all the conformation integrals are combined to obtain a standard chemical potential for the ligand, the receptor or the receptor-ligand complex in bound state. By replacing experiments via computer simulation, screening and optimizing accuracy for pilot drugs are greatly improved, and time and cost for screening and optimizing are greatly decreased.
Owner:南昌立德生物技术有限公司

Design and selection of genetic targets for sequence resolved organism detection and identification

A computer-implemented method as follows. Providing a list of target sequences associated with one or more organisms in a list of organisms. Providing a list of candidate prototype sequences suspected of hybridizing to one or more of the target sequences. Generating a collection of probes corresponding to each candidate prototype sequence, each collection of probes having a set of probes for every subsequence having a predetermined, fixed subsequence length of the corresponding candidate prototype sequence. The sets consist of the corresponding subsequence and every variation of the corresponding subsequence formed by varying a center nucleotide of the corresponding subsequence. Generating a set of fragments corresponding to each target sequence, each set of fragments having every fragment having a predetermined, fixed fragment length of the corresponding target sequence. Calculating the binding free energy of each fragment with a perfect complimentary sequence of the fragment. If any binding free energy is above a predetermined, fixed threshold, the fragment is extended one nucleotide at a time until the binding free energy is below the threshold or the fragment is the same length as the probe, generating a set of extended fragments. Determining which extended fragments are perfect matches to any of the probes. Assembling a base call sequence corresponding to each candidate prototype sequence. The base call sequence has a base call corresponding to the center nucleotide of each probe of the corresponding prototype sequence that is a perfect match to any extended fragment, but for which the other members of the set of probes containing the perfect match probe are not perfect matches to any extended fragment and a non-base call in all other circumstances.
Owner:THE UNITED STATES OF AMERICA AS REPRESENTED BY THE SECRETARY OF THE NAVY

Virtual screening method for micromolecular reversible inhibitor of alkaline metalloproteinase from flavobacterium YS-80-122

The invention relates to a virtual screening method for a micromolecular reversible inhibitor of an alkaline metalloproteinase from flavobacterium YS-80-122 and belongs to the field of marine biotechnologies. The virtual screening method comprises the following steps: determining the type of the micromolecular reversible inhibitor according to the known structural data of the alkaline metalloproteinase from the flavobacterium YS-80-122; measuring the inhibition constant of the micromolecular reversible inhibitor of the type to the alkaline metalloproteinase from the flavobacterium YS-80-122, and determining compounds composing a training set; conducting molecular docking on the compounds of the training set and the alkaline metalloproteinase from the flavobacterium YS-80-122; acquiring the theoretical binding free energy and the theoretical reversible inhibition constant of the compounds of the training set and the alkaline metalloproteinase from the flavobacterium YS-80-122; in combination with the measured data, making a screening rule and establishing a screen model; conducting virtual screening. The virtual screening method is high in screening speed, can quickly reduce the quantity of candidate molecules, and reduce waste of time and test materials.
Owner:YELLOW SEA FISHERIES RES INST CHINESE ACAD OF FISHERIES SCI

Design and selection of genetic targets for sequence resolved organism detection and identification

A computer-implemented method as follows. Providing a list of target sequences associated with one or more organisms in a list of organisms. Providing a list of candidate prototype sequences suspected of hybridizing to one or more of the target sequences. Generating a collection of probes corresponding to each candidate prototype sequence, each collection of probes having a set of probes for every subsequence having a predetermined, fixed subsequence length of the corresponding candidate prototype sequence. The sets consist of the corresponding subsequence and every variation of the corresponding subsequence formed by varying a center nucleotide of the corresponding subsequence. Generating a set of fragments corresponding to each target sequence, each set of fragments having every fragment having a predetermined, fixed fragment length of the corresponding target sequence. Calculating the binding free energy of each fragment with a perfect complimentary sequence of the fragment. If any binding free energy is above a predetermined, fixed threshold, the fragment is extended one nucleotide at a time until the binding free energy is below the threshold or the fragment is the same length as the probe, generating a set of extended fragments. Determining which extended fragments are perfect matches to any of the probes. Assembling a base call sequence corresponding to each candidate prototype sequence. The base call sequence has a base call corresponding to the center nucleotide of each probe of the corresponding prototype sequence that is a perfect match to any extended fragment, but for which the other members of the set of probes containing the perfect match probe are not perfect matches to any extended fragment and a non-base call in all other circumstances.
Owner:THE UNITED STATES OF AMERICA AS REPRESENTED BY THE SECRETARY OF THE NAVY

Method for measuring clay dispersion average binding free energy and adsorption free energy to cation

The method for measuring the average binding free energy and average adsorption free energy of soil clay particles to cations includes: a. preparing soil clay particles with a particle size of <2 μm and saturated with cations, and then preparing a soil suspension with deionized water or distilled water; b. Place the soil suspension under an electric field with an initial field strength ≤ 15kV cm-1, and gradually increase the field strength, measure the conductivity of the soil suspension under each field strength, and obtain the conductivity and field strength of the soil suspension c. Calculate the average binding free energy and adsorption free energy of soil clay particles to cations according to the following mathematical formulas: ΔGbo=RTln(2CEC Cp λ / EC0) (4); ΔGad=RTln(EC / EC0 ) (8); in the formula, R is the gas constant; T is the thermodynamic temperature; CEC is the cation exchange capacity, Cp is the concentration of soil clay particles in the suspension; λ is the equivalent conductance of dissociated cations; EC0 is the field strength ≤ 15kV Conductivity of the suspension under an electric field of cm-1; EC is the conductivity of the suspension under an electric field of field strength >15kV·cm-1.
Owner:INST OF SOIL SCI CHINESE ACAD OF SCI

Method and device for predicting binding free energy of protein and ligand molecules

The invention provides a method and device for predicting the binding free energy of protein and ligand molecules, and the method comprises the steps: S1, constructing a local database; s2, analyzingthe data to obtain a ligand molecule and an amino acid molecule in a protein binding pocket taking the ligand molecule as a center; s3, calculating the MACCS secret keys of the ligand molecules and the near amino acids; s4, calculating ECFP fingerprints of ligand molecules and near amino acids; s5, converting the MACCS key and ECFP fingerprint information of the ligand molecule and protein into aone-dimensional tensor to form a training set and a test set; s6, establishing a machine learning model, and training the machine learning model; s7, calculating and comparing a Pearson correlation coefficient and an absolute error, and verifying a prediction result of the machine learning model; and S8, predicting the binding constant of the protein and the ligand molecule by using the trained machine learning model, and calculating the binding free energy. Compared with the prediction result of a single fingerprint, the prediction result of the combined fingerprint is obviously better, and the accuracy of free energy prediction is improved.
Owner:JIANGSU UNIV OF TECH +1

An Algorithm for Quickly and Accurately Calculating the Free Energy of Affinity Between Protease and Drug Molecules

The invention belongs to the technical field of pharmacy and relates to an algorithm for quickly and accurately calculating free affinity between proteinase and drug molecules. The algorithm is characterized in that standard chemical potentials of a ligand and receptor in free state and a standard chemical potential of a receptor-ligand complex in bound state are calculated respectively, and differences among the standard chemical potentials are standard binding free energy; wherein in the calculation of the standard chemical potentials, M most steady-state conformations of the molecules are found first, j refers to energy wells corresponding to the most steady-state conformations, with j equal to 1...N, conformation integral zj of the corresponding energy well j of each most steady-state conformation is calculated, corresponding Boltzmann factor RT is calculated accordingly, and all the conformation integrals are combined to obtain a standard chemical potential for the ligand, the receptor or the receptor-ligand complex in bound state. By replacing experiments via computer simulation, screening and optimizing accuracy for pilot drugs are greatly improved, and time and cost for screening and optimizing are greatly decreased.
Owner:南昌立德生物技术有限公司
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