METHOD AND SYSTEM FOR ANALYZING SPECTRAL DATA Russian patent published in 2022 - IPC G16B45/00 G06F21/57 

Abstract RU 2764200 C2

FIELD: biotechnology.

SUBSTANCE: method for processing data, which is a characteristic of proteins, peptides and/or peptoids, is described. The method includes: application of controlled perturbation to proteins, peptides and/or peptoids in a solution; sequential obtaining of spectral images of proteins, peptides and/or peptoids in a solution using a quantum cascade laser microscope without the use of exogenous probes or additives, while sequentially obtained spectral images record induced changes in spectral intensity depending on the applied perturbation; identification and selection, in at least one of obtained spectral images, of an area of interest relatively to the applied perturbation; selection and analysis of spectral data, including data on side chains of amino acids in proteins, peptides and/or peptoids in a solution for the area of interest in a set of sequentially obtained spectral images, where the analysis of spectral data includes analysis of a mode of side chains of proteins, peptides and/or peptoids as internal probes; application of analysis of two-dimensional correlation and co-distribution spectroscopy (2DCDS) to build an asynchronous co-distribution graph for proteins, peptides and/or peptoids, and identification on the asynchronous co-distribution graph of at least one cross-peak correlating with an auto-peak associated with aggregation of proteins, peptides and/or peptoids. A system for processing data, which is a characteristic of proteins, peptides and/or peptoids is presented, while the system contains: a data collection module including a quantum cascade laser microscope performing following stages: sequential obtaining of spectral images of proteins, peptides and/or peptoids in a solution by means of the quantum cascade laser microscope without the use of exogenous probes or additives, while sequentially obtained spectral images record induced changes in spectral intensity depending on the controlled perturbation applied; identification and selection, in at least one of obtained spectral images, of an area of interest relatively to the applied perturbation; and selection and analysis of spectral data, including data on side chains of amino acids in proteins, peptides and/or peptoids in a solution for the area of interest in a set of sequentially obtained spectral images, where the analysis of spectral data includes analysis of a mode of side chains of proteins, peptides and/or peptoids as internal probes; and a correlation analysis module that performs following stages: application of analysis of two-dimensional correlation and co-distribution spectroscopy (2DCDS) to build an asynchronous co-distribution graph for proteins, peptides and/or peptoids; identification of a cross-peak associated with aggregation of proteins, peptides and/or peptoids on the asynchronous co-distribution graph. A non-volatile computer-readable media is also described, containing commands that, when implementing by one or more computers, make one or more computers to: obtain sequentially obtained spectral images, obtained using the quantum cascade laser microscope, of proteins, peptides and/or peptoids in a solution without the use of exogenous probes or additives, while sequentially obtained spectral images record induced changes in spectral intensity depending on the applied controlled perturbation; in accordance with the applied controlled perturbation, identify and isolate, in at least one of obtained spectral images, an area of interest relatively to the applied perturbation; select and analyze spectral data, including data on side chains of amino acids in proteins, peptides and/or peptoids in a solution for the area of interest in a set of sequentially obtained spectral images, where the analysis of spectral data includes analysis of a mode of side chains of proteins, peptides and/or peptoids as internal probes; apply analysis of two-dimensional correlation and co-distribution spectrometry (2DCDS) to build an asynchronous co-distribution graph for proteins, peptides and/or peptoids; identify on the asynchronous co-distribution graph a cross-peak correlating with an auto-peak associated with aggregation of proteins, peptides and/or peptoids; and use the cross-peak to determine a distribution order of the presence of spectral intensities in accordance with the applied perturbation.

EFFECT: invention expands the arsenal of means for processing data, which is a characteristic of proteins.

28 cl, 32 dwg, 14 tbl, 5 ex

Similar patents RU2764200C2

Title Year Author Number
MATRIX DEVICES FOR SAMPLES AND SYSTEM FOR SPECTRAL ANALYSIS 2017
  • Pastrana-Rios Belinda
  • Rodrigez-Toro Khose Ksaver
RU2753715C2
METHOD OF DETERMINING MEAN SQUARE DEVIATION OF OPTICAL SURFACE ROUGHNESS 2023
  • Denisov Dmitrii Gennadevich
  • Baryshnikov Nikolai Vasilevich
  • Zhivotovskii Ilia Vadimovich
  • Karasik Valerii Efimovich
  • Sakharov Aleksei Aleksandrovich
  • Patrikeeva Anastasiia Andreevna
RU2823018C1
ATOMIC BEAM FREQUENCY STANDARD 2009
  • Kharchev Oleg Prokop'Evich
  • Zholnerov Vadim Stepanovich
RU2395900C1
DIFFERENTIAL METHOD FOR DETERMINING VERTICAL PROFILE OF GASES CONCENTRATION IN ATMOSPHERE 2014
  • Sterljadkin Viktor Vjacheslavovich
RU2557335C1
QUANTUM FREQUENCY STANDARD BASED ON COHERENT POPULATION TRAPPING EFFECT 2013
  • Kharchev Oleg Prokop'Evich
  • Zholnerov Vadim Stepanovich
RU2529756C1
SYSTEM AND METHOD FOR AMYLOID PROTEIN DETECTION 2011
  • Hartung Paul D.
  • Valvo Vincent
  • Kerbage Charles
  • Cagle Gerald D.
  • Nilan Dennis J.
RU2577810C2
ATOMIC BEAM FREQUENCY STANDARD 2008
  • Zholnerov Vadim Stepanovich
  • Kharchev Oleg Prokop'Evich
RU2378757C1
ATOMIC BEAM FREQUENCY STANDARD 2009
  • Kharchev Oleg Prokop'Evich
  • Zholnerov Vadim Stepanovich
  • Bekentaev Rinat Akhmetzhanovich
  • Gerasimov Georgij Vladimirovich
  • Nesterov Aleksandr Viktorovich
RU2395901C1
METHOD FOR EVALUATING FUNCTIONAL STATE OF HUMAN BODY BASED UPON ANALYSIS OF CARDIAC RHYTHM VARIABILITY AND THAT OF RESPIRATORY CYCLE DURATION 2001
  • Mikhajlov V.M.
RU2195163C2
METHOD OF DETERMINING AGGREGATIVE STABILITY OF WATER-OIL EMULSION 1996
  • Verevkin A.P.
  • Khafizov A.R.
  • Ishmakov R.M.
RU2106629C1

RU 2 764 200 C2

Authors

Pastrana-Rios Belinda

Rodrigez-Toro Khose Ksaver

Dates

2022-01-14Published

2017-01-20Filed