15 research outputs found

    Computational approach to design of aptamers to the receptor binding domain of sars-cov-2

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    The aim of the research. In this work, in silico selection of DNA-aptamers to the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein was performed using molecular modeling methods. Material and methods. A new computational approach to aptamer in silico selection is based on a cycle of simulations, including the stages of molecular modeling, molecular docking, molecular dynamic simulations, and quantum chemical calculations. To verify the obtained calculated results flow cytometry, fluorescence polarization, and small-angle X-ray scattering methods were applied. Results. An initial library consisted of 256 16-mer oligonucleotides was modeled. Based on molecular docking results, the only one aptamer (Apt16) was selected from the library as a starting aptamer to the RBD protein. For Apt16/RBD complex, molecular dynamic and quantum chemical calculations revealed the pairs of nucleotides and amino acids whose contribution to the binding between aptamer and RBD is the largest. Taking into account these data, Apt16 was subjected to the structure modifications in order to increase the binding with the RBD. Thus, a new aptamer Apt25 was designed. The procedure of 1) aptamer structure modeling/modification, 2) molecular docking, 3) molecular dynamic simulations, 4) quantum chemical calculations was performed sev-eral times. As a result, four aptamers (Apt16, Apt25, Apt27, Apt31) to the RBD were designed in silico without any preliminary experimental data. Binding of the each modeled aptamer to the RBD was studied in terms of interactions between residues in protein and nucleotides in the aptamers. Based on the simulation results, the strongest binding with the RBD was predicted for two Apt27 and Apt31aptamers. The calculated results are in good agreement with experimental data obtained by flow cytometry, fluorescence polarization, and small-angle X-ray scattering methods. Conclusion. The proposed computational approach to selection and refinement of aptamers is universal and can be used for wide range of molecular ligands and targets. Key words

    Applicability of Capillary Gas-Liquid Chromatography for Determination of Parabens in Pharmaceutical Analysis

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    The traditional gas-liquid chromatography (GLC) method using packed columns is still used in pharmaceutical analysis for determination of parabens, despite the fact that this technique has a number of serious drawbacks.The aim of the study was to develop a more effective capillary GLC method for determination of parabens in active pharmaceutical ingredients and finished pharmaceutical products.Materials and methods: the study was performed using Agilent 6890N and Agilent 7890B systems with flame-ionisation detectors. The systems were equipped with Agilent 7683B and Agilent G4513A autosamplers, respectively. The following columns were used in the study: ZB-1 15 m Ρ… 0.32 mm Ρ… 0.25 pm, DB-1 30 m Ρ… 0.32 mm Ρ… 3.0 pm, Cp-Sil 5-CB 30 m Ρ… 0.32 mm Ρ… 3.0 pm.Results: the authors developed a method for methylparaben and propylparaben determination using capillary column GLC. The chromatographic parameters (chromatographic system performance, reproducibility of peak areas, peak asymmetry) were determined for both capillary and packed column GLC. The authors outlined the prospects for simultaneous determination of several compounds using the proposed method: a four-component mixture containing methyl-, ethyl-, propyl-, and butylparaben was separated in 9 minutes. The authors used Loma Lux Psoriasis to perform partial validation of the test method. They determined the linearity range and the limit of quantitation for methylparaben and propylparaben, and verified accuracy and intermediate precision of the test method.Conclusions: the results of the study allowed for selection of optimal chromatographic conditions for rapid and high-precision determination of methylparaben and propylparaben in medicinal products. The developed method is recommended for control of the content of these compounds in medicinal products

    Computational approach to design of aptamers to the receptor binding domain of SARS-CoV-2

    No full text
    The aim of the research. In this work, in silico selection of DNA-aptamers to the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein was performed using molecular modeling methods. Material and methods. A new computational approach to aptamer in silico selection is based on a cycle of simulations, including the stages of molecular modeling, molecular docking, molecular dynamic simulations, and quantum chemical calculations. To verify the obtained calculated results flow cytometry, fluorescence polarization, and small-angle X-ray scattering methods were applied. Results. An initial library consisted of 256 16-mer oligonucleotides was modeled. Based on molecular docking results, the only one aptamer (Apt16) was selected from the library as a starting aptamer to the RBD protein. For Apt16/RBD complex, molecular dynamic and quantum chemical calculations revealed the pairs of nucleotides and amino acids whose contribution to the binding between aptamer and RBD is the largest. Taking into account these data, Apt16 was subjected to the structure modifications in order to increase the binding with the RBD. Thus, a new aptamer Apt25 was designed. The procedure of 1) aptamer structure modeling/modification, 2) molecular docking, 3) molecular dynamic simulations, 4) quantum chemical calculations was performed sev-eral times. As a result, four aptamers (Apt16, Apt25, Apt27, Apt31) to the RBD were designed in silico without any preliminary experimental data. Binding of the each modeled aptamer to the RBD was studied in terms of interactions between residues in protein and nucleotides in the aptamers. Based on the simulation results, the strongest binding with the RBD was predicted for two Apt27 and Apt31aptamers. The calculated results are in good agreement with experimental data obtained by flow cytometry, fluorescence polarization, and small-angle X-ray scattering methods. Conclusion. The proposed computational approach to selection and refinement of aptamers is universal and can be used for wide range of molecular ligands and targets.nonPeerReviewe

    Π’ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡ‚ΡŒ примСнСния капиллярной газоТидкостной Ρ…Ρ€ΠΎΠΌΠ°Ρ‚ΠΎΠ³Ρ€Π°Ρ„ΠΈΠΈ Π² фармацСвтичСском Π°Π½Π°Π»ΠΈΠ·Π΅ ΠΏΡ€ΠΈ ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½ΠΈΠΈ ΠΏΠ°Ρ€Π°Π±Π΅Π½ΠΎΠ²

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    The traditional gas-liquid chromatography (GLC) method using packed columns is still used in pharmaceutical analysis for determination of parabens, despite the fact that this technique has a number of serious drawbacks.The aim of the study was to develop a more effective capillary GLC method for determination of parabens in active pharmaceutical ingredients and finished pharmaceutical products.Materials and methods: the study was performed using Agilent 6890N and Agilent 7890B systems with flame-ionisation detectors. The systems were equipped with Agilent 7683B and Agilent G4513A autosamplers, respectively. The following columns were used in the study: ZB-1 15 m Ρ… 0.32 mm Ρ… 0.25 pm, DB-1 30 m Ρ… 0.32 mm Ρ… 3.0 pm, Cp-Sil 5-CB 30 m Ρ… 0.32 mm Ρ… 3.0 pm.Results: the authors developed a method for methylparaben and propylparaben determination using capillary column GLC. The chromatographic parameters (chromatographic system performance, reproducibility of peak areas, peak asymmetry) were determined for both capillary and packed column GLC. The authors outlined the prospects for simultaneous determination of several compounds using the proposed method: a four-component mixture containing methyl-, ethyl-, propyl-, and butylparaben was separated in 9 minutes. The authors used Loma Lux Psoriasis to perform partial validation of the test method. They determined the linearity range and the limit of quantitation for methylparaben and propylparaben, and verified accuracy and intermediate precision of the test method.Conclusions: the results of the study allowed for selection of optimal chromatographic conditions for rapid and high-precision determination of methylparaben and propylparaben in medicinal products. The developed method is recommended for control of the content of these compounds in medicinal products.Π’ ΠΏΡ€Π°ΠΊΡ‚ΠΈΠΊΠ΅ фармацСвтичСского Π°Π½Π°Π»ΠΈΠ·Π° для опрСдСлСния ΠΏΠ°Ρ€Π°Π±Π΅Π½ΠΎΠ² примСняСтся ΠΈΠΌΠ΅ΡŽΡ‰ΠΈΠΉ ряд ΡΠ΅Ρ€ΡŒΠ΅Π·Π½Ρ‹Ρ… нСдостатков ΠΌΠ΅Ρ‚ΠΎΠ΄ классичСской газоТидкостной Ρ…Ρ€ΠΎΠΌΠ°Ρ‚ΠΎΠ³Ρ€Π°Ρ„ΠΈΠΈ (Π“Π–Π₯) с использованиСм насадочных ΠΊΠΎΠ»ΠΎΠ½ΠΎΠΊ.ЦСль Ρ€Π°Π±ΠΎΡ‚Ρ‹: Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Ρ‚ΡŒ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΡƒ Π±ΠΎΠ»Π΅Π΅ эффСктивного опрСдСлСния ΠΏΠ°Ρ€Π°Π±Π΅Π½ΠΎΠ² Π² фармацСвтичСских субстанциях ΠΈ лСкарствСнных срСдствах ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ капиллярной Π“Π–Π₯.ΠœΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Ρ‹ ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹: исслСдования ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈΡΡŒ Π½Π° Π³Π°Π·ΠΎΠ²Ρ‹Ρ… Ρ…Ρ€ΠΎΠΌΠ°Ρ‚ΠΎΠ³Ρ€Π°Ρ„Π°Ρ… Agilent 6890N ΠΈ Agilent 7890B с ΠΏΠ»Π°ΠΌΠ΅Π½Π½ΠΎ-ΠΈΠΎΠ½ΠΈΠ·Π°Ρ†ΠΈΠΎΠ½Π½Ρ‹ΠΌ Π΄Π΅Ρ‚Π΅ΠΊΡ‚ΠΎΡ€ΠΎΠΌ, оснащСнных автосамплСрами Agilent 7683B ΠΈ Agilent G4513A соотвСтствСнно. Π’ Ρ€Π°Π±ΠΎΡ‚Π΅ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Ρ‹ хроматографичСскиС ΠΊΠΎΠ»ΠΎΠ½ΠΊΠΈ ZB-1 15 ΠΌ Ρ… 0,32 ΠΌΠΌ Ρ… 0,25 ΠΌΠΊΠΌ, DB-1 30 ΠΌ Ρ… 0,32 ΠΌΠΌ Ρ… 3,0 ΠΌΠΊΠΌ, CP-Sil 5-CB 30 ΠΌ Ρ… 0,32 ΠΌΠΌ Ρ… 3,0 ΠΌΠΊΠΌ.Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹: Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½Π° ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠ° опрСдСлСния ΠΌΠ΅Ρ‚ΠΈΠ»ΠΏΠ°Ρ€Π°Π±Π΅Π½Π° ΠΈ ΠΏΡ€ΠΎΠΏΠΈΠ»ΠΏΠ°Ρ€Π°Π±Π΅Π½Π° с использованиСм ΠΌΠ΅Ρ‚ΠΎΠ΄Π° газоТидкостной Ρ…Ρ€ΠΎΠΌΠ°Ρ‚ΠΎΠ³Ρ€Π°Ρ„ΠΈΠΈ с капиллярной ΠΊΠΎΠ»ΠΎΠ½ΠΊΠΎΠΉ. ΠžΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½Ρ‹ ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€Ρ‹ (ΡΡ„Ρ„Π΅ΠΊΡ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒ хроматографичСской систСмы, Π²ΠΎΡΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΠΌΠΎΡΡ‚ΡŒ ΠΏΠ»ΠΎΡ‰Π°Π΄Π΅ΠΉ ΠΏΠΈΠΊΠΎΠ², асиммСтрия ΠΏΠΈΠΊΠΎΠ²) хроматографичСского опрСдСлСния ΠΏΠ°Ρ€Π°Π±Π΅Π½ΠΎΠ² ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ капиллярной Π“Π–Π₯ ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ Π“Π–Π₯ с насадочной ΠΊΠΎΠ»ΠΎΠ½ΠΊΠΎΠΉ. ΠžΠ±ΠΎΠ·Π½Π°Ρ‡Π΅Π½Ρ‹ пСрспСктивы Π΅Π΄ΠΈΠ½ΠΎΠ²Ρ€Π΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ опрСдСлСния Π½Π΅ΡΠΊΠΎΠ»ΡŒΠΊΠΈΡ… соСдинСний с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠΉ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ: Π·Π° 9 ΠΌΠΈΠ½ΡƒΡ‚ Π±Ρ‹Π»Π° Ρ€Π°Π·Π΄Π΅Π»Π΅Π½Π° чСтырСхкомпонСнтная смСсь ΠΌΠ΅Ρ‚ΠΈΠ»-, этил-, ΠΏΡ€ΠΎΠΏΠΈΠ»- ΠΈ Π±ΡƒΡ‚ΠΈΠ»ΠΏΠ°Ρ€Π°Π±Π΅Π½Π°. ΠŸΡ€ΠΎΠ²Π΅Π΄Π΅Π½Π° частичная валидация ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ Π½Π° ΠΏΡ€ΠΈΠΌΠ΅Ρ€Π΅ лСкарствСнного срСдства Β«Π›ΠΎΠΌΠ° Π›ΡŽΠΊΡ ΠŸΡΠΎΡ€ΠΈΠ°ΡΠΈΡΒ». УстановлСн Π΄ΠΈΠ°ΠΏΠ°Π·ΠΎΠ½ линСйности ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ, ΠΏΡ€Π΅Π΄Π΅Π» количСствСнного опрСдСлСния ΠΌΠ΅Ρ‚ΠΈΠ»ΠΏΠ°Ρ€Π°Π±Π΅Π½Π° ΠΈ ΠΏΡ€ΠΎΠΏΠΈΠ»ΠΏΠ°Ρ€Π°Π±Π΅Π½Π°, ΠΏΠΎΠ΄Ρ‚Π²Π΅Ρ€ΠΆΠ΄Π΅Π½Ρ‹ ΠΏΡ€Π°Π²ΠΈΠ»ΡŒΠ½ΠΎΡΡ‚ΡŒ ΠΈ ΠΏΡ€Π΅Ρ†ΠΈΠ·ΠΈΠΎΠ½Π½ΠΎΡΡ‚ΡŒ (ΡΡ…ΠΎΠ΄ΠΈΠΌΠΎΡΡ‚ΡŒ ΠΈ внутрилабораторная Π²ΠΎΡΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΠΌΠΎΡΡ‚ΡŒ).Π’Ρ‹Π²ΠΎΠ΄Ρ‹: ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½Π½Ρ‹Π΅ испытания ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΈ Π²Ρ‹Π±Ρ€Π°Ρ‚ΡŒ ΠΎΠΏΡ‚ΠΈΠΌΠ°Π»ΡŒΠ½Ρ‹Π΅ хроматографичСскиС условия для быстрого ΠΈ ΠΏΡ€Π΅Ρ†ΠΈΠ·ΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ опрСдСлСния ΠΌΠ΅Ρ‚ΠΈΠ»ΠΏΠ°Ρ€Π°Π±Π΅Π½Π° ΠΈ ΠΏΡ€ΠΎΠΏΠΈΠ»ΠΏΠ°Ρ€Π°Π±Π΅Π½Π° Π² лСкарствСнных срСдствах. Π Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½Π½ΡƒΡŽ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΡƒ Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄ΠΎΠ²Π°Π½ΠΎ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚ΡŒ для контроля содСрТания Π΄Π°Π½Π½Ρ‹Ρ… соСдинСний Π² срСдствах мСдицинского примСнСния
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