15 research outputs found
Computational approach to design of aptamers to the receptor binding domain of sars-cov-2
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
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
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
ΠΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΊΠ°ΠΏΠΈΠ»Π»ΡΡΠ½ΠΎΠΉ Π³Π°Π·ΠΎΠΆΠΈΠ΄ΠΊΠΎΡΡΠ½ΠΎΠΉ Ρ ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΠΈ Π² ΡΠ°ΡΠΌΠ°ΡΠ΅Π²ΡΠΈΡΠ΅ΡΠΊΠΎΠΌ Π°Π½Π°Π»ΠΈΠ·Π΅ ΠΏΡΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠΈ ΠΏΠ°ΡΠ°Π±Π΅Π½ΠΎΠ²
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 ΠΏΡΠ°ΠΊΡΠΈΠΊΠ΅ ΡΠ°ΡΠΌΠ°ΡΠ΅Π²ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° Π΄Π»Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΏΠ°ΡΠ°Π±Π΅Π½ΠΎΠ² ΠΏΡΠΈΠΌΠ΅Π½ΡΠ΅ΡΡΡ ΠΈΠΌΠ΅ΡΡΠΈΠΉ ΡΡΠ΄ ΡΠ΅ΡΡΠ΅Π·Π½ΡΡ
Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΊΠΎΠ² ΠΌΠ΅ΡΠΎΠ΄ ΠΊΠ»Π°ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π³Π°Π·ΠΎΠΆΠΈΠ΄ΠΊΠΎΡΡΠ½ΠΎΠΉ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΠΈ (ΠΠΠ₯) Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π½Π°ΡΠ°Π΄ΠΎΡΠ½ΡΡ
ΠΊΠΎΠ»ΠΎΠ½ΠΎΠΊ.Π¦Π΅Π»Ρ ΡΠ°Π±ΠΎΡΡ: ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°ΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΡ Π±ΠΎΠ»Π΅Π΅ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΏΠ°ΡΠ°Π±Π΅Π½ΠΎΠ² Π² ΡΠ°ΡΠΌΠ°ΡΠ΅Π²ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΡΠ±ΡΡΠ°Π½ΡΠΈΡΡ
ΠΈ Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΡΡ
ΡΡΠ΅Π΄ΡΡΠ²Π°Ρ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΊΠ°ΠΏΠΈΠ»Π»ΡΡΠ½ΠΎΠΉ ΠΠΠ₯.ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ: ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈΡΡ Π½Π° Π³Π°Π·ΠΎΠ²ΡΡ
Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠ°Ρ
Agilent 6890N ΠΈ Agilent 7890B Ρ ΠΏΠ»Π°ΠΌΠ΅Π½Π½ΠΎ-ΠΈΠΎΠ½ΠΈΠ·Π°ΡΠΈΠΎΠ½Π½ΡΠΌ Π΄Π΅ΡΠ΅ΠΊΡΠΎΡΠΎΠΌ, ΠΎΡΠ½Π°ΡΠ΅Π½Π½ΡΡ
Π°Π²ΡΠΎΡΠ°ΠΌΠΏΠ»Π΅ΡΠ°ΠΌΠΈ Agilent 7683B ΠΈ Agilent G4513A ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ. Π ΡΠ°Π±ΠΎΡΠ΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ 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·ΡΠ»ΡΡΠ°ΡΡ: ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π° ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠ° ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΌΠ΅ΡΠΈΠ»ΠΏΠ°ΡΠ°Π±Π΅Π½Π° ΠΈ ΠΏΡΠΎΠΏΠΈΠ»ΠΏΠ°ΡΠ°Π±Π΅Π½Π° Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΌΠ΅ΡΠΎΠ΄Π° Π³Π°Π·ΠΎΠΆΠΈΠ΄ΠΊΠΎΡΡΠ½ΠΎΠΉ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΠΈ Ρ ΠΊΠ°ΠΏΠΈΠ»Π»ΡΡΠ½ΠΎΠΉ ΠΊΠΎΠ»ΠΎΠ½ΠΊΠΎΠΉ. ΠΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Ρ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΡ (ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ, Π²ΠΎΡΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΠΌΠΎΡΡΡ ΠΏΠ»ΠΎΡΠ°Π΄Π΅ΠΉ ΠΏΠΈΠΊΠΎΠ², Π°ΡΠΈΠΌΠΌΠ΅ΡΡΠΈΡ ΠΏΠΈΠΊΠΎΠ²) Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΏΠ°ΡΠ°Π±Π΅Π½ΠΎΠ² ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΊΠ°ΠΏΠΈΠ»Π»ΡΡΠ½ΠΎΠΉ ΠΠΠ₯ ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΠΠ₯ Ρ Π½Π°ΡΠ°Π΄ΠΎΡΠ½ΠΎΠΉ ΠΊΠΎΠ»ΠΎΠ½ΠΊΠΎΠΉ. ΠΠ±ΠΎΠ·Π½Π°ΡΠ΅Π½Ρ ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Ρ Π΅Π΄ΠΈΠ½ΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΈΡ
ΡΠΎΠ΅Π΄ΠΈΠ½Π΅Π½ΠΈΠΉ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ: Π·Π° 9 ΠΌΠΈΠ½ΡΡ Π±ΡΠ»Π° ΡΠ°Π·Π΄Π΅Π»Π΅Π½Π° ΡΠ΅ΡΡΡΠ΅Ρ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠ½Π°Ρ ΡΠΌΠ΅ΡΡ ΠΌΠ΅ΡΠΈΠ»-, ΡΡΠΈΠ»-, ΠΏΡΠΎΠΏΠΈΠ»- ΠΈ Π±ΡΡΠΈΠ»ΠΏΠ°ΡΠ°Π±Π΅Π½Π°. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π° ΡΠ°ΡΡΠΈΡΠ½Π°Ρ Π²Π°Π»ΠΈΠ΄Π°ΡΠΈΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ Π½Π° ΠΏΡΠΈΠΌΠ΅ΡΠ΅ Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΡΡΠ΅Π΄ΡΡΠ²Π° Β«ΠΠΎΠΌΠ° ΠΡΠΊΡ ΠΡΠΎΡΠΈΠ°ΡΠΈΡΒ». Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ Π΄ΠΈΠ°ΠΏΠ°Π·ΠΎΠ½ Π»ΠΈΠ½Π΅ΠΉΠ½ΠΎΡΡΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ, ΠΏΡΠ΅Π΄Π΅Π» ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΌΠ΅ΡΠΈΠ»ΠΏΠ°ΡΠ°Π±Π΅Π½Π° ΠΈ ΠΏΡΠΎΠΏΠΈΠ»ΠΏΠ°ΡΠ°Π±Π΅Π½Π°, ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π΅Π½Ρ ΠΏΡΠ°Π²ΠΈΠ»ΡΠ½ΠΎΡΡΡ ΠΈ ΠΏΡΠ΅ΡΠΈΠ·ΠΈΠΎΠ½Π½ΠΎΡΡΡ (ΡΡ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡ ΠΈ Π²Π½ΡΡΡΠΈΠ»Π°Π±ΠΎΡΠ°ΡΠΎΡΠ½Π°Ρ Π²ΠΎΡΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΠΌΠΎΡΡΡ).ΠΡΠ²ΠΎΠ΄Ρ: ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠ΅ ΠΈΡΠΏΡΡΠ°Π½ΠΈΡ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΈ Π²ΡΠ±ΡΠ°ΡΡ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΠ΅ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΡΠ»ΠΎΠ²ΠΈΡ Π΄Π»Ρ Π±ΡΡΡΡΠΎΠ³ΠΎ ΠΈ ΠΏΡΠ΅ΡΠΈΠ·ΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΌΠ΅ΡΠΈΠ»ΠΏΠ°ΡΠ°Π±Π΅Π½Π° ΠΈ ΠΏΡΠΎΠΏΠΈΠ»ΠΏΠ°ΡΠ°Π±Π΅Π½Π° Π² Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΡΡ
ΡΡΠ΅Π΄ΡΡΠ²Π°Ρ
. Π Π°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΡ ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄ΠΎΠ²Π°Π½ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ Π΄Π»Ρ ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ Π΄Π°Π½Π½ΡΡ
ΡΠΎΠ΅Π΄ΠΈΠ½Π΅Π½ΠΈΠΉ Π² ΡΡΠ΅Π΄ΡΡΠ²Π°Ρ
ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠ³ΠΎ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ