Aleksey Lutsenko
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Aleksey Lutsenko has a total of 16 co-authors. Here are the top co-authors by number of shared publications:
- Alla Eduardovna Sidorova
Faculty of Physics, Lomonosov Moscow State University, Moscow, Russia
7 shared publications - Denis Shpigun
Department of Biophysics, Faculty of Physics, Lomonosov Moscow State University, Moscow, 119991, Russia
7 shared publications - Ekaterina Belova
Onсoatlas; I. M. Sechenov First Moscow State Medical University, Ministry of Health of Russia (Sechenov University); Lomonosov Moscow State University
7 shared publications - Vladimir Sergeevich Bystrov
Institute of Mathematical Problems of Biology, Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Pushchino, Russia
4 shared publications - Ilya Viatcheslavovitch Likhachev
Institute of Mathematical Problems of Biology, Russian Academy of Sciences, Branch of the Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, 142290 Pushchino, Russia
2 shared publications - Olga E. Bagrova
Lomonosov Moscow State Univ, Fac Phys, Dept Biophys, Moscow 119991, Russia
2 shared publications
Latest Publications
- Open Access
- 27 August 2026
- Published by MDPI AG in Algorithms
- Vol. 19 (9) , 724
A Chirality Calculation Algorithm for Supersecondary Protein Structural Motifs
Coiled coils, collagen superhelices, and -sheets belong to the supersecondary level of protein structure. Each of these classes of structural motifs is characterized by a particular chirality. However, methodology for mathematical determination of chirality of specific structures found in real proteins is currently underdeveloped. The aim of this work is to present a universal algorithm for calculating the chirality sign and value for supersecondary structure elements. In this algorithm, the basic calculation principles are the same for all three classes of structures, allowing different motifs to be compared directly. The results for a number of structures from each of the three classes are presented in tables and graphical plots. The calculated chirality signs generally agree with the predicted ones. The results also show that the chirality value is related to the number of amino acid residues in the structure and their distribution among the secondary structure elements. The relationship between amino acid composition and the chirality value is discussed using several examples. The more evident factors that determine the chirality sign and value for a particular structure are a promising subject for future research.- 27 August 2026
- Published by MDPI AG in Algorithms
- Vol. 19 (9) , 724
Open AccessA Chirality Calculation Algorithm for Supersecondary Protein Structural Motifs
Coiled coils, collagen superhelices, and -sheets belong to the supersecondary level of protein structure. Each of these classes of structural motifs is characterized by a particular chirality. However, methodology for mathematical determination of chirality of specific structures found in real proteins is currently underdeveloped. The aim of this work is to present a universal algorithm for calculating the chirality sign and value for supersecondary structure elements. In this algorithm, the basic calculation principles are the same for all three classes of structures, allowing different motifs to be compared directly. The results for a number of structures from each of the three classes are presented in tables and graphical plots. The calculated chirality signs generally agree with the predicted ones. The results also show that the chirality value is related to the number of amino acid residues in the structure and their distribution among the secondary structure elements. The relationship between amino acid composition and the chirality value is discussed using several examples. The more evident factors that determine the chirality sign and value for a particular structure are a promising subject for future research. - 28 August 2024
- Published by Elsevier in Biochemical and Biophysical Research Communications
- Vol. 734, 150613
Secondary structure analysis of proteins within the same topology group
- 28 August 2024
- Published by Elsevier in Biochemical and Biophysical Research Communications
- Vol. 734, 150613
Secondary structure analysis of proteins within the same topology group
- Open Access
A Method for Calculating the Sign and Degree of Chirality of Supercoiled Protein Structures
Chirality plays an important role in studies of natural protein structures. Therefore, much attention is paid to solving the problems associated with the development of criteria and methods for assessing the chirality of biomolecules. In this paper, a new method for calculating the sign and degree of chirality of superhelices is proposed. The method makes it possible to characterize the chirality sign and to quantify coiled-coils and collagen superhelices. The degree of chirality is understood as a value indicating the intensity of twisting of individual helices around the axis of the superhelix. The calculation requires information about the relative spatial arrangement of the alpha carbon of the amino acid residues of the helices that make up the superhelix. The use of a small amount of raw data makes the method easy to apply, and the validity of the results of this study is confirmed through the analysis of real protein structures.
Open AccessA Method for Calculating the Sign and Degree of Chirality of Supercoiled Protein Structures
Chirality plays an important role in studies of natural protein structures. Therefore, much attention is paid to solving the problems associated with the development of criteria and methods for assessing the chirality of biomolecules. In this paper, a new method for calculating the sign and degree of chirality of superhelices is proposed. The method makes it possible to characterize the chirality sign and to quantify coiled-coils and collagen superhelices. The degree of chirality is understood as a value indicating the intensity of twisting of individual helices around the axis of the superhelix. The calculation requires information about the relative spatial arrangement of the alpha carbon of the amino acid residues of the helices that make up the superhelix. The use of a small amount of raw data makes the method easy to apply, and the validity of the results of this study is confirmed through the analysis of real protein structures.
- 4 April 2022
- Published by Technosphera JSC in Nanoindustry Russia
- Vol. 15 (2) , 96-104
МЕТОД ОЦЕНКИ ХИРАЛЬНОСТИ БЕЛКОВ И ФЕНИЛАЛАНИНОВЫХ НАНОТРУБОК КАК ЭФФЕКТИВНЫЙ ИНСТРУМЕНТ НАНОБИОИНЖЕНЕРИИ
Работа посвящена рассмотрению закономерностей пространственного структурообразования в белках и их применению в нанобиоинженерии. Представлены методы оценки хиральности регулярных и нерегулярных структур белка, а также спиральных нанотрубок на основе фенилаланина. Рассчитаны величина и знак хиральности α-, 310- и π-спиралей, β- и α-поворотов, Ω-петель, а также правых и левых фенилаланиновых нанотрубок. Полученные результаты могут быть использованы в управлении сборкой природных и искусственных белков.
- 4 April 2022
- Published by Technosphera JSC in Nanoindustry Russia
- Vol. 15 (2) , 96-104
МЕТОД ОЦЕНКИ ХИРАЛЬНОСТИ БЕЛКОВ И ФЕНИЛАЛАНИНОВЫХ НАНОТРУБОК КАК ЭФФЕКТИВНЫЙ ИНСТРУМЕНТ НАНОБИОИНЖЕНЕРИИ
Работа посвящена рассмотрению закономерностей пространственного структурообразования в белках и их применению в нанобиоинженерии. Представлены методы оценки хиральности регулярных и нерегулярных структур белка, а также спиральных нанотрубок на основе фенилаланина. Рассчитаны величина и знак хиральности α-, 310- и π-спиралей, β- и α-поворотов, Ω-петель, а также правых и левых фенилаланиновых нанотрубок. Полученные результаты могут быть использованы в управлении сборкой природных и искусственных белков.
- Open Access
- 3 March 2022
- Published by MDPI AG in Nanomaterials
- Vol. 12 (5) , 861
Molecular Dynamics Simulation Study of the Self-Assembly of Phenylalanine Peptide Nanotubes
In this paper, we propose and use a new approach for a relatively simple technique for conducting MD simulation (MDS) of various molecular nanostructures, determining the trajectory of the MD run and forming the final structure using external force actions. A molecular dynamics manipulator (MD manipulator) is a controlled MDS type. As an example, the applicability of the developed algorithm for assembling peptide nanotubes (PNT) from linear phenylalanine (F or Phe) chains of different chirality is presented. The most adequate regimes for the formation of nanotubes of right chirality D from the initial L-F and nanotubes of left chirality L of their initial dipeptides D-F modes were determined. We use the method of a mixed (vector–scalar) product of the vectors of the sequence of dipole moments of phenylalanine molecules located along the nanotube helix to calculate the magnitude and sign of chirality of self-assembled helical phenylalanine nanotubes, which shows the validity of the proposed approach. As result, all data obtained correspond to the regularity of the chirality sign change of the molecular structures with a hierarchical complication of their organization.
- 3 March 2022
- Published by MDPI AG in Nanomaterials
- Vol. 12 (5) , 861
Open AccessMolecular Dynamics Simulation Study of the Self-Assembly of Phenylalanine Peptide Nanotubes
In this paper, we propose and use a new approach for a relatively simple technique for conducting MD simulation (MDS) of various molecular nanostructures, determining the trajectory of the MD run and forming the final structure using external force actions. A molecular dynamics manipulator (MD manipulator) is a controlled MDS type. As an example, the applicability of the developed algorithm for assembling peptide nanotubes (PNT) from linear phenylalanine (F or Phe) chains of different chirality is presented. The most adequate regimes for the formation of nanotubes of right chirality D from the initial L-F and nanotubes of left chirality L of their initial dipeptides D-F modes were determined. We use the method of a mixed (vector–scalar) product of the vectors of the sequence of dipole moments of phenylalanine molecules located along the nanotube helix to calculate the magnitude and sign of chirality of self-assembled helical phenylalanine nanotubes, which shows the validity of the proposed approach. As result, all data obtained correspond to the regularity of the chirality sign change of the molecular structures with a hierarchical complication of their organization.
- Open Access
- 5 December 2021
- Published by MDPI AG in Nanomaterials
- Vol. 11 (12) , 3299
Quantitative Assessment of Chirality of Protein Secondary Structures and Phenylalanine Peptide Nanotubes
In this study we consider the features of spatial-structure formation in proteins and their application in bioengineering. Methods for the quantitative assessment of the chirality of regular helical and irregular structures of proteins are presented. The features of self-assembly of phenylalanine (F) into peptide nanotubes (PNT), which form helices of different chirality, are also analyzed. A method is proposed for calculating the magnitude and sign of the chirality of helix-like peptide nanotubes using a sequence of vectors for the dipole moments of individual peptides.
- 5 December 2021
- Published by MDPI AG in Nanomaterials
- Vol. 11 (12) , 3299
Open AccessQuantitative Assessment of Chirality of Protein Secondary Structures and Phenylalanine Peptide Nanotubes
In this study we consider the features of spatial-structure formation in proteins and their application in bioengineering. Methods for the quantitative assessment of the chirality of regular helical and irregular structures of proteins are presented. The features of self-assembly of phenylalanine (F) into peptide nanotubes (PNT), which form helices of different chirality, are also analyzed. A method is proposed for calculating the magnitude and sign of the chirality of helix-like peptide nanotubes using a sequence of vectors for the dipole moments of individual peptides.
- Open Access
- 16 September 2021
- Published by MDPI AG in Nanomaterials
- Vol. 11 (9) , 2415
Modeling of Self-Assembled Peptide Nanotubes and Determination of Their Chirality Sign Based on Dipole Moment Calculations
The chirality quantification is of great importance in structural biology, where the differences in proteins twisting can provide essentially different physiological effects. However, this aspect of the chirality is still poorly studied for helix-like supramolecular structures. In this work, a method for chirality quantification based on the calculation of scalar triple products of dipole moments is suggested. As a model structure, self-assembled nanotubes of diphenylalanine (FF) made of L- and D-enantiomers were considered. The dipole moments of FF molecules were calculated using semi-empirical quantum-chemical method PM3 and the Amber force field method. The obtained results do not depend on the used simulation and calculation method, and show that the D-FF nanotubes are twisted tighter than L-FF. Moreover, the type of chirality of the helix-like nanotube is opposite to that of the initial individual molecule that is in line with the chirality alternation rule general for different levels of hierarchical organization of molecular systems. The proposed method can be applied to study other helix-like supramolecular structures.
- 16 September 2021
- Published by MDPI AG in Nanomaterials
- Vol. 11 (9) , 2415
Open AccessModeling of Self-Assembled Peptide Nanotubes and Determination of Their Chirality Sign Based on Dipole Moment Calculations
The chirality quantification is of great importance in structural biology, where the differences in proteins twisting can provide essentially different physiological effects. However, this aspect of the chirality is still poorly studied for helix-like supramolecular structures. In this work, a method for chirality quantification based on the calculation of scalar triple products of dipole moments is suggested. As a model structure, self-assembled nanotubes of diphenylalanine (FF) made of L- and D-enantiomers were considered. The dipole moments of FF molecules were calculated using semi-empirical quantum-chemical method PM3 and the Amber force field method. The obtained results do not depend on the used simulation and calculation method, and show that the D-FF nanotubes are twisted tighter than L-FF. Moreover, the type of chirality of the helix-like nanotube is opposite to that of the initial individual molecule that is in line with the chirality alternation rule general for different levels of hierarchical organization of molecular systems. The proposed method can be applied to study other helix-like supramolecular structures.
- Open Access
Protein Helical Structures: Defining Handedness and Localization Features
The quantitative evaluation of the chirality of macromolecule structures remains one of the exciting issues in biophysics. In this paper, we propose methods for quantitative analysis of the chirality of protein helical and superhelical structures. The analysis of the chirality sign of the protein helical structures (α-helices and 310-helices) is based on determining the mixed product of every three consecutive vectors between neighboring reference points—α-carbons atoms. The method for evaluating the chirality sign of coiled-coil structures is based on determining the direction and value of the angle between the coiled-coil axis and the α-helices axes. The chirality sign of the coiled coil is calculated by averaging the value of the cosine of the corresponding angle for all helices forming the superhelix. Chirality maps of helical and superhelical protein structures are presented. Furthermore, we propose an analysis of the distributions of helical and superhelical structures in polypeptide chains of several protein classes. The features common to all studied classes and typical for each protein class are revealed. The data obtained, in all likelihood, can reflect considerations about molecular machines as chiral formations.
Open AccessProtein Helical Structures: Defining Handedness and Localization Features
The quantitative evaluation of the chirality of macromolecule structures remains one of the exciting issues in biophysics. In this paper, we propose methods for quantitative analysis of the chirality of protein helical and superhelical structures. The analysis of the chirality sign of the protein helical structures (α-helices and 310-helices) is based on determining the mixed product of every three consecutive vectors between neighboring reference points—α-carbons atoms. The method for evaluating the chirality sign of coiled-coil structures is based on determining the direction and value of the angle between the coiled-coil axis and the α-helices axes. The chirality sign of the coiled coil is calculated by averaging the value of the cosine of the corresponding angle for all helices forming the superhelix. Chirality maps of helical and superhelical protein structures are presented. Furthermore, we propose an analysis of the distributions of helical and superhelical structures in polypeptide chains of several protein classes. The features common to all studied classes and typical for each protein class are revealed. The data obtained, in all likelihood, can reflect considerations about molecular machines as chiral formations.