Breast cancer is the most common and aggressive malignancy in females with a high prevalence rate of 77.9 million worldwide. Chemotherapy and tyrosine kinase inhibitors have been used to treat invasive and malignant tumors; however, invasive tumors have showed resistance to conventional therapies. ABC transporters play a crucial role in breast cancer due to their chemo-resistance and drug efflux abilities. Additionally, chemo-resistant roles of ABC transporters have been reported in several cancers such as cervical cancer, colon cancer, esophageal squamous cell carcinoma, glioma and HCC. The goal of this study was to identify the tumor suppressor role of miR-21, miR-15 and miR-let-7 to chemo-resistant genes majorly ABCA1, ABCB1 and ABCC1 in breast cancer. TargetScan, miRWalk, and miRDB were employed to predict microRNA-mRNA interactions. MC-Sym and RNAComposer were utilized for the tertiary structure prediction of shortlisted miRNAs and mRNAs. For molecular docking and visualization, HDOCK and PyMOL were employed. The present study identified 10, 7 and 13 interactions between microRNAs (miR-21, miR-15, and miR-let-7) and oncogenes (ABCA1, ABCB1, ABCC1) through miRWalk, miRDB and TargetScan respectively. RNA22 predicted the binding sites of microRNAs such as 22 miR-21, 11 miR-15 and 58 miR-let-7 on ABCA1, ABCB1 and ABCC1, respectively. Out of multiple docked complexes, the top 3 were shortlisted for visualization based on maximum confidence score and least binding affinity. The present study identifies the interactions of two novel (miR-15a-5p and let-7c-5p) microRNAs with ABCA1, ABCB1 and ABCC1 regions due to their maximum interactions. The findings of this research may help in developing miRNA drugs that could target ABC transporters specifically ABCA1, ABCB1 and ABCC1 to inhibit increased drug efflux and chemoresistance in breast cancer.
{"title":"In-silico Elucidation of the Role of ABC-Transporter Genes Expression Regulation by OncomiRs (miR-21, miR-15, and miR-let-7) in Drug Efflux and Chemoresistance in Breast Cancer","authors":"B. Khalaf, A. Suleiman, M. Suwaid","doi":"10.17537/2023.18.128","DOIUrl":"https://doi.org/10.17537/2023.18.128","url":null,"abstract":"\u0000Breast cancer is the most common and aggressive malignancy in females with a high prevalence rate of 77.9 million worldwide. Chemotherapy and tyrosine kinase inhibitors have been used to treat invasive and malignant tumors; however, invasive tumors have showed resistance to conventional therapies. ABC transporters play a crucial role in breast cancer due to their chemo-resistance and drug efflux abilities. Additionally, chemo-resistant roles of ABC transporters have been reported in several cancers such as cervical cancer, colon cancer, esophageal squamous cell carcinoma, glioma and HCC. The goal of this study was to identify the tumor suppressor role of miR-21, miR-15 and miR-let-7 to chemo-resistant genes majorly ABCA1, ABCB1 and ABCC1 in breast cancer. TargetScan, miRWalk, and miRDB were employed to predict microRNA-mRNA interactions. MC-Sym and RNAComposer were utilized for the tertiary structure prediction of shortlisted miRNAs and mRNAs. For molecular docking and visualization, HDOCK and PyMOL were employed. The present study identified 10, 7 and 13 interactions between microRNAs (miR-21, miR-15, and miR-let-7) and oncogenes (ABCA1, ABCB1, ABCC1) through miRWalk, miRDB and TargetScan respectively. RNA22 predicted the binding sites of microRNAs such as 22 miR-21, 11 miR-15 and 58 miR-let-7 on ABCA1, ABCB1 and ABCC1, respectively. Out of multiple docked complexes, the top 3 were shortlisted for visualization based on maximum confidence score and least binding affinity. The present study identifies the interactions of two novel (miR-15a-5p and let-7c-5p) microRNAs with ABCA1, ABCB1 and ABCC1 regions due to their maximum interactions. The findings of this research may help in developing miRNA drugs that could target ABC transporters specifically ABCA1, ABCB1 and ABCC1 to inhibit increased drug efflux and chemoresistance in breast cancer.\u0000","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"76 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90488388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The extracellular matrix (ECM) is best described as a dynamic three-dimensional mesh of various macromolecules. These include proteoglycans (e.g., perlecan andagrin), non-proteoglycan polysaccharides (e.g., hyaluronan), and fibrous proteins (e.g., collagen, elastin, fibronectin, and laminin). ECM proteins are involved in various biological functions and their functionality is largely governed by interaction with other ECM proteins as well as trans-membrane receptors including integrins, proteoglycans such assyndecan, other glycoproteins, and members of the immunoglobulin superfamily. In the present work, a machine learning approach is developed using sequence and evolutionary features for predicting ECM protein-receptor interactions. Two different feature vector representations, namely fusion of feature vectors and average of feature vectors are used within corporation of the best representation employing feature selection. The current results show that the feature vector representation is an important aspect of ECM protein interaction prediction, and that the average of feature vectors performed better than the fusion of feature vectors. The best prediction model with boosted random forest resulted in 72.6 % overall accuracy, 74.4 % sensitivity and 70.7 % specificity with the 200 best features obtained using the ReliefF feature selection algorithm. Further, a comparative analysis was performed for negative sample subset selection using three sampling methods, namely random sampling, k-Means sampling, and Uniform sampling. k-Means based representative sampling resulted in enhanced accuracy (75.5 % accuracy with 80.8 % sensitivity, 68.1 % specificity and 0.801 AUC) for the prediction of ECM protein-receptor interactions in comparison to the other sampling methods. On comparison with other three state of the art protein-protein interaction predictors, it is observed that the latter displayed low sensitivity but higher specificity. The current work presents the first machine learning based prediction model specifically developed for ECM protein-receptor interactions.
{"title":"Exploiting ensemble learning and negative sample space for predicting extracellular matrix receptor interactions","authors":"A. Nath, Sudama Rathore, Pangambam Sendash Singh","doi":"10.17537/2023.18.113","DOIUrl":"https://doi.org/10.17537/2023.18.113","url":null,"abstract":"\u0000The extracellular matrix (ECM) is best described as a dynamic three-dimensional mesh of various macromolecules. These include proteoglycans (e.g., perlecan andagrin), non-proteoglycan polysaccharides (e.g., hyaluronan), and fibrous proteins (e.g., collagen, elastin, fibronectin, and laminin). ECM proteins are involved in various biological functions and their functionality is largely governed by interaction with other ECM proteins as well as trans-membrane receptors including integrins, proteoglycans such assyndecan, other glycoproteins, and members of the immunoglobulin superfamily. In the present work, a machine learning approach is developed using sequence and evolutionary features for predicting ECM protein-receptor interactions. Two different feature vector representations, namely fusion of feature vectors and average of feature vectors are used within corporation of the best representation employing feature selection. The current results show that the feature vector representation is an important aspect of ECM protein interaction prediction, and that the average of feature vectors performed better than the fusion of feature vectors. The best prediction model with boosted random forest resulted in 72.6 % overall accuracy, 74.4 % sensitivity and 70.7 % specificity with the 200 best features obtained using the ReliefF feature selection algorithm. Further, a comparative analysis was performed for negative sample subset selection using three sampling methods, namely random sampling, k-Means sampling, and Uniform sampling. k-Means based representative sampling resulted in enhanced accuracy (75.5 % accuracy with 80.8 % sensitivity, 68.1 % specificity and 0.801 AUC) for the prediction of ECM protein-receptor interactions in comparison to the other sampling methods. On comparison with other three state of the art protein-protein interaction predictors, it is observed that the latter displayed low sensitivity but higher specificity. The current work presents the first machine learning based prediction model specifically developed for ECM protein-receptor interactions.\u0000","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82996253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
V. Fedorov, E. G. Kholina, M. Bulatov, I. Kovalenko
Molecular dynamics models of tubulin tetramers in complex with the anticancer drug taxol were created based on high-resolution spatial structures (PDB ID 3J6G). We tested performance of various computational architectures in molecular dynamics calculations of tubulin tetramers. We revealed the optimal computer architecture and carried out three 1 μs molecular dynamic trajectories of taxol-bound tubulin tetramer. We analyzed the conformational flexibility of tubulin tetramers in a complex with taxol, calculated the Euler angles for intra- and inter-dimer interfaces of the protofilament, as well as the degree and direction of protofilament bending. The stiffness of protofilaments was studied using the energy equipartition theorem. The results allowed us to conclude that taxol binding reduces stiffness at both the inter- and intra-dimer interfaces, which may facilitate the process of microtubule assembly.
基于高分辨率空间结构(PDB ID 3J6G)建立了微管蛋白四聚体与抗癌药物紫杉醇复合物的分子动力学模型。我们测试了各种计算架构在微管蛋白四聚体分子动力学计算中的性能。我们设计了最优的计算机结构，并对紫杉醇结合的微管蛋白四聚体进行了3个1 μs的分子动力学轨迹。我们分析了微管蛋白四聚体在紫杉醇配合物中的构象柔韧性，计算了原丝内和间二聚体界面的欧拉角，以及原丝弯曲的程度和方向。利用能量均分定理研究了原丝的刚度。结果表明，紫杉醇的结合降低了二聚体之间和内部界面的刚度，这可能有助于微管的组装过程。
{"title":"Design of a Molecular Dynamics Model for High-Performance Computing of Conformational Changes in Microtubule Protofilaments Associated with the Anticancer Drug Taxol","authors":"V. Fedorov, E. G. Kholina, M. Bulatov, I. Kovalenko","doi":"10.17537/2023.18.105","DOIUrl":"https://doi.org/10.17537/2023.18.105","url":null,"abstract":"\u0000Molecular dynamics models of tubulin tetramers in complex with the anticancer drug taxol were created based on high-resolution spatial structures (PDB ID 3J6G). We tested performance of various computational architectures in molecular dynamics calculations of tubulin tetramers. We revealed the optimal computer architecture and carried out three 1 μs molecular dynamic trajectories of taxol-bound tubulin tetramer. We analyzed the conformational flexibility of tubulin tetramers in a complex with taxol, calculated the Euler angles for intra- and inter-dimer interfaces of the protofilament, as well as the degree and direction of protofilament bending. The stiffness of protofilaments was studied using the energy equipartition theorem. The results allowed us to conclude that taxol binding reduces stiffness at both the inter- and intra-dimer interfaces, which may facilitate the process of microtubule assembly.\u0000","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"107 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76845788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
”Quorum sensing” as a special kind of communication in bacterial populations can be analyzed by means of methods and techniques of mathematical modeling and computer simulation. In the present study, a modification of a deterministic mathematical model of bacterial quorum sensing is proposed, taking into account the law of multiphase population dynamics. The mathematical model is formalized by an initial-boundary value problem for a system of semilinear reaction-diffusion partial differential equations. The equations include generation terms in view of changes in the biomass density. The model describes space-time dynamics of concentrations of special substances (signaling agents and Lactonase enzymes) that characterize the quorum sensing in Gram-negative bacteria. The problem is solved by means of the finite element method using the COMSOL Multiphysics platform. Computational experiments are performed to estimate concentrations of key substances characterizing quorum sensing for Pseudomonas putida bacterial strains in an expanded range of population dynamics.
{"title":"Modeling of Bacterial Communication in the Extended Range of Population Dynamics","authors":"Y. Shuai, A. Maslovskaya, C. Kuttler","doi":"10.17537/2023.18.89","DOIUrl":"https://doi.org/10.17537/2023.18.89","url":null,"abstract":"\u0000”Quorum sensing” as a special kind of communication in bacterial populations can be analyzed by means of methods and techniques of mathematical modeling and computer simulation. In the present study, a modification of a deterministic mathematical model of bacterial quorum sensing is proposed, taking into account the law of multiphase population dynamics. The mathematical model is formalized by an initial-boundary value problem for a system of semilinear reaction-diffusion partial differential equations. The equations include generation terms in view of changes in the biomass density. The model describes space-time dynamics of concentrations of special substances (signaling agents and Lactonase enzymes) that characterize the quorum sensing in Gram-negative bacteria. The problem is solved by means of the finite element method using the COMSOL Multiphysics platform. Computational experiments are performed to estimate concentrations of key substances characterizing quorum sensing for Pseudomonas putida bacterial strains in an expanded range of population dynamics.\u0000","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87329460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Angiogenesis, the formation of new blood vessels, is a critical and rate-limiting tumor growth step controlled by pro-angiogenic factors and specific inhibitors. Tumor angiogenesis is essential for cancer progression and metastasis. Platelet growth factors (PDGF) and their receptors (PDGFR) are associated with tumor angiogenesis through overexpression of PDGF. Inhibition of PDGF and its signaling pathway is a new approach to the discovery of anticancer therapeutic agents. The present study focuses on the PDGF-C protein in the identification of novel anti-angiogenic compounds. MODELLER 9.10 software allows users to create and refine a 3D homology model of the PDGF-C protein (345 a.a. length). Secondary structure analysis of the 3D energy model reveals 16 β sheets held together by four cation–π and one π–σ interactions, and three salt bridges. The quality of the model is assessed using the Ramachandran plot (90 percent amino acids in the favorable region) and the ProSA server (Z-score = –2.28). Active site residues are identified using Castp, QSite search engine, site map, and protein docking of the protein to its receptor. In addition, virtual screening is performed at the active site using the Glide module of the Schrodinger Suite. Glide score, glide energy and ADME are being measured to discover new benefits of pyrazolone and pyrrolidine-2,3-dione scaffolds as potent PDGF-C antagonists for anti-angiogenic cancer chemotherapy drugs.
{"title":"Cancer Therapeutics: Structure-Based Drug Design of Inhibitors for a Novel Angiogenic Growth Factor","authors":"Navaneetha Nambigari","doi":"10.17537/2023.18.72","DOIUrl":"https://doi.org/10.17537/2023.18.72","url":null,"abstract":"\u0000Angiogenesis, the formation of new blood vessels, is a critical and rate-limiting tumor growth step controlled by pro-angiogenic factors and specific inhibitors. Tumor angiogenesis is essential for cancer progression and metastasis. Platelet growth factors (PDGF) and their receptors (PDGFR) are associated with tumor angiogenesis through overexpression of PDGF. Inhibition of PDGF and its signaling pathway is a new approach to the discovery of anticancer therapeutic agents. The present study focuses on the PDGF-C protein in the identification of novel anti-angiogenic compounds. MODELLER 9.10 software allows users to create and refine a 3D homology model of the PDGF-C protein (345 a.a. length). Secondary structure analysis of the 3D energy model reveals 16 β sheets held together by four cation–π and one π–σ interactions, and three salt bridges. The quality of the model is assessed using the Ramachandran plot (90 percent amino acids in the favorable region) and the ProSA server (Z-score = –2.28). Active site residues are identified using Castp, QSite search engine, site map, and protein docking of the protein to its receptor. In addition, virtual screening is performed at the active site using the Glide module of the Schrodinger Suite. Glide score, glide energy and ADME are being measured to discover new benefits of pyrazolone and pyrrolidine-2,3-dione scaffolds as potent PDGF-C antagonists for anti-angiogenic cancer chemotherapy drugs.\u0000","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"55 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72536403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The results of numerical modelling of the necrotic death of myocardial cells and immune response dynamics in type II ischemic infarction are presented. The initial conditions were consistent with the experimental data. The adopted minimal mathematical model focused on the balance of pro- and anti-inflammatory factors of aseptic inflammation and their influence on the process of cardiomyocyte death. The issue of the formation of nonlinear dynamic structures in the adopted reaction-diffusion system of equations in the absence of convective terms has been examined. It is shown that a stable localization of the solution of the initial-boundary value problem within the spatial region of practically unchanged size is observed in a fairly wide range of parameters of the initial conditions set in the form of bell-shaped finite functions. Qualitative properties of solutions allow biological interpretation. Within the framework of the adopted model, we considered several important examples and, on this basis, described a typical scenario of a heart attack with a favorable outcome. We have studied the most general patterns of the formation of demarcation inflammation near a large necrosis focus in a typical acute infarction scenario, taking into account individual differences in the topology of the coronary vascular network and the topography of the infarction. The adequacy of the results is confirmed by quantitative and qualitative agreement with a fairly wide range of experimental data on the dynamics of infarction in the left ventricle of the mouse heart.
{"title":"Numerical Modelling of Myocardial Infarction. I. Analysis of Spatiotemporal Aspects of the Local Inflammatory Response","authors":"O. F. Voropaeva, Ch. A. Tsgoev","doi":"10.17537/2023.18.49","DOIUrl":"https://doi.org/10.17537/2023.18.49","url":null,"abstract":"\u0000The results of numerical modelling of the necrotic death of myocardial cells and immune response dynamics in type II ischemic infarction are presented. The initial conditions were consistent with the experimental data. The adopted minimal mathematical model focused on the balance of pro- and anti-inflammatory factors of aseptic inflammation and their influence on the process of cardiomyocyte death. The issue of the formation of nonlinear dynamic structures in the adopted reaction-diffusion system of equations in the absence of convective terms has been examined. It is shown that a stable localization of the solution of the initial-boundary value problem within the spatial region of practically unchanged size is observed in a fairly wide range of parameters of the initial conditions set in the form of bell-shaped finite functions. \u0000\u0000Qualitative properties of solutions allow biological interpretation. Within the framework of the adopted model, we considered several important examples and, on this basis, described a typical scenario of a heart attack with a favorable outcome. We have studied the most general patterns of the formation of demarcation inflammation near a large necrosis focus in a typical acute infarction scenario, taking into account individual differences in the topology of the coronary vascular network and the topography of the infarction. The adequacy of the results is confirmed by quantitative and qualitative agreement with a fairly wide range of experimental data on the dynamics of infarction in the left ventricle of the mouse heart.\u0000\u0000\u0000","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81024711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The double proton transfer reaction paths in AT and CG base pairs of DNA molecule are calculated in the Complete Active Space Self-Consistent Field method and compared with the same paths in Density Functional Theory with B3LYP approximation approach. We found that an essential increase of an activation energy, which significantly reduces the probability of spontaneous mutations in DNA via double proton transfer. There exist two transition points on the singlet potential energy surface divided by a flat region for GC base pair. The applicability of various quantum-chemical methods for description of double proton transfer reactions was discussed.
{"title":"Proton Reaction Path in Base Pairs of DNA Molecule According to the Complete Active Space Self-Consistent Field Method","authors":"K. Simon, A. V. Tulub","doi":"10.17537/2023.18.33","DOIUrl":"https://doi.org/10.17537/2023.18.33","url":null,"abstract":"\u0000The double proton transfer reaction paths in AT and CG base pairs of DNA molecule are calculated in the Complete Active Space Self-Consistent Field method and compared with the same paths in Density Functional Theory with B3LYP approximation approach. We found that an essential increase of an activation energy, which significantly reduces the probability of spontaneous mutations in DNA via double proton transfer. There exist two transition points on the singlet potential energy surface divided by a flat region for GC base pair. The applicability of various quantum-chemical methods for description of double proton transfer reactions was discussed.\u0000","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90537192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Andrianov, K. V. Furs, A. V. Gonchar, L.H. Aslanyan, A. Tuzikov
A virtual screening of the molecular library of biologically active compounds was carried out to identify potential inhibitors of SARS-CoV-2 main protease (Mpro) which plays an important role in the process of virus replication. Using molecular docking and molecular dynamics, the binding energy of these compounds to the catalytic site of the enzyme was assessed, resulting in six molecules that exhibited high chemical affinity for SARS-CoV-2 Mpro. This is evidenced by the low values of the binding free energy of the ligand/Mpro complexes comparable with those predicted for the potent non-covalent SARS-CoV-2 Mpro inhibitor using the identical computational protocol. Based on the data obtained, it was concluded that the identified compounds have a good therapeutic potential for inhibiting the catalytic activity of the enzyme and form promising basic structures for the development of new effective drugs against COVID-19.
{"title":"Application of Virtual Screening and Molecular Modeling Technologies to Identify Potential SARS-CoV-2 Main Protease Inhibitors","authors":"A. Andrianov, K. V. Furs, A. V. Gonchar, L.H. Aslanyan, A. Tuzikov","doi":"10.17537/2023.18.15","DOIUrl":"https://doi.org/10.17537/2023.18.15","url":null,"abstract":"\u0000A virtual screening of the molecular library of biologically active compounds was carried out to identify potential inhibitors of SARS-CoV-2 main protease (Mpro) which plays an important role in the process of virus replication. Using molecular docking and molecular dynamics, the binding energy of these compounds to the catalytic site of the enzyme was assessed, resulting in six molecules that exhibited high chemical affinity for SARS-CoV-2 Mpro. This is evidenced by the low values of the binding free energy of the ligand/Mpro complexes comparable with those predicted for the potent non-covalent SARS-CoV-2 Mpro inhibitor using the identical computational protocol. Based on the data obtained, it was concluded that the identified compounds have a good therapeutic potential for inhibiting the catalytic activity of the enzyme and form promising basic structures for the development of new effective drugs against COVID-19.\u0000","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"1732 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78282523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Bessonova, A. A. Rybina, D. Marakulina, A. Kaznadzey, M. Gelfand, O. Ozoline, M. Tutukina
Until recently, no examples of the in-frame translation of several proteins from one gene in bacteria were known. The first one was the VirF transcription factor controlling pathogenicity development in Shigella flexneri and CobB sirtuin in Salmonella enterica. Recently, we observed synthesis of shortened protein products for YjjM (LgoR) and LeuO functioning as transcription factors in Escherichia coli. To determine the evolutionary factors that could lead to the appearance of alternative start codons, we performed phylogenetic analysis and showed that each protein had a unique phylogenetic history, and additional starting methionines appeared only in Enterobacteria. Using the Western-blot analysis of proteins synthesized from the Escherichia coli K-12 MG1655 chromosome with the his-tagged leuO gene two shortened variants of LeuO, corresponding to translation starting from Met34 and Met48 were detected. Synthesis of all three LeuO forms was inhibited in the absence of the yjjM gene, suggesting interplay of these transcription factors. The YjjM recognition motif revealed from the ChIP-seq data appeared to be very similar to that of LeuO, known previously. Taking this into account, we compared ChIP and SELEX data for LeuO and YjjM and found six common targets. At least five of them were confirmed to be under control of these regulators by qRT-PCR. Interestingly, the effects were more prominent during anaerobic growth at 37°C simulating conditions inside a host organism. Two genes, coding for the enterobactin transporter FepA, and a repressor of genes responsible for flagellar biosynthesis and virulence YjjQ, were repressed, mainly by YjjM, only in these conditions, while tsr coding for the chemotaxis receptor protein was more repressed under lower temperature and higher aeration.
{"title":"Phylogeny and cross-regulation of the YjjM and LeuO transcription factors translated as multiple protein forms from one gene in Escherichia coli","authors":"T. Bessonova, A. A. Rybina, D. Marakulina, A. Kaznadzey, M. Gelfand, O. Ozoline, M. Tutukina","doi":"10.17537/2023.18.1","DOIUrl":"https://doi.org/10.17537/2023.18.1","url":null,"abstract":"\u0000Until recently, no examples of the in-frame translation of several proteins from one gene in bacteria were known. The first one was the VirF transcription factor controlling pathogenicity development in Shigella flexneri and CobB sirtuin in Salmonella enterica. Recently, we observed synthesis of shortened protein products for YjjM (LgoR) and LeuO functioning as transcription factors in Escherichia coli. To determine the evolutionary factors that could lead to the appearance of alternative start codons, we performed phylogenetic analysis and showed that each protein had a unique phylogenetic history, and additional starting methionines appeared only in Enterobacteria. Using the Western-blot analysis of proteins synthesized from the Escherichia coli K-12 MG1655 chromosome with the his-tagged leuO gene two shortened variants of LeuO, corresponding to translation starting from Met34 and Met48 were detected. Synthesis of all three LeuO forms was inhibited in the absence of the yjjM gene, suggesting interplay of these transcription factors. The YjjM recognition motif revealed from the ChIP-seq data appeared to be very similar to that of LeuO, known previously. Taking this into account, we compared ChIP and SELEX data for LeuO and YjjM and found six common targets. At least five of them were confirmed to be under control of these regulators by qRT-PCR. Interestingly, the effects were more prominent during anaerobic growth at 37°C simulating conditions inside a host organism. Two genes, coding for the enterobactin transporter FepA, and a repressor of genes responsible for flagellar biosynthesis and virulence YjjQ, were repressed, mainly by YjjM, only in these conditions, while tsr coding for the chemotaxis receptor protein was more repressed under lower temperature and higher aeration.\u0000","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84862521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper proposes a two-component discrete-time model of the plankton community, taking into account features of the development and interaction of phytoplankton and zooplankton. To describe the interaction between these species and to compare the system dynamics, we use the following set of response functions: type II and III Holling function and the Arditi–Ginzburg response function, each of which describes trophic interactions between phytoplankton and zooplankton. An analytical and numerical study of the model proposed is made. The analysis shows that the variation of trophic functions does not change the dynamic behavior of the model fundamentally. The stability loss of nontrivial fixed point corresponding to the coexistence of phytoplankton and zooplankton can occur through a cascade of period-doubling bifurcations and according to the Neimark–Saker scenario, which allows us to observe the appearance of long-period oscillations representing the alternation of peaks and reduction in the number of species as a result of the predator-prey interaction. As well, the model has multistability areas, where a variation in initial conditions with the unchanged values of all model parameters can result in a shift of the current dynamic mode. Each of the models is shown to demonstrate conditional coexistence when a variation of the current community structure can lead to the extinction of the entire community or its part. Considering the characteristics of the species composition, the model with the type II Holling function seems a more suitable for describing the dynamics of the plankton community. Such a system is consistent with the idea that phytoplankton is a fast variable and predator dynamics is slow; thus, long-period fluctuations occur at high phytoplankton growth rates and low zooplankton ones. The model with the Arditi–Ginzburg functional response demonstrates quasi-periodic fluctuations in a narrow parametric aria with a high predator growth rate and low prey growth rate. The quasi-periodic dynamics regions in the model with the Holling type III functional response correspond to the conception of fast and slow variables, however in this case, the stability of the system increases, and the Neimark-Sacker bifurcation occurs even at a higher growth rate of zooplankton.
{"title":"Comparative Dynamics Analysis of Simple Mathematical Models of the Plankton Communities Considering Various Types of Response Function","authors":"G. P. Neverova, O. Zhdanova","doi":"10.17537/2022.17.465","DOIUrl":"https://doi.org/10.17537/2022.17.465","url":null,"abstract":"\u0000The paper proposes a two-component discrete-time model of the plankton community, taking into account features of the development and interaction of phytoplankton and zooplankton. To describe the interaction between these species and to compare the system dynamics, we use the following set of response functions: type II and III Holling function and the Arditi–Ginzburg response function, each of which describes trophic interactions between phytoplankton and zooplankton. An analytical and numerical study of the model proposed is made. The analysis shows that the variation of trophic functions does not change the dynamic behavior of the model fundamentally. The stability loss of nontrivial fixed point corresponding to the coexistence of phytoplankton and zooplankton can occur through a cascade of period-doubling bifurcations and according to the Neimark–Saker scenario, which allows us to observe the appearance of long-period oscillations representing the alternation of peaks and reduction in the number of species as a result of the predator-prey interaction. As well, the model has multistability areas, where a variation in initial conditions with the unchanged values of all model parameters can result in a shift of the current dynamic mode. Each of the models is shown to demonstrate conditional coexistence when a variation of the current community structure can lead to the extinction of the entire community or its part. Considering the characteristics of the species composition, the model with the type II Holling function seems a more suitable for describing the dynamics of the plankton community. Such a system is consistent with the idea that phytoplankton is a fast variable and predator dynamics is slow; thus, long-period fluctuations occur at high phytoplankton growth rates and low zooplankton ones. The model with the Arditi–Ginzburg functional response demonstrates quasi-periodic fluctuations in a narrow parametric aria with a high predator growth rate and low prey growth rate. The quasi-periodic dynamics regions in the model with the Holling type III functional response correspond to the conception of fast and slow variables, however in this case, the stability of the system increases, and the Neimark-Sacker bifurcation occurs even at a higher growth rate of zooplankton.\u0000","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"256 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91323938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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