Computational investigation of cancer-associated molecular mechanism in Aurora A (S155R) mutation

2D-QSAR, molecular docking and MD simulation based virtual screening of the herbal molecules against Alzheimer's disorder: an approach to predict CNS activity

Acetylcholinesterase (AChE) is one of the key enzyme targets that have been used clinically for the management of Alzheimer's Disorder (AD). Numerous reports in the literature predict and demonstrate in-vitro, and in-silico anticholinergic activity of herbal molecules, however, majority of them failed to find clinical application. To address these issues, we developed a 2D-QSAR model that could efficiently predict the AChE inhibitory activity of herbal molecules along with predicting their potential to cross the blood-brain-barrier (BBB) to exert their beneficial effects during AD. Virtual screening of the herbal molecules was performed and amentoflavone, asiaticoside, astaxanthin, bahouside, biapigenin, glycyrrhizin, hyperforin, hypericin, and tocopherol were predicted as the most promising herbal molecules for inhibiting AChE. Results were validated through molecular docking, atomistic molecular dynamics simulations and Molecular mechanics-Poisson Boltzmann surface area (MM-PBSA) studies against human AChE (PDB ID: 4EY7). To determine whether or not these molecules can cross BBB to inhibit AChE within the central nervous system (CNS) for being beneficial for the management of AD, we determined a CNS Multi-parameter Optimization (MPO) score, which was found in the range of 1 to 3.76. Overall, the best results were observed for amentoflavone and our results demonstrated a PIC50 value of 7.377 nM, molecular docking score of -11.5 kcal/mol, and CNS MPO score of 3.76. In conclusion, we successfully developed a reliable and efficient 2D-QSAR model and predicted amentoflavone to be the most promising molecule that could inhibit human AChE enzyme within the CNS and could prove beneficial for the management of AD.Communicated by Ramaswamy H. Sarma.

Bioinformatics analysis of markers based on m6 A related to prognosis combined with immune invasion of renal clear cell carcinoma

The incidence rate of renal cell carcinoma (RCC) is about 3% of all adult cancers. Of these, the Kidney clear cell renal cell carcinoma (KIRC) is the most common type, accounting for about 70%-75% of RCC. KIRC is difficult to be detected in time clinically. KIRC still has no effective treatment at this stage. We combined high-throughput bioinformatics analysis to obtained the structural sequence transcriptome data, relevant clinical information, and m⁶ A gene map of KIRC patients from genomics TCGA database. Pearson's correlation analysis was used to explore m⁶ A related gene long noncoding RNAs (lncRNAs), and then univariate Cox regression analysis was performed to screen the prognostic role of KIRC patients. Lasso-Cox regression was performed to establish the lncRNAs risk model associated with m⁶ A.LINC02154 and AC016773.2, Z98200.2, AL161782.1, EMX2OS, AC021483.2, CD27-AS1, AC006213.3 were iidentif. Compared with the low-risk group, the overall survival of patients in the high-risk group was significantly worse. Analyzing whether there are differences in immune cells between high-risk and low-risk subgroups. There were CD4 memory resting, Monocytes, Macrophages M1, Dendritic cells activated, Mast cells resting, which had higher infiltrations in the low-risk group. We performed Go enrichment analysis, Kyoto Encyclopedia of Genes and Genomes enrichment analysis and gene set enrichment analysis enrichment analysis. Overall, our results suggest that the component of m6A-related lncRNAs in the prognostic signal may be a key mediator in the immune microenvironment of KIRC, which represents a promising therapeutic effect.

Molecular Dynamics Simulation and Essential Dynamics of Deleterious Proline 12 Alanine Single-Nucleotide Polymorphism in PPARγ2 Associated with Type 2 Diabetes, Cardiovascular Disease, and Nonalcoholic Fatty Liver Disease

Background. Peroxisome proliferator-activated receptor-γ (PPARγ) gene is located at 3p25 position. PPARγ functions as the master regulator of glucose homeostasis and lipoprotein metabolism, and recent studies have reported that it is involved in various metabolic diseases such as diabetes mellitus, hyperlipidemia, coronary artery disease (CAD), and nonalcoholic fatty liver disease (NAFLD). PPARγ1 and PPARγ2 are necessary for the development of adipose tissue and insulin sensitivity regulation. But PPARγ2 is the isoform that was controlled in response to nutrient intake and obesity. Methodology. In this study, we used computational techniques to show the impact of Pro12Ala polymorphism on PPARγ2. The 3-D structure of PPARγ2 was modeled using I-TASSER server. The modeled structure was validated with the ZLab server, and the mutation was created with SPDB viewer. Stability prediction tools were used. Molecular dynamics simulation (MDS) was used to understand the structural and functional behavior of the wild type and mutant. Essential dynamics was also applied. Results and Conclusions. Stability prediction tools were showed that this mutation has a destabilizing effect on the PPARγ2 structure. The RMSD, RMSF, Rg, SASA, and DSSP were in line with H-bond results that showed less flexibility in the mutant structure. Essential dynamics was used to verify MDS results. Pro12Ala polymorphism leads to rigidity of the PPARγ2 protein and might disturb the conformational changes and interactions of PPARγ2 and results in type 2 diabetes mellitus (T2DM), CAD, and NAFLD. This study can help scientists to develop a drug therapy against these diseases.

Computational Analysis of Gly482Ser Single-Nucleotide Polymorphism in PPARGC1A Gene Associated with CAD, NAFLD, T2DM, Obesity, Hypertension, and Metabolic Diseases

Peroxisome proliferator-activated receptor-gamma coactivator 1-alpha (PPARGC1A) regulates the expression of energy metabolism's genes and mitochondrial biogenesis. The essential roles of PPARGC1A encouraged the researchers to assess the relation between metabolism-related diseases and its variants. To study Gly482Ser (+1564G/A) single-nucleotide polymorphism (SNP) after PPARGC1A modeling, we substitute Gly482 for Ser482. Stability prediction tools showed that this substitution decreases the stability of PPARGC1A or has a destabilizing effect on this protein. We then utilized molecular dynamics simulation of both the Gly482Ser variant and wild type of the PPARGC1A protein to analyze the structural changes and to reveal the conformational flexibility of the PPARGC1A protein. We observed loss flexibility in the RMSD plot of the Gly482Ser variant, which was further supported by a decrease in the SASA value in the Gly482Ser variant structure of PPARGC1A and an increase of H-bond with the increase of β-sheet and coil and decrease of turn in the DSSP plot of the Gly482Ser variant. Such alterations may significantly impact the structural conformation of the PPARGC1A protein, and it might also affect its function. It showed that the Gly482Ser variant affects the PPARGC1A structure and makes the backbone less flexible to move. In general, molecular dynamics simulation (MDS) showed more flexibility in the native PPARGC1A structure. Essential dynamics (ED) also revealed that the range of eigenvectors in the conformational space has lower extension of motion in the Gly482Ser variant compared with WT. The Gly482Ser variant also disrupts PPARGC1A interaction. Due to this single-nucleotide polymorphism in PPARGC1A, it became more rigid and might disarray the structural conformation and catalytic function of the protein and might also induce type 2 diabetes mellitus (T2DM), coronary artery disease (CAD), and nonalcoholic fatty liver disease (NAFLD). The results obtained from this study will assist wet lab research in expanding potent treatment on T2DM.

Polymorphisms at site 469 of B-RAF protein associated with skin melanoma may be correlated with dabrafenib resistance: An in silico study

Melanoma is a type of skin cancer. Numerous genes and their proteins are strongly associated with melanoma susceptibility. This study aims to use an in silico method to identify genetic variants in the melanoma susceptibility gene. The COSMIC database was queried for genes and cross-referenced with three environment-gene interaction databases (EGP, SeattleSNPs and CTD) to identify shared genes. The majority of approved skin melanoma drugs were found to act on the protein serine/threonine-protein kinase (B-RAF) encoded by the BRAF gene, which was also present in all three referenced databases. Comprehensive computational analysis was performed to predict deleterious genetic variants associated with skin melanoma, and the nsSNPs G469V and G469E were prioritized based on their predicted deleterious effects. Molecular dynamic simulation analysis of the B-RAF protein mutants G469V and G469E reveals that variations in the amino acid conformation at the drug binding site result in inconsistency in drug interaction. Additionally, this analysis showed that the G469V and G469E mutants have lower binding energy for dabrafenib than the wild type. The population with the highest frequency of each deleterious and pathogenic variant has been determined. The study's findings would support the development of more effective treatment strategies for skin melanoma. Communicated by Ramaswamy H. Sarma.

Gain of native conformation of Aurora A S155R mutant by small molecules

Aurora A is a mitotic serine/threonine kinase protein that is a proposed target of the first-line anticancer drug design. It has been found to be overexpressed in many human cancer cells, including hematological, breast, and colorectal. Here, we focus on a particular somatic mutant S155R of Aurora kinase A protein, whose activity decreases because of loss of interaction with a TPX2 protein that results in ectopic expression of the Aurora kinase A protein, which contributes chromosome instability, centrosome amplification, and oncogenic transformation. The primary target of this study is to select a drug molecule whose binding results in gaining S155R mutant interaction with TPX2. The computational methodology applied in this study involves mapping of hotspots (for uncompetitive binding), virtual screening, protein-ligand docking, postdocking optimization, and protein-protein docking approach. In this study, we screen and validate ZINC968264, which acts as a potential molecule that can improve the loss of function occurred because of mutation (S155R) in Aurora A. Our approaches pave a suitable path to design a potential drug against physiological condition manifested because of S155R mutant in Aurora A.

Essential dynamics analysis captures the concerted motion of the integrin-binding site in jerdostatin, an RTS disintegrin

Disintegrins, small molecular weight proteins contained in the venom of vipers and rattlesnakes, are high-affinity and selectivity integrin antagonists. Disintegrins inhibitory epitope mainly consists in a tripeptide sequence localized in a mobile loop protruding from the protein core. RTS and/or KTS tripeptide characterizes the most recently discovered group of disintegrins that selectively block α1β1 integrin receptor. A NMR study dedicated to structure and dynamics properties of jerdostatin, an RTS disintegrin, demonstrated that the substitution of the native RTS with KTS motif impaired flexibility and inhibitory activity of the molecule. Here we add atomic details to the experimental profiles of jerdostatin and its R24K mutant by analyzing the dynamics behavior of the molecules through computational methods. For jerdostatin wild type, molecular dynamics simulations and essential dynamics analyses showed that Y31 residue acts as hinge element in the concerted motions involving the active loop and the C-terminal tail. R24 side chain ability to engage both cation-π and H-bond interactions with Y31 residue was found crucial for that breathing mechanism. Less significant loop-tail concerted motions were observed for the R24K mutant. The description at atomic resolution of jerdostatin dynamics is useful for decoding the influence of specific residues on disintegrin functional properties.

Ubiquitin-Mediated Degradation of Aurora Kinases

The Aurora kinases are essential regulators of mitosis in eukaryotes. In somatic cell divisions of higher eukaryotes, the paralogs Aurora kinase A (AurA) and Aurora kinase B (AurB) play non-overlapping roles that depend on their distinct spatiotemporal activities. These mitotic roles of Aurora kinases depend on their interactions with different partners that direct them to different mitotic destinations and different substrates: AurB is a component of the chromosome passenger complex that orchestrates the tasks of chromosome segregation and cytokinesis, while AurA has many known binding partners and mitotic roles, including a well-characterized interaction with TPX2 that mediates its role in mitotic spindle assembly. Beyond the spatial control conferred by different binding partners, Aurora kinases are subject to temporal control of their activation and inactivation. Ubiquitin-mediated proteolysis is a critical route to irreversible inactivation of these kinases, which must occur for ordered transition from mitosis back to interphase. Both AurA and AurB undergo targeted proteolysis after anaphase onset as substrates of the anaphase-promoting complex/cyclosome (APC/C) ubiquitin ligase, even while they continue to regulate steps during mitotic exit. Temporal control of Aurora kinase destruction ensures that AurB remains active at the midbody during cytokinesis long after AurA activity has been largely eliminated from the cell. Differential destruction of Aurora kinases is achieved despite the fact that they are targeted at the same time and by the same ubiquitin ligase, making these substrates an interesting case study for investigating molecular determinants of ubiquitin-mediated proteolysis in higher eukaryotes. The prevalence of Aurora overexpression in cancers and their potential as therapeutic targets add importance to the task of understanding the molecular determinants of Aurora kinase stability. Here, we review what is known about ubiquitin-mediated targeting of these critical mitotic regulators and discuss the different factors that contribute to proteolytic control of Aurora kinase activity in the cell.

Computational analyses and prediction of guanylin deleterious SNPs

Human guanylin, coded by the GUCA2A gene, is a member of a peptide family that activates intestinal membrane guanylate cyclase, regulating electrolyte and water transport in intestinal and renal epithelia. Deregulation of guanylin peptide activity has been associated with colon adenocarcinoma, adenoma and intestinal polyps. Besides, it is known that mutations on guanylin receptors could be involved in meconium ileus. However, there are no previous works regarding the alterations driven by single nucleotide polymorphisms in guanylin peptides. A comprehensive in silico analysis of missense SNPs present in the GUCA2A gene was performed taking into account 16 prediction tools in order to select the deleterious variations for further evaluation by molecular dynamics simulations (50 ns). Molecular dynamics data suggest that the three out of five variants (Cys104Arg, Cys112Ser and Cys115Tyr) have undergone structural modifications in terms of flexibility, volume and/or solvation. In addition, two nonsense SNPs were identified, both preventing the formation of disulfide bonds and resulting in the synthesis of truncated proteins. In summary the structural analysis of missense SNPs is important to decrease the number of potential mutations to be in vitro evaluated for associating them with some genetic diseases. In addition, data reported here could lead to a better understanding of structural and functional aspects of guanylin peptides.

Use of long term molecular dynamics simulation in predicting cancer associated SNPs

Computational prediction of cancer associated SNPs from the large pool of SNP dataset is now being used as a tool for detecting the probable oncogenes, which are further examined in the wet lab experiments. The lack in prediction accuracy has been a major hurdle in relying on the computational results obtained by implementing multiple tools, platforms and algorithms for cancer associated SNP prediction. Our result obtained from the initial computational compilations suggests the strong chance of Aurora-A G325W mutation (rs11539196) to cause hepatocellular carcinoma. The implementation of molecular dynamics simulation (MDS) approaches has significantly aided in raising the prediction accuracy of these results, but measuring the difference in the convergence time of mutant protein structures has been a challenging task while setting the simulation timescale. The convergence time of most of the protein structures may vary from 10 ns to 100 ns or more, depending upon its size. Thus, in this work we have implemented 200 ns of MDS to aid the final results obtained from computational SNP prediction technique. The MDS results have significantly explained the atomic alteration related with the mutant protein and are useful in elaborating the change in structural conformations coupled with the computationally predicted cancer associated mutation. With further advancements in the computational techniques, it will become much easier to predict such mutations with higher accuracy level.

AKT kinase pathway: a leading target in cancer research

AKT1, a serine/threonine-protein kinase also known as AKT kinase, is involved in the regulation of various signalling downstream pathways including metabolism, cell proliferation, survival, growth, and angiogenesis. The AKT kinases pathway stands among the most important components of cell proliferation mechanism. Several approaches have been implemented to design an efficient drug molecule to target AKT kinases, although the promising results have not been confirmed. In this paper we have documented the detailed molecular insight of AKT kinase protein and proposed a probable doxorubicin based approach in inhibiting miR-21 based cancer cell proliferation. Moreover, the inhibition of miR-21 activation by raising the FOXO3A concentration seems promising in reducing miR-21 mediated cancer activation in cell. Furthermore, the use of next generation sequencing and computational drug design approaches will greatly assist in designing a potent drug molecule against the associated cancer cases.

Cancer associated E17K mutation causes rapid conformational drift in AKT1 pleckstrin homology (PH) domain

BACKGROUND

AKT1 (v-akt murine thymoma viral oncogene homologue 1) kinase is one of the most frequently activated proliferated and survival pathway of cancer. Recently it has been shown that E17K mutation in the Pleckstrin Homology (PH) domain of AKT1 protein leads to cancer by amplifying the phosphorylation and membrane localization of protein. The mutant has shown resistance to AKT1/2 inhibitor VIII drug molecule. In this study we have demonstrated the detailed structural and molecular consequences associated with the activity regulation of mutant protein.

METHODS

The docking score exhibited significant loss in the interaction affinity to AKT1/2 inhibitor VIII drug molecule. Furthermore, the molecular dynamics simulation studies presented an evidence of rapid conformational drift observed in mutant structure.

RESULTS

There was no stability loss in mutant as compared to native structure and the major cation-π interactions were also shown to be retained. Moreover, the active residues involved in membrane localization of protein exhibited significant rise in NHbonds formation in mutant. The rise in NHbond formation in active residues accounts for the 4-fold increase in the membrane localization potential of protein.

CONCLUSION

The overall result suggested that, although the mutation did not induce any stability loss in structure, the associated pathological consequences might have occurred due to the rapid conformational drifts observed in the mutant AKT1 PH domain.

GENERAL SIGNIFICANCE

The methodology implemented and the results obtained in this work will facilitate in determining the core molecular mechanisms of cancer-associated mutations and in designing their potential drug inhibitors.