scholarly journals In SilicoInvestigation of Potential PARP-1 Inhibitors from Traditional Chinese Medicine

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Kuan-Chung Chen ◽  
Mao-Feng Sun ◽  
Calvin Yu-Chian Chen
Keyword(s):  
Docking Simulation ◽  
Binding Domain ◽  
Scoring Functions ◽  
Binding Affinities ◽  
Damage Repair ◽  
Dna Strand ◽  
The Stability ◽  
Dynamics Simulations ◽  
Aurantiamide Acetate ◽  
Parp 1

Poly(ADP-ribose) polymerases (PARPs) are nuclear enzymes which catalyze the poly-ADP-ribosylation involved in gene transcription, DNA damage repair, and cell-death signaling. As PARP-1 protein contains a DNA-binding domain, which can bind to DNA strand breaks and repair the damaged DNA over a low basal level, the inhibitors of poly(ADP-ribose) polymerase 1 (PARP-1) have been indicated as the agents treated for cancer. This study employed the compounds from TCM Database@Taiwan to identify the potential PARP-1 inhibitors from the vast repertoire of TCM compounds. The binding affinities of the potential TCM compounds were also predicted utilized several distinct scoring functions. Molecular dynamics simulations were performed to optimize the result of docking simulation and analyze the stability of interactions between protein and ligand. The top TCM candidates, isopraeroside IV, picrasidine M, and aurantiamide acetate, had higher potent binding affinities than control, A927929. They have stable H-bonds with residues Gly202 and, Ser243 as A927929 and stable H-bonds with residues Asp105, Tyr228, and His248 in the other side of the binding domain, which may strengthen and stabilize ligand inside the binding domain of PARP-1 protein. Hence, we propose isopraeroside IV and aurantiamide acetate as potential lead compounds for further study in drug development process with the PARP-1 protein.

scholarly journals In SilicoInvestigation of Potential Pyruvate Kinase M2 Regulators from Traditional Chinese Medicine against Cancers

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Kuan-Chung Chen ◽  
Kuen-Bao Chen ◽  
Hsin-Yi Chen ◽  
Calvin Yu-Chian Chen
Keyword(s):  
Virtual Screening ◽  
Drug Development ◽  
Pyruvate Kinase ◽  
Md Simulation ◽  
Docking Simulation ◽  
Target Protein ◽  
Binding Affinities ◽  
Pyruvate Kinase M2 ◽  
Lead Compounds ◽  
The Stability

A recent research in cancer research demonstrates that tumor-specific pyruvate kinase M2 (PKM2) plays an important role in chromosome segregation and mitosis progression of tumor cells. To improve the drug development of TCM compounds, we aim to identify potent TCM compounds as lead compounds of PKM2 regulators. PONDR-Fit protocol was utilized to predict the disordered disposition in the binding domain of PKM2 protein before virtual screening as the disordered structure in the protein may cause the side effect and downregulation of the possibility of ligand to bind with target protein. MD simulation was performed to validate the stability of interactions between PKM2 proteins and each ligand after virtual screening. The top TCM compounds, saussureamine C and precatorine, extracted fromLycium chinenseMill. andAbrus precatoriusL., respectively, have higher binding affinities with target protein in docking simulation than control. They have stable H-bonds with residues A:Lys311 and some other residues in both chains of PKM2 protein. Hence, we propose the TCM compounds, saussureamine C and precatorine, as potential candidates as lead compounds for further study in drug development process with the PKM2 protein against cancer.

scholarly journals Potential Drugs Against COVID-19 Revealed by Gene Expression Profile, Molecular Docking and Molecular Dynamic Simulation

2020 ◽  
Author(s):  
Claudia Cava ◽  
Gloria Bertoli ◽  
Isabella Castiglioni
Keyword(s):  
Gene Expression ◽  
Gene Expression Analysis ◽  
Distress Syndrome ◽  
Docking Simulation ◽  
Biological Pathways ◽  
Second Step ◽  
Main Protease ◽  
The Stability ◽  
Dynamics Simulations ◽  
Bioinformatic Approach

Abstract BackgroundSARS-CoV-2 coronavirus, an emerging Betacoronavirus, is the causative agent of the severe acute respiratory distress syndrome outbreak in 2019 (COVID-19). Currently, there are neither specific and selective antiviral drugs for the treatment nor vaccines to prevent contagion. Here we propose a bioinformatic approach in order to test in silico the efficacy of existing drugs for COVID-19. ResultsIn the first step of our study we identified, through a gene expression analysis, several drugs that could act on the biological pathways altered in COVID-19. In the second step, we performed a docking simulation in order to test the properties of the identified drugs to target the 3CL main protease of SARS-CoV-2. The drugs that showed higher binding affinity are bardoxolone (-8.78 kcal/ mol), Irinotecan (-8.40 kcal/mol) and Pyrotinib (-8.40 kcal/mol). Molecular dynamics simulations were carried out on the three selected drugs to validate the stability and interactions of the complexes. Among other promising drugs we found also AZD-8055, Olaparib, Tyrphostin AG 879, Topotecan Hydrochloride, MP-412, S-222611, Allitinib, 7-Ethyl-10-Hydroxy-Camptothecin, and Falnidamol. ConclusionsWe suggested some drugs that could efficient in COVID-19. However further studies are suggested to confirm the affinity of these drugs with 3CL main protease of SARS-CoV-2.

DNA break repair: refined rules of an already complicated game

2005 ◽  
Vol 83 (3) ◽  
pp. 365-373 ◽  
Author(s):  
Melita Vidaković ◽  
Goran Poznanović ◽  
Juergen Bode
Keyword(s):  
Nuclear Architecture ◽  
Strand Break ◽  
End Joining ◽  
Dna Strand Break ◽  
Damage Repair ◽  
Break Repair ◽  
Non Homologous End Joining ◽  
Dna Strand ◽  
The Many ◽  
Parp 1

Of the many types of DNA-damage repair, this review concentrates on the aspects of DNA single- and double-strand break repair. Originally considered to represent separate routes based on distinct enzymatic machineries, it has recently been shown that these pathways converge and are interlinked at a number of points. Poly(ADP-ribose) polymerase-1 (PARP-1) is a central player in this complicated game. We present new data and our view on the mechanisms by which PARP-1 is guided to its respective interaction partners to coordinate or participate in repair or apoptosis.Key words: DNA strand break repair (DSBR), non-homologous end joining (NHEJ), nuclear architecture, nuclear matrix, PARP-1.

The Role of Hydrophobicity in the Stability and pH-Switchability of (RXDX)4 and Coumarin-RXDX Conjugate β-Sheets

2020 ◽  
Author(s):  
Ryan Weber ◽  
Martin McCullagh
Keyword(s):  
Biological Imaging ◽  
Ph Sensing ◽  
Hydrophobic Residue ◽  
Ideal Candidate ◽  
Self Assembling ◽  
Sensing Applications ◽  
Β Sheets ◽  
The Stability ◽  
Dynamics Simulations

<p>pH-switchable, self-assembling materials are of interest in biological imaging and sensing applications. Here we propose that combining the pH-switchability of RXDX (X=Ala, Val, Leu, Ile, Phe) peptides and the optical properties of coumarin creates an ideal candidate for these materials. This suggestion is tested with a thorough set of all-atom molecular dynamics simulations. We first investigate the dependence of pH-switchabiliy on the identity of the hydrophobic residue, X, in the bare (RXDX)<sub>4</sub> systems. Increasing the hydrophobicity stabilizes the fiber which, in turn, reduces the pH-switchabilty of the system. This behavior is found to be somewhat transferable to systems in which a single hydrophobic residue is replaced with a coumarin containing amino acid. In this case, conjugates with X=Ala are found to be unstable and both pHs while conjugates with X=Val, Leu, Ile and Phe are found to form stable β-sheets at least at neutral pH. The (RFDF)<sub>4</sub>-coumarin conjugate is found to have the largest relative entropy value of 0.884 +/- 0.001 between neutral and acidic coumarin ordering distributions. Thus, we posit that coumarin-(RFDF)<sub>4</sub> containing peptide sequences are ideal candidates for pH-sensing bioelectronic materials.</p>

Destabilizing the Structural Integrity of SARS-CoV2 Receptor Proteins by Curcumin Along with Hydroxychloroquine: An Insilco Approach for a Combination Therapy

2020 ◽  
Author(s):  
Akhileshwar Srivastava ◽  
Divya Singh
Keyword(s):  
Binding Energy ◽  
Combination Therapy ◽  
Receptor Binding ◽  
Structural Integrity ◽  
Binding Domain ◽  
Receptor Binding Domain ◽  
Receptor Proteins ◽  
Main Protease ◽  
The Stability ◽  
Therapeutic Activities

Presently, an emerging disease (COVID-19) has been spreading across the world due to coronavirus (SARS-CoV2). For treatment of SARS-CoV2 infection, currently hydroxychloroquine has been suggested by researchers, but it has not been found enough effective against this virus. The present study based on in silico approaches was designed to enhance the therapeutic activities of hydroxychloroquine by using curcumin as an adjunct drug against SARS-CoV2 receptor proteins: main-protease and S1 receptor binding domain (RBD). The webserver (ANCHOR) showed the higher protein stability for both receptors with disordered score (<0.5). The molecular docking analysis revealed that the binding energy (-24.58 kcal/mol) of hydroxychloroquine was higher than curcumin (-20.47 kcal/mol) for receptor main-protease, whereas binding energy of curcumin (<a>-38.84</a> kcal/mol) had greater than hydroxychloroquine<a> (-35.87</a> kcal/mol) in case of S1 receptor binding domain. Therefore, this study suggested that the curcumin could be used as combination therapy along with hydroxychloroquine for disrupting the stability of SARS-CoV2 receptor proteins

scholarly journals SMPLIP-Score: predicting ligand binding affinity from simple and interpretable on-the-fly interaction fingerprint pattern descriptors

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Surendra Kumar ◽  
Mi-hyun Kim
Keyword(s):  
Ligand Binding ◽  
Binding Affinity ◽  
Scoring Functions ◽  
Binding Affinities ◽  
Ligand Interaction ◽  
Fingerprint Pattern ◽  
Comparable Performance ◽  
Direct Interpretation ◽  
Benchmark Datasets ◽  
Complex Features

AbstractIn drug discovery, rapid and accurate prediction of protein–ligand binding affinities is a pivotal task for lead optimization with acceptable on-target potency as well as pharmacological efficacy. Furthermore, researchers hope for a high correlation between docking score and pose with key interactive residues, although scoring functions as free energy surrogates of protein–ligand complexes have failed to provide collinearity. Recently, various machine learning or deep learning methods have been proposed to overcome the drawbacks of scoring functions. Despite being highly accurate, their featurization process is complex and the meaning of the embedded features cannot directly be interpreted by human recognition without an additional feature analysis. Here, we propose SMPLIP-Score (Substructural Molecular and Protein–Ligand Interaction Pattern Score), a direct interpretable predictor of absolute binding affinity. Our simple featurization embeds the interaction fingerprint pattern on the ligand-binding site environment and molecular fragments of ligands into an input vectorized matrix for learning layers (random forest or deep neural network). Despite their less complex features than other state-of-the-art models, SMPLIP-Score achieved comparable performance, a Pearson’s correlation coefficient up to 0.80, and a root mean square error up to 1.18 in pK units with several benchmark datasets (PDBbind v.2015, Astex Diverse Set, CSAR NRC HiQ, FEP, PDBbind NMR, and CASF-2016). For this model, generality, predictive power, ranking power, and robustness were examined using direct interpretation of feature matrices for specific targets.

scholarly journals Prediction of Functional Consequences of Missense Mutations in ANO4 Gene

2021 ◽  
Vol 22 (5) ◽  
pp. 2732
Author(s):  
Nadine Reichhart ◽  
Vladimir M. Milenkovic ◽  
Christian H. Wetzel ◽  
Olaf Strauß
Keyword(s):  
Transmembrane Protein ◽  
Functional Characterization ◽  
Missense Mutations ◽  
Mutant Proteins ◽  
Functional Consequences ◽  
New Perspective ◽  
The Stability ◽  
Dynamics Simulations ◽  
And Function

The anoctamin (TMEM16) family of transmembrane protein consists of ten members in vertebrates, which act as Ca2+-dependent ion channels and/or Ca2+-dependent scramblases. ANO4 which is primarily expressed in the CNS and certain endocrine glands, has been associated with various neuronal disorders. Therefore, we focused our study on prioritizing missense mutations that are assumed to alter the structure and stability of ANO4 protein. We employed a wide array of evolution and structure based in silico prediction methods to identify potentially deleterious missense mutations in the ANO4 gene. Identified pathogenic mutations were then mapped to the modeled human ANO4 structure and the effects of missense mutations were studied on the atomic level using molecular dynamics simulations. Our data show that the G80A and A500T mutations significantly alter the stability of the mutant proteins, thus providing new perspective on the role of missense mutations in ANO4 gene. Results obtained in this study may help to identify disease associated mutations which affect ANO4 protein structure and function and might facilitate future functional characterization of ANO4.

scholarly journals Analysis of the interaction of thermoacoustic modes with a Green’s function approach

2018 ◽  
Vol 10 (4) ◽  
pp. 326-336 ◽  
Author(s):  
Alessandra Bigongiari ◽  
Maria Heckl
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Initial Perturbation ◽  
Time History ◽  
Function Approach ◽  
Stability Maps ◽  
Flame Describing Function ◽  
The Stability ◽  
Dynamics Simulations ◽  
Fast Prediction

In this paper, we will present a fast prediction tool based on a one-dimensional Green's function approach that can be used to bypass numerically expensive computational fluid dynamics simulations. The Green’s function approach has the advantage of providing a clear picture of the physics behind the generation and evolution of combustion instabilities. In addition, the method allows us to perform a modal analysis; single acoustic modes can be treated in isolation or in combination with other modes. In this article, we will investigate the role of higher-order modes in determining the stability of the system. We will initially produce the stability maps for the first and second mode separately. Then the time history of the perturbation will be computed, where both the modes are present. The flame will be modelled by a generic Flame Describing Function, i.e. by an amplitude-dependent Flame Transfer Function. The time-history calculations show the evolution of the two modes resulting from an initial perturbation; both transient and limit-cycle oscillations are revealed. Our study represents a first step towards the modelling of nonlinearity and non-normality in combustion processes.

scholarly journals Potential Mitochondrial Isocitrate Dehydrogenase R140Q Mutant Inhibitor from Traditional Chinese Medicine against Cancers

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Wen-Yuan Lee ◽  
Kuan-Chung Chen ◽  
Hsin-Yi Chen ◽  
Calvin Yu-Chian Chen
Keyword(s):  
Isocitrate Dehydrogenase ◽  
Point Mutations ◽  
Docking Simulation ◽  
Myelogenous Leukemia ◽  
Mutant Protein ◽  
Binding Affinities ◽  
Isocitrate Dehydrogenase 1 ◽  
Lead Compounds ◽  
Arginine Residues ◽  
Acute Myelogenous

A recent research of cancer has indicated that the mutant of isocitrate dehydrogenase 1 and 2 (IDH1and2) genes will induce various cancers, including chondrosarcoma, cholangiocarcinomas, and acute myelogenous leukemia due to the effect of point mutations in the active-site arginine residues of isocitrate dehydrogenase (IDH), such as IDH1/R132, IDH2/R140, and IDH2/R172. As the inhibition for those tumor-associated mutant IDH proteins may induce differentiation of those cancer cells, these tumor-associated mutant IDH proteins can be treated as a drug target proteins for a differentiation therapy against cancers. In this study, we aim to identify the potent TCM compounds from the TCM Database@Taiwan as lead compounds of IDH2 R140Q mutant inhibitor. Comparing to the IDH2 R140Q mutant protein inhibitor, AGI-6780, the top two TCM compounds, precatorine and abrine, have higher binding affinities with target protein in docking simulation. After MD simulation, the top two TCM compounds remain as the same docking poses under dynamic conditions. In addition, precatorine is extracted fromAbrus precatoriusL., which represents the cytotoxic and proapoptotic effects for breast cancer and several tumor lines. Hence, we propose the TCM compounds, precatorine and abrine, as potential candidates as lead compounds for further study in drug development process with the IDH2 R140Q mutant protein against cancer.

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