Relative Molecular Similarity in Compound Structures Modulating Neurodegenerative Apoptosis

Neurodegeneration is attributable to metabolic disturbances in the various cell types responsible for this condition, in respect of glucose utilisation and dysfunctional mitochondrial oxidative mechanisms. The properties of neurotoxins and antagonists that limit their action are well documented in disease models, whereas effective therapy is very limited. Cell apoptosis, a general marker of neurodegeneration, is also of therapeutic interest in the treatment of cancer. cGMP nucleotide influences apoptosis and has a role in maintaining equilibrium within cell redox parameters. The chemical structure of cGMP provides a comparative template for demonstrating relative molecular similarity within the structures of natural and synthetic compounds influencing tumour cell apoptosis. The present study uses computational software to investigate molecular similarity within the structures of cGMP and compounds that modulate cell apoptosis in experimental models of diabetic peripheral neuropathy (DPN), Parkinson’s and multiple sclerosis. Differential molecular similarity demonstrated in neurotoxin and antagonist structures implicate metabolite impairment of cGMP signaling function as a common mechanism in the initial phases of these neurodegenerative conditions.

Cytotoxicity of Cholesterol Oxides and the Consequences of Relative Molecular Similarity to cGMP Nucleotide

Cholesterol and cholesterol oxides impact on the functional properties of cells, in respect of the intracellular and extracellular distribution of compounds across cell membranes, carcinogenesis and drug resistance. Abnormal levels of cholesterol oxides and steroids in cancerous tissues promote interest in steroid receptor cross-talk during cell-signalling and the steroid metabolome of cancer patients. The research literature links the cytotoxic properties of oxysterols to interference with the NO/cGMP pathway. cGMP participates in cell-signalling and has a molecular structure that relates to cancer-inducing and cancer-preventing agents. This study uses a molecular modelling approach to compare the structures of cholesterol oxides to cGMP. Cholesterol and cholesterol oxide structures fit to a cGMP structural template in several ways, some of which are replicated by corticosteroids and gonadal steroid hormones. The results of this study support the concept that cholesterol oxides modulate cell apoptosis and autophagy via the NO/cGMP pathway and in conjunction with steroid hormones participate in modulating regulation of cell function by cGMP.

Molecular Similarity Based on Super-Ball Algorithm

The molecular similarity of 139 organic compounds was calculated by the topologic index method, the flexible super-ball algorithm was used to scan similar molecules and structures. The results show that the properties of organic compounds estimated from this method are reliable.

Molecular Similarity between Gibberellic Acid and Gliotoxin： Unravelling the Mechanism of Action for Plant Growth Promotion by Trichoderma harzianum

Besides control of the fungal plant pathogens, another interesting aspect observed when plants are treated with Trichoderma harzianum include effects such as complete and even stand of plants, improved seed germination, increases in plant height and overall enhanced plant growth. No research has yet been conducted to elucidate the mechanism by which these effects occur. Improved seed germination, in particular, suggest that Trichoderma harzianum produces a metabolite that may mimic the plant growth hormone gibberellic acid. The metabolite gliotoxin, produced by Trichoderma harzianum appear to be structurally most similar to gibberellic acid. In this study, common pharmacophore generation and molecular ligand docking simulations were used to evaluate the molecular similarity between gibberellic acid, specifically GA3, and gliotoxin. For the common pharmacophore evaluation, the structure of various gibberellic acids were used to construct a pharmacophore space to which gliotoxin was aligned, and during the molecular docking simulations the gibberellic acid receptor, GID1, served as ligand target for GA3 and gliotoxin. During the common pharmacophore evaluation, gliotoxin was successfully aligned to the common pharmacophore model constructed from various gibberellic acids. Furthermore, molecular docking simulations of gliotoxin and GA3 into the gibberellic acid receptor （GIDI） yielded docking scores of-10.78 kcal/mol for the GA3 molecule from Corina and a docking score of-10.17 kcal/mol for glioto^in. The docking scores suggest that gliotoxin may be able to competitively occupy the receptor space for gibberellic acid, and as such elicit the similar physiological responses observed in literature.

Molecular Similarity within Carcinogen and Guanine Cyclic Nucleotide Structures

Tumor promoters, apoptosis and autophagy modulators, chemotherapy drugs, and endogenous steroids demonstrate molecular similarity relative to cyclic nucleotide structure. This study explores relative molecular similarity within established human carcinogen structures using computational chemistry software. Molecular structures of conventional carcinogenic drugs and industrial agents demonstrate molecular similarity with a focus on the guanine base and nucleotide cyclized ring. Structures of volatile and gaseous anesthetic carcinogens do not conform to conventional 3-point pharmacophore-based fits characteristic of receptor-binding drugs. The results of this study provide some insight into how carcinogen structures may interact with endogenous compounds to disrupt cyclic nucleotide-driven homeostatic mechanisms.

Molecular Similarity： Methods and Performance

Molecular similarity has long been a hot topic, which has been evaluated and compared by various approaches and plays a significant role in protein-ligand and protein-protein interactions recognition. There are currently many types of molecular similarity evaluation methods with their own advantages and disadvantages. Molecular finger- prints are the most common methods for molecular similarity evaluation which only concern about rapid 2D com- mon substructure retrieval but lack the ability to encode the information about 3D conformers. 3D molecular de- scriptor based methods bear the advantages of representing the structure information of a conformer, but the de- scriptors are not guaranteed to describe the molecules precisely. Molecular alignment based methods try to super- impose two molecules and evaluate the similarity using the optimal poses which are generally more precise than the molecular descriptor but require a time-consuming optimization process. Pharmacophore based methods only focus on the chemical features about a molecule and are not capable of dealing with the molecular shape similarity. In or- der to evaluate the performance of molecular similarity based screening, many kinds of metrics are available, e.g., visual representation, quantitative measurements and scaffold hopping ability measurements. Further applications of molecular similarity include construction of molecule interaction network or generation of diverse compounds li- brary.

Cyclic Nucleotide Structural Differentiation of Compounds Modulating Apoptosis and Drug Resistance

Carcinogenesis is associated with malfunction in the cGMP-mediated regulation of cytosolic Ca2+ and reactive oxygen species. Chemotherapy resistant cancer cells are re-sensitised to apoptosis by the action of a substantial number of natural compounds on cell membrane multidrug resistant proteins. Chemical structures of pro-apoptotic and anti-apoptotic compounds demonstrate relative molecular similarity to cGMP. This study uses a computational chemistry program to investigate molecular similarity within cGMP and chemo-preventative structures. Chemotherapeutic drugs and resistance modulators provide multiple fits to a nucleotide template that differ in their relationship to the cyclised ring of cGMP. The alternative fits of drug and modulator structures may relate to the development and unblocking of apoptosis and drug resistance.

Contributors to Cancer Susceptibility, Development and Treatment: Cyclic Nucleotides, Steroids and Autophagy Modulators

Cell autophagy and apoptosis processes are of interest in drug development and contribute to the chemotherapy outcomes of patients receiving cancer treatment. The functional roles of cyclic nucleotides in cells include maintenance of metabolic homeostasis. cGMP and steroid compounds participate in apoptotic and autophagic events, and modulate the function of multi-drug resistance proteins. Endogenous steroid and cyclic nucleotide ratios change with ageing and this may initiate detrimental changes in cell function. This study uses a computational chemistry approach to investigate molecular similarity within chemotherapeutic and steroid compound structures. Modulators of autophagy/apoptosis and endogenous steroid structures all demonstrate molecular similarity to the structure of cGMP. Relative molecular similarity within these structures facilitates additive and synergistic treatment effects. Endogenous steroids are natural modulators of autophagy and apoptosis;concentration changes consequently have the potential to impact cancer risks.

Quantitative structure-activity relationship of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives with AT1 receptor antagonistic activity

The quantitative structure-activity relationship(QSAR) of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives was studied.Three different alignment methods were used to get the models of the comparative molecular field analysis(CoMFA),the comparative molecular similarity indices analysis(CoMSIA),and the hologram quantitative structure?activity relationship(HQSAR).The statistical results from the established models show believable predictivity based on the cross-validated value(q2>0.5) and the non-validated value(r2>0.9),The analysis on contour maps of CoMFA and CoMSIA models suggests that hydrophobic and hydrogen-bond acceptor fields are important factors that affect the AT1 antagonistic activity of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives besides the steric and electrostatic fields,The structural modification information from different atom contributions in the HQSAR model is in agreement with that in the 3D-QSAR models.

Isosteric design of friction-reduction and anti-wear lubricant additives with less sulfur content

To reduce harmful sulfur content in lubricant additives, making use of isosterism has been shown to be an effective strategy. When thiobenzothiazole compounds were used as templates, the exchange of sulfur atoms in the thiazole ring with oxygen atoms and NH groups produced twelve isosteres. Similarly, 2-benzothiazole- S-carboxylic acid esters were used as template molecules to produce six isosteres. About 30% of the isosteres exhibited a satisfactory deviation of ±5% relative to the template, ignoring the specific changes in the base oils, the differences in molecular structure, and the friction or wear properties. The template molecules and isosteres in triisodecyl trimellitate exhibited better tribological properties than in trimethylolpropane trioleate or bis(2- ethylhexyl) adipate. Comparative molecular field analysis(CoM FA)- and comparative molecular similarity index analysis(CoMSIA)-quantitative structure tribo-ability relationship(QSTR) models were employed to study the correlation of molecular structures between the base oils and additives. The models indicate that the higher the structural similarities of the base oils and additives are, the more synergetic the molecular force fields of the lubricating system are; the molecular force fields creating synergistic effects will improve tribological performance.

Metabolite-Disease Association Prediction Algorithm Combining DeepWalk and Random Forest

Identifying the association between metabolites and diseases will help us understand the pathogenesis of diseases,which has great significance in diagnosing and treating diseases.However,traditional biometric methods are time consuming and expensive.Accordingly,we propose a new metabolite-disease association prediction algorithm based on DeepWalk and random forest(DWRF),which consists of the following key steps:First,the semantic similarity and information entropy similarity of diseases are integrated as the final disease similarity.Similarly,molecular fingerprint similarity and information entropy similarity of metabolites are integrated as the final metabolite similarity.Then,DeepWalk is used to extract metabolite features based on the network of metabolite-gene associations.Finally,a random forest algorithm is employed to infer metabolite-disease associations.The experimental results show that DWRF has good performances in terms of the area under the curve value,leave-one-out cross-validation,and five-fold cross-validation.Case studies also indicate that DWRF has a reliable performance in metabolite-disease association prediction.