Computer-aided design of polyketides with the required properties

An approach to rational design of new polyketides with the required spectrum of biological activity has been proposed. We have developed the BioGenPharm software, which generates combinatorial libraries of polyketides based on the user-defined input parameters, performs prediction of biological activity spectra for the generated structures and selection of molecuels with the required properties. PASS algorithm has been applied for prediction of polyketide activity spectra (http://www.ibmc.msk.ru/PASS). Validation of PASS prediction ability for polyketides was performed vs. the evaluation set containing 242 natural macrolides from the Dictionary of Natural Products. The mean prediction accuracy was 75.5%. The problem of choice of the cutting points for probability of the presence of activity (Pa), which provides optimal combination of such parameters as sensitivity, specificity, concordance has been considered. Applicability of the described method has been illustrated by generation of a virtual library of the erythromycin analogues and selection of substances with low probability of the hepatotoxic effect.     

Synthesis and in silico biological activity evaluation of new N-substituted pyrazolo-oxazin-2-one systems

Cyclisation of pyrazolo-beta-enaminones 3 readily obtained from 4-aceto acetyl pyrazol 2 with triphosgene led to the formation of N-substituted pyrazolo-1,3-oxazin-2-ones 4 in good yields. Estimation of pharmacotherapeutic potential, possible molecule mechanisms of action, toxic/side effects and interaction with drug-metabolizing enzymes were made for synthesised compounds on the basis of prediction of activity spectra for substances (PASS) prediction results and their analysis by PharmaExpert software. COX inhibition predicted by PASS was confirmed by experimental evaluation.     

Capacities of computer evaluation of hidden potential of phytochemicals of medicinal plants of the traditional Indian Ayurvedic medicine

Applicability of our computer programs PASS and PharmaExpert for prediction of biological activity spectra of rather complex and structurally diverse phytocomponents of medicinal plants, both separately and in combinations has been evaluated. For this purpose we have created the web-resource containing known information about structural formulas and biological activity of 1906 phytocomponents of 50 Ayurvedic medicinal plants used in Traditional Indian Medicine (TIM) (http://ayurveda.pharmaexpert.ru). The PASS training set was updated by addition of information about structure and biological activity of 946 natural compounds; then the training procedure and validation were performed, to estimate the quality of PASS prediction. It was shown that the differences between the average accuracy of prediction obtained in leave-5%-out cross-validation (94.467%) and in leave-one-out cross-validation (94.605%) are very small thus demonstrating high predictive ability of the program. Results of biological activity spectra prediction for all phytocomponents included in our database coincided in 83.5% of cases with known experimental data. Additional types of biological activity predicted with high probability indicate further promising directions for further studies of certain phytocomponents of some medicinal plants. The analysis of prediction results of sets of phytocomponents in each of 50 medicinal plants was made by the PharmaExpert software. Based on this analysis, we found that the combination of phytocomponents from Passiflora incarnata may exhibit nootropic, anticonvulsant, and antidepressant effects. Experiments carried out in mice models confirmed the predicted effects of P. incarnata extracts.     

Computer-aided rodent carcinogenicity prediction

The potential of the computer program PASS (Prediction Activity Spectra for Substances) to predict rodent carcinogenicity for chemical compounds was studied. PASS predicts carcinogenicity of chemical compounds on the basis of their structural formula and of structure-activity relationship analysis of known carcinogens and non-carcinogens. The data on structures and experimental results of 2-year carcinogenicity assays for 412 chemicals from the NTP (National Toxicological Program) and 1190 chemicals from the CPDB (Carcinogenic Potency Database) were used in our study. The predictions take into consideration information about species and sex of animals. For evaluation of the predictive accuracy we used two procedures: leave-one-out cross-validation (LOO CV) and leave-20%-out cross-validation. In the last case we randomly divided the studied data set 20 times into two subsets. The data from the first subset, containing 80% of the compounds, were added to the PASS training set (which includes about 46,000 compounds with about 1500 biological activity types collected during the last 20 years to predict biological activity spectra), the second subset with 20% of the compounds was used as an evaluation set. The mean accuracy of prediction calculated by LOO CV is about 73% for NTP compounds in the 'equivocal' category of carcinogenic activity and 80% for NTP compounds in the 'evidence' category of carcinogenicity. The mean accuracy of prediction for the CPDB database is 89.9% calculated by LOO CV and 63.4% calculated by leave-20%-out cross-validation. Influence of incorporation of species and sex data on the accuracy of carcinogenicity prediction was also investigated. It was shown that the accuracy was increased only for data on male animals.     

Synthesis,antibacterial studies,and molecular modeling studies of 3,4-dihydropyrimidinone compounds

The syntheses of dihydropyrimidinones (DHPMs) using solvent-free grindstone chemistry method. All the synthesized compounds exhibited significant activity against pathogenic bacteria. The current effort has been developed to obtain new DHPM derivatives that focus on the bacterial ribosomal A site RNA as a drug target. Molecular docking simulation analysis was applied to confirm the target specificity of DHPMs. The crystal structure of bacterial 16S rRNA and human 40S rRNA was taken as receptors for docking. Finally, the docking score, binding site interaction analysis revealed that DHPMs exhibit more specificity towards 16S rRNA than known antibiotic amikacin. Accordingly, targeting the bacterial ribosomal A site RNA with potential drug leads promises to overcome the bacterial drug resistance. Even though, anti-neoplastic activities of DHPMs were also predicted through prediction of activity spectra for substances (PASS) tool. Further, the results establish that the DHPMs can serve as perfect leads against bacterial drug resistance.     

Computer prediction of biological activity spectra for low-molecular peptides and peptidomimetics

The wide variety of the biological effects of peptides and their high activity are the main reasons for the search for new basic drug structures among them. The most promising compounds can be selected using the PASS computer system (Prediction of Activity Spectra for Substances). This system was originally developed to predict the activities of low-molecular "drug-like" organic compounds. Its predictive capacity is described here by the example of 134 peptides and peptidomimetics with nine known biological activities. Its average predictive power is shown to be approximately 97%. Such an accuracy demonstrates that computer prediction can be applied both to the evaluation of effects and mechanisms of action of endogenous and synthetic peptides and to the screening of new therapeutic agents among the most promising basic structures.     

Computer prediction of biological activity spectra for low-molecular peptides and peptidomimetics

The wide variety of the biological effects of peptides and their high activity are the main reasons for the search for new basic drug structures among them. The most promising compounds can be selected using the PASS computer system (Prediction of Activity Spectra for Substances). This system was originally developed to predict the activities of low-molecular “drug-like” organic compounds. Its predictive capacity is described here by the example of 134 peptides and peptidomimetics with nine known biological activities. Its average predictive power is shown to be approximately 97%. Such an accuracy demonstrates that computer prediction can be applied both to the evaluation of effects and mechanisms of action of endogenous and synthetic peptides and to the screening of new therapeutic agents among the most promising basic structures.     

Potential inhibitors of the enzyme acetylcholinesterase and juvenile hormone with insecticidal activity: study of the binding mode via docking and molecular dynamics simulations

Abstract

Models validation in QSAR, pharmacophore, docking and others can ensure the accuracy and reliability of future predictions in design and selection of molecules with biological activity. In this study, pyriproxyfen was used as a pivot/template to search the database of the Maybridge Database for potential inhibitors of the enzymes acetylcholinesterase and juvenile hormone as well. The initial virtual screening based on the 3D shape resulted in 2000 molecules with Tanimoto index ranging from 0.58 to 0.88. A new reclassification was performed on the overlapping of positive and negative charges, which resulted in 100 molecules with Tanimoto's electrostatic score ranging from 0.627 to 0.87. Using parameters related to absorption, distribution, metabolism and excretion and the pivot molecule, the molecules selected in the previous stage were evaluated regarding these criteria, and 21 were then selected. The pharmacokinetic and toxicological properties were considered and for 12 molecules, the DEREK software not fired any alert of toxicity, which were thus considered satisfactory for prediction of biological activity using the Web server PASS. In the molecular docking with insect acetylcholinesterase, the Maybridge3_002654 molecule had binding affinity of ?11.1?kcal/mol, whereas in human acetylcholinesterase, the Maybridge4_001571molecule show in silico affinity of ?10.2?kcal/mol, and in the juvenile hormone, the molecule MCULE-8839595892 show in silico affinity value of ?11.6?kcal/mol. Subsequent long-trajectory molecular dynamics studies indicated considerable stability of the novel molecules compared to the controls.

Abbreviations QSAR quantitative structure–activity relationships

PASS prediction of activity spectra for substances

Communicated by Ramaswamy H. Sarma     

Novel chemiluminescence system with calcein as chemiluminescent reagent.

Chemiluminescence (CL) was observed when calcein reacted with potassium ferricyanide. Several metal ions and organic compounds could enhance this CL signal. The possible mechanisms for the CL reactions and the enhancement effect were investigated via studies of the CL kinetic characteristics, the CL spectra of some related reactions, the UV absorption spectra and the fluorescence spectra of some substances. The merits of figures for some substances with CL activity were obtained. A new CL system with calcein as the CL reagent was preliminarily established.     

Rapid access to new bioconjugates of betulonic acid via click chemistry

Plant-derived pentacyclic triterpenoids of lupane and oleanane families provide a versatile structural platform for the discovery of new biologically active compounds. A number of semisynthetic derivatives of these molecules, possess high medical efficiency including antiviral (HIV-1), anticancer and immunomodulating activity. Even small structural changes in these triterpenoid derivatives were reported to lead to significant changes in their activity, making a convincing case for a systematic study of structure-activity relationships in this class of compounds.Our earlier work opened synthetic access to alkynes derived from the betulonic scaffold and enabled the development of a new family of biohybrids using Click Chemistry (CC). The computer-aided prediction of several types of biological activity were performed with program PASS (Prediction Activity Spectra of Substances. Experimental studies based on mouse models verified the SAR predictions obtained by the PASS program. The observed correlation between the anti-inflammatory and antioxidant activity indicates substantial contribution of the latter in the mechanism of anti-inflammatory effect of the triazole derivatives of betulonic acid.     

Pentacyclic Triterpenoids Inhibit IKKβ Mediated Activation of NF-κB Pathway: In Silico and In Vitro Evidences

Pentacyclic Triterpenoids (PTs) and their analogues as well as derivatives are emerging as important drug leads for various diseases. They act through a variety of mechanisms and a majority of them inhibit the nuclear factor kappa-beta (NF-κB) signaling pathway. In this study, we examined the effects of the naturally occurring PTs on IκB kinase-β (IKKβ), which has great scientific relevance in the NF-κB signaling pathway. On virtual screening, 109 PTs were screened through the PASS (prediction of activity spectra of substances) software for prediction of NF-κB inhibitory activity followed by docking on the NEMO/IKKβ association complex (PDB: 3BRV) and testing for compliance with the softened Lipinski’s Rule of Five using Schrodinger (LLC, New York, USA). Out of the projected 45 druggable PTs, Corosolic Acid (CA), Asiatic Acid (AA) and Ursolic Acid (UA) were assayed for IKKβ kinase activity in the cell free medium. The UA exhibited a potent IKKβ inhibitory effect on the hotspot kinase assay with IC50 of 69 μM. Whereas, CA at 50 μM concentration markedly reduced the NF-κB luciferase activity and phospho-IKKβ protein expressions. The PTs tested, attenuated the expression of the NF-κB cascade proteins in the LPS-stimulated RAW 264.7 cells, prevented the phosphorylation of the IKKα/β and blocked the activation of the Interferon-gamma (IFN-γ). The results suggest that the IKKβ inhibition is the major mechanism of the PTs-induced NF-κB inhibition. PASS predictions along with in-silico docking against the NEMO/IKKβ can be successfully applied in the selection of the prospective NF-κB inhibitory downregulators of IKKβ phosphorylation.     

Prediction of Drug-Target Interactions for Drug Repositioning Only Based on Genomic Expression Similarity

Small drug molecules usually bind to multiple protein targets or even unintended off-targets. Such drug promiscuity has often led to unwanted or unexplained drug reactions, resulting in side effects or drug repositioning opportunities. So it is always an important issue in pharmacology to identify potential drug-target interactions (DTI). However, DTI discovery by experiment remains a challenging task, due to high expense of time and resources. Many computational methods are therefore developed to predict DTI with high throughput biological and clinical data. Here, we initiatively demonstrate that the on-target and off-target effects could be characterized by drug-induced in vitro genomic expression changes, e.g. the data in Connectivity Map (CMap). Thus, unknown ligands of a certain target can be found from the compounds showing high gene-expression similarity to the known ligands. Then to clarify the detailed practice of CMap based DTI prediction, we objectively evaluate how well each target is characterized by CMap. The results suggest that (1) some targets are better characterized than others, so the prediction models specific to these well characterized targets would be more accurate and reliable; (2) in some cases, a family of ligands for the same target tend to interact with common off-targets, which may help increase the efficiency of DTI discovery and explain the mechanisms of complicated drug actions. In the present study, CMap expression similarity is proposed as a novel indicator of drug-target interactions. The detailed strategies of improving data quality by decreasing the batch effect and building prediction models are also effectively established. We believe the success in CMap can be further translated into other public and commercial data of genomic expression, thus increasing research productivity towards valid drug repositioning and minimal side effects.     

The effect of biguanide derivatives on antioxidant status during the development of oxidative stress

The intensity of free radical processes, activity of antioxidant enzymes (superoxide dismutase, catalase), and the content of low molecular weight antioxidants (reduced glutathione, citrate) in skeletal muscle and liver from rats with experimental rheumatoid arthritis administered with biguanide synthetic derivatives (2,4-dicarbomethoxyphenyl-biguanide and 4-methyl-phenyl biguanide) selected by Prediction of Activity Spectra for Substances (PASS), a computer program for the prediction of biological activity, were studied. The observed changes in the studied parameters toward the reference values under the effect of tested compounds can be explained by their antioxidant and protective properties during pathology, which are accompanied by oxidative stress. The results can be used for the development of new methods for the prevention and treatment of rheumatoid arthritis.     

Diversity-oriented synthesis: exploring the intersections between chemistry and biology

Diversity-oriented synthesis (DOS) is an emerging field involving the synthesis of combinatorial libraries of diverse small molecules for biological screening. Rather than being directed toward a single biological target, DOS libraries can be used to identify new ligands for a variety of targets. Several different strategies for library design have been developed to target the biologically relevant regions of chemical structure space. DOS has provided powerful probes to investigate biological mechanisms and also served as a new driving force for advancing synthetic organic chemistry.     

Adapting EcoCyc for use on the World Wide Web

The World Wide Web (WWW) offers the potential to deliver specialized information to an audience of unprecedented size. Along with this exciting new opportunity comes a challenge for software developers: instead of rewriting our software applications to operate over the WWW, how can we maximize software reuse by retrofitting existing applications? We have developed a Web server tool. written in Common Lisp, that allows existing graphical user interface applications written using the Common Lisp Interface Manager (CLIM) to hook easily into the WWW. This tool — CWEST (CLIM-WEb Server Tool, pronounced “quest”) — was developed to operate with EcoCyc, an electronic encylopedia of the genes and metabolism of the bacterium E. coli. EcoCyc consists of a database of objects relevant to E. coli biochemistry and a user interface, implemented in CLIM, that runs on the X-window system and generates graphical displays appropriate to biological objects. Each query to the EcoCyc WWW server is treated as a command to the EcoCyc program, which dynamically generates an appropriate CLIM drawing. CWEST translates that drawing, which can be a mixture of text and graphics, into the HyperText Markup Language (HTML) and/or the Graphics Interchange Format (GIF), which are returned to the client. Sensitive regions embedded in the CLIM drawing are converted to hyperlinks with Universal Resource Locators (URLs) that generate further EcoCyc queries. This tight coupling of CLIM output with Web output makes CLIM a powerful high-level programming tool for Web applications. The flexibility of Common Lisp and CLIM made implementation of the server tool surprisingly easy, requiring few changes to the existing EcoCyc program. The results can be seen at URL http://www.ai.sri.com/ecocyc/browser.html. We have made CWEST available to the CLIM community at large, with the hope that it will spur other software developers to make their CLIM applications available over the WWW.     

GPS-CCD: a novel computational program for the prediction of calpain cleavage sites

As one of the most essential post-translational modifications (PTMs) of proteins, proteolysis, especially calpain-mediated cleavage, plays an important role in many biological processes, including cell death/apoptosis, cytoskeletal remodeling, and the cell cycle. Experimental identification of calpain targets with bona fide cleavage sites is fundamental for dissecting the molecular mechanisms and biological roles of calpain cleavage. In contrast to time-consuming and labor-intensive experimental approaches, computational prediction of calpain cleavage sites might more cheaply and readily provide useful information for further experimental investigation. In this work, we constructed a novel software package of GPS-CCD (Calpain Cleavage Detector) for the prediction of calpain cleavage sites, with an accuracy of 89.98%, sensitivity of 60.87% and specificity of 90.07%. With this software, we annotated potential calpain cleavage sites for hundreds of calpain substrates, for which the exact cleavage sites had not been previously determined. In this regard, GPS-CCD 1.0 is considered to be a useful tool for experimentalists. The online service and local packages of GPS-CCD 1.0 were implemented in JAVA and are freely available at: http://ccd.biocuckoo.org/.     

Wnt signalling pathway in bladder cancer

Bladder cancer (BC) is one of the most common tumours of the urinary system and is also known as a highly malignant tumour. In addition to conventional diagnosis and treatment methods, recent research has focused on studying the molecular mechanisms related to BC, in the hope that new, less toxic and effective targeted anticancer drugs and new diagnostic markers can be discovered. It is known that the Wingless (Wnt) signalling pathway and its related genes, proteins and other substances are involved in multiple biological processes of various tumours. Clarifying the contribution of the Wnt signalling pathway in bladder tumours will help establish early diagnosis indicators, develop new therapeutic drugs and evaluate the prognosis for BC. This review aims to summarise previous studies related to BC and the Wnt signalling pathway, with a focus on exploring the participating substances and their mechanisms in the regulation of the Wnt signalling pathway to better determine how to promote new chemotherapeutic drugs, potential therapeutic targets and diagnostic biomarkers.     

Predicting new molecular targets for rhein using network pharmacology

Background

Drugs can influence the whole biological system by targeting interaction reactions. The existence of interactions between drugs and network reactions suggests a potential way to discover targets. The in silico prediction of potential interactions between drugs and target proteins is of core importance for the identification of new drugs or novel targets for existing drugs. However, only a tiny portion of drug-targets in current datasets are validated interactions. This motivates the need for developing computational methods that predict true interaction pairs with high accuracy. Currently, network pharmacology has used in identifying potential drug targets to predicting the spread of drug activity and greatly contributed toward the analysis of biological systems on a much larger scale than ever before.

Methods

In this article, we present a computational method to predict targets for rhein by exploring drug-reaction interactions. We have implemented a computational platform that integrates pathway, protein-protein interaction, differentially expressed genome and literature mining data to result in comprehensive networks for drug-target interaction. We used Cytoscape software for prediction rhein-target interactions, to facilitate the drug discovery pipeline.

Results

Results showed that 3 differentially expressed genes confirmed by Cytoscape as the central nodes of the complicated interaction network (99 nodes, 153 edges). Of note, we further observed that the identified targets were found to encompass a variety of biological processes related to immunity, cellular apoptosis, transport, signal transduction, cell growth and proliferation and metabolism.

Conclusions

Our findings demonstrate that network pharmacology can not only speed the wide identification of drug targets but also find new applications for the existing drugs. It also implies the significant contribution of network pharmacology to predict drug targets.