Web-based cheminformatics tools deployed via corporate Intranets

Web-Based Tools for Polypharmacology Prediction

Drug promiscuity or polypharmacology is the ability of small molecules to interact with multiple protein targets simultaneously. In drug discovery, understanding the polypharmacology of potential drug molecules is crucial to improve their efficacy and safety, and to discover the new therapeutic potentials of existing drugs. Over the past decade, several computational methods have been developed to study the polypharmacology of small molecules, many of which are available as Web services. In this chapter, we review some of these Web tools focusing on ligand based approaches. We highlight in particular our recently developed polypharmacology browser (PPB) and its application for finding the side targets of a new inhibitor of the TRPV6 calcium channel.

Potential of the chlorogenic acid as multitarget agent: Insulin-secretagogue and PPAR α/γ dual agonist

The chlorogenic acid (CGA) is a natural product isolated from Cecropia obtusifolia, which possesses several pharmacological properties, such as: anti-carcinogenic, neuroprotective, antioxidant, anti-inflammatory, hypoglycemic, and hypolipidemic. In relation to its effects on the hyperglycemia and hypertriglyceridemia, few is known about the mechanisms in which this compound may be acting, therefore, the aim of the present study was to determine if CGA acts as an insulin secretagogue increasing intracellular calcium concentrations ([Ca²⁺]_i) in RINm5F cells; or as an insulin sensitizer and lipid-lowering agent stimulating the expression of PPARγ and PPARα, respectively, in 3T3-L1 adipocytes. As results, RINm5F cells treated with 200μM of CGA showed an increase in [Ca²⁺]_i of 9-times versus control and 4-times as compared to positive control; in addition, an increase in insulin secretion was observed similarly to those of positive control. CGA also significantly increased the mRNA expression of PPARγ (150%) and GLUT4 (220%), as well PPARα (40%) and FATP (25%) as it was appreciated by RT-PCR. Additionally, a chemoinformatic analysis suggested that CGA has suitable physicochemical properties to be considered as leader bioactive molecule for the development of novel agents with similar properties. Together, our results indicate that CGA possesses multiple mechanisms of action for the development of highly effective therapeutics in the treatment of metabolic diseases such as type 2 diabetes.

Reporting biological assay screening results for maximum impact

A very large corpus of biological assay screening results exist in the public domain. The ability to compare and analyze this data is hampered due to missing details and lack of a commonly used terminology to describe assay protocols and assay endpoints. Minimum reporting guidelines exist that, if followed, would greatly enhance the utility of biological assay screening data so it may be independently reproduced, readily integrated, effectively compared, and rapidly analyzed.

An Overview of the Challenges in Designing, Integrating, and Delivering BARD: A Public Chemical-Biology Resource and Query Portal for Multiple Organizations, Locations, and Disciplines

Recent industry-academic partnerships involve collaboration among disciplines, locations, and organizations using publicly funded "open-access" and proprietary commercial data sources. These require the effective integration of chemical and biological information from diverse data sources, which presents key informatics, personnel, and organizational challenges. The BioAssay Research Database (BARD) was conceived to address these challenges and serve as a community-wide resource and intuitive web portal for public-sector chemical-biology data. Its initial focus is to enable scientists to more effectively use the National Institutes of Health Roadmap Molecular Libraries Program (MLP) data generated from the 3-year pilot and 6-year production phases of the Molecular Libraries Probe Production Centers Network (MLPCN), which is currently in its final year. BARD evolves the current data standards through structured assay and result annotations that leverage BioAssay Ontology and other industry-standard ontologies, and a core hierarchy of assay definition terms and data standards defined specifically for small-molecule assay data. We initially focused on migrating the highest-value MLP data into BARD and bringing it up to this new standard. We review the technical and organizational challenges overcome by the interdisciplinary BARD team, veterans of public- and private-sector data-integration projects, who are collaborating to describe (functional specifications), design (technical specifications), and implement this next-generation software solution.

State-of-the-art and dissemination of computational tools for drug-design purposes: a survey among Italian academics and industrial institutions

During the first edition of the Computationally Driven Drug Discovery meeting, held in November 2011 at Dompé Pharma (L'Aquila, Italy), a questionnaire regarding the diffusion and the use of computational tools for drug-design purposes in both academia and industry was distributed among all participants. This is a follow-up of a previously reported investigation carried out among a few companies in 2007. The new questionnaire implemented five sections dedicated to: research group identification and classification; 18 different computational techniques; software information; hardware data; and economical business considerations. In this article, together with a detailed history of the different computational methods, a statistical analysis of the survey results that enabled the identification of the prevalent computational techniques adopted in drug-design projects is reported and a profile of the computational medicinal chemist currently working in academia and pharmaceutical companies in Italy is highlighted.

Web tools for predictive toxicology model building

INTRODUCTION

The development and use of web tools in chemistry has accumulated more than 15 years of history already. Powered by the advances in the Internet technologies, the current generation of web systems are starting to expand into areas, traditional for desktop applications. The web platforms integrate data storage, cheminformatics and data analysis tools. The ease of use and the collaborative potential of the web is compelling, despite the challenges.

AREAS COVERED

The topic of this review is a set of recently published web tools that facilitate predictive toxicology model building. The focus is on software platforms, offering web access to chemical structure-based methods, although some of the frameworks could also provide bioinformatics or hybrid data analysis functionalities. A number of historical and current developments are cited. In order to provide comparable assessment, the following characteristics are considered: support for workflows, descriptor calculations, visualization, modeling algorithms, data management and data sharing capabilities, availability of GUI or programmatic access and implementation details.

EXPERT OPINION

The success of the Web is largely due to its highly decentralized, yet sufficiently interoperable model for information access. The expected future convergence between cheminformatics and bioinformatics databases provides new challenges toward management and analysis of large data sets. The web tools in predictive toxicology will likely continue to evolve toward the right mix of flexibility, performance, scalability, interoperability, sets of unique features offered, friendly user interfaces, programmatic access for advanced users, platform independence, results reproducibility, curation and crowdsourcing utilities, collaborative sharing and secure access.

Software platform virtualization in chemistry research and university teaching

Background

Modern chemistry laboratories operate with a wide range of software applications under different operating systems, such as Windows, LINUX or Mac OS X. Instead of installing software on different computers it is possible to install those applications on a single computer using Virtual Machine software. Software platform virtualization allows a single guest operating system to execute multiple other operating systems on the same computer. We apply and discuss the use of virtual machines in chemistry research and teaching laboratories.

Results

Virtual machines are commonly used for cheminformatics software development and testing. Benchmarking multiple chemistry software packages we have confirmed that the computational speed penalty for using virtual machines is low and around 5% to 10%. Software virtualization in a teaching environment allows faster deployment and easy use of commercial and open source software in hands-on computer teaching labs.

Conclusion

Software virtualization in chemistry, mass spectrometry and cheminformatics is needed for software testing and development of software for different operating systems. In order to obtain maximum performance the virtualization software should be multi-core enabled and allow the use of multiprocessor configurations in the virtual machine environment. Server consolidation, by running multiple tasks and operating systems on a single physical machine, can lead to lower maintenance and hardware costs especially in small research labs. The use of virtual machines can prevent software virus infections and security breaches when used as a sandbox system for internet access and software testing. Complex software setups can be created with virtual machines and are easily deployed later to multiple computers for hands-on teaching classes. We discuss the popularity of bioinformatics compared to cheminformatics as well as the missing cheminformatics education at universities worldwide.

Electronic supplementary material

The online version of this article (doi:10.1186/1758-2946-1-18) contains supplementary material, which is available to authorized users.

RP-HPLC determination of lipophilicity in series of quinoline derivatives

In the present paper we describe results on the synthesis and lipophilicity determination of a series of biologically active compounds based on their heterocyclic structure. For synthesis of styrylquinoline-based compounds we applied microwave irradiation and solid phase techniques. The correlation between RP-HPLC retention parameter log k (the logarithm of retention factor k) and log P data calculated in various ways is discussed, as well as, the relationships between the lipophilicity and the chemical structure of the studied compounds.

Optimizing the use of open-source software applications in drug discovery

Drug discovery is a time consuming and costly process. Recently, a trend towards the use of in silico computational chemistry and molecular modeling for computer-aided drug design has gained significant momentum. This review investigates the application of free and/or open-source software in the drug discovery process. Among the reviewed software programs are applications programmed in JAVA, Perl and Python, as well as resources including software libraries. These programs might be useful for cheminformatics approaches to drug discovery, including QSAR studies, energy minimization and docking studies in drug design endeavors. Furthermore, this review explores options for integrating available computer modeling open-source software applications in drug discovery programs.