Automated reaction family generation and analysis using cheminformatics

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An extensible web interface for databases and its application to storing biochemical data

This paper presents a generic web-based database interface implemented in Prolog. We discuss the advantages of the implementation platform and demonstrate the system's applicability in providing access to integrated biochemical data. Our system exploits two libraries of SWI-Prolog to create a schema-transparent interface within a relational setting. As is expected in declarative programming, the interface was written with minimal programming effort due to the high level of the language and its suitability to the task. We highlight two of Prolog's features that are well suited to the task at hand: term representation of structured documents and relational nature of Prolog which facilitates transparent integration of relational databases. Although we developed the system for accessing in-house biochemical and genomic data the interface is generic and provides a number of extensible features. We describe some of these features with references to our research databases. Finally we outline an in-house library that facilitates interaction between Prolog and the R statistical package. We describe how it has been employed in the present context to store output from statistical analysis on to the database.Comment: Online proceedings of the Joint Workshop on Implementation of Constraint Logic Programming Systems and Logic-based Methods in Programming Environments (CICLOPS-WLPE 2010), Edinburgh, Scotland, U.K., July 15, 201

BKM-react, an integrated biochemical reaction database

<p>Abstract</p> <p>Background</p> <p>The systematic, complete and correct reconstruction of genome-scale metabolic networks or metabolic pathways is one of the most challenging tasks in systems biology research. An essential requirement is the access to the complete biochemical knowledge - especially on the biochemical reactions. This knowledge is extracted from the scientific literature and collected in biological databases. Since the available databases differ in the number of biochemical reactions and the annotation of the reactions, an integrated knowledge resource would be of great value.</p> <p>Results</p> <p>We developed a comprehensive non-redundant reaction database containing known enzyme-catalyzed and spontaneous reactions. Currently, it comprises 18,172 unique biochemical reactions. As source databases the biochemical databases <it>BRENDA</it>, <it>KEGG</it>, and <it>MetaCyc </it>were used. Reactions of these databases were matched and integrated by aligning substrates and products. For the latter a two-step comparison using their structures (<it>via InChIs</it>) and names was performed. Each biochemical reaction given as a reaction equation occurring in at least one of the databases was included.</p> <p>Conclusions</p> <p>An integrated non-redundant reaction database has been developed and is made available to users. The database can significantly facilitate and accelerate the construction of accurate biochemical models.</p

[COMMODE] a large-scale database of molecular descriptors using compounds from PubChem

BACKGROUND: Molecular descriptors have been extensively used in the field of structure-oriented drug design and structural chemistry. They have been applied in QSPR and QSAR models to predict ADME-Tox properties, which specify essential features for drugs. Molecular descriptors capture chemical and structural information, but investigating their interpretation and meaning remains very challenging. RESULTS: This paper introduces a large-scale database of molecular descriptors called COMMODE containing more than 25 million compounds originated from PubChem. About 2500 DRAGON-descriptors have been calculated for all compounds and integrated into this database, which is accessible through a web interface at http://commode.i-med.ac.at

CDK-Taverna: an open workflow environment for cheminformatics

<p>Abstract</p> <p>Background</p> <p>Small molecules are of increasing interest for bioinformatics in areas such as metabolomics and drug discovery. The recent release of large open access chemistry databases generates a demand for flexible tools to process them and discover new knowledge. To freely support open science based on these data resources, it is desirable for the processing tools to be open source and available for everyone.</p> <p>Results</p> <p>Here we describe a novel combination of the workflow engine Taverna and the cheminformatics library Chemistry Development Kit (CDK) resulting in a open source workflow solution for cheminformatics. We have implemented more than 160 different workers to handle specific cheminformatics tasks. We describe the applications of CDK-Taverna in various usage scenarios.</p> <p>Conclusions</p> <p>The combination of the workflow engine Taverna and the Chemistry Development Kit provides the first open source cheminformatics workflow solution for the biosciences. With the Taverna-community working towards a more powerful workflow engine and a more user-friendly user interface, CDK-Taverna has the potential to become a free alternative to existing proprietary workflow tools.</p

Computational Design of Novel Candidate Drug Molecules for Schistosomiasis

Schistosomiasis is a parasitic disease that leads to chronic ill-health. Infection is acquired from infested freshwater containing the larval forms (cercariae) of blood flukes, known as schistosomes. The three main species of the parasite that infect humans are Schistosoma haematobium, S.japonicum, and S.mansoni. Schistosomiasis affects at least 230 million people worldwide. The infection is prevalent in tropical and sub-tropical areas, in poor communities without potable water and adequate sanitation. The disease is considered as one of the Neglected Tropical Diseases and so far praziquantel is the only drug used for treatment. Should the parasites develop resistance to praziquantel, treatment would be problematic.  This study incorporated a computational approach to design novel compounds with unprecedented potential as candidate drug compounds for the disease. The Schistosoma mansoni fatty acid binding protein was selected as a suitable drug target for its crucial role in the dependence of the parasite on its host for fatty acids. Screening for potential lead compounds was done using molecular docking software.  Identified lead compounds were analyzed and optimized in silico for their ADMET properties then re-evaluated for suitability of their binding energies. Eight novel compounds with good predicted ADMET properties were designed and found to interact with the S.mansoni fatty acid binding protein with favorable binding energy, showing potential to inhibit this protein. This study opens up new possibilities in antischistosomal drug inquiry and potentiates efficacy studies of such compounds against schistosomiasis. Keywords: computational design, antischistosomal drug inquiry, binding energy, lead optimization, ADMET properties

Designing algorithms to aid discovery by chemical robots

Recently, automated robotic systems have become very efficient, thanks to improved coupling between sensor systems and algorithms, of which the latter have been gaining significance thanks to the increase in computing power over the past few decades. However, intelligent automated chemistry platforms for discovery orientated tasks need to be able to cope with the unknown, which is a profoundly hard problem. In this Outlook, we describe how recent advances in the design and application of algorithms, coupled with the increased amount of chemical data available, and automation and control systems may allow more productive chemical research and the development of chemical robots able to target discovery. This is shown through examples of workflow and data processing with automation and control, and through the use of both well-used and cutting-edge algorithms illustrated using recent studies in chemistry. Finally, several algorithms are presented in relation to chemical robots and chemical intelligence for knowledge discovery