Current Drug Discovery Technologies

ISSN: 1570-1638

Current Drug Discovery Technologies
Volume 3, Number 3, September 2006

Contents


Ligand-Based Drug Design Methodologies in Drug Discovery Process: An Overview Pp. 155-165
Magdalena Bacilieri and Stefano Moro
[Abstract]


Align: a C++ Class Library and Web Server for Rapid Sequence Alignment Prototyping Pp. 167-173
Silvio C.E. Tosatto, Alessandro Albiero, Alessandra Mantovan, Carlo Ferrari, Eckart Bindewald and Stefano Toppo
[Abstract]


Application of Graph-Based Analysis of Genomic Sequence Context for Characterization of Drug Targets Pp. 175-188
Petr Pancoska
[Abstract]


Integrated Approaches to Perform In Silico Drug Discovery Pp. 189-197
Govindan Subramanian, Adnan M. M. Mjalli and Michael E. Kutz
[Abstract]


Proteomics Approach to Illustrate Drug Action Mechanisms Pp. 199-209
Ying Wang, Jen-Fu Chiu and Qing-Yu He
[Abstract]


Prodrug Strategy for Enhancing Drug Delivery via Skin Pp. 211-224
Jia-You Fang and Yann-Lii Leu
[Abstract]


Prediction of Antigenic Epitopes of Neurotoxin Bmbktx1 from Mesobuthus martensii Pp. 225-229
Virendra S. Gomase
[Abstract]




Abstracts


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Ligand-Based Drug Design Methodologies in Drug Discovery Process: An Overview
Magdalena Bacilieri and Stefano Moro

Ligand-based drug design represents an important research field in the drug discovery and optimisation process. This review provides an overview about the theoretical background of the quantitative structure activity relationship (QSAR) models.


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Align: a C++ Class Library and Web Server for Rapid Sequence Alignment Prototyping
Silvio C.E. Tosatto, Alessandro Albiero, Alessandra Mantovan, Carlo Ferrari, Eckart Bindewald and Stefano Toppo

Sequence alignment remains a fundamental tool in most tasks related to the prediction of protein sequence and structure. A C++ class library was developed to facilitate the rapid implementation of a variety of state-of-the-art pairwise sequence alignment techniques. These range from simple sequence to sequence to the advanced profile to profile alignments with optional secondary structure information. Suboptimal alignments, frequently used to estimate regions of confidence, can also be generated. The object oriented design facilitates rapid implementation, testing and extension of existing functionality. A simple web interface, which can also be useful in bioinformatics education, is also provided. Source code, online documentation and a prototypical web interface are freely accessible to academic users from the URL: http://protein.cribi.unipd.it/align/. A sample case study in the modelling of human Cytochrome P450 is discussed.


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Application of Graph-Based Analysis of Genomic Sequence Context for Characterization of Drug Targets
Petr Pancoska

We show that analyzing individual genes of target proteins in terms of multiplicities of possible realizations of position-dependent thermodynamic states of their DNA molecules constitutes a new bioinformatics paradigm. It provides information that is unique and complementary to results of existing methods of sequence analysis. Using this graph-theory based approach, we developed informative and computationally immensely tractable tool to gain insight into intricate details of properties of drug targets. We present validation of our method by processing seventeen target genes for approved drugs in complexes with known 3D structures. Our novel method can identify coding segments that form important parts of the active and binding sites (individual significance estimated by p-values =0.001). We discuss limitations and advantages of the methodology. Because of its generality, this approach can be used for novel quantitative target-drug assessment and it is applicable to analysis of coding as well as non-coding regions. We also propose the application of this method in quantitative sequence-activity models.


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Integrated Approaches to Perform In Silico Drug Discovery
Govindan Subramanian, Adnan M. M. Mjalli and Michael E. Kutz

Computer assisted, or in silico, drug discovery approaches play an important role in the search for small molecule hits and leads. These include structure- and ligand-based methods, as well as data mining and QSAR. They are used to analyze and predict ligand-receptor binding, as well as pharmacokinentic profiles of compounds with therapeutic potential. A diversity of offerings is publically/commercially available for performing these tasks. Each offering comprises select combinations of in silico methods. Efficient in silico drug discovery requires effective use of combinations of these tools. Unfortunately, no single vendor offering integrates all in silico capabilities. Typically, different vendors offer different “flavors” of the same method and specific “flavors” have associated strengths and weaknesses. Furthermore, significant inter-vendor format incompatibilities exist. Consequently, extensive scripting as well as manual intervention is required in order to overcome disparate data formats. In this article, we introduce the architecture and implementation of a highly efficient, and automated in silico drug discovery engine that integrates multi-vendor software. A single graphical user interface enables the user to ‘Click & Configure’ modeling tools and permits ‘Mix & Match’-ing components from various vendors. It deploys a ‘Divide & Conquer’ strategy to marshal the resources of a multi-node compute cluster for compute-intensive tasks. This basic framework in performing in silico modeling activities (work-flow automation) envisions the integration of structure-based, ligand-based, and other modes of in silico drug discovery.


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Proteomics Approach to Illustrate Drug Action Mechanisms
Ying Wang, Jen-Fu Chiu and Qing-Yu He

The recently developed proteomic technology features high-throughput parallel analysis of all proteins expressed from a genome, and thus opens up the possibility of providing details on the molecular mechanisms in a global level. Proteomic approaches combined with other biochemical methods can reconstruct regulatory networks, signaling cascades and metabolic pathways upon drug treatment. In this review, an overview will be given on recent progresses in proteomic research strategies that have an impact on drug discovery and their applications in illustrating action mechanisms of anticancer drugs including angiogenesis inhibitors, predicting drug resistance, and examining signaling pathways and phosphoproteome alterations upon drug treatment. The review concludes by exemplifying concrete data-driven studies in pharmaceutical research, which demonstrate the value of integrated proteomic platforms for drug target identification and validation, screening assay development, as well as the evaluations of drug candidate efficacy and toxicity.


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Prodrug Strategy for Enhancing Drug Delivery via Skin
Jia-You Fang and Yann-Lii Leu

Skin as a route for drug delivery has been extensively investigated. However, because of the predominant barrier function of stratum corneum in skin, the clinical application is limited. One strategy to solve this problem of drug permeation via skin is the use of prodrugs. Prodrugs are inactive compounds which are metabolized either chemically or enzymatically in a controlled or predictable manner to its parent active drug. Prodrugs can enhance dermal/transdermal drug delivery via different mechanisms, including increased skin partitioning, increased aqueous solubility, and reduced crystallization, etc. Besides the prodrug itself, the optimization of vehicle is important as well. The prodrug partitioning between skin and vehicle as well as prodrug-vehicle interaction may influence the enhancing efficacy on skin permeation. This review explores the synthesis and enhancing mechanisms of prodrugs for topical drug delivery. The prodrugs categorized by the therapeutic use of the parent drugs, including anticancer drugs, analgesics, anti-inflammatory drugs and vitamins, are systemically introduced in this review.


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Prediction of Antigenic Epitopes of Neurotoxin Bmbktx1 from Mesobuthus martensii
Virendra S. Gomase

Gene therapy or recombinant DNA vaccines targeting multiple antigenic components to direct empower the immune system. Antigenic epitopes on neurotoxin Mesobuthus martensii (Buthus martensii) are important determinant of protection against cardiovascular disorder. Small segments 4-YSSDCRVKCVAM-15, 18-SSGKCINSKC-27 of neuro-toxin protein called the antigenic epitopes is sufficient for eliciting the desired immune response. In analysis predicted antigenic epitopes neurotoxin protein is seen. Immunization cassettes should be capable of immunizing of broad immunity against both humoral and cellular epitope thus giving vaccines the maximum ability to deal with neurotoxin protein of M. martensii. We have predicted a successful immunization.