Computational systems approach for drug target discovery

Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a `bird's eye view' of the biological systems under study, at the same time allowing us to `zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.

Design for sustainability: The role of CAD

The term design in this paper particularly refers to the process (verb) and less-to the outcome or product. Design comprises a complex set of activities today involving both man and machine. Sustainability is a fundamental paradigm and carries significance in any process, natural or manmade, and its outcome. In simple terms, sustainability implies a state of sustainable living, viz, health and continuity, nurtured by diversity and evolution (innovations) in an ever-changing world. Design, in a similar line, has been comprehensively investigated and its current manifestations including design-aids (Computer Aided Design) have been evaluated in terms of sustainability. The paper investigates the rationale of sustainability to design as a whole - its purpose, its adoption in the natural world, its relevance to humankind and the technologies involved. Throughout its history, technology has been used to aid design. But in the current context of advanced algorithms and computational capacity, design no longer remains an exclusively animate faculty. Given this scenario, investigating sustainability in the light of advanced design aids such as CAD becomes pertinent. Considering that technology plays a part in design activities, the paper explores where technology must play a part and to what degree amongst the various activities that comprise design. The study includes an examination of the morphology of design and the development of a systems-thinking integrated forecasting model to evaluate the implications of CAD tools in design and sustainability. The results of the study along with a broad range of recommendations have been presented. (c) 2012 Elsevier Ltd. All rights reserved.