Small Molecule Drug Design Research Articles

New approaches and technologies in drug design and discovery

Traditional and novel approaches to drug design and screening techniques and strategies are described, and the potential benefits of new technologies are discussed. Sophisticated new approaches and technologies in the discovery and design of new drugs are replacing the traditional methods. Rational or structure-based methods of drug design and discovery that integrate techniques of x-ray crystallography, computational chemistry, and nuclear magnetic resonance spectroscopy are becoming the predominant methods. New technologies and methods for drug screening may yield significant savings in time and money, as well as increased diversity and specificity of lead compounds. Intense research activity is now being focused on small-molecule structure-based drug design, in which drugs would mimic the complex molecular interactions of natural proteins. The new approaches and technologies hold promise for dramatic therapeutic advances, particularly in the areas of transcriptionally active drugs and gene therapy. Rapid advances in drug design and screening, brought about through new technologies, may yield significant therapeutic advances and cost-effective therapies.

Supporting drug design using an incremental learning approach

An intelligence computer system must have the capability to learn. Developing a design support system that is capable of learning is difficult as our understanding of design as an intelligent behaviour is limited and there is, as yet, no computational theory of the design process. From a learning point of view, design can be modelled as an incremental process of discovering the structure of a design problem. Here we present an investigation into how the capability of an AI-based design support system can be enhanced by utilising inductive learning techniques to do this. In this paper, an incremental inductive learning approach to small-molecule drug design is presented. Detailed descriptions of drug design concepts, knowledge representation of drug design objects, and the learning algorithm used are presented to demonstrate how an incremental learning strategy can be integrated into a drug design support system, to provide better solutions to one of the major problems in the domain of small-molecule drug design, the identification of a pharmacophore from a set of active molecules.