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Structure-based drug design (SBDD) and Ligand-based drug design (LBDD)
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Computer aided drug design (CADD) is a growing area of research encompassing many facets. It consists of various aspects of applied and basic research. Both applied research and basic research merge together and stimulate their potentials accordingly. The theoretical basis of CADD involves quantum mechanics and molecular modeling studies like struc...
Citations
... Utilizing the CADD approach, it is possible to find hits for each target while simultaneously searching for medications against a range of targets. The true-hits rates should be higher than the falsehits rates against the targets when doing multi-target searches for enrichment in 60, 61, and 62 [19]. ...
Since its discovery in 1964 by Hansch, the Quantitative Structure Activity Relationship (QSAR) has remained an important tool in drug design. The work of a huge number of scientists has improved the strength, utility and efficiency of this vital technique in molecular modeling. The original formulation of the method was in two dimensions, the molecular descriptors i.e., the physico-chemical constants were correlated with the biological activity, however, advances in technology, computational efficiency and the brilliant ideas of researchers have added many descriptors/dimensions leading to the 3D, 4D, 5D and 6DQSAR techniques. The different forms of QSAR have not only contributed to understanding the pharmacophoric features required for improvement in the activity but has also helped to improve the pharmacokinetic and pharmacodynamic characteristics of drug candidates. The beauty of the QSAR technique is that it does not require information about the receptor (though well and good if known) and hence is helpful in the design and improvement of probable drug molecules not only against vital diseases/disorders but even against those which were long neglected. The diseases of tropical countries have been neglected for two reasons, poverty in these regions and remoteness to the developed parts of the world. The diseases which are top on this list are malaria, tuberculosis, leshmaniasis etc. However, in recent times the scenario has changed with many organizations, governments and research institutions showing an interest in eradicating such diseases mainly due to the serious problems of drug resistance. Under these circumstances, QSAR provides a good weapon for the design of novel candidates. Many QSAR studies have been reported in the literature both on the molecules synthesized and tested against the whole micro organism and also on molecules directed against specific targets of the micro organisms. This chapter will briefly cover the basics of the QSAR technique and will be followed by examples of the discovery of antitubercular agents through the QSAR methodology.
Abstract In the last decades homology modeling has become a popular tool to access theoretical three-dimensional (3D) structures of molecular targets. So far several 3D models of proteins have been built by this technique and used in a great diversity of structural biology studies. But are those models consistent enough with experimental structures to make this technique an effective and reliable tool for drug discovery? Here we present, briefly, the fundamentals and current state of the art of the homology modeling techniques used to build 3D structures of molecular targets, which experimental structures are not available in databases, and list some of the more important works, using this technique, available in literature today. In many cases those studies have afforded successful models for the drug design of more selective agonists/antagonists to the molecular targets in focus and guided promising experimental works, proving that, when the appropriate templates are available, useful models can be built using some of the several software available today for this purpose. Limitations of the experimental techniques used to solve 3D structures allied to constant improvements in the homology modeling software will maintain the need for theoretical models, establishing the homology modeling as a fundamental tool for the drug discovery.
