000			02632nam a2200229Ia 4500
003			MX-MdCICY
005			20250625140643.0
040			_cCICY
090			_aB-11040
245	1	0	_aComputational chemistry approaches to drug discovery in signal transduction
490	0		_vBiotechnology Journal, 3(4), p.456-509, 2008
520	3		_aThe advent of therapeutic strategies aimed at targeting specific macromolecular components of deregulated signaling pathways associated with particular disease states has given rise to the idea that it should be possible to design ligands as drug candidates to these targets from first principles. This concept has been beckoning for a long time but structure-based ligand design only became feasible once it was possible to determine the 3-D structures of molecular targets at atomic resolution. However, structure-based design turned out to be difficult, chiefly because under physiological conditions both receptors and ligands are not static but they behave dynamically. While it is possible to design ligands with high steric and electronic complementarity to a receptor site, it is always uncertain how biologically relevant the assumed conformations of both ligand and receptor actually are. The fact that it remains beyond our current abilities to predict with sufficient accuracy the affinity between hypothetical ligand and receptor poses is in part connected with this problem and continues to confound the reliable prediction of drug-like ligands for therapeutic targets. Nevertheless, significant progress has been made and so-called virtual screening methods that use computational methods to dock candidate ligands into receptor sites and to score the resulting complexes are now used routinely as one of the components in drug discovery screening campaigns. Here an overview is given of the underlying principles, implementations, and applications of structure-guided computational design technologies. Although the emphasis is on receptor-based strategies, mention will also be made of some of the more established ligand- based approaches, such as similarity analyses and quantitative structure-activity relationship methods.
650	1	4	_aCOMPUTATIONAL CHEMISTRY
650	1	4	_aMOLECULAR MODELING
650	1	4	_aMOLECULAR RECOGNITION
650	1	4	_aSTRUCTURE-BASED DRUG DESIGN
650	1	4	_aVIRTUAL SCREENING
700	1	2	_aFischer, P.M.
856	4	0	_uhttps://drive.google.com/file/d/11TWe7iCOCqwMnAo5hb3UwFG_7USVHvW3/view?usp=drivesdk _zPara ver el documento ingresa a Google con tu cuenta: @cicy.edu.mx
942			_2Loc _cREF1
008			250602s9999 xx |||||s2 |||| ||und|d
999			_c45267 _d45267