Rational Drug Design Techniques
Rational Drug Design Techniques CH 405/505
Popular in Medicinal Chemistry
Popular in Chemistry
This 13 page Class Notes was uploaded by Evan Roberts on Friday February 27, 2015. The Class Notes belongs to CH 405/505 at University of Alabama - Tuscaloosa taught by Timothy Snowden in Spring2015. Since its upload, it has received 104 views. For similar materials see Medicinal Chemistry in Chemistry at University of Alabama - Tuscaloosa.
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Date Created: 02/27/15
Patrick An Introduction to Medicinal Chemistry 5e Chapter 1 7 24 1 maples mam m a investigated as an antihypertensive but found to relieve ED during phase I clinical trials inhibitor of cGMP PDES 5m h o Pawn 39 dd 7 investigated as an antibiotic but found to promote severe hypoglycemia during clinical trials Developed as rst antidiabetic agent 39 K channel blocker in pancreas D M 4 a l3 6 QVJAWAQW of SU e JD M rur i Cmpuunds using Spectrosmpy NO OBSERVABLE BIOLOGICAL EFFECT 2 39 Optimize ep ope of Lead Compounds quotif vsm Optimize Optimize epitope epitope LEAD COMPOUND ign of Lead Compounds using Spectroscopy Optimize Optimize epitope epitope Fragment Based D Epitope linkers are commonly created using a 6 9 emery l Z iT azole Discovery of a highly potent acetylcholinesterase inhibitor Cycloaddltlon Cth alkyne gt Kd10 m uM Fraigme m DEW a e L I I H g V 39 g Hall39MHPil mums Kdlcm mum 02mm a 3 ll i39mM F r 03mM IWI HM I I g 3 ll 11 quot U H gr HONH 1 ICuIMMPI I Mquotbe Nature Reviews Drug Discovery 57 nM N 35 M 39 2007 6 211 Patrick An Introduction to Medicinal Chemistry 5e Chapter 17 MOLECUL DDELLING DE Nam DRUG ESIGN L De noun drug The design of novel lead compounds based on the structure of the logo 061ch erfjal J 0Cocrystallise protein ligand oDetermine crystal structure by Xray crystallography oDownload for molecular modelling studies Identify the binding site Identify binding interactions Identify other potential binding regions in the binding site oDesign ligands to fit and bind to the binding site in silico Calculate strength of binding Synthesize and test promising structures L De New Drug s I g l Molecular Similarity Calculati EN 39 Overlay by visual Min 7 13L DEE inspection inaccuratel overlay NH Procalno g Overlay ir 3 Compounds from virtual databases can be compared and scored to suggest possible hits Computational best fit Cocaine Prouan Molecular Similarity Calculation MNDDEK v Program learns from a 7 alarm n 1 rm i of input known biologically active and inactive compounds J 39 Creates rules in form of pairwise distances between fragments of substructure with apparent Email m thaw a if r HBD HBA sterics moments electron density li ydrophobieityjlfhsed rin aromatiea retract Virtual screening conducted to identify potential hits that have physieoehe39lnical properties appropriately positioned in 3D space but which a r or i tH r l3 Ctrn to training set offers a means of Idt n c yi njgiul acti w Corrifm mls l Pharmacnpllmre Mapping pi 39 Vi Representative pharmacophore map with i a 339 I 39I 39II I l i39 aromaticityhydrophobity centroids and charge densityHB vectors AJRMW 39 CIMMJYF doeb l mshiy kn aw whc L Rochoaqlr 104 g Preg L g quotI 4111 Mn39h3 kin A Jab Cowpbf39Cr quot BqS LA 63 do do Dash A Shadurn Mam I3 3930 WCQPNrc mappin M 0Pkor35 3D ensemble 0 Maia elmMunic Ramos Hausa1 0 24130quot o9ch HumeHons ladwan a hsm m3 ancm i 530logicktkt1 j and 0 8339 or block 6 rcsponsL 0 3DSSPGHAJ Pa39H39U39f opprwrh39es HLad Lamar from b vcms u muf m bf lloj39m cadhm I I an absth GQI W 4K ACLLMJ Radanal r0 4 3r IhQ Orma h o c a P quot Do Now Drug D igll Pharmamphore Mapping Process of pharmacophore determination I Choose training set of f39rmrjmmhiy gingiw Emits 39 lter v g More is belte1 Siartwith most stem comicmi i i quot irt u V u I 39 11M of betternoiency Hh h39 Esphag SAK f i 5 j39 if r 2 Lock in bliioactwe low energy conformations Ii ii 1 d 7 39 39 3 Superimpose and determine common abstractions I 4 Validatetest against r r 39 70M thouM outVIN naeft V63 Re ne as new validated actives become known Nomi Drug Pharmaco plmre Mapping I39I v 39 W I Idontlfy WW 0 cemrl V Ikd an pharmacophoro triangles Identify I j ltrquot 1 i V 1 a i39 a 5 Hbond acceptor 125a Vi quoti Aromatic ahuwnz h centre Hbnnd 339 acceptor ho L n 1 WWW WW Focus m cmer 9 r in TMNR V WW mung Ems ar il N ASHMG W inkrnodi mj g TLIQJ I Aggrastat Glycoprotin IIbIIIa inhibitor on blood platelet surfaces antiplatelet drug Developed through pharmacophore mappingvirtual screening Key Considerations Avoid designing structures that g i the binding site experimental error in crystal structures amp many proteins are exible different binding modes from predicted space needed for drug optimisation 0 Fle bu non e s are better than rigid allows alternative binding modes exibility will be optimized later a as 3 ahmrm eonAH in frJ he bk Synthetic feasibility Stable conformations Energy of desolvation vs Manual Operator directs study quotAHDWS input of designeris ideas MW PD P1 4 333 iUseful for identi cation of few potential hits Slow and limited to designer s originality tnted Program is automated No 64 introduced by operator Useful for generating a l as H Um r of possible hits Identi es not6 structures Mfwhn39f adwnhkx oMay generate Mfrs e lagsmi I 1 for synthesis Scoring structures for binding strengths is Unre limbQ many rm were m Onkl quot6 0239 We as A Compogndy EmPl39rg39ca i7roWHP S OS compoun 5 was Lag Lao was POMC I 4 LJ 0 BI Oavu q 5 2 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