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10.1021/cn200100h http://scihub22266oqcxt.onion/10.1021/cn200100h 22267984/?report=reader!3260741!22267984     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       ACS+Chem+Neurosci 2012 ; 3 (1): 50-68 Nephropedia Template TP {{tp|p=22267984|t=2012. Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery |pdf=|usr=}}{{22267984}} gab.com Text Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery JO: ACS Chem Neurosci http://www.kidney.de/pget.php?&tw=1&pmid=22267984 #FOAvip The central nervous system (CNS) is the major area that is affected by aging. Alzheimer's disease (AD), Parkinson's disease (PD), brain cancer, and stroke are the CNS diseases that will cost trillions of dollars for their treatment. Achievement of appropriate blood-brain barrier (BBB) penetration is often considered a significant hurdle in the CNS drug discovery process. On the other hand, BBB penetration may be a liability for many of the non-CNS drug targets, and a clear understanding of the physicochemical and structural differences between CNS and non-CNS drugs may assist both research areas. Because of the numerous and challenging issues in CNS drug discovery and the low success rates, pharmaceutical companies are beginning to deprioritize their drug discovery efforts in the CNS arena. Prompted by these challenges and to aid in the design of high-quality, efficacious CNS compounds, we analyzed the physicochemical property and the chemical structural profiles of 317 CNS and 626 non-CNS oral drugs. The conclusions derived provide an ideal property profile for lead selection and the property modification strategy during the lead optimization process. A list of substructural units that may be useful for CNS drug design was also provided here. A classification tree was also developed to differentiate between CNS drugs and non-CNS oral drugs. The combined analysis provided the following guidelines for designing high-quality CNS drugs: (i) topological molecular polar surface area of <76 A(2) (25-60 A(2)), (ii) at least one (one or two, including one aliphatic amine) nitrogen, (iii) fewer than seven (two to four) linear chains outside of rings, (iv) fewer than three (zero or one) polar hydrogen atoms, (v) volume of 740-970 A(3), (vi) solvent accessible surface area of 460-580 A(2), and (vii) positive QikProp parameter CNS. The ranges within parentheses may be used during lead optimization. One violation to this proposed profile may be acceptable. The chemoinformatics approaches for graphically analyzing multiple properties efficiently are presented. Twit Text FOAVip Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery ????ACS Chem Neurosci http://www.kidney.de/pget.php?&tw=1&pmid=22267984 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=22267984 #FOAvip English Wikipedia <ref>{{Cite pmid|22267984}}</ref> Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery #MMPMID22267984 Ghose AK; Herbertz T; Hudkins RL; Dorsey BD; Mallamo JP ACS Chem Neurosci 2012[Jan]; 3 (1): 50-68 PMID22267984show ga The central nervous system (CNS) is the major area that is affected by aging. Alzheimer's disease (AD), Parkinson's disease (PD), brain cancer, and stroke are the CNS diseases that will cost trillions of dollars for their treatment. Achievement of appropriate blood-brain barrier (BBB) penetration is often considered a significant hurdle in the CNS drug discovery process. On the other hand, BBB penetration may be a liability for many of the non-CNS drug targets, and a clear understanding of the physicochemical and structural differences between CNS and non-CNS drugs may assist both research areas. Because of the numerous and challenging issues in CNS drug discovery and the low success rates, pharmaceutical companies are beginning to deprioritize their drug discovery efforts in the CNS arena. Prompted by these challenges and to aid in the design of high-quality, efficacious CNS compounds, we analyzed the physicochemical property and the chemical structural profiles of 317 CNS and 626 non-CNS oral drugs. The conclusions derived provide an ideal property profile for lead selection and the property modification strategy during the lead optimization process. A list of substructural units that may be useful for CNS drug design was also provided here. A classification tree was also developed to differentiate between CNS drugs and non-CNS oral drugs. The combined analysis provided the following guidelines for designing high-quality CNS drugs: (i) topological molecular polar surface area of <76 A(2) (25-60 A(2)), (ii) at least one (one or two, including one aliphatic amine) nitrogen, (iii) fewer than seven (two to four) linear chains outside of rings, (iv) fewer than three (zero or one) polar hydrogen atoms, (v) volume of 740-970 A(3), (vi) solvent accessible surface area of 460-580 A(2), and (vii) positive QikProp parameter CNS. The ranges within parentheses may be used during lead optimization. One violation to this proposed profile may be acceptable. The chemoinformatics approaches for graphically analyzing multiple properties efficiently are presented. äKnowledge-Based, Central Nervous System (CNS) Lead Selection and Lead (epmc).pdf DeepDyve Pubget Overpricing