drug discovery strategy final draft
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Drug Discovery
Anaeli Shockey
Delaine M. Zayas-Bazán
Nicollle A. Rosa
Zuleika Velázquez
Student Mentor: Mr. Carlos Castroda
Introduction • Food and Drug Administration (FDA)– Drug Discovery and Development– Clinical Trials– FDA Reviews and New Drug Application (NDA)– Manufacturing
• Considered Parameters– Absorption– Distribution– Metabolism– Excretion
• What is In silico drug discovery?
. Pharmacophore
identification and Pharmacophore Model
Generation (LigandScout)
Identification of Top-hits and potential
Lead Compounds. (Ranking of binding
energies)
Drug Discovery Strategy
Primary Sequence Analysis; degree
conservation (NCBI/Swiss-Prot)
Biological Problem (Biomedically Relevant Condition or Process)
Identification of optimal target (s)
for drug development
Identification of compounds that fulfill requirements of Pharmacophore model
Filtering Small chemical
compoundsDatabases
Target Analysis Number, quality and distance of “hot spots’
3D Structurewww.pdb.org
PyMol
BioAssay
Secondary Screening (AutoDock Vina)
Primary Screening:Pharmacophore Model
(ZINCPharmer)
High AffinityLead
Compounds
Further refinement of Pharmacophore
Model
FTMap and In Silico
screening ofchemical probes
Therapeutically relevant protein
targets
Docking/screening of Filtered Databases
B
C
D
A
Identification of Top-hits and potential
Lead Compounds. (Ranking of binding
energies)
Drug Discovery Strategy
Identification of compounds that fulfill requirements of Pharmacophore model
BioAssay
Secondary Screening (AutoDock Vina)
High AffinityLead
Compounds
Further refinement of
Pharmacophore Model
Docking/screening of
Filtered Databases
D
Work Plan
Work Plan• Run the Docking/Screening (“AutoDock Vina”)
– This is needed for the analysis of the top hits
– It is achieved by the utilization of the program Auto Dock• Download Results and Ranking of Top Hits
– For this, the programs CyberDuck and Excel were used.
– The results were downloaded and then opened with Excel to sort by affinity
– Select the drugs with the highest affinity
– Look for information about the drugs and take the pictures
Work Plan• Analyze Interactions
–Open Autodock and let the program analyze the results
–Take pictures of the interactions
Name AffinityZINC06716957 -11.4
ZINC14880002 -11.4
ZINC22940637 -10.6
CID_64143_Nelfinavir -10.5
Zinc14879987_Tipranavir -10.5
ZINC02570819 -10.4
ZINC00896717 -10.4
ZINC03951740 -10.4
zinc_3951740_lopinavir -10.4
ZINC22448696 -10.2
DMP -10
ZINC03914169 -10
ZINC52955754 -10
Zinc22448696_indinavir -10
Identification of Top-hitsSteps One and Two
Nilotinib• ZINC06716957 -11.4
• Tyrosine kinase inhibitor
• Chronic myelogenous leukemia treatment
• Hydrochloride monohydrate salt
• Oral ingestion
Lopinavir
• zinc_3951740_lopinavir -10.4
• Antiretroviral of the protease inhibitor class
• Used with ritonavir (protease inhibitor)
• Oral ingestion
Ergoloid• ZINC00896717 -10.4
• Mixture of methanesulfonate salts
• Used to treat dementia and age-related cognitive impairments
• Also used in a patients recovery after stroke
• Oral ingestion and parenteral
Zafirlukast• ZINC14880002 -11.4
• Oral ingestion
• Leukotriene receptor antagonist
• Inhibits what causes inflammation in respiratory system
Images of the Drug’s Interactions with the amino acids of the Proteases of HIV
Images of the Drug’s Interactions with the amino acids of the Proteases of HIV
• Due to technical difficulties with the program, the images of the other three drugs’ interactions with the amino acids of the proteases could not be presented.
• This images composed the last step: the analysis of the results.
Conclusion• The fourteen drugs with the highest affinity were
chosen.• These range from -10 to -11.4• Nilotinib, Lopinavir, Ergoloid, and Zafirlukast
were evaluated using AutoDock Vina, CyberDuck and Excel.
• The drugs with the highest affinity to the HIV related protein are Zafirlukast and Nilotinib.