in silico discovery of inhibitors using structure-based approaches jasmita gill structural and...
TRANSCRIPT
![Page 1: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/1.jpg)
In silico discovery of inhibitors using
structure-based approaches
Jasmita Gill
Structural and Computational Biology Group,
ICGEB, New Delhi
Nov 2005
![Page 2: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/2.jpg)
Target protein 3D structure
Find an inhibitor
Molecular modeling
In silico screening
Computational Techniques
Computational approach
![Page 3: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/3.jpg)
In silico screening
Structure based virtual screening
docking methods to fit putative ligands into 3D structure of target receptor
![Page 4: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/4.jpg)
Structure-based inhibitor discovery
3D structure of target protein Public drug-like in silico libraries
In silico screening
Short listed hits provided for testing in biological assays
Binding site (s) identification
Post-scoring and analysis of results
Literature, Visual analysis
FlexX
Cscore, Visual analysis, Unity
VendorsProtein Data Bank
![Page 5: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/5.jpg)
Sybyl® – Molecular modelling suite
Tools and Techniques
Analysis of molecular surfaces of proteins
Preparation of target protein and ligand(s) for screening
Screening utility -- FlexX
Post-scoring -- Cscore
Data Mining -- Unity
Public in silico chemical compound libraries used
![Page 6: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/6.jpg)
FlexX – an overview
Input
OutputEnergetically best ranked ligand placements in target site (s)
Each placement has variable conformations
Target protein with pre-defined active site (s)
and
Ligands with designated base fragment (s)
Thomas Lengauer et. al, J Mol. Bio. 1996
![Page 7: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/7.jpg)
- Multiple conformations determined by torsion angles of
acyclic single bonds in the ligands
- Low energy conformation of the complex is the goal
Considerations in FlexX
Receptor target protein rigid
Ligand Conformational Flexibility
![Page 8: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/8.jpg)
Modeling protein-ligand interactions
Interaction geometries
protein ligand
Interactions types
H-acceptor H-donor
Metal acceptor Metal
Aromatic-ring-atom,
Methyl, amide
Aromatic-ring-center
Main scoring criteria
Free energy of binding of protein-ligand
Consensus scoring ‘Cscore’
![Page 9: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/9.jpg)
Public drug-like in silico libraries
• A database of structures of small molecule compounds
• Most libraries are free to download
• Lead-like properties
• Available for purchase
Name No. of Compounds
NCI Diversity set
NCI Open Collection
1990
~200,000
Maybridge ~95,000
Specs ~202,000
Peakdale ~20,000
![Page 10: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/10.jpg)
In silico Screening
Preparation of the target protein structure
Templates for charged, neutral, non-polar residues
Charges Hydrogens
Preparation of ligand structure Charges Hydrogens Filtering was done based on Lipinski’s rule of 5
Mw < 500 daltons (relaxed, <=900) H-bond acceptors < 10 H-bond donors < 5 ClogP (solubility indicator) < 5
Definition of binding site (s) : whole protein in case of Pfg27
![Page 11: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/11.jpg)
Final output of screening:
Ranking based on free energy of binding of protein-ligand complex
Visual
Mathematical
Binding sites to which compounds docked
Conformations
H-bonding interactions
Hydrophobic interactions
Van Der Waals attractions
Cscore
Screening results
Analysis
![Page 12: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/12.jpg)
Application to Pfg27
![Page 13: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/13.jpg)
Binding sites of interest on Pfg27
• Two RNA binding sites per dimer
• Four SH3 binding sites per dimer
• A dimer interface
From literature
• Revealed a deep cavity on a unique surface
Visual/computational analysis
![Page 14: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/14.jpg)
RNA binding site
SH3 binding site (N)
Dimer interface
RNA binding site
Deep cavity
![Page 15: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/15.jpg)
Colour coding
Basic
Acidic
Non-polar
Polar
![Page 16: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/16.jpg)
Deep cavity
Depth
Surface
Deepest cavity in Pfg27
![Page 17: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/17.jpg)
Cavities in the dimer interface
Cavities
![Page 18: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/18.jpg)
SH3 binding site
Cavity
Cavities in the SH3 binding site (N)
![Page 19: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/19.jpg)
Cavities in the RNA binding site
Multiple cavities of different depths
![Page 20: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/20.jpg)
NCI-diversity set: 1820 compounds
30% in the RNA binding site
30% in the dimer interface
20% in deep cavity
10% in SH3 binding site (N)
10% on other sites
Docking patterns on Pfg27
Visual analysis of top 200
![Page 21: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/21.jpg)
• Best binding energies observed:
from -44.363 KJ/mol to –24.056 KJ/mol
• Chemical composition Most hits had an electronegative character: N, O-, SO3
-, Cl-, F-, Br-
• CLogP: –3.59 to 1 (-4 to 4 range is acceptable for solubility)
• Cscore
3 to 5 (a good score is 4-5)
Score of 3 – 37 compounds
Score of 4 – 43 compounds
Score of 5 – 48 compounds
Analysis of top 200 compounds
![Page 22: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/22.jpg)
Dockings in the RNA binding site
Most compounds interact with Arg70, Arg74, Arg78, Arg80 and Val71
![Page 23: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/23.jpg)
Dockings in the deep cavity
Most compounds interact with Ser107, Lys112 and Ile122
![Page 24: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/24.jpg)
Dockings at the dimer interface
Most compounds interact with Asp40, Arg36, Glu134, Arg131, Phe43, Leu126, Trp127
![Page 25: In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005](https://reader036.vdocuments.site/reader036/viewer/2022062517/56649f005503460f94c15f99/html5/thumbnails/25.jpg)
Dockings in SH3 binding sites
Most hits interact with Arg34