Network Pharmacology Tri-Con 022212

Computational Approaches in Network Pharmacology Philip E. Bourne University of California San Diego [email_address] http://www.sdsc.edu/pb Tri-Con San Francisco, Feb. 22, 2012

Big Questions in the Lab
Can we improve how science is disseminated and comprehended?
What is the ancestry and organization of the protein structure universe and what can we learn from it?
Are there alternative ways to represent proteins from which we can learn something new?
What really happens when we take a drug?
Can we contribute to the treatment of neglected {tropical} diseases?
Motivators

Our Motivation
Tykerb – Breast cancer
Gleevac – Leukemia, GI cancers
Nexavar – Kidney and liver cancer
Staurosporine – natural product – alkaloid – uses many e.g., antifungal antihypertensive
Collins and Workman 2006 Nature Chemical Biology 2 689-700 Motivators

Our Broad Approach
Involves the fields of:
Structural bioinformatics
Cheminformatics
Biophysics
Systems biology
Pharmaceutical chemistry
L. Xie, L. Xie, S.L. Kinnings and P.E. Bourne 2012 Novel Computational Approaches to Polypharmacology as a Means to Define Responses to Individual Drugs, Annual Review of Pharmacology and Toxicology 52 : 361-379
L. Xie, S.L. Kinnings, L. Xie and P.E. Bourne 2012 Predicting the Polypharmacology of Drugs: Identifying New Uses Through Bioinformatics and Cheminformatics Approaches in Drug Repurposing M. Barrett and D. Frail (Eds.) Wiley and Sons. (available upon request)
Disciplines Touched & 2012 Reviews

A Quick Aside – RCSB PDB Pharmacology/Drug View 2012
Establish linkages to drug resources (FDA, PubChem, DrugBank, ChEBI, BindingDB etc.)
Create query capabilities for drug information
Provide superposed views of ligand binding sites
Analyze and display protein-ligand interactions
Mockups of drug view features RCSB PDB’s Drug Work RCSB PDB Team Led by Peter Rose Drug Name Asp Aspirin Has Bound Drug % Similarity to Drug Molecule 100

A Quick Aside PDB Scope/Deliverables
Part I: small molecule drugs, nutraceuticals, and their targets ( DrugBank) - 2012
Part II: peptide derived compounds (PRD)- tbd
Part III: toxins and toxin targets (T3DB), human metabolites (HMDB)
Part IV: biotherapeutics, i.e., monoclonal antibodies
Part V: veterinary drugs (FDA Green Book)
RCSB PDB’s Drug Work

Our Approach
We characterize a known protein-ligand binding site from a 3D structure (primary site) and search for similar sites (secondary sites) on a proteome wide scale independent of global structure similarity
We try a static and dynamic network-based approach to understand the implications of drug binding to multiple sites
Methodology

Applications Thus Far
Repositioning existing pharmaceuticals and NCEs (e.g., tolcapone, entacapone, nelfinavir )
Early detection of side-effects ( J&J )
Late detection of side-effects ( torcetrapib )
Lead optimization (e.g., SERMs, Optima, Limerick )
Drugomes ( TB , P. falciparum, T. cruzi)
Applications

Approach - Need to Start with a 3D Drug-Receptor Complex – Either Experimental or Modeled Computational Methodology Generic Name Other Name Treatment PDBid Lipitor Atorvastatin High cholesterol 1HWK, 1HW8… Testosterone Testosterone Osteoporosis 1AFS, 1I9J .. Taxol Paclitaxel Cancer 1JFF, 2HXF, 2HXH Viagra Sildenafil citrate ED, pulmonary arterial hypertension 1TBF, 1UDT, 1XOS.. Digoxin Lanoxin Congestive heart failure 1IGJ

Some Numbers to Show Limitations TB-drugome pF-Drugome Target gene 3996 5491 Target protein in PDB 284 136 Solved structure in PDB 749 333 Reliable homology models 1446 1236 S tructure coverage 43.29% 25.02% Drugs 274 321 Drug binding sites 962 1569

A Reverse Engineering Approach to Drug Discovery Across Gene Families Characterize ligand binding site of primary target (Geometric Potential) Identify off-targets by ligand binding site similarity (Sequence order independent profile-profile alignment) Extract known drugs or inhibitors of the primary and/or off-targets Search for similar small molecules Dock molecules to both primary and off-targets Statistics analysis of docking score correlations … Computational Methodology Xie and Bourne 2009 Bioinformatics 25(12) 305-312

Initially assign C  atom with a value that is the distance to the environmental boundary
Update the value with those of surrounding C  atoms dependent on distances and orientation – atoms within a 10A radius define i
Conceptually similar to hydrophobicity
or electrostatic potential that is
dependant on both global and local
environments
Characterization of the Ligand Binding Site - The Geometric Potential Xie and Bourne 2007 BMC Bioinformatics, 8(Suppl 4):S9 Computational Methodology

Discrimination Power of the Geometric Potential
Geometric potential can distinguish binding and non-binding sites
100 0 Geometric Potential Scale Computational Methodology Xie and Bourne 2007 BMC Bioinformatics, 8(Suppl 4):S9 For Residue Clusters

Local Sequence-order Independent Alignment with Maximum-Weight Sub-Graph Algorithm L E R V K D L L E R V K D L Structure A Structure B
Build an associated graph from the graph representations of two structures being compared. Each of the nodes is assigned with a weight from the similarity matrix
The maximum-weight clique corresponds to the optimum alignment of the two structures
Xie and Bourne 2008 PNAS , 105(14) 5441 Computational Methodology

Similarity Matrix of Alignment
Chemical Similarity
Amino acid grouping: (LVIMC), (AGSTP), (FYW), and (EDNQKRH)
Amino acid chemical similarity matrix
Evolutionary Correlation
Amino acid substitution matrix such as BLOSUM45
Similarity score between two sequence profiles
f a , f b are the 20 amino acid target frequencies of profile a and b , respectively S a , S b are the PSSM of profile a and b , respectively Computational Methodology Xie and Bourne 2008 PNAS , 105(14) 5441

Applications

Nelfinavir
Nelfinavir may have the most potent antitumor activity of the HIV protease inhibitors
Joell J. Gills et al, Clin Cancer Res, 2007; 13(17)
Warren A. Chow et al, The Lancet Oncology, 2009, 10(1)
Nelfinavir can inhibit receptor tyrosine kinase(s)
Nelfinavir can reduce Akt activation
Our goal:
to identify off-targets of Nelfinavir in the human proteome
to construct an off-target binding network
to explain the mechanism of anti-cancer activity
Possible Nelfinavir Repositioning PLoS Comp. Biol. , 2011 7(4) e1002037

Possible Nelfinavir Repositioning

binding site comparison protein ligand docking MD simulation & MM/GBSA Binding free energy calculation structural proteome off-target? network construction & mapping drug target Clinical Outcomes 1OHR Possible Nelfinavir Repositioning

Binding Site Comparison
5,985 structures or models that cover approximately 30% of the human proteome are searched against the HIV protease dimer (PDB id: 1OHR)
Structures with SMAP p-value less than 1.0e-3 were retained for further investigation
A total 126 structures have significant p-values < 1.0e-3
Possible Nelfinavir Repositioning PLoS Comp. Biol. , 2011 2011 7(4) e1002037

Enrichment of Protein Kinases in Top Hits
The top 7 ranked off-targets belong to the same EC family - aspartyl proteases - with HIV protease
Other off-targets are dominated by protein kinases (51 off-targets) and other ATP or nucleotide binding proteins (17 off-targets)
14 out of 18 proteins with SMAP p-values < 1.0e-4 are protein kinases

Distribution of Top Hits on the Human Kinome p-value < 1.0e-3 p-value < 1.0e-4 Manning et al., Science , 2002, V298, 1912 Possible Nelfinavir Repositioning

Interactions between Inhibitors and Epidermal Growth Factor Receptor (EGFR) – 74% of binding site resides are comparable 1. Hydrogen bond with main chain amide of Met793 (without it 3700 fold loss of inhibition) 2. Hydrophobic interactions of aniline/phenyl with gatekeeper Thr790 and other residues H-bond: Met793 with quinazoline N1 H-bond: Met793 with benzamide hydroxy O38 EGFR-DJK Co-crys ligand EGFR-Nelfinavir DJK = N-[4-(3-BROMO-PHENYLAMINO)-QUINAZOLIN-6-YL]-ACRYLAMIDE

Off-target Interaction Network Identified off-target Intermediate protein Pathway Cellular effect Activation Inhibition Possible Nelfinavir Repositioning PLoS Comp. Biol. , 2011 7(4) e1002037

Other Experimental Evidence to Show Nelfinavir inhibition on EGFR, IGF1R, CDK2 and Abl is Supportive The inhibitions of Nelfinavir on IGF1R, EGFR, Akt activity were detected by immunoblotting. The inhibition of Nelfinavir on Akt activity is less than a known PI3K inhibitor Joell J. Gills et al. Clinic Cancer Research September 2007 13; 5183 Nelfinavir inhibits growth of human melanoma cells by induction of cell cycle arrest Nelfinavir induces G1 arrest through inhibition of CDK2 activity. Such inhibition is not caused by inhibition of Akt signaling. Jiang W el al. Cancer Res. 2007 67(3) BCR-ABL is a constitutively activated tyrosine kinase that causes chronic myeloid leukemia (CML) Druker, B.J., et al New England Journal of Medicine, 2001. 344 (14): p. 1031-1037 Nelfinavir can induce apoptosis in leukemia cells as a single agent Bruning, A., et al. , Molecular Cancer, 2010. 9 :19 Nelfinavir may inhibit BCR-ABL Possible Nelfinavir Repositioning

Summary
The HIV-1 drug Nelfinavir appears to be a broad spectrum low affinity kinase inhibitor
Most targets are upstream of the PI3K/Akt pathway
Findings are consistent with the experimental literature
More direct experiment is needed

Applications

Case Study: Torcetrapib Side Effect
Cholesteryl ester transfer protein ( CETP ) inhibitors treat cardiovascular disease by raising HDL and lowering LDL cholesterol (Torcetrapib, Anacetrapib, JTT-705).
Torcetrapib withdrawn due to occasional lethal side effect, severe hypertension .
Cause of hypertension undetermined; off-target effects suggested.
Predicted off-targets include metabolic enzymes. Renal function is strong determinant of blood pressure. Causal off-targets may be found through modeling kidney metabolism.

Constraint-based Metabolic Modeling S · v = 0 Matrix representation of network Metabolic network reactions Flux space Change in system capacity Perturbation constraint Steady-state assumption Flux

Recon1: A Human Metabolic Network (Duarte et al Proc Natl Acad Sci USA 2007) http://bigg.ucsd.edu Global Metabolic Map Comprehensively represents known reactions in human cells Pathways (98) Reactions (3,311) Compounds (2,712) Genes (1,496) Transcripts (1,905) Proteins (2,004) Compartments (7)

Context-specific Modeling Pipeline metabolic network metabolomic biofluid & tissue localization data constrain exchange fluxes preliminary model gene expression data refine based on capabilities set flux constraints objective function literature GIMME normalize & set threshold set minimum objective flux model metabolic influx metabolic efflux

Predicted Hypertension Causal Drug Off-Targets *Clinically linked to hypertension.

Applications

The Future as a High Throughput Approach…..

The Problem with Tuberculosis
One third of global population infected
1.7 million deaths per year
95% of deaths in developing countries
Anti-TB drugs hardly changed in 40 years
MDR-TB and XDR-TB pose a threat to human health worldwide
Development of novel, effective and inexpensive drugs is an urgent priority
Repositioning - The TB Story

The TB-Drugome
Determine the TB structural proteome
Determine all known drug binding sites from the PDB
Determine which of the sites found in 2 exist in 1
Call the result the TB-drugome
A Multi-target/drug Strategy Kinnings et al 2010 PLoS Comp Biol 6(11): e1000976

1. Determine the TB Structural Proteome
High quality homology models from ModBase (http://modbase.compbio.ucsf.edu) increase structural coverage from 7.1% to 43.3%
284 1, 446 3, 996 2, 266 TB proteome homology models solved structures A Multi-target/drug Strategy Kinnings et al 2010 PLoS Comp Biol 6(11): e1000976

2. Determine all Known Drug Binding Sites in the PDB
Searched the PDB for protein crystal structures bound with FDA-approved drugs
268 drugs bound in a total of 931 binding sites
No. of drug binding sites Methotrexate Chenodiol Alitretinoin Conjugated estrogens Darunavir Acarbose A Multi-target/drug Strategy Kinnings et al 2010 PLoS Comp Biol 6(11): e1000976

Map 2 onto 1 – The TB-Drugome http://funsite.sdsc.edu/drugome/TB/ Similarities between the binding sites of M.tb proteins (blue), and binding sites containing approved drugs (red).

From a Drug Repositioning Perspective
Similarities between drug binding sites and TB proteins are found for 61/268 drugs
41 of these drugs could potentially inhibit more than one TB protein
No. of potential TB targets raloxifene alitretinoin conjugated estrogens & methotrexate ritonavir testosterone levothyroxine chenodiol A Multi-target/drug Strategy Kinnings et al 2010 PLoS Comp Biol 6(11): e1000976

Top 5 Most Highly Connected Drugs Drug Intended targets Indications No. of connections TB proteins levothyroxine transthyretin, thyroid hormone receptor α & β -1, thyroxine-binding globulin, mu-crystallin homolog, serum albumin hypothyroidism, goiter, chronic lymphocytic thyroiditis, myxedema coma, stupor 14 adenylyl cyclase, argR , bioD, CRP/FNR trans. reg ., ethR , glbN , glbO, kasB , lrpA , nusA , prrA , secA1 , thyX , trans. reg. protein alitretinoin retinoic acid receptor RXR- α , β & γ , retinoic acid receptor α , β & γ -1&2, cellular retinoic acid-binding protein 1&2 cutaneous lesions in patients with Kaposi's sarcoma 13 adenylyl cyclase, aroG , bioD, bpoC, CRP/FNR trans. reg. , cyp125 , embR , glbN , inhA , lppX , nusA , pknE , purN conjugated estrogens estrogen receptor menopausal vasomotor symptoms, osteoporosis, hypoestrogenism, primary ovarian failure 10 acetylglutamate kinase, adenylyl cyclase, bphD , CRP/FNR trans. reg. , cyp121 , cysM, inhA , mscL , pknB , sigC methotrexate dihydrofolate reductase, serum albumin gestational choriocarcinoma, chorioadenoma destruens, hydatidiform mole, severe psoriasis, rheumatoid arthritis 10 acetylglutamate kinase, aroF , cmaA2 , CRP/FNR trans. reg. , cyp121 , cyp51 , lpd , mmaA4 , panC , usp raloxifene estrogen receptor, estrogen receptor β osteoporosis in post-menopausal women 9 adenylyl cyclase, CRP/FNR trans. reg., deoD, inhA, pknB , pknE , Rv1347c , secA1, sigC

Vignette within Vignette
Entacapone and tolcapone shown to have potential for repositioning
Direct mechanism of action avoids M. tuberculosis resistance mechanisms
Possess excellent safety profiles with few side effects – already on the market
In vivo support
Assay of direct binding of entacapone and tolcapone to InhA reveals a possible lead with no chemical relationship to existing drugs
Kinnings et al. 2009 PLoS Comp Biol 5(7) e1000423

Summary from the TB Alliance – Medicinal Chemistry
The minimal inhibitory concentration (MIC) of 260 uM is higher than usually considered
MIC is 65x the estimated plasma concentration
Have other InhA inhibitors in the pipeline
Repositioning - The TB Story Kinnings et al. 2009 PLoS Comp Biol 5(7) e1000423

Acknowledgements Sarah Kinnings Lei Xie Li Xie http://funsite.sdsc.edu Roger Chang Bernhard Palsson Jian Wang

Network Pharmacology Tri-Con 022212

by Philip Bourne

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