MOLECULAR MODELING IN COMPUTER AIDED DRUG DESIGN
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Transcript of MOLECULAR MODELING IN COMPUTER AIDED DRUG DESIGN
G. Narahari Sastry
Molecular Modelling GroupOrganic Chemical Sciences
Indian Institute of Chemical TechnologyHyderabad – 500 007
[email protected]; [email protected]://203.199.182.73/gnsmmg
National Seminar on BioInformatics - Pondicherry
Drug Discovery & DevelopmentIt starts with disease identification
Isolate proteininvolved in disease (2-5 years)
Find a drug effectiveagainst disease protein(2-5 years)
Preclinical testing(1-3 years)
Formulation
Human clinical trials(2-10 years)
Scale-up
FDA approval(2-3 years)
Discovery and Development of Drugs
Discover mechanism of action of disease
Identify target protein
Screen known compounds against target or
Chemically develop promising leads
Find 1-2 potential drugs
Toxicity, pharmacology
Clinical Trials
Genomic Approach to Drug Discovery
Target Discovery
Existing Chemical and biochemical knowledge
Target gene annotation
Literature
Functional & comparative Genomics
Functionally validated target
A CBTarget
PrioritizationBiochemical & Cell
Based Assays
Drug Development Small molecule lead
Screening and improvementHTS+/- in silico SBDD
Therapeutic Application
Translated gene products
A B C
Sequence-structure analysis
Experimental Validation Comparative Proteomics
Genome data
GO terms 1. Molecular Function 2. Biological process 3. Cellular component
Role of targets in disease
Screening and Optimization Cycle with in-silico components
Structure based design
Target Selected
Assay developed
HTS Chemistry begins
Target structure obtained
Candidate taken forward
Database clustering
Similarity analysis
QSAR pharmacophore
Virtual Screening
106 small-molecule compounds
vHTS: MM + scoring functions
N x 102 leads
Filters: ADMET / QSAR
M x 101 leads
Filters: synthesis / manufacturing / IP / patent / biological assays
1 - 5 leads
Integration of Chemoinformatics and BioinformaticsIntegration of Chemoinformatics and Bioinformatics
Computational chemistry
SmallMolecules
Large MoleculeTargets
Genomic Biology
Bioinformatics Cheminformatics
In silico
HighThroughputScreening
Assays
Much About StructureMuch About Structure
• Structure Function
• Structure Mechanism
• Structure Origins/Evolution
• Structure Anything!!!
• Exact solutions are available only for Hydrogen atom.
• Modeling any realistic system needs approximations (mathematically not solvable)
• Plenty of approximations were put forward to tackle mathematic complexity
Quantum Mechanics
“The underlying physical laws necessary for the mathematical theory of…the whole of chemistry are thus completely known, and the difficulty is only that the exact application of these laws leads to equations much too
complicated to be soluble.” -P. A. M. Dirac
Chemistry is an experimental science
ExperimentalX-Ray
NMR
Structure, Stability
and Reactivity
Thermochemistry
…
…
ComputationalSemiempirical
Ab Initio
DFT
Molecular Dynamics
Simulations
Monte Carlo
…
ResultsFactual Data!!!
Understanding, Patterning and Predicting Qualitative theory, Concepts, Rules, CorrelationsBasis for Doing Science and Doing it Better
But alternative routes are attractive at times!!!
The Jargon of nomenclature • Molecular Modeling• Computational Chemistry• Theoretical Chemistry• Simulations• Quantum Chemistry• Computational Biology• Molecular Dynamics• Mathematical Chemistry
Central Paradigm: Deriving information on molecular systemswithout really synthesizing them.
Computational Chemistry
Quantum Mechanics (QM) Molecular Mechanics (MM)
Hybrid QM / MM Semi-empirical (SE)
The current scenario in chemistry
• Computation has become an effective alternative to explore the structural, energetic, mechanistic and other properties of small molecules (say less than 8-10 atoms).
SOMETIMES THE COMPUTATIONAL ACCURACY SUPERCEDES THE
EXPERIMNTAL ACCURACY
Every Computational Experiment at Any Level of Theory Yields an Answer… Usually Answers for Many Questions
Judging the Reliability is the Crucial Task
Just Like Experiments Fail, Computations Fail
However, the challenges are of different kind in modeling
chemistry and biology!!
It is not only the size but the philosophy!!!..!!!
The paradigm shift …
MESDAMESETMESSRSMYNAMEISWALTERYALLKINCALLMEWALLYIPREFERDREVILMYSELFIMACENTERDIRATVANDYINTENNESSEEILIKENMRANDDYNAMICSRPADNAPRIMASERADCALCYCLINNDRKINASEMRPCALTRACTINKARKICIPCDPKIQDENVSDETAVSWILLWINITALL
3D structure
Biological StructureBiological Structure
Organism
CellSystem Dynamics
CellStructures
SSBs
polymerase
Assemblies
helicase
primase
Complexes
Sequence
Structural Scales
Bottlenecks in developing Bottlenecks in developing Structure – Function RelationshipsStructure – Function Relationships
Structures determined by NMR, computation, or X-ray crystallography are static snapshots of highly dynamic molecular systems
Biological process (recognition, interaction, chemistry) require molecular motions and time dependent.
To comprehend and facilitate thinking about the dynamic structure of molecules is crucial.
Relevant timescalesRelevant timescales
10-15
femto10-12
pico10-9
nano10-6
micro10-3
milli100
seconds
Bond vibration
Isomeris-ation
Waterdynamics
Helixforms
Fastestfolders
typicalfolders
slowfolders
long MD run
where weneed to be
MDstep
where we’dlove to be
Conformational transitions
Enzyme catalysis
Ligand binding
Protein folding
How does the drug differ from an inhibitor?
SelectivityLess toxicityBioavailabilityReach the targetEase of synthesisLow priceSlow (or) no development of resistance Stability upon storage as tablet or solutionPharmacokinetic parametersNo allergies
Bioavailability (ADMET)
• ADMET• Adsorption• Distribution• Metabolism• Excretion• Toxicity
• Model and Predict:• Biotransformations & metabolites• Catalytic reactions• Drug-receptor interactions• GI physiology• Transepithelial transport• Epithelial permeability• Solubility• Toxicity
Ligand (analog)based drug design
Receptor structure is not knownMechanism is known/ unknownLigands and their biological activities are known
Target (structure) based drug design
Receptor structure is knownMechanism is knownLigands and their biological activities are known/ unknown
Various Steps InvolvedVarious Steps Involved
• Get the structure of the receptor
• Identify the active site
• Build a library of possible ligands
• Docking & Scoring
• Understand receptor-ligand interactions
• Design new ligands
Structure Based Ligand DesignStructure Based Ligand Design
O
NH
O
H
O
NH
?
O
O
O
H
O
NH
NSO
O
H
O
NH
O
H
O
NHS?
?
O
H
O
NH
??
?
OO
H
O
NH
DockingBuilding
Linking
CADD Success Stories• FKBP Ligand
• docking and scoring• P. Burkhard et al., J. Mol. Biol. 287, 853-858, 1999
• K+ ion channel blocker• fragment-based evolutionary design• G. Schneider et al., J. Computer-Aided Mol. Design 14, 487-494, 2000
• Ca2+ antagonist / T-channel blocker• pharmacophore similarity search• G. Schneider et al., Angew. Chem. Int. Ed. Engl. 39, 4130-4133, 2000
• Glyceraldehyde-phosphate DH inhibitors• combinatorial docking• J.C. Bressi et al., J. Med. Chem. 44, 2080-2093, 2001
• Thrombin inhibitor• docking, de-novo design• H.J. Bohm et al., J. Computer-Aided Mol. Design 13, 51-56, 1999
• HIV-1 RNA TAR inhibitor• docking, database search• A.V. Filikov et al., J. Computer-Aided Mol. Design 14, 593-610, 2000
• Aldose reductase inhibitors• 3-D database searching• Y. Iwata et al., J. Med. Chem. 44, 1718-1728, 2001
• DNA gyrase inhibitor• structure-based virtual screening• H.J. Boehm et al., J. Med. Chem. 43, 2664-2674, 2000
Broad Objectives: Aiding the experimentalists in Drug/Molecule/Reaction design
• Theoretical/computational approaches to bring insights which might trigger interest of the prospective experimental groups
(Usually with no collaboration with experimentalists)• Rationalizing the experimental finding with
computations and participate in the designing of experiments
(In collaboration with experimentalists or groups of experimentalists)
We strongly believe that while chemistry and biology are experimental sciences
THEORY-EXPERIMENT INTERPLAY IS INDISPENSABLE
In our pursuit to engage with experimentalists for lead discovery or optimization, our efforts become
restricted in the absence of an experimental structure of the receptor protein/enzyme.
When we analyze, it occurred to us that most of these ‘important target receptors’ whose structures are not available belong to the class of ‘membrane
proteins’.
Non-availability of the receptor structure is a bottleneck…
• Membrane proteins are those that exist in cell membranes.
• They can serve as structural supports, as both passive and active channels for ions and chemicals, or serve more specialized functions such as light reception.
• Membrane proteins form about 25% of all protein sequences.
(They constitute close to 70% of drug targets)
• Only 2% of PDB structures belong to membrane proteins!
MEMBRANE PROTEINS – What are they
Sastry et al, Computational Biology and Chemistry, 2006, in press
Membrane proteins form about 25% of all protein sequences. Only 2% of PDB structures belong to this class!
Membrane Proteins: Classification…
• Receptors for extracellular ligandsEx :- G-Protein coupled receptors Tyrosine kinase receptors
• Transport proteinsEx :- Molecular translocators Ion channels
• Membrane-bound enzymesEx :- Lipid synthases Cytochrome P-450 enzymes
• Proteins associated with cytoskeletal networkEx :- Cytoskeletal attachments
• Proteins associated with energy production Ex :- Photosynthetic complexes
Respiratory chain complexes
Challenges in computer simulations of membrane proteins.
•Heavy molecular weight and size.
•Their association with lipid bilayer.
•Technical limitations related to the accuracy of the
empirical potential function.
•Difficulties with accurately incorporating important variables
such as pH, transmembrane potential.
•Starting configuration of a simulation may also bias the
results in undesirable ways.
•Comparative protein modelling approaches are very
essentialSastry et al, Computational Biology and Chemistry, 2006, in press
•Membrane bound microsomal cytochrome P450 enzyme.•Converts androgens to estrogens by aromatisation of A-ring of steroids.•Estrogens and their carcinogenic metabolites are responsible for progression of breast cancer. WHAT IS THE ROLE OF THESE ACIDIC RESIDUES IN THE AROMATIZATION MECHANISM?
HUMAN AROMATASE: A PERIPHERAL MPHUMAN AROMATASE: A PERIPHERAL MP
PLAY A MAJOR ROLE IN STEROID ANDINHIBITOR BINDING.
HEME
ACIDIC RESIDUES
HOMOLOGY MODEL
Sastry et al, J. Com. Aided Mol. Design, 2006, in press
Our Attempts of Modeling Aromatase
• A protein model is constructed (based on CYP 2C5 (pdb code: 1NR6, sequence identity is found to be 28%)
• The role of acidic residues in controlling the function(substrate binding with androstenedione, testosterone and nor-androgens) is studied.
• Studies help in designing putative inhibitors to control the aromatase activity.
Sastry et al, J. Com. Aided Mol. Design, 2006, in press
MOLECULAR DYNAMICS SIMULATIONSBefore complexation to steroidal substrates
Environment suitable for carboxylate formation
High conformational flexibility
No H-bond interaction
ACTIVE SITE ACIDIC RESIDUES
MOLECULAR DOCKINGAfter complexation to steroidal substrates
A MOLECULE WHICH ARRESTS THESE PROPERTIES IS PROPOSED TO BE AN INHIBITOR
Flexibility decreases. Environmentsuitable for carboxylate formation.
CLAMPED !
H-Bond formation
Repulsive interaction predicted.
Inhibition of aromatase activity by 4-hydroxy androstenedione (formestane)
Critical H-bond between inhibitor and T310 hampering its’ role in the mechanism.
ACTIVE SITE
ONE COULD DESIGN A MOLECULEBY ADDING OR DELETING A GROUP FROM ANDROGENSKELETON TO ARREST THE
PROPERTIES OBSERVED FOLLOWINGCOMPLEXATION.
O
O
A
O
O
A
OH
ANDROSTENE-DIONE(Substrate)
FORMESTANE(Inhibitor)
Human 5-lipoxygenase (5-LO)-Peripheral MPHuman 5-lipoxygenase (5-LO)-Peripheral MP
MODELMODEL
Catalytic domainCatalytic domain
β-barrel domain
•5-LO catalyses the rate limiting steps in leukotriene synthesis. •Calcium binds reversibly to 5-LO, triggering its translocation from the cytoplasm to the nuclear membrane.
Ca(2+) binding
Mg(2+) binding
Tryptophan residues
Non-heme iron
Sastry et al, Biophys. Biochem. Res. Comm, 2004, 320, 461-467
barrel domainbarrel domain•Two calcium binding sites are identified ; ligating residues: F14, A15, G16, Two calcium binding sites are identified ; ligating residues: F14, A15, G16, D18, D19, L76 and D79. D18, D19, L76 and D79.
Ca(2+) location
Important residues which affect activity are marked.
Transmembrane
Lumenal
CytoplasmicATP binds here
Phosphorylation.
Inhibitor binding sites.
E1E2
•Expose ion binding sites sequentially to each side of the membrane.Expose ion binding sites sequentially to each side of the membrane.
Cation binding sites
Sastry et al, Biophys. Biochem. Res. Comm, 2004, 319, 312-320; Biophys. Biochem. Res. Comm, 2005, 336, 961-966
Gastric Proton Pump H(+)K(+)-ATPase – Integral MPGastric Proton Pump H(+)K(+)-ATPase – Integral MPANTI-ULCER TARGETANTI-ULCER TARGET
Inhibitor binding sites
CYS323
CYS815Omeprazole
Covalent linkage
Inhibitor Binding in TM region
However, the large SBA in E2 precludes the covalent binding of Cys815 to omeprazole. This suggested another intermediate conformation with slightly more exposed Cys815. The existence of stable intermediate structures has been proved in 2004.
Cation binding in E1 conformation
H3O+
H3O+
Cα – carbons of arenes in the pump.Regular dispositionaids hydronium transport.
T825
Q941
E797
N794
A341
V340
V343
E345E822
D826
Proposed hydronium binding.
Amino acid ligands (D,E,N,Q) that bind to metal ions in proteins
In general, the acidic amino acid or their amides (ASP, GLU, ASN, GLN) are present in the ligating sphere of the cations (Ca, Na, K, Mg, etc.) .Additional ligating amino acid residues: Ala, Val, Thr, Leu, Phe etc.
Typical non-covalent binding to cations (from PDB). The distances between the ligating atoms and ion vary for different cations.
# of Binding structures for metals
PDB (June 2004)
Ca2+ : 2020; Cu(II) : 298 Ni(II) : 118
Na+ : 678; Mn (II) : 454 Co(II) :101
K+ : 258; Fe (II) : 100 Fe(III) :269
Mg2+ : 1167; Zn (II) : 1545
Asp Glu Asn Gln
An investment in knowledgeAn investment in knowledge pays the best interest. pays the best interest.
Benjamin FranklinBenjamin Franklin
CAUTION….
macromolecular structure
protocols
methods
Structure determinations methods
•Don't be a naive user!?!
•When computers are applied to biology, it is vital to understand the difference between mathematical & biological significance
•computers don’t do biology, they do sums quickly
DoneDone99 98 97 96 95 94 93 92 91
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It’s like a game of LUDO
Drug Discovery
““This isn’t rocket science. This isn’t rocket science. This is much harder.”This is much harder.”
-- Alan Holmer-- President, PhRMA
GNS, Dr. G. Madhavi Sastry, Dr. Y. Soujanya, Srinivas Reddy, Punnagai, Gayatri, Srivani, Sateesh, Nagaraju, Dolly, Srinivasa Rao, Prasad, Mukesh, Murty, Usha Rani, Srinivas, Janardhan, Bharat, Upendra.Past Ph.D. students: Dr. U. Deva Priyakumar, Mr. T.C. Dinadayalane