Drug Discovery and Development Process

Research team formed and objectives test Novel chemical synthesis

Chemicals tested for efficacy and safety in test tubes and animals. Results used to choose drug candidate

Formulation, stability scale-up synthesis, chronic safety in animals

Company fileInvestigational NewDrug application with FDA

Clinical studies:Phase I, II, and III

Company filesNew Drug

Application (NDA)

FDA reviews NDADrug is approved formarketing

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Drug Design• Drug design is an integrated developing discipline which

means era of ‘tailored drug’.

• It involves the study of effects of biologically activecompounds on the basis of molecular interactions in terms ofmolecular structure or its physicochemical propertiesinvolved.

• It studies the processes by which the drug produce theireffects, how they react with the protoplasm to elicit aparticular pharmacological effect or response how they aremodified or detoxified, metabolized or eliminated by theorganism.

• The biological activity may be “positive” as in drug design or “negative” as in toxicology.

• Drug design involves either total innovation of a molecule or an optimization of already available one.

• The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient.

• In the most basic sense, drug design involves the design of small molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it.

• Drug design frequently but not necessarily relies on computer modelling techniques. This type of modelling is often referred to as computer-aided drug design.

Pharmacokinetics of Drug Design

• Drugs must be polar - to be soluble in aqueous conditions to interact with molecular targets

• Drugs must be ‘fatty’ - to cross cell membranes to avoid rapid excretion

• Drugs must have both hydrophilic and lipophilic characteristics

Traditional vs. Contemporary Approaches

Traditional vs. rational drug design• Traditional is the origin of discovery from natural and accidental

cases.

• It was not targeted, but advancement in the pharmaceuticalsciences changed them to the systemized modern drug discovery.

• Traditional discoveries were through random discovery, trials,ethnopharmacology, serendipity, and classical pharmacology

Examples of traditional approach, such as using cinchona bark(quinine) to reduce fever, licorice roots in sore throats and stomachulcer, penicillin, etc.

Rational drug design

Developing molecules as a ligand either for targetsknown the structure and function or the structuralinformation not known; however, it has predefinedproperties and information can be taken from globalgene expression data.

Rational drug design

It can be divided in to 1. Ligand based drug designa. QSARb. Pharmacophore investigation2. Structure based drug designa. Docking b. De novo drug design

Hit Compound• Once a promising drug target has been identified, researchers

aim to identify molecules that can interact with the target toproduce desired biological effects.

• A hit compound is a molecule that shows the desired type ofactivity in a screening assay.

• It is important to develop pharmacologically relevantscreening assays for hit discovery and for the subsequent hit-to-lead selection process.

Lead compound• Lead compound is a prototype compound that has the desired

biological or pharmacological activity but may have manyundesirable characteristics.

• Providing lead compounds (via traditional medicines, naturalproducts, biological macromolecules, compound libraries,computational chemistry, etc.)

• Lead compounds are selected from a collection of hits by refiningthe screening criteria to enable the selection of the most promisingmolecules for further development. The secondary assaysemployed for lead selection may screen for off-target effects as wellas physicochemical and ADME (absorption, distribution,metabolism and excretion) characteristics.

1. Where is the starting point of drug discovery?

2. What are the essential causes of the drugs fail to reach the clinic?

3. What are the characteristics of good target?4. What are the types of target?

Good target characteristics

• Plays a critical role in health-related issues• Modulated without killing human or serious

harmful effect• The structure of the target should be unique• Well defined molecular structure of the target• Modulate through designing small molecule

• Target sites are enzymes, receptors, ion channels, DNA, RNA, proteins, viral surface proteins, etc.

• What are the most targets of the current drugs?

• Many experts believe that “without a well-validated targets, pharmaceutical companies unable to maintain current level of profitability” therefore, it’s one of the stressing issues in the R&D.

• The process of the design of drugs typically involves understanding the character of targets (e.g. enzyme, cell, tissues, etc) related to the disease.

H to L LD and LOHit Lead Candidate

H to L: focus on target potency and selectivity; defined in vitro properties profile.LD: focus on identifying a novel compound with the desired activity in vitro and vivo, with refinement of physical properties.LO: focus on fine tuning ADMET properties to identify one or more preclinical development candidates.

Hit to Lead evolved in the 1990’s to addressa growing problem with drug candidate failures

• In the “old” days—

Ø Focus only on potency; SAR advancement emphasized potency

with minimal consideration of other attributesØ Result: compounds with poor bioavailability, high

clearance, high risk off-target effects, low solubility and low dissolution properties, clinical trial failures

Ø Success rate of drug candidates from candidate nomination to market: 4-6%

The modern day H to L process was developed to identify and eliminate poor quality leads right up front

• Different screening strategies can be applied

1. Literature2. HTS3. Phenotypic screening4. Computer Aided Drug DesignA. Structure-based drug designB. Ligand-based drug designC. Fragment screeningD. Virtual screening (Docking and Scoring)

1. The source of the hit• Natural product leads tend to be structurally complex

2. The nature of the screening library• Historical compound collections are a legacy of past discovery programs;

poorly managed DMSO solvated libraries may show considerable degradation

3. The quality and precision of the screening method• Noisy or low resolution screens introduce high false positives

4. The nature of the molecular target• Molecular targets designed to interact with lipoidal ligands/substrates

tend to favor lipophilic hits; protein-protein interfaces favor structurally complex (high MW) ligands

• Molecular weight (MW)• Molecular volume and dimensions• Calculated partition coefficient (clogP)• Rotatable bonds• Total polar surface area (tPSA)• Aromatic rings• Hydrogen bond donors and acceptors• Physical properties influence the behavior of a compound in

the tissue and the effectiveness of the treatment• Properties for most marketed drugs fall within a well-defined

range of values• Lipinski’s ‘Rule of 5’ used to define potential drug candidates

Lipinski’s Rule of Fives

It also known as the Pfizer's rule of five or simplythe Rule of five (RO5) is a rule of thumb to evaluatedrug likeness or determine if a chemical compoundwith a certain pharmacological or biological activityhas properties that would make it a likely orallyactive drug in humans. The rule was formulated byChristopher A. Lipinski in 1997, based on theobservation that most medication drugs arerelatively small and lipophilic molecules.

• The rule describes molecular properties important fora drug's pharmacokinetics in the human body,including their absorption, distribution, metabolism,and excretion("ADME"). However, the rule does notpredict if a compound is pharmacologically active.

• The rule is important to keep in mind during drugdiscovery when a pharmacologically active leadstructure is optimized step-wise to increase the activityand selectivity of the compound as well as to insuredrug-like physicochemical properties are maintained asdescribed by Lipinski's rule. Candidate drugs thatconform to the RO5 tend to have lower attrition ratesduring clinical trials and hence have an increasedchance of reaching the market

Components of the rule :

• Lipinski's rule states that, in general, an orally active drug has no more than one violation of the following criteria:

• Not more than 5 hydrogen bond donors (nitrogen or oxygen atoms with one or more hydrogen atoms)

• Not more than 10 hydrogen bond acceptors (nitrogen or oxygen atoms)

• A molecular mass less than 500 Daltons• An octanol-water partition coefficient log P not greater

than 5

Lipinski “Rule of 3” for “Lead-Like” Hits• MW < 300• H-bond donors ≤ 3• H-bond acceptors ≤ 6• cLogP < 3Additional considerations:• tPSA < 60 ang2

• CADD is also called in silico drug design.• It is based on computationally synthesising molecules and analysing

molecular interactions to assist and speed up hit molecule identification,lead selection and optimisation and also to predict potentialpharmacokinetic difficulties.

• CADD can considerably reduce the time, cost and workload in drugdiscovery projects; for example, selecting compounds from a library ofmolecules through virtual screening before experimental tests couldproduce the same level of lead identification at much reduced time andcost.

• It has the potential to improve efficacy, reduce toxicity and optimisepharmacokinetic activities of the selected molecules.

• It may be applied to design new molecules or modify existing structures toproduce a novel compound.

Virtual Screening •  Virtual screening refers to a range of in-silico techniques used to

search large compound databases to select a smaller number for biological testing

•  Virtual screening can be used to

−  Select compounds for screening from in-house databases

−  Choose compounds to purchase from external suppliers

−  Decide which compounds to synthesise next

•  The technique applied depends on the amount of information available about the particular disease target

•  Typical goal is to find a lead compound that can be optimised to give a drug candidate

−  Optimisation: using chemical synthesis to modify the lead molecule in order to improve its chances of being a successful drug

Virtual Screening

Ligand-Based Methods

Structure-Based Methods

Unknown

3D Structure of Target

Known

Actives known Actives and inactives known

Machine learning methods

Pharmacophore mapping

Similarity searching

Protein Ligand Docking

• Ligand-based drug design (LBDD) is one of the approaches of in

silico drug design to find a lead molecule and optimise it when the

3D structure of the potential target is typically unknown.

• Structural investigations of the ligand molecule and its

pharmacophore are performed.

• Because LBDD is a ligand knowledge-based technique, previous

information from active ligands is used to build up a picture of the

similarity of the active sites and functional groups.

Rationale for similarity searching

•  The similar property principle states that structurally similar molecules tend to have similar properties

•  Basis of medicinal chemistry efforts and of all ligand-based virtual screening methods −  Despite the existence of “activity cliffs”

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hydrogen bond acceptor (HBA) feature + projected

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hydrophobic feature

hydrophobic feature

aromatic ring feature + projected

point

Cannabinoid Receptor 1 (CB1) antagonist pharmacophore

other common feature types (not used here): •  hydrogen bond donor •  positive/negative features (charged/ionizable) •  customized features •  inclusion/exclusion volume spheres (shape)

Example: Rimonabant

• It can also be described as a receptor-based drug design, encompasses identifying a lead compound and optimising it on the basis of knowledge of the 3D crystal or nuclear magnetic resonance (NMR) structure of the potential target.

• Docking and screening are applied to a library of selected molecules to find the most appropriate molecule as a novel compound to activate or inhibit (as required) the target receptor through predicting interaction energies between them.

• Detailed structural information on the target is the basis for designing ligand molecules and then docking.

• A major factor driving the development of SBDD has been the proteomic and genomic evolution, which has resulted in the production of hundreds of new proteins and availability of their high-resolution X-ray crystal structures that can be used as potential drug targets.

• Most of the high resolution crystal structures of approximately one hundred thousand proteins are published in the Protein Data Bank (PDB) and Cambridge Crystallographic Data Centre that can be used as potential sources for SBDD.

• Formerly, static structures of the proteins were used in SBDD, but in reality, protein samples are ensembles of various conformation states, each conformation has a different free energy.

• Usually, proteins occupy a low energy state that their structures may be significantly different from the crystal structure; consequently, docking ligands to a single, specific conformation of the receptor may well lead to incorrect predictions, as it may not be the ligand bound conformation.

• Now molecular dynamics and molecular modelling computational tools are helping solve these issues, as they can simulate and estimate a protein’s conformational space as a collection of snapshots for each protein structure describing their fluctuations due to conformational sampling.

Protein-Ligand Docking

•  How does a ligand (small molecule) bind into the active site of a protein?

•  Docking algorithms are based on two key components −  search algorithm

•  to generate “poses” (conformation, position and orientation) of the ligand within the active site

−  scoring function •  to identify the most likely pose for an individual ligand •  to assign a priority order to a set of diverse ligands docked to the

same protein – estimate binding affinity

Issues related to the protein

•  Need to ensure all residues are in the correct protonation and tautomeric states

•  Protein conformation −  Can be several examples of the same protein but with different

ligands bound

−  The conformation of the binding site can vary from one complex to another

−  Which should be used in the virtual screening experiment?

•  Ensemble docking to different protein conformations may be required where there are large changes in the binding site

Issues related to the ligands

•  The protonation state and tautomeric form of a ligand can influence its hydrogen bonding ability −  Need to ensure all ligands are in the correct protonation and

tautomeric states or enumerate and dock all possibilities

•  Conformations −  Need to ensure sufficient sampling of conformational space has

been carried out

−  Can we be sure the bioactive conformation has been generated?

−  May want to apply filtering techniques to prune unlikely candidates prior to carrying out the docking

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