Why it Takes Two Decades to Make a Drug: Compound Screening

Drugs aren’t as magical and miraculous as they might seem.

You go to your doctor and get diagnosed with a particular illness. The doctor then prescribes you with an over-the-counter prescription medication, which has neatly outlined instructions and a clear dosage. You just follow the instructions. Hopefully, the drug works, and you’re cured of your illness. But if not, the cycle repeats itself, again and again.

But that’s just what you see, and it’s a very small part of the story.

Those drugs took 2 decades to get to the pharmacy and probably cost more than 350 million dollars (sometimes more than one billion!) for R&D (Research and Development).

To understand why drugs take so long to develop and why they cost so much, you’ll first need to understand what they are.

What are drugs: the definition

Drugs can be defined in a variety of different ways. Let’s look at the standard dictionary.com definition of a drug.

Drug: “A chemical substance used in the treatment, cure, prevention, or diagnosis of disease or used to otherwise enhance physical or mental well-being”

Okay… You probably already knew that, but let’s break it down a little more technical and generalize to the most common types of drugs involved in treatment and cure.

  • “A chemical substance” → A small (likely organic) molecule

Also, the definition is vague in that it doesn’t go over how the drug leads to its benefits. Again, here we’ll generalize to the most common types of drugs.

  • “used in the treatment, cure… of disease” → that functions as a ligand that binds to a receptor to modulate a biochemical pathway

So here’s the definition that you’re going to need to familiarize yourself with for the rest of this article.

If you don’t know what ligands and receptors are — don’t worry, we’ll cover that in a later section. Just know that the drug binds to a larger molecule within our bodies.

Important Factors in Drug Selection

If there was a pharmacy, which had all possible drugs stored within it, that pharmacy would probably have an infinite number of aisles with an infinite number of drugs per aisle. So you can be pretty sure that finding a drug to achieve a medical purpose is not as easy as just going through a few possible drug candidates.

Here are the main steps involved in drug selection (we’ll go through some of these in more detail further on in the article)

  • The target for drug development is identified based on the desired effect of the drug and metabolic pathways associated with the target.
  • Millions of small molecules are computationally screened based on mechanistic factors (how well the drug binds to the receptor molecule). This is known as the primary assay.
  • In vitro testing with the lead compounds from the primary assay provides researchers with a list of “hit” compounds
  • Lead “optimization” — during this stage, developers look at how the drug affects your body and how your body affects the drug, and they further narrow down the list of drugs
  • Clinical trials — drugs are tested on people for months to years. Once the drug is validated as safe and effective, without reasonable side effects, the drug is released into the market.

You can kind of think of this process kind of like a funnel. Billions of possible compounds start at the top and with each step of the development process, the number of possible candidates is exponentially cut down. After 1–2 decades of research, ~1 billion dollars in funding, and FDA approval, the drug finally reaches the market.

Read on to understand the first step in the process

Target Identification and Compound Screening

The main goal of using drugs is to alter cellular processes at the molecular level in order to induce physiological benefits. As mentioned before, the main way that is done is that a drug (ligand) binds to a protein (receptor).

The interactions between the ligand and receptor often involve complex chemistry, but the main idea is that by binding to the receptor, the ligand is altering a certain biochemical pathway.

Here are two examples of examples where drugs alter cellular pathways in different ways:

  • a drug can function as an inhibitor which prevents an enzyme from binding with its normal ligand. An example is ibuprofen, which blocks the active site of the enzyme cyclooxygenase, thereby preventing pain-causing molecules called prostaglandins from being produced.
  • a drug can function as an allosteric modulator, which binds to a secondary site on the protein and remotely triggers changes in shape from that location. A class of drugs called benzodiazepines has sleep-inducing, muscle-relaxing, and anti-anxiety effects on the human brain. By allosterically modifying the GABA receptor in the brain, it enhances the activity of the neurotransmitter GABA.

The goal of this first step of drug development is to first find a target receptor which plays a vital role in pathways involved in a medical condition.

Compound Screening

Imagine that you have to open a locked door. But here’s the challenge: only one of the keys will open the door. And here’s what makes it even harder: each of the keys has ridges and notches that differ ever so slightly from the other keys. So even though there’s only one key that opens the door, there might be 100s of other keys that fit into the lock but don’t actually the door.

This is what compound screening is all about. Trying all the keys and seeing which ones actually fit in the lock. We aren’t yet turning the keys to see which one actually open the door. That process happens during lead optimization.

The ridges and notches on each key represent the atoms and bonds that make up each prospective drug candidate.

The way that the atoms and bonds are arranged changes how the ligand interacts with the receptor. In the case of drugs, the goal is to find the molecule that binds most strongly with the receptor. The next section focuses on these chemical interactions.

There are a couple of key forces involved in ligand-receptor interactions and here are brief descriptions for each of them:

  • Hydrogen Bonds: Attractions resulting from the partial charges of atoms in O-H, H-F, and H-N bonds
  • Electrostatic attractions: Attractions between complete positive and negative charges
  • Covalent linkages: Linkages between atoms in the receptor and atoms in the ligand that result from the sharing of electrons
  • Aromatic interactions: Attractions between rings of carbon atoms
A possible drug candidate (in violet) that occupies the active site of a protein called NNMT, which is involved in cancer. The two dotted yellow lines depict hydrogen bonds. Although they are not displayed, there are aromatic interactions (π-π stacking) between the drug’s aromatic ring and aromatic amino acid below it.

Potential drug candidates identified are carried onto the “hit validation” and “lead optimization” phases of drug development (A topic of future articles).

Innovations in Drug Screening

Currently, software that triest to calculate the binding affinity between a drug and its receptor (such as Autodock Vina) are relatively inefficient and unreliable. New innovations in drug screening are trying to include AI and machine learning to accelerate the process and eliminate more compounds that are dead ends.

Some companies with innovations in this field include:

  • Atomwise: This company has created a deep learning neural network (AtomNet) that increases speed and accuracy for small molecule binding affinity predictions.
AtomNet is teaching itself how to recognize a certain type of functional group
Here AtomNet’s speed is demonstrated. Hundreds of molecules can be tested per minute.

Although compound screening one of the initial steps in drug development, it is arguably the most important in terms of efficiency. Here’s why: as drug development progresses, more time is spent on assessing the candidacy of each “hit” compound. Therefore, by eliminating compounds that are dead ends earlier on in the process, efficiency is maximized and less time is wasted.

Thank you for reading my article! If you feel that you enjoyed it, please leave some claps and connect with me on LinkedIn! Look forward to reading more articles about other steps in the drug development process and recent innovations in each step!

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Innovator passionate about the intersection between structural biology, machine learning, and chemiinformatics. Currently @ 99andbeyond.