Molecular Design of Drug Resistance Resistant Inhibitors
Introduction
AIDS is one of the major killers in the modern world,
but despite the many treatments that have been developed, the HIV virus
continues to spread. One of the main problems in designing drugs to combat
HIV is the potential for the virus to develop resistance via mutation.
This is a problem that affects drugs targeted at many organisms and is
likely to become more of a problem with increased use of drugs to target
viral and bacterial infection.
We have developed a strategy to help prevent this type
of resistance by designing the drug molecule to mimic the exact shape
of the substrates of the protein targets. The idea being that any mutations
that affect drug binding will also affect substrate binding and thus have
a deleterious effect on the organism. This is termed the substrate envelope
hypothesis.
Methods
The first step in our drug design scheme is the generation of the substrate
envelope, which is created by taking a mould of the target\x{2019}s active site
from a crystal structure of the target bound to the substrate. This envelope
acts as a barrier, and any designs which pierce this barrier are removed,
as they could potentially be knocked out by viral mutants without affecting
substrate binding (See Figure 1).
Figure 1 A candidate design which almost fits within the
substrate envelope
To aid in the synthesis of our designs and reduce the
computational load, a fixed scaffold is used as a basis for inhibitor
design. These scaffolds are based off of known, successful drugs and are
either flexibly or rigidly docked within the envelope. They contain a
number of variable sites upon which different functional groups can be
grown, and by searching this functional group space, we are able to design
inhibitors with a high predicted free energy of binding. However, the
large number of scaffold positions combined with a large number of choices
at each position and the necessity to search many conformations make this
a complex problem. We use a combination of dead end
elimination [1] and the A* algorithm [2] to
analyze the many possibilities. This allows us to search a large portion
of the space in a reasonable amount of time.
Model Systems
All of our work thus far has been focused on designing
inhibitors to HIV-1 protease, as it is a widely studied system and is
considered to be one of the most effective targets to slow the spread
of HIV. We use the backbone structures of three of the most potent HIV
inhibitors, Amprenavir, Lopinavir, and Atazanavir (See Figure 2) as our drug scaffolds.
Figure 2 The scaffolds of Amprenavir, Lopinavir and Atazanavir
used for inhibitor design.
A variety of commercially available compounds are used at the R1, R2
and R3 positions to design inhibitors with a high predicted free energy
of binding.
Current Progress
A set of compounds based on the core of Amprenaivir have been designed,
synthesised and tested against a panel of four HIV-1 Protease mutants
that represent the most commonly occurring mutations. Results are promising.
The tightest binding compound has an affinity of 14pM by isothermal titration
calorimetry and, from the set of compounds that have been tested against
the mutant panel, the best lose less than tenfold affinity.
We have also designed a series of compounds from the Lopinavir
core. There are two sets of compounds. Half fit within the substrate
envelope and half are larger and predicted to bind more tightly but
do not fit within the substrate envelope. Examples of both of these sets
of compounds can be seen in Figure 2. All these
compounds are being tested for affinity and against the panel of mutants.
Figure 3 Compounds predicted to bind inside (left) and outside
(right) the substrate envelope
We have also been working with medicinal chemists in an attempt to optimise
some highly promising compounds based on the amprenavir scaffold. The
marriage of experiment and theory will hopefully yield some highly promising
inhibitors.
Future Plans
We hope to prove the concept of the substrate envelope hypothesis by
designing and making molecules that mimic the shape of the peptide substrate
of HIV protease and have good activity against a variety of mutant proteases.
We can then establish a simple and effective methodology for to avoiding
the problems associated with drug resistance in the future. This could
greatly aid future efforts in drug discovery.
Acknowledgements
The Amprenavir predictions and much of the coding for this work was done
by Michael D. Altman.
References:
[1] J. Desmet, M. Demaeyer, B. Hazes and I. Lasters. The dead-end
elimination theorem and its use in protein side-chain positioning.
Nature, 356:539-542, 1992.
[2] A. R. Leach and A. P. Lemon. Exploring the conformational space
of protein side chains using dead-end elimination and the A* algorithm.
Proteins: Structure Function and Genetics, 33:227-239, 1998.
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