only a knowledge of primary structure? To date, the protein folding problem remains
unsolved—we cannot predict the overall three-dimensional structure of a protein.
There have been many attempts to solve the protein folding problem. The first attempts
initiated the process by focusing on secondary structure prediction, starting from the amino
acid sequence. The first commonly used method was the Chou and Fasman method. From
an analysis of known structures, Chou and Fasman devised propensity tables, which gave
the probability of a given secondary structure for each individual amino acid. The Garnier,
Osguthorpe and Robson (GOR) method is an extension of this statistical approach.
However, extending beyond secondary structure prediction has proven difficult. One
method of attempting to predict three-dimensional structure is via sequence alignmentand
homology modeling. In this process, the calculations begin with the crystal structure of a
known protein. Then, a protein with an unknown three-dimensional structure is “aligned”
with the structure of the known protein. Similar amino acids are aligned with each other;
for example, a glutamate in one protein may be aligned with an aspartate in the other pro-
tein. Regions of the two proteins with similar amino acids are aligned against each other
and are said to have sequence homology. The three-dimensional structure of the unknown
protein is then set to be analogous to the three-dimensional structure of the known protein.
Although useful, this procedure still does not solve the protein folding problem and it does
require a similar protein with an experimentally solved structure.
Another important application of large-scale quantum pharmacology calculations to
drug molecule design is the process of docking simulation. Either molecular mechanics
calculations in isolation or QM/MM calculations may be used to simulate a drug mole-
cule interacting with a proposed receptor site in a macromolecule such as a protein. Such
simulations may be of value in understanding a drug’s mechanism of action at a molecu-
lar or atomic level of refinement and may also be of utility in designing improved analogs
of the drug molecule. These simulations (sometimes referred to as in silico[preferred] or
in computo experiments to distinguish them from in vitro andin vivo experiments) may
be made more physiologic by including solvation effects. Sometimes, it is possible to add
hundreds if not thousands of explicit water molecules around the docking simulation
about the drug and its receptor. The presence of solvating waters influences the confor-
mation and reactive properties of the drug and its receptor. The task of adding many water
molecules dramatically increases the computational intensity of this work.
Through the consideration of large molecules, quantum pharmacology may someday
make the jump to quantum medicine. More than simply permitting an elucidation of
optimal geometries for purposes of drug design, quantum medicine will enable a
detailed molecular and submolecular understanding of human disease at a rigorous and
quantitative level of conceptual refinement.
1.6.5 The Clinical–Molecular Interface: “Butterfly Angles”
in Tricyclic DrugsTricyclic molecules are frequently used in drug design and as drugs to treat a diversity
of disorders. Tricyclic drugs contain three rings fused together. Molecules belonging to this
structural class are routinely used for the treatment of psychosis, schizophrenia, depression,
epilepsy, headache, insomnia, and chronic pain. In treating these many disorders, tricyclic
drugs demonstrate an ability to bind to a plethora of different (and structurally quite
distinct) receptors, including many types of dopamine receptors, serotonin receptors,
DRUG MOLECULES: STRUCTURE AND PROPERTIES 55