Computational design of new drugs

The search for drugs to recover or maintain a state of health, to alleviate symptoms and/or avoid pain has been a constant in the history of mankind. Depending on their origin, these drugs can be classified as natural, synthetic or semi-synthetic. The former can have their origin in the animal, vegetable or mineral kingdom. Synthetics are made from materials produced in a laboratory, while semi-synthetics are hybrids, i.e. they are obtained by converting materials or compounds that come directly from nature into other products by means of specific chemical reactions.

Finding an effective drug can take a long time from initial research to market launch. This can take ten to 15 years, a complex and costly process. To get a clearer idea of its implications, we can divide it into at least four phases, which are:.

• Discovery phase: when a disease-associated protein is identified and confirmed to play an important role in targeting the disease. Then a series of chemical compounds that can bind to it and significantly affect the disease are sought. The compound is then tested for safety and efficacy; it is then that it becomes a drug candidate.


• Preclinical phase: the biological activity of the drug candidate is evaluated in the laboratory.


• Clinical phase: it identifies how it acts in the organism and its efficacy in the treatment of the disease with established safety limits.


• Approval and registration phase: the drug is registered and marketing is requested.

Figure 1. Phases involved in drug design

In recent decades, thanks to the development of computers and specialized software, there have been important advances in the design and analysis of drugs by computer, and this type of study is called in silico.

Computational studies have significantly helped to accelerate phases 1 and 2 of drug development as explained in Figure 1 and at a lower cost than when using traditional methodologies.

What do they consist of? The binding of the drug to the receptor protein is analyzed at the molecular level: this has been identified to be of utmost importance to determine the pharmacokinetic profile of the compounds proposed as drugs. For this purpose, computational algorithms have been developed to model the coupling of the 3D structure of a molecule (drug) to the receptor protein binding site, see Figure 2. This helps to identify the associated molecular interactions.

To carry out this docking there are two main and independent processes. The first corresponds to the generation of the correct pose (conformation and orientation) of the ligands (drugs) within the receptor binding site (protein); while the second is related to the assessment of the binding affinity. The higher the affinity, the greater the chance that the proposed drug can efficiently combat the disease.

In this sense, molecular docking studied in silico has contributed significantly to reducing both the experimental work and the associated costs and time required to design new drugs.

Molecular coupling between a protein and a drug and the formation of the complex generated.

After molecular docking studies have been performed and demonstrate that the compound can interact with the protein at a specific site with some particular conformation or conformations, it becomes necessary to determine the structural stability of the drug at that site. In this sense, molecular dynamics simulations are a powerful tool to study in detail the chemical behaviors and events that can occur in molecular systems.

Thus, it is possible to analyze the flexibility of the protein and the conformational changes of the drug over time. This is relevant to correctly assess the behavior and binding modes of the chemical compound with the protein, and thus be able to find structural changes that give rise to active or inactive conformations. The latter makes it possible to explain its pharmacokinetic mechanism, which has been useful for efficient filtering of the compounds that are most likely to be successful in attacking a disease.

Here it is important to mention that the use of molecular docking and molecular dynamics has shown to be able to adequately predict the interaction between proteins and drugs, identifying possible mechanisms of drug action. This represents important advantages during the search or design of new drugs. This methodology has made it possible to reduce the time and cost associated with the design of new drugs.