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Drug Design and Development

Drug Design

Can Drug Be Designed?

The need for ongoing development of new drugs needs no emphasis in light of the current global situation of health and disease. Traditionally, the process of drug development has revolved around a screening approach, as nobody knows which compound or approach could serve as a drug or therapy. Such almost blind screening approach is very time-consuming and laborious.

The shortcoming of traditional drug discovery; as well as the allure of a more deterministic approach to combating disease has led to the concept of "Rational drug design" (Kuntz 1992).

Nobody could design a drug before knowing more about the disease or infectious process than past. For "rational" design, the first necessary step is the identification of a molecular target critical to a disease process or an infectious pathogen. Then the important prerequisite of "drug design" is the determination of the molecular structure of target, which makes sense of the word "rational".

In fact, the validity of "rational" or "structure-based"drug discovery rests largely on a high-resolution target structure of sufficient molecule detail to allow selectivity in the screening of compounds.

How To esign A Drug

In the real work, the researchers will exploit all of the possible approaches to design or find good candidates for drug. The following figure briefly shows the flowing of drug design.

Almost nobody could design a drug without any assistance of computer tools, even after knowing the detail information of the target molecule.

Useful Tools

-Structure-based Drug Design

Solely based on a fine structure of target molecule,one whole new ligand could be constructed. This is just De novo of a ligand. Ligbuild is a rather powerful tool to build a ligand just based on a protein structure in Brookheaven format.

When building a new ligand, or screening the ligand from a database, it is critical to evaluate the bind energy of the complex. This is so-called scoring approach. SCORE is a tool to evaluate the binding affinity of protein-ligand complex with known three-dimensional structure.


After obtaining a number of candidate molecules of drug from database screening or De novo design, there are several criteria for further screening out appropriate molecules to perform the experiment test.

Permeation across the biomembrane is a major limitation of many compounds to serve as drug. At present, the logarithm of the partition coefficient of a solute between octanol and water, log P , is widely used to evaluate the hydrophilic and hydrophobicity, which represents the permeation across the biomembrane of the given molecules.

XLOGP can calculate log P of the common organic compounds. By using a large number of compounds (1853 altogether) as training set, it can give rather accurate log P values of the most interesting molecules with known structures. Furthermore, XLOGP can provide detailed hydrophobicity distribution information of the molecule.

To complement the inefficient calculation of peptides, another package, PLOGP , has been developed to meet this need. This package calculates the log P values of peptides particularly. But the present version can not deal with the analogues of peptides. On the other hand, PLOGP can produce Molecular Lipophilicity Potential (MLP) profile of a protein with known structure.

Of cause, one compound with rather high toxicity could not become a drug, even when it may meet all of the other criteria required for a potential drug. To prevent a "toxicant" to be chosen for the experimental or even clinical evaluation, our laboratory is actively developing a database-based predictive system to assess the risk of the chemicals in the early stage of drug design. The methodology combines activity prediction with the exploration of chemical database with structural diversity, which mainly includes three parts:

  1. Fast and efficient clustering of molecules based on molecular shape.
  2. Field-based similarity computation of molecular structure based on shape cluster.
  3. Flexible QSAR analysis of molecules based on shape cluster.
  In the past ten years, CoMFA, as a kind of 3D QSAR method,  has been applied widely. But with more and more reasearch work around it, some limitations in CoMFA have been found. Here we provide a program( AOS/APS )to solve some of these limitations .  

Drug Development

Producing a new drug is an expensive and time-consuming process that is subject to extensive regulation.

Drugs are substances that exert some kind of physiological or biochemical effect on our bodies. They may be single compounds or mixtures, and their effects may be beneficial or harmful. All drugs interact with specific targets, which are usually proteins but in some cases DNA or RNA. Drugs work either by stimulating or blocking the activity of their targets.

The development of a new therapeutic drug is a complex, lengthy and expensive process. It can take from 10-15 years and over £500 000 000 to bring a drug from concept to market. This includes 2-4 years of pre-clinical development, 3-6 years of clinical development and additional time for dealing with the regulatory authorities

The first stage of the process is drug discovery. In the past, many drugs have been discovered accidentally (such as penicillin) or through the analysis of folk medicines (such as quinine). Others have been designed based around the natural ligands of known drug targets.

Today, more systematic approaches are used. High-throughput screening is used to test thousands of potential targets with thousands of diverse chemical compounds in order to identify promising lead compounds (chemical entities that interact with targets and therefore have potential as drugs). The alternative method of rational drug design involves the design and synthesis of compounds based on the known structure of either a specific target or one of its natural ligands. The results of the Human Genome Project and human pathogen genome projects provide many new potential drug targets. For this reason, target identification must be followed by target validation, which confirms the likelihood that interfering with the target protein will impact on the disease.

Drug discovery has a high attrition rate. High-throughput screening may identify hundreds of potential lead compounds, but many of these will be eliminated in the first round of testing either because of toxicity or lack of efficacy in cultured cells and animals. This pre-clinical development stage aims to establish how drugs are absorbed and distributed in the body, and how they are broken down and eliminated. If appropriate, there may be a process of lead optimization where promising chemicals are modified in an attempt to alter their properties in subtle ways.

Once the pre-clinical studies have been completed, the hundreds of lead compounds will have been whittled down to many fewer useful candidate drugs. Some of these may then be advanced to the clinical development stage, which involves testing in humans. Before this can take place, the pre-clinical studies must be submitted to the appropriate regulatory authorities. If the application is successful, the compound can be registered as an ‘investigational new drug'.

Clinical development usually consists of phase I, phase II and phase III clinical trials. These are tests on human volunteers that provide more information on drug safety and activity. By the end of the clinical development phase, most of the investigational new drugs will have been eliminated on safety or efficacy grounds and only a very few compounds will be submitted to the regulatory authorities as a new drug application, which includes permission to market.

After approval, pharmaceutical companies have a short period of exclusivity before patents expire and other companies can market the same drugs as generics. This time is used to recoup the massive investment required to develop and launch a new drug. However, the companies must also continue to test their drugs and monitor the feedback from healthcare professionals in order to identify undiscovered side effects, risk factors and interactions.


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