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Rational drug design - Biomatics.org

Rational drug design

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Rational drug design is the approach of finding drugs by design, based on their biological targets. Typically a drug target is a key molecule involved in a particular metabolic or signalling pathway that is specific to a disease condition or pathology, or to the infectivity or survival of a microbial pathogen.

Some approaches attempt to stop the functioning of the pathway in the diseased state by causing a key molecule to stop functioning. Drugs may be designed that bind to the active region and inhibit this key molecule. However these drugs would also have to be designed in such a way as not to affect any other important molecules that may be similar in appearance to the key molecules. Sequence homologies are often used to identify such risks.

Other approaches may be to enhance the normal pathway by promoting specific molecules in the normal pathways that may have been affected in the diseased state.

The structure of the drug molecule that can specifically interact with the biomolecules can be modeled using computational tools. These tools can allow a drug molecule to be constructed within the biomolecule using knowledge of its structure and the nature of its active site. Construction of the drug molecule can be made inside out or outside in depending on whether the core or the R-groups are chosen first. However many of these approaches are plagued by the practical problems of chemical synthesis.

Newer approaches have also suggested the use of drug molecules that are large and proteinaceous in nature rather than as small molecules. There have also been suggestions to make these using mRNA. Gene silencing may also have therapeutical applications.

 

Contents

Rational drug design

Unlike the historical method of drug discovery, by trial-and-error testing of chemical substances on animals, and matching the apparent effects to treatments, rational drug design begins with a knowledge of specific chemical responses in the body or target organism, and tailoring combinations of these to fit a treatment profile. Due to the complexity of the drug design process two terms of interest are still serendipity and bounded rationality. Those challenges are caused by the large chemical space describing potential new drugs without side-effects.

A particular example of rational drug design involves the use of three-dimensional information about biomolecules obtained from such techniques as x-ray crystallography and NMR spectroscopy. This approach to drug discovery is sometimes referred to as structure-based drug design. The first unequivocal example of the application of structure-based drug design leading to an approved drug is the carbonic anhydrase inhibitor dorzolamide which was approved in 1995. [1][2]

Another important case study in rational drug design is imatinib, a tyrosine kinase inhibitor designed specifically for the bcr-abl fusion protein that is characteristic for Philadelphia chromosome-positive leukemias (chronic myelogenous leukemia and occasionally acute lymphocytic leukemia). Imatinib is substantially different from previous drugs for cancer, as most agents of chemotherapy simply target rapidly dividing cells, not differentiating between cancer cells and other tissues.

The activity of a drug at its binding site is one part of the design. Another to take into account is the molecule's druglikeness, which summarizes the necessary physical properties for effective absorption. One way of estimating druglikeness is Lipinski's Rule of Five.

 

Examples of designed drugs

  • Cimetidine, the prototypical H2-receptor antagonist from which the later members of the class were developed
  • dorzolamide, a carbonic anhydrase inhibitor used to treat glaucoma
  • Many of the atypical antipsychotics
  • Selective COX-2 inhibitor NSAIDs
  • SSRIs (selective serotonin reuptake inhibitors), a class of antidepressants
  • Zanamivir, an antiviral drug
  • Enfuvirtide, a peptide HIV entry inhibitor
  • Probenecid

 

See also

  • Drug development
  • Drug discovery
  • Designer drug
  • Molecular modelling
  • Enzyme inhibitors
  • Bioinformatics
  • Cheminformatics
  • Biomedical informatics
  • Pharmaceutical company
  • Polyanhydrides
  • Training in Medicinal Chemistry and Drug Design

 

References

  1. ^ Greer J, Erickson JW, Baldwin JJ, Varney MD (1994). "Application of the three-dimensional structures of protein target molecules in structure-based drug design". J Med Chem 37 (8): 1035 - 1054. PMID 8164249. 
  2. ^ Gubernator K, Böhm HJ (1998). Structure-Based Ligand Design, Methods and Principles in Medicinal Chemistry. Weinheim: Wiley-VCH. 

Designing amino acids to determine the local conformations of peptides

  1. A W Burgess

+Author Affiliations

  1. Ludwig Institute for Cancer Research, Melbourne, Australia.
Abstract

The local conformations of proteins and peptides are determined by the amino acid sequence. However, the 20 amino acids encoded by the genome allow the peptide backbone to fold into many conformations, so that even for a small peptide it becomes very difficult to predict the three-dimensional structure. By using empirical conformational energy calculations, a set of amino acids has been designed that would be expected to constrain the conformation of a peptide or a protein to one or two local minima. Most of these amino acids are based on asymmetric substitutions at the C alpha atom of each residue. The H alpha atom of alanine was replaced by various groups: -OCH3, -NCH3, -SCH3, -CONH2, -CONHCH3, -CON(CH3)2, -NH.CO.CH3, -phenyl, or -o-(OCH3)phenyl. Several of these new amino acids are predicted to fold into unique peptide conformations such as right-handed alpha-helical, left-handed alpha-helical, or extended. In an attempt to produce an amino acid that favored the C(eq)7 conformation (torsion angles: phi = -70 degrees and psi = +70 degrees), an extra amide group was added to the C beta atom of the asparagine side chain. Conformationally restricted amino acids of this type could prove useful for developing new peptide pharmaceuticals, catalysts, or polymers. 
http://www.pnas.org/content/91/7/2649.abstract

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