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  IN THIS Article
 ::  Abstract
 ::  The Drug Design ...
 ::  Examples
 ::  Limitations
 ::  Conclusion
 ::  References
 ::  Article Figures

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TECHNOLOGY REVIEW
Year : 2009  |  Volume : 55  |  Issue : 4  |  Page : 301-304

Structure-based drug design and modern medicine


Department of Medicine, Saint Vincent Hospital, Worcester, MA, USA

Date of Web Publication14-Jan-2010

Correspondence Address:
R Vijayakrishnan
Department of Medicine, Saint Vincent Hospital, Worcester, MA
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0022-3859.58943

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 :: Abstract 

Drug discovery has evolved through various stages into more rational and evidence-based drug designing. Compared to conventional methods which were time consuming and less logical, new drug designing based on structure is rational, evidence based, faster and more scientific in nature. In the era of modern medicine, where newer insights into molecular level of disease processes are available, it is very essential that drug designing be based on molecular mechanism of pathologic processes. Structure-based drug designing has made tremendous contributions in the field of cancer chemotherapy, drug resistant infections, neurological diseases, to mention a few. New drug discovery methods are furthered by developments in the technology especially computers, bioassay techniques and calibrated instruments. Computational structure-based drug designing opens the door to novel treatments in modern medicine.


Keywords: Designed drugs, discovery, drug, structure-based drug design


How to cite this article:
Vijayakrishnan R. Structure-based drug design and modern medicine. J Postgrad Med 2009;55:301-4

How to cite this URL:
Vijayakrishnan R. Structure-based drug design and modern medicine. J Postgrad Med [serial online] 2009 [cited 2023 Mar 22];55:301-4. Available from: https://www.jpgmonline.com/text.asp?2009/55/4/301/58943


There has been a renaissance in modern medicine with the introduction of structure-based drug design. Conventional drug designing was time consuming, expensive and did not always yield good results. In addition, there was also a lack of rationalism in the approach toward drug discovery. In contrast, this new elegant technique promises high specificity and efficacy. Also of importance is the positive impact of these techniques on the economies of the pharmaceutical industry. The structure of proteins and nucleic acids are being increasingly known, opening new avenues for drug designing. [1] In this era of questioning "why things are done in the way they are done", structure-based drug design provides the correct rationale behind the drug discovery. In this article, we briefly describe the various processes involved in drug designing and cite examples of its impact in practice of modern medicine.

The basis of functions and interactions of biomolecules lies in their structure. Proteins are the functioning molecules of living organisms and they are involved in the key processes such as metabolism, signal transduction, immune response, transport and cell cycle. The function of proteins is determined by their three-dimensional structure. The functional site of interaction can be an active site (as in the case of an enzyme) or a binding pocket (as in the case of a receptor where the interacting molecule, the ligand binds).

The strength and specificity of the interaction is determined by the geometry and charge complementarity of the surfaces of the ligand and the target. The three-dimensional structure, as determined by the X-ray crystallography or NMR spectroscopy, of the ligand-target complex reveals the nature of the binding site and detailed interactions with the ligand. This information can be exploited to design new chemical compounds that are more effective and specific for the target. Such a strategy is known as structure-based drug design. [2]


 :: The Drug Design Process Top


The drug designing process starts with the identification of a target molecule, [Figure 1]which plays a key role in the metabolic or signal pathway and whose blocking or enhancing will cause the desired medical outcome/s. The knowledge about the molecular mechanisms of biological or disease processes have given us immense insight into target identification. In human beings, most of these target molecules are proteins (although DNA and RNA also function as targets occasionally).

The second step in the process is understanding the three- dimensional (3D) structure of these target molecules. The most reliable method is the X-ray crystallographic structure of the target molecule itself. NMR spectroscopy structures (citing BMRB) are the next best option for drug discovery. The third option with drug designer is to homology model the target molecule from an identical molecule whose 3D structure is already known. There are huge databanks from which information about the 3D-structure of proteins can be obtained. Protein data bank (PDB), [3] BioMag Res Bank (BMRB) (BioMagResBank), [4] European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI) [5] are examples of such data banks.

The next step involves the software validation process. There are many computer softwares that can be used for drug designing and validation process. AutoDock, ZDOCK, DiscoveryStudio, DOCK, FlexX are some of the major softwares used frequently for drug discovery. The software validation involves the docking and analysis of the interactions of the target molecule with the drug or ligand, whose interaction parameters have already been biochemically and biophysically proved.

Once software validation is complete, the designing of the ligand or lead compound begins. This involves the thorough knowledge about the active site or allosteric site structure, biochemistry and possible favorable biophysical interactions. The process of identifying a new chemical compound that could lead to a new drug involves two main computational techniques: (1) conformational analysis to predict the 3D structure (conformation) of the designed compound and (2) docking to predict the position, binding and activity of the designed compound. Rational or structure-based drug design involves proposing or evaluating novel ligands to biological receptors prior to synthesis, based on structure information. This structural information can be:

  1. Explicit, as in the availability of a single X-ray structure of the protein target or
  2. Implicit, as in the availability of enough structure/activity data for a variety of ligands to develop a 3-D pharmacophore map.
There are instances in which the rational design of inhibitors can be performed without target structure. A good example is a two-step protocol for developing protease inhibitors: (i) characterize the substrate specificities of the protease: and (ii) synthesize peptides with similar features but with the hydrolysable amide bond replaced by a nonreactive "isotere". The peptides can subsequently be optimized by modifications in the side chain or a backbone.

Once a few ligand molecules are obtained, the various interactions between them and the target molecule active/allosteric site can be determined with the help of various computer softwares mentioned above. The best among them is chosen based on its low free energy of binding and high affinity and is known as the lead compound. This process can be called lead optimization [Figure 1]. There are many ligand databases which can provide useful insights into designing the lead compounds e.g., Cambridge Structural Database. [6]

The central assumption of structure-based drug design is that good ligands must possess significant structural and chemical complementarity to their target receptor. [7] A structure of any form of receptor provides a starting point for the direct modeling activities. The structure of ligand receptor complexes or homologous receptors also contains valuable information. Computer programs such as DOCK [8] that are used to solve the 3-D jigsaw puzzle of fitting putative ligands into appropriate sites on the receptor can provide a rapid and controlled exploration of the geometric intricacies of target sites.

The lead compound undergoes thorough biokinetic in-vitro and/or in-vivo analysis before it goes into various phases of clinical trials. The entire process of drug designing [Figure 1] needs to be repeated, if the lead compound is not found to have the predicted activity and/or safety profile in the in-vitro, in-vivo or clinical trials. The advantage of such drugs is the high specificity to target site with least possible side effects.


 :: Examples Top


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. [9]

Antibiotics

Increasing use of antibiotics has resulted in an ever-rising threat of drug resistance. To combat this resistance, two main avenues of drug discovery are being pursued. [10]

  1. Identifying new microbial proteins so that drugs could be directed against them through drug discovery efforts, and
  2. Designing innovative drugs that target existing proteins.
Tuberculosis is the most important cause of mortality worldwide among infectious diseases and hence a major focus of research. Shen and co-workers deduced the structure of indole-3-glycerol phosphate synthase (IGPS) of M. tuberculosis keeping in mind the role of tryptophan biosynthetic pathways in survival of mycobacteria. They then identified an inhibitor ATB107 that might be a potential target for the development of new anti-TB drugs exemplifying the first avenue of drug research. [11]

Kumar and co-workers used structure-based drug designing approach to design novel anti-TB drug against known drug target Dihydrofolate reductase (DHFR) exemplifying the second avenue of drug research. [12]

Anti HIV drugs

The initiation of HAART treatment against HIV remarkably changed the prognosis of this disease. Retroviral protease, a key enzyme, was identified a decade ago and realized to be a potential target for drug designing. Nelfinavir, a protease inhibitor drug, is one of the major drugs developed by means of structure-based drug designing. A new and very promising strategy for HIV drug discovery consists in blocking the multiple functional interactions between HIV-1 integrase (IN) and its cellular cofactors. [13] Research is also underway for antiretroviral drugs blocking CCR-5 (fusion receptor) e.g., enfuvirtide, Gp 120 (viral entry), [14] novel nonnucleotide reverse transcriptase inhibitors, etc. Although drug resistance is an emerging problem in drug development, structure-based drug designing helps identify the molecular basis of these drug resistances and hence also their solutions. [15]

Anticancer drugs

Cancer pathogenesis has a complex pathway and a key determinant for successful drug designing is to find a suitable target. The advent of monoclonal antibodies targeted at tumor-associated or tumor-specific antigens provides a novel approach for the treatment of a broad range of malignancies. Given the modest toxicity of these naked antibodies, they avail themselves as ideal partners for combining with conventional chemotherapy to produce results that often appear to be greater than merely additive. The clinical response is not always impressive in oncology due to activation of alternate signal transduction pathways and acquisition of new mutations. CD20, bcr: Abl, Her-2/NEU, and epidermal growth factor receptor(EGFR) are examples of important targets for the modern drug discovery. [16],[17]

Imatinib, a tyrosine kinase inhibitor, is 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. [18]

The target, Her-2/Neu, was identified by Weinberg and colleagues [19] as a transforming factor in a malignant glial cell line. Slamon [20] recognized the importance of this oncogenic receptor tyrosine kinase in certain forms of breast cancer ultimately leading to the development of trastuzumab. [21]

Anti-inflammatory agents

The concept of selective COX2 (cyclooxygenase enzyme 2) inhibitor drugs emerged from the need to overcome the unwanted gastrointestinal sideeffects of the nonsteroidal anti-inflammatory drugs. By definition, selectivity is the degree of preference a drug has for a target with respect to another target molecule. For being COX2 selective (popularly known as Coxibs), biochemical assays must reveal more than a 100-fold difference in the concentration of drug to inhibit COX2 as compared with COX1. [22] Recent reports on the harmful cardiovascular and renal side effects of the conventional NSAIDs as well as the COX2 selective inhibitors valdecoxib and rofecoxib have once again led to the quest for a novel class of COX2 selective inhibitors. [23] The author and co-workers have designed peptides that inhibit COX2 with potency in the nanomolar range. Furthermore, it is found to be a million-fold selective for COX2 as compared with COX1. [24]

Drugs for neurological diseases

Rituximab is one promising monoclonal antibody directed against B cells. It is being tested in relapsing remitting multiple sclerosis and has been shown to reduce relapses and MRI activity. [25] Natalizumab - Cell-adhesion molecule a4b1 integrin plays a key role in homing of immune cells to the central nervous system. Antibody against this molecule, natalizumab, showed very promising results but was withdrawn due to reports of progressive multifocal leucoencephalopathy (PML). [26],[27]


 :: Limitations Top


Drugs designed via molecular approaches are usually against single targets but they may have unanticipated side effects due to off-target interactions. These side effects are often noted during large clinical trials or during use in market. Natalizumab is one such drug that was withdrawn due to neurological side effects. [28] The financial impact of drug discovery and development has been extensively contemplated. It is estimated that the cost of bringing a new drug to the end of Phase III clinical testing is US $802 million. [29] The current paucity of knowledge about targets will lead to longer development time and higher costs in the short run. New technologies could eventually reduce research and development costs by approximately one-third. [30]


 :: Conclusion Top


This communication describes the importance of molecular drug designing in the field of modern medicine. There are many drugs that have been designed to date to bring about novel cure and even more potential areas, which are yet to be explored. It is extremely important to validate the efficacy and safety of these drugs in clinical trials. Like any technology, molecular drug designing is also a double-edged sword and unless used conscientiously, can lead to many financial burdens and also may mislead scientific community.

 
 :: References Top

1.Kuhn P, Wilson K, Patch MG, Stevens RC. The genesis of high- throughput structure-based drug discovery using protein crystallography. Curr Opin Chem Biol 2002;6:704-10.  Back to cited text no. 1  [PUBMED]  [FULLTEXT]  
2.Subba Rao G, Rajakrishnan V. Bioinformatics and Computational Biology. In: Swati B, editor. 1 st ed. New Delhi: 2006. p. 29-34.  Back to cited text no. 2      
3.Berman HM, Westbrook J, Feng Zeta, Gilliland G, Bhat TN, Weissig H, et al. The Protein Data Bank. Nucleic Acids Res 2000;28:235-42.  Back to cited text no. 3      
4.Ulrich EL, Akutsu H, Doreleijers JF, Harano Y, Ioannidis YE, Lin J, et al. "BioMagResBank". Nucleic Acids Res 2007;36: D402-8.  Back to cited text no. 4  [PUBMED]  [FULLTEXT]  
5.Lopez R, Duggan K, Harte N, Kibria A. Public services from the European Bioinformatics Institute. Brief Bioinform 2003;4:332-40.  Back to cited text no. 5  [PUBMED]  [FULLTEXT]  
6.Allen FH. The Cambridge Structural Database: A quarter of a million crystal structures and rising. Acta Cryst 2002;B58:380-388.  Back to cited text no. 6      
7.Kuntz ID. Structure-based strategies for drug design and discovery. Science 1992;257:1078-82.  Back to cited text no. 7  [PUBMED]  [FULLTEXT]  
8.Selinski BS, Gupta K, Sharkey CT, Loll PJ. Biochemistry 2001;40:5172-80.  Back to cited text no. 8      
9.Kubinyi H. Chance favors the prepared mind-from serendipity to rational drug design. J Recept Signal Transduct Res 1999;19:15-39.   Back to cited text no. 9  [PUBMED]  [FULLTEXT]  
10.Nicola G, Abagyan R. Structure-based approaches to antibiotic drug discovery. Curr Protoc Microbiol 2009;17:17.2.  Back to cited text no. 10      
11.Shen H, Wang F, Zhang Y, Huang Q, Xu S, Hu H, et al. A novel inhibitor of indole-3-glycerol phosphate synthase with activity against multidrug-resistant Mycobacterium tuberculosis. FEBS J 2009;276:144-54.  Back to cited text no. 11  [PUBMED]  [FULLTEXT]  
12.Kumar M, Vijayakrishnan R, Subba Rao G. In silico structure-based design of a novel class of potent and selective small peptide inhibitor of Mycobacterium tuberculosis Dihydrofolate reductase, a potential target for anti-TB drug discovery. Mol Divers. 2009 Aug 21. [Epub ahead of print].  Back to cited text no. 12      
13.Reeves JD, Piefer AJ. Emerging Drug Targets for Antiretroviral Therapy. Drugs 2005;65:1747-66.  Back to cited text no. 13  [PUBMED]  [FULLTEXT]  
14.Berchanski A, Lapidot A. Computer-based design of novel HIV-1 entry inhibitors: Neomycin conjugated to arginine peptides at two specific sites. J Mol Model 2009;15:281-94.  Back to cited text no. 14  [PUBMED]  [FULLTEXT]  
15.Wlodawer A, Vondrasek J. Inhibitors of HIV-protease: A Major Success of Structure Assisted Drug Design. Annu Rev Biophys Biomol Struct 1998;27:249-84.  Back to cited text no. 15  [PUBMED]  [FULLTEXT]  
16.Hait WN. Targeted Cancer Therapeutics. Cancer Res 2009;69:1263-7.  Back to cited text no. 16      
17.Buchanan FG, Holla V, Katkuri S, Matta P, DuBois RN. Targeting cyclooxygenase-2 and the epidermal growth factor receptor for the prevention and treatment of intestinal cancer. Cancer Res 2007;67:9380-8.  Back to cited text no. 17  [PUBMED]  [FULLTEXT]  
18.Druker BJ, Talpaz M, Resta DJ, Peng B, Buchdunger E, Ford JM, et al. Efficacy and safety of a specific inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia. N Engl J Med 2001;344:1031-7.  Back to cited text no. 18  [PUBMED]  [FULLTEXT]  
19.Bacus SS, Ruby SG, Weinberg DS, Chin D, Ortiz R, Bacus JW. HER-2/neu oncogene expression and proliferation in breast cancers. Am J Pathol 1990;137:103-11.  Back to cited text no. 19  [PUBMED]  [FULLTEXT]  
20.Slamon DJ, Godolphin W, Jones LA, Holt JA, Wong SG, Keith DE, et al. Studies of the HER-2/neu proto-oncogene in human breast and ovarian cancer. Science 1989;244:707-12.  Back to cited text no. 20  [PUBMED]  [FULLTEXT]  
21.Slamon DJ, Leyland-Jones B, Shak S, Fuchs H, Paton V, Bajamonde A, et al. Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl J Med 2001;344:783-92.  Back to cited text no. 21  [PUBMED]  [FULLTEXT]  
22.Rehman Q, Sack KE. When to try COX-2-specific inhibitors. Safer than standard NSAIDs in some situations. Postgrad Med 1999;106:95-106.  Back to cited text no. 22      
23.Solomon DH, Avorn J, Sturmer T, Glynn RJ, Mogun H, Schneeweiss S. Cardiovascular outcomes in new users of coxibs and nonsteroidal antiinflammatory drugs: High-risk subgroups and time course of risk. Arthritis Rheum 2006;54:1378-89.  Back to cited text no. 23      
24.Rajakrishnan V, Manoj VR, Subba Rao G. Computer-aided, rational design of a potent and selective small peptide inhibitor of cyclooxygenase 2 (COX2). J Biomol Struct Dyn 2008;25:535-42.  Back to cited text no. 24  [PUBMED]  [FULLTEXT]  
25.Chaudhuri A, Behan PO. Rituximab in relapsing-remitting multiple sclerosis. N Engl J Med 2008;358:2646.  Back to cited text no. 25  [PUBMED]  [FULLTEXT]  
26.Noseworthy J, Kirkpatrick P. Natalizumab. Nature Rev Drug Discov 2005;4:101-2.  Back to cited text no. 26      
27.Sheridan C. Third Tysabri adverse case hits drug class. Nature Rev. Drug Discov 2005;4:357-8.  Back to cited text no. 27      
28.van der Greef J, McBurney RN. Innovation: Rescuing drug discovery: In vivo systems pathology and systems pharmacology. Nat Rev Drug Discov 2005;4:961-7.  Back to cited text no. 28  [PUBMED]  [FULLTEXT]  
29.Editorial. Costing drug development. Nat Rev Drug Discov 2003;2:247.  Back to cited text no. 29      
30.DiMasi JA. The value of improving the productivity of the drug development process: Faster times and better decisions. Pharmacoeconomics 2002;20:1-10.  Back to cited text no. 30      


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