By Ayma Aftab, Khalid Masood
THE USE of computers and computational methods saturate all aspects of drug discovery today and forms the core of structure-based drug design. In silico methods can help in identifying drug targets through bioinformatics tools. They can also be used to evaluate target structures for possible binding/active sites, to generate candidate molecules, to check for their drug-like properties. In addition such methods can be used to dock these molecules with the target, to rank them according to their binding affinities, and to further optimize the molecules to improve binding characteristics.
Pharmaceutical industry takes approximately 12-14 years and costing up to $1.2 - $1.4 billion dollars to discover and market a drug;
(1) Conventionally, drugs were synthesized in time-consuming multi-step processes and further investigating the promising candidates for their pharmacokinetic properties, metabolism and potential toxicity. Such a development process has resulted in with failures attributed to poor pharmacokinetics (39%), lack of efficacy (30%), animal toxicity (11%), adverse effects in humans (10%) and various commercial and miscellaneous factors.
(2) Computational tools offer the benefit of discovering new drug candidates more quickly and at a lower cost. Major roles of computation in drug discovery are; (i) Virtual screening & de novo design (ii) in silico ADME/T prediction and (iii) Advanced methods for determining protein-ligand binding.
Virtual Screening:
Pharmaceutical companies are always searching for new leads as a drug. One search method is virtual high-throughput screening. vHTS screens protein targets against databases of small-molecule compounds to distinguish which molecules bind strongly to the target. A “hit” with a particular compound can be extracted from the database for further testing. Now-a-days several million compounds can be screened in a few days with the help of insilico drug designing. Therefore, hunt a handful of promising leads can hoard researchers considerable time and expense.
Steps of virtual screening are:
Lead discovery: Lead compounds can be identified depending upon their chemical properties available at various data bases. Although it is not possible to foretell with much accuracy about toxicity and side effects, anticipate transport of a drug. Once a lead is selected, its structures can be modified to get an effective drug.
Identification of Pharmacophore: Only a small part of a lead compounds may be involved in the appropriate interaction. Quantitative structure-activity relationships QSAR studies are performed to optimize lead compound. It basically provides relationship between the biological and pharmacological activity of a compound, and its structural, physical and chemical properties. It actually causes the lead to behave as if in invivo environment.
Active site Identification: Analyze the binding pocket of protein in question. The space inside the ligand binding region would be studied with respect to any ligand having corresponding properties of hydrophobic atom, H-bond donor, H-bond acceptor, Polar atom.
Docking: It is the step to dock ligand on the target site by using different tools. In this step either the ligand can be kept flexible or receptor according to the research aims. Tools for docking are: FlexLigdock, GOLD, Zdock server, HEX, Autodock.
ADME properties: The most powerful study of “Lipinski’s rule-of-five” identifies several vital properties that should be considered for compounds with oral delivery. The key characteristics for drugs are Absorption, Distribution, Metabolism, Excretion, Toxicity (ADMET) and efficacy—in other words bioavailability and bioactivity. Bioinformatics tools to calculate ADME properties are: C2-ADME, TOPKAT, CLOGP, DrugMatrix, AbSolv, Bioprint, GastroPlus etc.
Conclusion:
Ligand docking aims to find the optimum binding position and orientation for a compound in active site of the proteins. The best docking programmes correctly dock about 70–80% of ligands when tested on large sets of protein–ligand complexes. Nevertheless, virtual screening has proved helpful in docking and ranking a large number of compounds so that the highest-ranking compounds can be selected for gaining or synthesis and experimentally tested for affinity against the target protein. Virtual screening provides a significant enrichment, perhaps twenty fold, of true hits in a selected subset of compounds.
http://www.technologytimes.pk/mag/2011/jan11/issue01/in_silico_drug_designing_via.php
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