Introduction
The information provided by pharmacokinetics is important in the discovery of new drugs and in screening drug candidates. It helps in drug research and can determine the concentration of a drug present in the body. The discovery of new medicines not only depends on pharmacological activity but on pharmacokinetic parameters as well. Pharmacokinetics includes absorption, distribution, metabolism and execration (ADME). Absorption is the absorbing of a drug in the blood stream. There are two types of absorption, passive and active. The physico-chemical properties are responsible for passive transportation while the active transportation determines the binding of a molecule to the target site. The route a drug is administered; physic-chemical properties and the formulation of drugs determine how the drug is absorbed. The failure of absorption may occur due to the drug binding to other molecules in the gut, log p >5, molecular weight>500, more than five hydrogen binding donors, more than ten hydrogen acceptors and clog>5(Lipinski 1997).The second step after absorption is the distribution of drug to tissues and organs through the main bloodstream. It has important roles on the half –life, dose regime and toxicity (Chohan et al 2008).There are some factors which can affect the distribution of drugs such as p-glycoprotein, ion trapping and passive diffusion and binding to macromolecules. (Philip Rowe 2012)
Metabolism includes all the chemical and physical changes in the body. It is divided into two types, catabolism and anabolism. The liver is the main organ responsible for metabolism, but the metabolism enzyme may be found in the skin, blood, the brain barrier, the placenta, kidney and the gut. All the drugs subject to metabolism first pass metabolism while absorption form gastrointestinal tract. The cytochrome (P450) has many functions such as oxidation and de halogenations. The CYP2C9, CYP 3A4 and CYP2D6 play an important role in the metabolism of the majority of drugs. (J.C.MADDEN, 2010). Excretion removes waste from the body and transforms it to urine. The toxicity depends on the properties of ADME. There is a relationship between the ADME and toxicity. The ADME usually has an effect on the concentration of a drug, so it will control its toxicity. The last few years have seen the discovery and improvement of many drugs through their use in the silicon models to predict ADME .The understanding of the properties that influence the ADME are important, leading to the discovery and improvement of a large number of drugs (J.C.MADDEN, 2010).
In recent years a large number of drugs have been used by many descriptors in the models to predict the properties of ADME. There are many descriptors used in the modes, such as log P, log D, polar surface area and functional group. There are some software programs which can predict the ADME properties, such as Accerlrys, Bio-Rad, Chemistry Software Store, computer Drug and molecular discovery. The Accelryes can predict the absorption, blood brain penetration, plasma protein binding and toxicity, store, compuDrug and Cyprotex. The Bio Rad can predict the bio availability, half-life volume of distribution and metabolism. While the Chemistry Software Store predicts the physic-chemical properties and absorption. The compuDrug predicts the first pass metabolism .The molecular discovery predicts the metabolic transformation. The prediction of toxicity is more reliable on the models that predict bio availability and metabolism (J.C.MADDEN, 2010). The properties of ADME are so significant to discover new medicine (TingiunHou et al ,2007).
Clearance
The clearance is the drug completely cleared from the volume of blood in unit time .Most of the drugs is cleared by the liver or the kidney. The total clearance (CL tot) is determined by the amount of drug that is eliminated. The total clearance (CL tot) can determine the steady–state concentration of drug and the dose (C.W.Yap et al). The prediction of liver clearance is significant in the discovery of new drugs and the prediction of the clearance rate has been contributed to the discovery of new drugs. The prediction of clearance provides information about drugs that are quickly eliminated from the body. The prediction of clearance can be used in clinical studies to calculate the initial dose. It is considered to be one of the most important pharmacokinetic parameters. (Zuegge et al 2001). The quantitative structure –pharmacokinetic relationships(QSPKR) can be used to predict the total clearance. (C.W.Yap et al).
Bioavailability, half-life (t1/2)
Bioavailability is the fraction of dose reached by the system circulation without change in the characteristics of the drug. There are some routes of administering drugs which will increase the bioavailability, such as intravenous administration. There are some physical factors that affect the bioavailability such as first pass metabolism, dissolution in gastrointestinal tract and stability. Also there are some phsico-chemical factors which affect the bioavailability such as lipid solubility, salt form, molecular size and hydrogen bond and polymorphism.(Marianne Ashford 2002 ). The absorption and first pass metabolism govern the bioavailability (karl-Heinz Baringhaus and Hans Matter2004).
The half-life (t1/2) is the time required for drugs for the concentration or amount of drug in the body to be reduced by one-half. The volume of distribution (Vd) and the rate of clearance (Cl) control the drug’s half-life. As illustrated in this equation t1/2=0.693Vd / Cl .(J.C.MADDEN, 2010).
t1/2= 0.693Vd/Cl
The half –life is important to toxicity because it determine the period of time the drugs remain in the body. (Judith C. Duffy 2004)
Chemoinformatics
Chemoinformatics is the use of computer and informational techniques, applied to a range of problems in the field of chemistry. In the field of chemo informatics, the chemical structure can be drawn. Also databases can be created. Chemoinformatics is widely used in the industry. Recently chemo informatics has become widely used to reduce toxicity, improve activity and to discover new drugs. The chemical information is significant in providing information about structure, properties, activity, uses, synthesis and manufacture. All this information can be saved in a database. (Mark T.D. Cronin 2011)
Information from the chemical structure can be used to calculate the physical and chemical properties of the molecule and this is called prediction. Therefore it is not necessary to measure the properties. Prediction is sometimes more reliable for some properties, for example log p, however it is less reliable for others, for example pka and boiling point. The addition of the methyl group increased log p, while the addition of the hydroxyl group decreased log p. (Mark T.D. Cronin 2011)
Attempts have long been made to determine the relationship between the structure and biological information. Structure activity relationships (SARs) determine the fragments or chemical group molecules that are responsible for activity. Also it can affect the potency. Structure activity relationships (SARs) play an important role in discovering the toxicity e.g. carcinogenic. (Mark T.D. Cronin 2011)
Quantitative structure activity relationships (QSARs).
The activity of compounds can be predicted by using the silicomodels which use computational methods such as quantitative structure activity relationships (QSARs).They attempt to find a statistical relationship between the biological activity of a substance and its physic-chemical structure. The biological activity includes the pharmacological activity and toxicological activity, while the physic-chemical properties include the activity on the lipophilicity, electronic, steric and topological. There are many advantages of QSAR. For example, it can predict the biological activity, and can also explain the action mechanism. Furthermore it saves time and reduces cost. It can also calculate the physic-chemical properties and has multiple chemical structure descriptors. QSAR has successfully predicted the toxicity and ADME of the molecular characteristic and chemical structure many times. QSAR contains three important parts: biological data, physic-chemical properties and statistical method to link biological activity and physic-chemical structure. (Mark T.D. Cronin 2010)
The biological data is significant in making predictions. Biological details are more reliable when obtained from the same biological test in the same laboratory by the same technicians. Errors sometimes happen, but work of high quality will reduce these errors. There are two types of biological data, continuous and categorical .(Mark T.D.Cronin and T.Wayne Schultz 2003)
Physio-chemical properties and descriptors
The physiochemical properties play an important role in the discovery of new drugs, such as lipophilicity and solubility. The chemical and physical properties can be determined by the shape and structure of molecules. Thephysico- chemical properties or parameters describe thephysico- chemical characteristics of molecules such as the functional group, lipophilicity, steric parameter, electronic parameter, topological and structure information. Lipophilicity can govern the pharm dynamic and pharmacokinetics of the molecule. Theoctanol- water partition coefficient (p) can be used to measure the lipophilicity. It will be used as log P in the QSAR. The octanol- water partition coefficient (p) can be used to measure shake- flask, slow stirring and chromatographic methods(M.T.D.Cronin 2010).The octanol- water partition coefficient (p) is consider the best parameter.(crowinhansch et al,2004)
It can also be used the logarithms of the distribution coefficient (logD) and logarithms of the high performance liquid chromatography (HPLC) capacity factor measured the lipophilicity. Furthermore the logarithms of aqueous solubility (logSaq) can be used to measure lipophilicity. (M.T.D.Cronin 1992).
The lipohilicity can play impotent role on the absorption and distribution of drug. (Han Van de waterbeemd and Eric Gifford 2003).
Electronics play an important role as a binding receptor, for example H- bonding and ionic. It also has an important role in regard to metabolism; reactivity and interactivity .The specific toxicities will be affected by electronic reactivity. The electronic descriptor includes hydrogen bond donating and accepting (HD/HA), energy of the highest unoccupied molecular orbital (EHOMO) and energy of the lowest unoccupied molecular orbital (ELUMO). The electrophonic has (ELUMO), while the nucleophile has (EHOMO). The (ELUMO) can measure the ability to accept electrons. (J.C.MADDEN, 2010).
The steric parameters include the size and shape of molecules that are significant in determining the ability of a molecule to bind to a drug receptor. The size and shape of molecules can have an effect on dissolution. The molecular volume can be used to determine the size. The software will calculate the molecular volume. The molecular weight can also determine the size. The software will calculate the accessibly of surface area .Sterol is used to determine the length and width. The Sterol is considered as a substituent parameter (please write here the difference between the substituent parameter and whole molecule parameter and please provide reverence for that don’t speak more ).The topological parameters depend on the information of graph theory. There are a large number of molecular descriptors used in QSAR. (Mark T.D. Cronin 2010)
The Statistical methods have many details.Theycollect,interpret and analyse the data of biological and physic-chemical properties. The main methods are simple plot (biological activity vs. physic-chemical parameters).also the linear regression analysis and multiple linear regression analysis. Furthermore the statistical measures of goodness of fit are assessed by correlation coefficient(r), coefficient of determination (r2), standard error(s), fisher’s statistic (F), t-ratio and predictive (q2).Statistical regression analysis contains a data matrix with lots of descriptors. (Mark T.D. Cronin 2010)
In the last few decades QSAR has achieved many things contributing to the development of a large number of drugs, for example the prediction of h ERG inhibition and also the prediction of QSAR to Blood Brain Barrier permeation. Furthermore it has achieved the prediction of COX-2 inhibition and the prediction of ADME properties. There are some methods of QSAR to predict (h ERG) such as 2 D QSAR. In the prediction of Blood Brain Barrier permeation (BBB) have been used 3 D solvatochromic to determine the relationship between the 3 D molecular interaction field (MIFs) and BBB permeation. In the predicting of COX 2 have been used Co MFA and CoMSIA. (F.Bajot 2010)
The prediction of the rate of liver clearance is so significant because the clearancecontrolsthe volume of distribution, half –life, metabolism and also the required dose. Therefore clearance plays an important role in administering the dose (Han Van de waterbeemd and Eric Gifford 2003).
The measurement of in vitro clearance by hepatocyte and microtomes.Recently the molecular descriptors have contributed to improve the predicting of drug clearance in liver by both in vivo and in vitrodata from literature. (Soyong Lee and Dongsup Kim 2010)
Molecular descriptors are best at accurately predicting clearance rate in the liver. The molecular descriptors can also be used to predict absorption, blood brain barrier partitioning ,metabolism, cytochrome p450and volume of distribution. In the prediction of liver clearance can use molecular descriptors such as hydrophobicity, molecular weight and aromatic rings. Ito and Houston published data in 2005 about in vitro clearance intrinsic (CL int) and in vivo clearance hepatocyte (CLh) which included 52 compounds( Soyong Lee and Dongsup Kim 2010 ).
The aim
-To determine the relationship between structure and / or properties of chemicals to predict clearance rate in liver (using in vitro and / or in vivo data from the literature)
The Objectives of the Project
Methodology
Firstly the endpoint is selected. Then data is collected by using resources such as web of sciences , other data will collected from literature for example(Ito and Houston 2005) that containing the information of intrinsic clearance values (CLint) in vivo and in vitro human micro some experimental.
After the data collection and the quality of the data is checked, then molecule descriptors will be generated to describe the physic-chemical properties that affect the activity (hydrophobic, electronic parameters and steric parameter). The logarithm of the partition coefficient (log p) will be used to indicate the hydrophobicity.
Afterwards the statistical method will be used to determine the relationship between the biological effect and physic-chemical properties. Multiple linear regression analysis may be used, May also build classification models use for example low and high of clearance.
References
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