Predictive ADME

There are a plethora of very critical and most vital pharmacokinetic characteristic properties so as to obtain a highly specific and effective therapeutic drug substance. Lipinski et. al. (1997) postulated that the three major physical variables viz., potency, solubility and permeability may be carefully adapted to increase the overall activity of potential oral drug substances predominantly. They also observed that relatively poor permeation i.e., absorption) is commonly attributed by the following characteristic features either inducted alone or more than one right into the proposed drug molecule a Plus five H-bond donors, a Plus ten H-bond acceptors, a More than 500 molecular weight, and a More than five computed Tog P (hydrophobicity) values. 

Singh et al. (2003) put forward a more latest predictive model (design) for the cytochrome P-450 (CYP) 3A4 metabolism. This method exclusively rests upon the primary lateral sclerosis (PLS), however, one of the descriptors is totally based on acute myocardial infarction (AMl)-calculated H-atom abstraction process. 

In fact, there are several important assumptions, namely  

AMI-H-atom Abstraction The AMl-calculations essentially makes use of a procedure to explain the fact that unpaired electrons are involved, which eventually interacted on a series of known drug substances. It may be modified duly according to the availability of chemical descriptors. 

In short, CADD has already acclaimed enormous qualified success in the recent past, and intend to accomplish still greater peak in the years yet to come. 

---

Use in silico systems to predict ADME and toxic properties... 

Krejsa, C.M., Horvath, D., Rogalski, S.L., Penzotti, J.E., Mao, B., Barbosa, F. and Migeon, J.C. (2003) Predicting ADME properties and side effects the BioPrint approach. Current Opinion in Drug Discovery and Development, 6, 471-480. 

Butina D, Segall MD, Frankcombe K. Predicting ADME properties in silico methods and models, Drug Discovery Today 1 (May) S83-S88 (2002). 

A recent review evaluating virtual screening lists in terms of predicted ADME and toxicology properties demonstrates some advantages of the integration of in silico approaches in search for viable lead structures [298]. 

Bereseord, A.P., Selick, H.E., and Tarbit, M.H. The emerging importance of predictive ADME simulation in drug discovery. Drug Disc. Today 2002, 7, 109-116. 

Krejsa CM, Horvath D, Rogalski SL, et al. (2003) Predicting ADME properties and side effects The BioPrint approach. Curr. Opini. Drug Discov. Dev. 6 470-480. 

Yamashita F, Hashida M (2004) In silico approaches for predicting ADME properties of drugs. Drug Metab Pharmacokinet 19, 327-338. 

A further increase in the interest for predictive ADME/T methods is due to the development of high-throughput screening and synthesis methods. The possibility to design, make and test millions of compounds has increased the... 

Each year, a growing number of publications report on computational methods for the development of predictive ADME/T models. However, currently available methods are not reliable enough and are limited in their application, despite the recognition of their importance in the drug discovery process. Are we able to generate such reliable models, considering the severe limitations related to the intrinsic chemical diversity, the quantity and quality of the data In this chapter, we critically review data and approaches used to develop physicochemical and biological ADME/T models, in an attempt to address this question. 

Extensive use has been tnade of semiempirieal methods in drug design. " Calculations of the highc.si occupied MO and lowe.st unoccupied MO IHOMO/LUMO) energies for a series of active and inactive compounds have been used as de.scriptors for QSAR. AMI. for example, has recently been used to develop a predictive ADME model for P-450 oxidation of drugs, which is di.scu.sscd below. 

The landscape of pharmaceutical research has changed. There is increased pressure to discover medicines and to get those medicines into patient populations as quickly and inexpensively as possible. This pressure drives efforts to predict ADME properties in humans with human in vitro metabolism data, and correlations between in vitro and in vivo animal data. These same factors, speed and cost, also fuel research to use in vitro data alone to predict in vivo ADME properties in animals. While the exclusive use of in vitro data would... 

ADME properties have been recognized as a major reason for the failure of dmg candidates thus, several efforts are performed to develop molecular descriptors and models able to predict ADME properties of dmg candidates before their synthesis. Bibliographic references to theoretical aspects and QSAR studies on ADME properties are reported in the thematic bibliography. 

---