Lipinski s "rule

To become familiar with Lipinski s Rule of Five"... 

In general, the first step in virtual screening is the filtering by the application of Lipinski s Rule of Five [20]. Lipinski s work was based on the results of profiling the calculated physical property data in a set of 2245 compounds chosen from the World Drug Index. Polymers, peptides, quaternary ammonium, and phosphates were removed from this data set. Statistical analysis of this data set showed that approximately 90% of the remaining compounds had ... 

IC5o=1.0pM, MW=294, HA=22). Open circles indicate compounds with R05>1 (at least one parameter from Lipinski s Rule-of 5 is out of range). Activity data extracted from GVKBIO. 

At the broadest end of the spectrum, filters based on the calculation of physiochemical properties, the most obvious being the Lipinski s rule of... 

In a comparison between Lipinski s rules and the J-Alert, we have found that the Rule of 5 accurately identifies some of the compounds that have unfavorable ADME properties, but also allows many of the poor compounds to go undetected. By contrast, the J-Alert identifies a much higher fraction of the unfavorable compounds but additionally identifies many ADME positives. 

The genesis of in silico oral bioavailability predictions can be traced back to Lip-inski s Rule of Five and others qualitative attempts to describe drug-like molecules [13-15]. These processes are useful primarily as a qualitative tool in the early stage library design and in the candidate selection. Despite its large number of falsepositive results, Lipinski s Rule of Five has come into wide use as a qualitative tool to help the chemist design bioavailable compounds. It was concluded that compounds are most likely to have poor absorption when the molecular weight is >500, the calculated octan-l-ol/water partition coefficient (c log P) is >5, the number of H-bond donors is >5, and the number of H-bond acceptors is >10. Computation of these properties is now available as an ADME (absorption, distribution, metabolism, excretion) screen in commercial software such as Tsar (from Accelrys). The rule-of-5 should be seen as a qualitative, rather than quantitative, predictor of absorption and permeability [16, 17]. 

Medicinal chemists have always been adept in recognizing trends in physicochemical properties of molecules and relating them to molecular structure. With rapid increase in the number of hits and leads, computational tools have been proposed to calculate molecular properties that may predict potential absorption hurdles. For example, Lipinski s "Rule of 5"14 states that poor absorption or permeation are likely when ... 

Interestingly, the PRCC is relatively free of compounds that violate Lipinski s Rule of Five (ROF) [15] as shown in Table 13.1. Similar ROF behavior has also been observed by Oprea [16] for other compound databases including the ACD and the MDDR (MDL Drug Data Report, MDL Information Systems, San Leandro, CA). 

None of these methods gives a perfect prediction, particularly because H-bonding potential needs to be overlaid over intrinsic lipophilicity. For this reason Lipinski s rule-of-five becomes valuable in defining the outer limits in which chemists can work [9]. Lipinski defined the boundaries of good absorption potential by demonstrating that poor permeability is produced by ... 

Based on the analysis of 2245 compounds from the WDI which were investigated in Phase II and later clinical trials, Lipinski s Rule-of-5 predicts... 

The pioneers of bioavailability modeling can be traced back to year 2000. Andrews and coworkers [57] developed a regression model to predict bioavailability for 591 compounds. Compared to the Lipinski s "Rule of Five," the false negative predictions were reduced from 5% to 3%, while the false positive predictions decreased from 78% to 53%. The model could achieve a relatively good correlation (r2 = 0.71) for the training set. But when 80/20 cross-validation was applied, the correlation was decreased to q1 — 0.58. 

The optimization of physicochemical properties can be dealt with by applying simple thresholds such as Lipinski s rule-of-five (19). The rule states that if a compound violates any two of the following rules it is predicted to have poor oral absorption ... 

Owing to drug developability requirements, design criteria such as Lipinski s rules of 5 (16), Veber s rotatable bond rule (17), and drug-likeness concept... 

Lipinski s Rule of 5 (16) states that compounds associated with good developability properties have MW less than 500, logP less than 5, and no more than 5 donors or 10 acceptors. We took these four terms as our initial set of developability parameters, in each case taking the term to be minimized as the fraction of the total number of molecules in the library that fall outside of the limit for each term. Lipinski s values for each term are used as defaults, but all are variables under the control of the user. 

Simple empirical rules (e.g. Lipinski s rule of 5 ) based on observations of existing drugs to filter out oompounds with unwanted physicochemical properties or stmctural elements... 

Figure 2.1 The evolution of the drug-likeness concept. Drug-likeness evolved from empirical rules such as Lipinski s rule of 5 through more sophisticated data mining algorithms into utilization of preclinical profiling and safety pharmacology data [3].

This has been shown to work well for a diverse set of libraries (see Note 2) (4). In Fig. 17.3, the offset is calculated for the oxazolidine library for properties related to Lipinski s rule of five (8) the number of hydrogen bond acceptors (HBA), the number of hydrogen bond donors (HBD), the number of non-hydrogen atoms (NHA), and the calculated log P (9). 

They found that with regard to absorption, which is primarily passive in fish, compounds that are ionized are less likely to be taken up than neutral compounds, and that increased bioavailability was a function of molecular weight (<500), logPe/w (<5), H-bond acceptors (<4—5), and H-bond donors (<7-10) based on drug design from Lipinski s rule of five [57, 58]. de Wolf et al. [59] recommended that compounds with a molecular length of >4.3 nm indicates no uptake or bioconcen-... 

---