yes i am also curious to know Why Lipinski Rules of Five is popular?

and what is success after applying this science in drug discovery?

Hi Chintamani,

Lipinski's rule of five (Ro5) is popular as the properties are simple to calculate and like Yogesh stated they are a quick filter to highlight potential problematic compounds.

There have been alternatives to the Ro5 that have been published the overall results are that these newer rules do not really differ much from Lipinski's original Ro5. This could be due to the that the chemical properties of successful drugs has not changed very much and have remained pretty constant - but this is probably no longer the case now with compounds being larger, having higher lipophilicity and therefore poor solubility.

Although using the Ro5 does not guarantee compound success, compounds that violate > 2 of the rules have less chances of survival to progress through drug development. However there are exceptions to this.

BLAKE, J. F. (2005) Identification and Evaluation of Molecular Properties Related to Preclinical Optimization and Clinical Fate. Medicinal Chemistry, 1, 649-655.

Indeed there are many limitations to the rule of five (Ro5). It is a metric that can predict drug-likeness, although biologicals, natural products and parenteral drugs are not included in this prediction. I too believe that the key feature in the Ro5 is its simplicity. Making it an efficient tool early in the design process. However, this "rule" should be used with caution and more complicated metrics should be used where appropriate.

Hi Maria, can you share which caution we should consider while using Ro5?

Hello Chintamani!

I meant that we should know the limitations of Ro5 so that we don't try to forcefully apply this rule on drugs that are known to be exceptions to the rule such as biologicals, natural products and parenteral drugs. Moreover, the Ro5 is a good metric for the initial stages of drug development (hit/lead identification), whereas easiliy calculated metrics that include both physicochemical properties and activity are to be used in the optimization procedures (useful metrics in this view are LE or BEI, LLE, LELP etc).

Maria, where i can get the depth information about this LE or BEI, LLE, LELP metrics.

Is their any better substitute for Ro5.

Chintamani hello again

If you want further info about these metrics (apart from Deepak's nice intro) I believe you should read these papers:

1) Hopkins, A. L.; Groom, C. R.; Alex, A. Ligand efficiency: a useful metric for lead selection. Drug Discov Today 2004, 9, 430-431

2) Leeson, P. D.; Springthorpe, B. The influence of drug-like concepts on decision-making in medicinal chemistry. Nat Rev Drug Discov 2007, 6, 881-890.

3) Keseru, G. M.; Makara, G. M. The influence of lead discovery strategies on the properties of drug candidates. Nat Rev Drug Discov 2009, 8, 203-212.

4) Perola, E. An analysis of the binding efficiencies of drugs and their leads in successful drug discovery programs. J Med Chem 2010, 53, 2986-2997.

5) Hann, M. M. Molecular obesity, potency and other addictions in drug discovery. MedChemComm 2011, 2, 349-355.

6) Tarcsay, A.; Nyiri, K.; Keseru, G. M. Impact of lipophilic efficiency on compound quality. J Med Chem 2012, 55, 1252-60.

Enjoy!!

Have a look on following article/os

https://www.researchgate.net/publication/236731043_Open_Source_Software_and_Web_Services_for_Designing_Therapeutic_Molecules?ev=prf_pub

http://osddlinux.osdd.net/

Article Open Source Software and Web Services for Designing Therapeu...

Thank you Deepak, Maria and Gajendra sir.

Maria the articles suggested by you seem valuable. I will back to you, if i will find any query. Thank you.

The only reason to use Ro5 in computer aided drug design is to exclude many compounds that seem not look like orally bioavailable drug (what CADD is usually interesting in) at the early stage of virtual screening. Why Ro5 - it requires calculation very simple descriptors that can be easily calculated. Yes, too strong bias towards Ro5 would exclude many drugs. But Ro5 should be used on the EARLY stage and it is not good idea to use it in hit and lead optimization. That is why I personally don't understand why we need more complicated filters of drug-likeness like proposed. Computation of it requires as much time as QSAR models, that is applied on already filtered dataset. There can be some needs in it, but as I feel proposed idea would not be as popular as simple and crude Ro5.

The ro5 seems to be popular because its easy to remember and its pretty simply to enunciate and apply

It can also be easily applied when designing compound datasets

Jorgensen's rule of three for predicting oral bioavailability is also very practical but not very cited.

Dear Fidele, could you share what is Jorgensen's rule? I'm collecting them.

Jorgensen's rule was designed by Professor William L. Jorgensen calculated using Qikprop 2.5 tool of Schrodinger software. It evaluates the acceptability of analogs based on Lipinski’s rule of five which is essential to ensure drug-like pharmacokinetic profile while using rational drug design.

According to Jorgensen’s rule of three, there

should have QPlogS>-5.7, QPPCaco>22nm/s, # Primary Metabolites

It's basic and simple to use! Helps to weed out unlikely candidates early enough. Hit and lead optimization usually lead to non-compliance with Ro5. Ro3 may be more relevant in identifying lead-like candidates prior to hit and lead optimization.

In my humble opinion  the popularity of the Lipinski rules is that  the rules give a researcher something like a  moral right to make in vivo or virtual screening with a significantly truncated local data base, and this save the time and computer resources. 

Dear Dr. kathayat,

Here is the site where you can download the software DRULITO

http://en.freedownloadmanager.org/Windows-PC/DruLiTo-FREE.html