Search Filters

    Here are some examples showing how some well-known chemical rules used for searching chemical databases can be formulated by the help of the Chemical Terms language:

    Lipinski's Rule Of Five

    This rule states that the absorption or permeation of a molecule is more likely when the molecular weight is under 500 g/mol, the value of logP is lower than 5, and the molecule has utmost 5 H-donor and 10 H-acceptor atoms.

    At first, all components of the rule can be translated to the Chemical Terms language:

    
    mass()<=500
    logP()<=5
    donorCount()<=5
    acceptorCount()<=10

    Then, the relation of the individual components can be indicated by the use of the "AND" logical operator:

    
    (mass()<=500) AND
    (logP()<=5) AND
    (donorCount()<=5) AND
    (acceptorCount()<=10)

    Thus, molecules fulfilling the requirements of the Lipinski rule, do not violate any term of this chemical expression.

    {primary} Note the parenthesis pattern of the created expression.

    Ghose filter

    This filter defines drug-likeness constraints as follows: calculated log P is between -0.4 and 5.6, molecular weight is between 160 and 480, molar refractivity is between 40 and 130, and the total number of atoms is between 20 and 70.

    First we formulate all components of the rule with Chemical Terms:

    logP()>=-0.4
    logP()<=5.6
    mass()>=160
    mass()<=480
    atomCount()>=20
    atomCount()<=70
    refractivity()>=40
    refractivity()<=130

    {primary} In spite of having only four properties in the filter, every property should be included twice as two conditions are applied for each property.

    Subsequently, properties can be combined to formulate the Ghose filter:

    (logP()>=-0.4) AND (logP()<=5.6) AND
    (mass()>=160) AND (mass()<=480) AND
    (atomCount()>=20) AND (atomCount()<=70) AND
    (refractivity()>=40) AND (refractivity()<=130)

    References

    1. Lipinski, C.A.; Lombardo, F.; Dominy, B. W., Feeney, P. J.: Experimental and computational approaches to estimate solubility and permeabilityin drug discovery and development settings., Adv. Drug Deliv. Rev., 23 , 3 (1997)

    2. Ghose, AK.; Viswanadhan, VN.; Wendoloski JJ.: A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases., J. Comb. Chem. , 1 , 55 (1999)