Quorum Sensing

(sharon) #1

3 Methods


3.1 Virtual Screening 1. The database including 0.5 million compounds from Specs
Ltd. is first converted into 3D structures using the CON-
CORD program [27] and filtered using drug-like property
criteria [28] by the FILTER 2.0.1 software [29].



  1. The protein structure is added with hydrogen atoms. All atoms
    are assigned Kollman-all charges by the SYBYL 7.1 program
    (SYBYL 7.1, 2005 Tripos Inc., St. Louis, MS).

  2. The 3D structures of the small molecules are added with
    hydrogen and assigned AM1-BCC partial charges.

  3. The active site for the virtual screening is in the radius of 6 A ̊
    around the center of AI-2, includes residues Pro74, Gln77,
    Ser79, Asp80, Tyr81, Trp 82, Pro109, Asn159, His180,
    Phe206, Ile211, Arg215, Cys264, Ser265, Thr266, Asp267,
    Trp289, Gly290, Gly291, Glu295, and Arg310. In the LuxPQ
    holo-form crystal structure, the borate moiety of AI-2 generates
    several hydrogen bonds with the positively charged residues
    Arg215 and Arg310 for stabilizing the negative charge. Mean-
    while, this borate group can also form hydrogen bonding with
    Ser79 and Thr266. Further, residues Trp82, Ser79, and Gln77
    provide multiple hydrogen bonds with the two hydroxyl
    groups of AI-2 also have, and Asn159 and Arg215 has hydro-
    gen bonds with the oxygen atom of furanoyl ring (Fig.3).

  4. The position and conformation of each compound are opti-
    mized first by the anchor fragment orientation and then by the
    torsion minimization method implemented in the DOCK6
    program [30, 31].

  5. Each compound is generated with 50 conformations and a
    maximum of 100 anchor orientations. By the way, all of
    the docked conformations are energy minimized by 100 itera-
    tions [31].

  6. The docked molecules are ranked based on the sum of thevan
    der Waalsand electrostatic energies to get the top 1000 hits.

  7. In order to identify a specific association between the ligands
    and LuxP, the resulting structures are analyzed using PyMOL
    0.99, HBPLUS 3.06, and Ligplotþ1.4.5.


3.2 Compounds
Selection



  1. Carry out a consensus scoring evaluation of the top 1000 hits
    from virtual screening results and select the top 10% com-
    pounds (seeNote 2). Our consensus scoring efforts consisted
    of ChemScore, OEChemscore, PLP, ScreenScore, Chem-
    Gauss3, CGO, and ShapeGauss implemented in the FRED
    2.2.3 software (FRED 2.2.3, 2007 OpenEye Scientific Soft-
    ware, Inc., Santa Fe, NM).


In silicoIdentification of AI-2 Inhibitors 357
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