Similarity-driven flexible ligand docking

Abstract

A similarity‐driven approach to flexible ligand docking is presented. Given a reference ligand or a pharmacophore positioned in the protein active site, the method allows inclusion of a similarity term during docking. Two different algorithms have been implemented, namely, a similarity‐penalized docking (SP‐DOCK) and a similarity‐guided docking (SG‐DOCK). The basic idea is to maximally exploit the structural information about the ligand binding mode present in cases where ligand‐bound protein structures are available, information that is usually ignored in standard docking procedures. SP‐DOCK and SG‐DOCK have been derived as modified versions of the program DOCK 4.0, where the similarity program MIMIC acts as a module for the calculation of similarity indices that correct docking energy scores at certain steps of the calculation. SP‐DOCK applies similarity corrections to the set of ligand orientations at the end of the ligand incremental construction process, penalizing the docking energy and, thus, having only an effect on the relative ordering of the final solutions. SG‐DOCK applies similarity corrections throughout the entire ligand incremental construction process, thus affecting not only the relative ordering of solutions but also actively guiding the ligand docking. The performance of SP‐DOCK and SG‐DOCK for binding mode assessment and molecular database screening is discussed. When applied to a set of 32 thrombin ligands for which crystal structures are available, SG‐DOCK improves the average RMSD by ca. 1 Å when compared with DOCK. When those 32 thrombin ligands are included into a set of 1,000 diverse molecules from the ACD, DIV, and WDI databases, SP‐DOCK significantly improves the retrieval of thrombin ligands within the first 10% of each of the three databases with respect to DOCK, with minimal additional computational cost. In all cases, comparison of SP‐DOCK and SG‐DOCK results with those obtained by DOCK and MIMIC is performed. Proteins 2000;40:623–636. © 2000 Wiley‐Liss, Inc.

The Basis for Target‐Based Virtual Screening: Protein Structures

“…Category 3 covers constraints that enforce similarity to a known binding mode of a ligand (see, for example, Ref. [64]). In this category, there are scaffold-based constraints, where a known ligand scaffold is detected in each ligand and made to occupy the same site as an ideally placed scaffold.…”

Virtual Screening in Drug Discovery

“…For example, if it is known that there is a requirement for a bound water in the active site, this can be included as part of the receptor in the dock run. If it is seen that there is always a specific interaction or pharmacophore that occurs, this can be forced on the ligands in the dock run, either as part of the run if the software allows or in postprocessing of the results (Fradera et al, 2000;Good et al, 2003;Hindle et al, 2002;Verdonk et al, 2004). Kinase targets provide a good example, where there are known important interactions, such as a hydrogen bond to a main-chain NH group in the hinge region (Fig.…”

Unsupervised guided docking of covalently bound ligands

“…DOCK is the main program, while MIMIC is used to calculate similarity corrections when needed. MacDOCK can perform standard docking calculations, as in DOCK 4.0, and several kinds of similarity-driven docking calculations [15].…”

“…In our laboratory, we have been developing a guided docking approach (MacDOCK [15]) aiming at maximally exploiting all the structural information present in ligand-bound protein structures by combining a protein-ligand docking method (DOCK 4.0 [16]) and a ligand-ligand superposition method (MIMIC [17]). Within this approach, the docking of a ligand into the protein cavity is guided by the presence of functional groups or structural features from bound ligands, so that the final ligand orientations obtained are a balance between having a good interaction within the cavity and retaining a good overlap with the ligand-based structural information provided.…”