Identification of Target Associations for Polypharmacology from Analysis of Crystallographic Ligands of the Protein Data Bank

Abstract

The design of a chemical entity that potently and selectively binds to a biological target of therapeutic relevance has dominated the scene of drug discovery so far. However, recent findings suggest that multitarget ligands may be endowed with superior efficacy and be less prone to drug resistance. The Protein Data Bank (PDB) provides experimentally validated structural information about targets and bound ligands. Therefore, it represents a valuable source of information to help identifying active sites, understanding pharmacophore requirements, designing novel ligands, and inferring structure–activity relationships. In this study, we performed a large-scale analysis of the PDB by integrating different ligand-based and structure-based approaches, with the aim of identifying promising target associations for polypharmacology based on reported crystal structure information. First, the 2D and 3D similarity profiles of the crystallographic ligands were evaluated using different ligand-based methods. Then, activity data of pairs of similar ligands binding to different targets were inspected by comparing structural information with bioactivity annotations reported in the ChEMBL, BindingDB, BindingMOAD, and PDBbind databases. Afterward, extensive docking screenings of ligands in the identified cross-targets were made in order to validate and refine the ligand-based results. Finally, the therapeutic relevance of the identified target combinations for polypharmacology was evaluated from comparison with information on therapeutic targets reported in the Therapeutic Target Database (TTD). The results led to the identification of several target associations with high therapeutic potential for polypharmacology.

LigAdvisor: a versatile and user-friendly web-platform for drug design

“…This type of search is expected to help identify novel potential multi-target ligands, based on the concept that structurally similar compounds could have similar biological activities ( 29 ). These results could also be useful to identify the more suitable protein conformation(s) for subsequent structure-based in silico polypharmacology design, as previously reported ( 13 , 15 , 23 ). Targets can be queried through their UniProt identifiers or names via a drop-down menu, which was designed to dynamically restrict the search upon the keyword typed in the dedicated input text box (Figure 2C ).…”

“…In a recent study ( 15 ), we performed extensive in silico investigations within the Protein Data Bank (PDB) ( 16 ), with the aim of identifying promising target combinations for polypharmacology. The results of this study allowed us to conclude that ligands reported within the PDB represent a reliable source of structural and biological information for multi-target drug design and repurposing ( 15 ).…”

“…In a recent study ( 15 ), we performed extensive in silico investigations within the Protein Data Bank (PDB) ( 16 ), with the aim of identifying promising target combinations for polypharmacology. The results of this study allowed us to conclude that ligands reported within the PDB represent a reliable source of structural and biological information for multi-target drug design and repurposing ( 15 ). Moreover, we also discussed on how the chemical space covered by crystallographic ligands in the PDB is significantly less populated by pan-assay interference (PAINS) and potential false positive compounds, even if it is lower in size with respect to other bioactivity-oriented databases ( e.g ., PubChem ( 17 ) and ChEMBL ( 18 ), these aspects being of crucial interest in target-driven drug discovery.…”

Dual Targeting Strategies on Histone Deacetylase 6 (HDAC6) and Heat Shock Protein 90 (Hsp90)

“…Thus, the potential benefit in targeting HDAC6 and Hsp90 with dual-acting drug has garnered considerable interest from the scientific community. Rationally designing multi-target ligands is still a challenge, especially for targets as Hsp90 and HDAC6, which do not share significant binding site similarity [41][42][43][44]. However, computational approaches have proved to be of help in screening and selecting suitable candidates [45,46].…”

Identification of potential biological targets of oxindole scaffolds via in silico repositioning strategies

“…10 A repurposing workflow integrating different computational approaches was implemented in order to increase the robustness of the adopted in silico protocol, 6 such a procedure having already demonstrated to increase the screening performances in polypharmacology contexts. 11 In particular, we firstly carried out extensive 2D fingerprint-and 3D shape-based similarity estimations on the investigated library of compounds against ligands with a known profile of activity, extracted from the DrugBank, Protein Data Bank and ChEMBL databases. [12][13][14] Interestingly, several targets emerged as valuable candidates for the repositioning of the compounds.…”