KRDS: a web server for evaluating drug resistance mutations in kinases by molecular docking

Aeri Lee,Seungpyo Hong,Dongsup Kim

doi:10.1186/s13321-018-0274-y

Abstract

Kinases are major targets of anti-cancer therapies owing to their importance in signaling processes that regulate cell growth and proliferation. However, drug resistance has emerged as a major obstacle to cancer therapy. Resistance to drugs has various underlying mechanisms, including the acquisition of mutations at drug binding sites and the resulting reduction in drug binding affinity. Therefore, the identification of mutations that are relevant to drug resistance may be useful to overcome this issue. We hypothesized that these mutations can be identified by combining recent advances in computational methods for protein structure modeling and ligand docking simulation. Hence, we developed a web-based tool named the Kinase Resistance Docking System (KRDS) that enables the assessment of the effects of mutations on kinase-ligand interactions. KRDS receives a list of mutations in kinases, generates structural models of the mutants, performs docking simulations, and reports the results to users. The changes in docking scores and docking conformations can be analyzed to infer the effects of mutations on drug binding and drug resistance. We expect our tool to improve our understanding of drug binding mechanisms and facilitate the development of effective new drugs to overcome resistance related to kinases; it may be particularly useful for biomedical researchers who are not familiar with computational environments. Our tool is available at http://bcbl.kaist.ac.kr/KRDS/.

Highlights

Kinases constitute approximately 30% of human cellular proteins and are involved in the transmission of cellular signals by transferring a phosphate group to their specific targets [1, 2]
The docking scores with both the original and mutant kinases are reported for the quantitative evaluation of the effects of mutations on ligand binding (Fig. 2a)
We observed that molecular docking generated moderate docking scores in general for the various conformations of kinases in each state (Additional file 1: Table S4, Figure S2). We examined whether these results are reproduced by our system in which the docking calculations were performed by taking a single Protein Data Bank (PDB) structure from DFG-in and from DFG-out, generating ensembles, conducting dockings on ensembles with ligands, and extracting maximum values among ensembles for each ligand

Summary

Introduction

Kinases constitute approximately 30% of human cellular proteins and are involved in the transmission of cellular signals by transferring a phosphate group to their specific targets [1, 2]. Kinases play important roles in the regulation of cell growth and proliferation and they are potential targets for anti-cancer therapies; kinase inhibitors have been successfully developed into anti-cancer drugs [3,4,5]. Sandgren et al [16] established a well-curated public database containing mutations related to tuberculosis drug resistance, and users can find information on how often certain mutations are observed for particular drugs The association between various mutations and Herceptin in H342-positive breast cancer can be found in the HerceptinR database [21] These databases offer a list of mutations and drug-target associations. Researchers can determine if a certain mutation is associated with drug resistance based on the information in these databases, and the structural changes caused by mutations can be integrated

Methods

Results

Conclusion