Computational Multi-Target Drug Design

  • Azizeh Abdolmaleki
  • Fereshteh Shiri
  • Jahan B. GhasemiEmail author
Part of the Methods in Pharmacology and Toxicology book series (MIPT)


Multi-target (mt) therapy is an attractive approach as well as a challenging task in drug discovery research and pharmaceutical industry. The multi-target drug design strategy is an opportunity to find new drugs for the treatment of two or more targets simultaneously. Advanced characterization of bioactive molecules, computational science, and molecular biology have contributed to planning of new bioactive compounds and evaluating different features of multi-targeted drugs. Computational methods have different roles in drug candidate searching, analysis, and prediction in this field. Here, we discuss several in silico methodologies and computer-aided drug design (CADD) as structure-activity relationship (SAR), quantitative SAR (QSAR), pharmacophore modeling, and molecular docking in the process of drug discovery in the field of multi-targeted drugs (MTDs). Computational efficiency of each method has been stated in relation to their key strength and weakness. These capacities for binding affinity prediction are rationally effective with promising potential in easing drug discovery directed at selective multiple targets.


CADD Drug discovery Molecular docking MTD/MTDD Multi-target Pharmacophore QSAR SAR 




Absorption, distribution, metabolism, excretion, and toxicity


Artificial neural network


Active pharmaceutical ingredient


Computer-aided drug design


Consensus Induced Fit Docking


Central nervous system


Drug-drug interaction


Decision trees


Emerging chemical patterns


Feature net


Graphics processing unit


Group-based QSAR


High-throughput screening


k-nearest neighbor


Linear discriminant analysis


Logistic regression


Molecular dynamics




Multi-targeted drugs


Multi-target drug discovery/design


Multi-target docking


Multitask learning


Multitask learning


Multi-targeted molecular dynamics


Multi-target quantitative structure-activity relationships


Multi-target structure-activity relationships


Receiver operating characteristics


Structure-activity relationships


Support vector machines


Virtual screening




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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Azizeh Abdolmaleki
    • 1
  • Fereshteh Shiri
    • 2
  • Jahan B. Ghasemi
    • 3
    Email author
  1. 1.Department of Chemistry, Tuyserkan BranchIslamic Azad UniversityTuyserkanIran
  2. 2.Department of ChemistryUniversity of ZabolZabolIran
  3. 3.Drug Design in Silico Lab., Chemistry FacultyUniversity of TehranTehranIran

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