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Computational Multi-Target Drug Design

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

Abstract

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.

Keywords

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

Notes

Glossary

ADME/Tox

Absorption, distribution, metabolism, excretion, and toxicity

ANN

Artificial neural network

API

Active pharmaceutical ingredient

CADD

Computer-aided drug design

cIFD

Consensus Induced Fit Docking

CNS

Central nervous system

DDI

Drug-drug interaction

DT

Decision trees

ECP

Emerging chemical patterns

FN

Feature net

GPU

Graphics processing unit

GQSAR

Group-based QSAR

HTS

High-throughput screening

kNN

k-nearest neighbor

LDA

Linear discriminant analysis

LR

Logistic regression

MD

Molecular dynamics

MI

MARCH-INSIDE

MTD

Multi-targeted drugs

MTDD

Multi-target drug discovery/design

mt-docking

Multi-target docking

MTL

Multitask learning

MTL

Multitask learning

MTMD

Multi-targeted molecular dynamics

mt-QSARs

Multi-target quantitative structure-activity relationships

mt-SARs

Multi-target structure-activity relationships

ROC

Receiver operating characteristics

SARs

Structure-activity relationships

SVM

Support vector machines

VS

Virtual screening

WSOF

Weighted-sum-of-objective-functions

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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
  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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