In silico methods and tools for drug discovery

被引:301
作者
Shaker, Bilal [1 ]
Ahmad, Sajjad [2 ]
Lee, Jingyu [1 ]
Jung, Chanjin [1 ]
Na, Dokyun [1 ]
机构
[1] Chung Ang Univ, Dept Biomed Engn, 84 Heukseok Ro, Seoul 06974, South Korea
[2] Abasyn Univ, Dept Hlth & Biol Sci, Peshawar 25000, Pakistan
基金
新加坡国家研究基金会;
关键词
Computational drug discovery; Computer-aided drug design; Target identification; Virtual screening; Toxicity prediction; IMMUNODEFICIENCY-VIRUS PROTEASE; MOLECULAR-DYNAMICS SIMULATIONS; ORALLY BIOAVAILABLE INHIBITOR; LIGAND-BINDING-SITES; WEB SERVER; TARGET IDENTIFICATION; STRUCTURE PREDICTION; MEDICINAL CHEMISTRY; HIGH-THROUGHPUT; HIT IDENTIFICATION;
D O I
10.1016/j.compbiomed.2021.104851
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In the past, conventional drug discovery strategies have been successfully employed to develop new drugs, but the process from lead identification to clinical trials takes more than 12 years and costs approximately $1.8 billion USD on average. Recently, in silico approaches have been attracting considerable interest because of their potential to accelerate drug discovery in terms of time, labor, and costs. Many new drug compounds have been successfully developed using computational methods. In this review, we briefly introduce computational drug discovery strategies and outline up-to-date tools to perform the strategies as well as available knowledge bases for those who develop their own computational models. Finally, we introduce successful examples of antibacterial, anti-viral, and anti-cancer drug discoveries that were made using computational methods.
引用
收藏
页数:15
相关论文
共 270 条
[1]   Computational/in silico methods in drug target and lead prediction [J].
Agamah, Francis E. ;
Mazandu, Gaston K. ;
Hassan, Radia ;
Bope, Christian D. ;
Thomford, Nicholas E. ;
Ghansah, Anita ;
Chimusa, Emile R. .
BRIEFINGS IN BIOINFORMATICS, 2020, 21 (05) :1663-1675
[2]   Identification of natural inhibitors against Acinetobacter baumannii D-alanine-D-alanine ligase enzyme: A multi-spectrum in silico approach [J].
Ahmad, Sajjad ;
Raza, Saad ;
Abbasi, Sumra Wajid ;
Azam, Syed Sikander .
JOURNAL OF MOLECULAR LIQUIDS, 2018, 262 :460-475
[3]   Apalutamide: A Review in Non-Metastatic Castration-Resistant Prostate Cancer [J].
Al-Salama, Zaina T. .
DRUGS, 2019, 79 (14) :1591-1598
[4]   A New Approach for Drug Target and Bioactivity Prediction: The Multifingerprint Similarity Search Algorithm (MuSSeL) [J].
Alberga, Domenico ;
Trisciuzzi, Daniela ;
Montaruli, Michele ;
Leonetti, Francesco ;
Mangiatordi, Giuseppe Felice ;
Nicolotti, Orazio .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2019, 59 (01) :586-596
[5]   QSAR-Co: An Open Source Software for Developing Robust Multitasking or Multitarget Classification-Based QSAR Models [J].
Ambure, Pravin ;
Halder, Amit Kumar ;
Gonzalez Diaz, Humbert ;
Cordeiro, M. Natalia D. S. .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2019, 59 (06) :2538-2544
[6]   The process of structure-based drug design [J].
Anderson, AC .
CHEMISTRY & BIOLOGY, 2003, 10 (09) :787-797
[7]   Computational discovery of putative quorum sensing inhibitors against LasR and RhlR receptor proteins of Pseudomonas aeruginosa [J].
Annapoorani, Angusamy ;
Umamageswaran, Venugopal ;
Parameswari, Radhakrishnan ;
Pandian, Shunmugiah Karutha ;
Ravi, Arumugam Veera .
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN, 2012, 26 (09) :1067-1077
[8]  
[Anonymous], 1990, M 196 1988 LOS ANG C
[9]  
[Anonymous], 2014, J. Transl. Toxicol, DOI DOI 10.1166/JTT.2014.1005
[10]   The polypharmacology browser: a web-based multi-fingerprint target prediction tool using ChEMBL bioactivity data [J].
Awale, Mahendra ;
Reymond, Jean-Louis .
JOURNAL OF CHEMINFORMATICS, 2017, 9