1
|
ER-RAJY M, EL FADILI M, MRABTI NN, ZAROUGUI S, ELHALLAOUI M. QSAR, molecular docking, ADMET properties in silico studies for a series of 7-propanamide benzoxaboroles as potent anti-cancer agents. CHINESE JOURNAL OF ANALYTICAL CHEMISTRY 2022. [DOI: 10.1016/j.cjac.2022.100163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
|
2
|
Jiménez-Luna J, Grisoni F, Weskamp N, Schneider G. Artificial intelligence in drug discovery: recent advances and future perspectives. Expert Opin Drug Discov 2021; 16:949-959. [PMID: 33779453 DOI: 10.1080/17460441.2021.1909567] [Citation(s) in RCA: 83] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Introduction: Artificial intelligence (AI) has inspired computer-aided drug discovery. The widespread adoption of machine learning, in particular deep learning, in multiple scientific disciplines, and the advances in computing hardware and software, among other factors, continue to fuel this development. Much of the initial skepticism regarding applications of AI in pharmaceutical discovery has started to vanish, consequently benefitting medicinal chemistry.Areas covered: The current status of AI in chemoinformatics is reviewed. The topics discussed herein include quantitative structure-activity/property relationship and structure-based modeling, de novo molecular design, and chemical synthesis prediction. Advantages and limitations of current deep learning applications are highlighted, together with a perspective on next-generation AI for drug discovery.Expert opinion: Deep learning-based approaches have only begun to address some fundamental problems in drug discovery. Certain methodological advances, such as message-passing models, spatial-symmetry-preserving networks, hybrid de novo design, and other innovative machine learning paradigms, will likely become commonplace and help address some of the most challenging questions. Open data sharing and model development will play a central role in the advancement of drug discovery with AI.
Collapse
Affiliation(s)
- José Jiménez-Luna
- Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland
| | - Francesca Grisoni
- Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland
| | - Nils Weskamp
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an Der Riss, Germany
| | - Gisbert Schneider
- Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland
| |
Collapse
|
3
|
Rabelo VWH, Romeiro NC, Abreu PA. Design strategies of oxidosqualene cyclase inhibitors: Targeting the sterol biosynthetic pathway. J Steroid Biochem Mol Biol 2017; 171:305-317. [PMID: 28479228 DOI: 10.1016/j.jsbmb.2017.05.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Revised: 04/29/2017] [Accepted: 05/04/2017] [Indexed: 01/04/2023]
Abstract
Targeting the sterol biosynthesis pathway has been explored for the development of new bioactive compounds. Among the enzymes of this pathway, oxidosqualene cyclase (OSC) which catalyzes lanosterol cyclization from 2,3-oxidosqualene has emerged as an attractive target. In this work, we reviewed the most promising OSC inhibitors from different organisms and their potential for the development of new antiparasitic, antifungal, hypocholesterolemic and anticancer drugs. Different strategies have been adopted for the discovery of new OSC inhibitors, such as structural modifications of the natural substrate or the reaction intermediates, the use of the enzyme's structural information to discover compounds with novel chemotypes, modifications of known inhibitors and the use of molecular modeling techniques such as docking and virtual screening to search for new inhibitors. This review brings new perspectives on structural insights of OSC from different organisms and reveals the broad structural diversity of OSC inhibitors which may help evidence lead compounds for further investigations with various therapeutic applications.
Collapse
Affiliation(s)
- Vitor Won-Held Rabelo
- Laboratório de Modelagem Molecular e Pesquisa em Ciências Farmacêuticas, LaMCiFar, Universidade Federal do Rio de Janeiro - Campus Macaé, Av. São José do Barreto, Macaé 27965-045, RJ, Brazil; Programa de Pós-Graduação em Produtos Bioativos e Biociências, Universidade Federal do Rio de Janeiro, Campus Macaé Professor Aloísio Teixeira, Macaé, RJ, Brazil
| | - Nelilma Correia Romeiro
- Laboratório Integrado de Computação Científica, LICC, Universidade Federal do Rio de Janeiro, Campus Macaé, Macaé, RJ, 27965-045, Brazil
| | - Paula Alvarez Abreu
- Laboratório de Modelagem Molecular e Pesquisa em Ciências Farmacêuticas, LaMCiFar, Universidade Federal do Rio de Janeiro - Campus Macaé, Av. São José do Barreto, Macaé 27965-045, RJ, Brazil.
| |
Collapse
|
4
|
Kuok CF, Hoi SO, Hoi CF, Chan CH, Fong IH, Ngok CK, Meng LR, Fong P. Synergistic antibacterial effects of herbal extracts and antibiotics on methicillin-resistant Staphylococcus aureus: A computational and experimental study. Exp Biol Med (Maywood) 2017; 242:731-743. [PMID: 28118725 DOI: 10.1177/1535370216689828] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Antibiotic resistance has become a serious global concern, and the discovery of antimicrobial herbal constituents may provide valuable solutions to overcome the problem. In this study, the effects of therapies combining antibiotics and four medicinal herbs on methicillin-resistant Staphylococcus aureus (MRSA) were investigated. Specifically, the synergistic effects of Magnolia officinalis, Verbena officinalis, Momordica charantia, and Daphne genkwa in combination with oxacillin or gentamicin against methicillin-resistant (ATCC43300) and methicillin-susceptible (ATCC25923) S. aureus were examined. In vitro susceptibility and synergistic testing were performed to measure the minimum inhibitory concentration and fractional inhibitory concentration (FIC) index of the antibiotics and medicinal herbs against MRSA and methicillin-susceptible S. aureus. To identify the active constituents in producing these synergistic effects, in silico molecular docking was used to investigate the binding affinities of 139 constituents of the four herbs to the two common MRSA inhibitory targets, penicillin binding proteins 2a (PBP2a) and 4 (PBP4). The physicochemical and absorption, distribution, metabolism, and excretion properties and drug safety profiles of these compounds were also analyzed. D. genkwa extract potentiated the antibacterial effects of oxacillin against MRSA, as indicated by an FIC index value of 0.375. M. officinalis and V. officinalis produced partial synergistic effects when combined with oxacillin, whereas M. charantia was found to have no beneficial effects in inhibiting MRSA. Overall, tiliroside, pinoresinol, magnatriol B, and momorcharaside B were predicted to be PBP2a or PBP4 inhibitors with good drug-like properties. This study identifies compounds that deserve further investigation with the aim of developing therapeutic agents to modulate the effect of antibiotics on MRSA. Impact statement Antibiotic resistant is a well-known threat to global health and methicillin-resistant Staphylococcus aureus is one of the most significant ones. These resistant bacteria kill thousands of people every year and therefore a new effective antimicrobial treatment is necessary. This study identified the herbs and their associated bioactive ingredients that can potential the effects of current antibiotics. These herbs have long history of human usage in China and have well-defined monograph in the Chinese Pharmacopeia. These indicate their relatively high clinical safety and may have a quicker drug development process than that of a new novel antibiotic. Based on the results of this study, the authors will perform further in vitro and animal studies, aiming to accumulate significant data for the application of clinical trial.
Collapse
Affiliation(s)
- Chiu-Fai Kuok
- School of Health Sciences, Macao Polytechnic Institute, Macao 999078, China
| | - Sai-On Hoi
- School of Health Sciences, Macao Polytechnic Institute, Macao 999078, China
| | - Chi-Fai Hoi
- School of Health Sciences, Macao Polytechnic Institute, Macao 999078, China
| | - Chi-Hong Chan
- School of Health Sciences, Macao Polytechnic Institute, Macao 999078, China
| | - Io-Hong Fong
- School of Health Sciences, Macao Polytechnic Institute, Macao 999078, China
| | - Cheong-Kei Ngok
- School of Health Sciences, Macao Polytechnic Institute, Macao 999078, China
| | - Li-Rong Meng
- School of Health Sciences, Macao Polytechnic Institute, Macao 999078, China
| | - Pedro Fong
- School of Health Sciences, Macao Polytechnic Institute, Macao 999078, China
| |
Collapse
|
5
|
Yang B, Yang YS, Yang N, Li G, Zhu HL. Design, biological evaluation and 3D QSAR studies of novel dioxin-containing pyrazoline derivatives with thiourea skeleton as selective HER-2 inhibitors. Sci Rep 2016; 6:27571. [PMID: 27273260 PMCID: PMC4897788 DOI: 10.1038/srep27571] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2015] [Accepted: 05/23/2016] [Indexed: 12/31/2022] Open
Abstract
A series of novel dioxin-containing pyrazoline derivatives with thiourea skeleton have been designed, synthesized and evaluated for their EGFR/HER-2 inhibitory and anti-proliferation activities. A majority of them displayed selective HER-2 inhibitory activity against EGFR inhibitory activity. Compound C20 displayed the most potent activity against HER-2 and MDA-MB-453 human breast cancer cell line (IC50 = 0.03 μM and GI50 = 0.15 μM), being slightly more potent than the positive control Erlotinib (IC50 = 0.16 μM and GI50 = 1.56 μM) and comparable with Lapatinib (IC50 = 0.01 μM and GI50 = 0.03 μM). It is a more exciting result that C20 was over 900 times more potent against HER-2 than against EGFR while this value was 0.19 for Erlotinib and 1.00 for Lapatinib, indicating high selectivity. The results of docking simulation indicate that the dioxin moiety occupied the exit of the active pocket and pushed the carbothioamide deep into the active site. QSAR models have been built with activity data and binding conformations to begin our work in this paper as well as to provide a reliable tool for reasonable design of EGFR/HER-2 inhibitors in future.
Collapse
Affiliation(s)
- Bing Yang
- Institute of Chemistry and BioMedical Sciences, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Yu-Shun Yang
- Institute of Chemistry and BioMedical Sciences, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.,State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, Nanjing 210093, China
| | - Na Yang
- Institute of Chemistry and BioMedical Sciences, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.,State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, Nanjing 210093, China
| | - Guigen Li
- Institute of Chemistry and BioMedical Sciences, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Hai-Liang Zhu
- State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, Nanjing 210093, China
| |
Collapse
|
6
|
Hewitt M, Ellison CM, Cronin MTD, Pastor M, Steger-Hartmann T, Munoz-Muriendas J, Pognan F, Madden JC. Ensuring confidence in predictions: A scheme to assess the scientific validity of in silico models. Adv Drug Deliv Rev 2015; 86:101-11. [PMID: 25794480 DOI: 10.1016/j.addr.2015.03.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2014] [Revised: 03/05/2015] [Accepted: 03/11/2015] [Indexed: 11/28/2022]
Abstract
The use of in silico tools within the drug development process to predict a wide range of properties including absorption, distribution, metabolism, elimination and toxicity has become increasingly important due to changes in legislation and both ethical and economic drivers to reduce animal testing. Whilst in silico tools have been used for decades there remains reluctance to accept predictions based on these methods particularly in regulatory settings. This apprehension arises in part due to lack of confidence in the reliability, robustness and applicability of the models. To address this issue we propose a scheme for the verification of in silico models that enables end users and modellers to assess the scientific validity of models in accordance with the principles of good computer modelling practice. We report here the implementation of the scheme within the Innovative Medicines Initiative project "eTOX" (electronic toxicity) and its application to the in silico models developed within the frame of this project.
Collapse
Affiliation(s)
- Mark Hewitt
- School of Pharmacy, Faculty of Science and Engineering, University of Wolverhampton, City Campus, Wulfruna Street, WV1 1SB, England, United Kingdom; School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, England, United Kingdom.
| | - Claire M Ellison
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, England, United Kingdom.
| | - Mark T D Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, England, United Kingdom.
| | - Manuel Pastor
- Research Programme on Biomedical Informatics (GRIB), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, IMIM (Hospital del Mar Medical Research Institute), Dr. Aiguader 88, E-08003 Barcelona, Spain.
| | - Thomas Steger-Hartmann
- Bayer HealthCare, Bayer Pharma AG, Investigational Toxicology, Müllerstraße 178, 13352 Berlin, Germany.
| | - Jordi Munoz-Muriendas
- Chemical Sciences, Computational Chemistry, GlaxoSmithKline, Stevenage, SG1 2NY, England, United Kingdom.
| | - Francois Pognan
- Biochemical & Cellular Toxicology, Discovery Investigative Safety - PreClinical Safety, Novartis Pharma AG, Werk Klybeck, Postfach, CH-4002 Basel, Switzerland.
| | - Judith C Madden
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, England, United Kingdom.
| |
Collapse
|
7
|
Caldwell GW. In silico tools used for compound selection during target-based drug discovery and development. Expert Opin Drug Discov 2015; 10:901-23. [DOI: 10.1517/17460441.2015.1043885] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- Gary W Caldwell
- Janssen Research & Development LLC, Discovery Sciences, Spring House, PA, USA
| |
Collapse
|
8
|
Prediction of placental barrier permeability: a model based on partial least squares variable selection procedure. Molecules 2015; 20:8270-86. [PMID: 25961165 PMCID: PMC6272791 DOI: 10.3390/molecules20058270] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2015] [Revised: 04/20/2015] [Accepted: 04/30/2015] [Indexed: 11/27/2022] Open
Abstract
Assessing the human placental barrier permeability of drugs is very important to guarantee drug safety during pregnancy. Quantitative structure–activity relationship (QSAR) method was used as an effective assessing tool for the placental transfer study of drugs, while in vitro human placental perfusion is the most widely used method. In this study, the partial least squares (PLS) variable selection and modeling procedure was used to pick out optimal descriptors from a pool of 620 descriptors of 65 compounds and to simultaneously develop a QSAR model between the descriptors and the placental barrier permeability expressed by the clearance indices (CI). The model was subjected to internal validation by cross-validation and y-randomization and to external validation by predicting CI values of 19 compounds. It was shown that the model developed is robust and has a good predictive potential (r2 = 0.9064, RMSE = 0.09, q2 = 0.7323, rp2 = 0.7656, RMSP = 0.14). The mechanistic interpretation of the final model was given by the high variable importance in projection values of descriptors. Using PLS procedure, we can rapidly and effectively select optimal descriptors and thus construct a model with good stability and predictability. This analysis can provide an effective tool for the high-throughput screening of the placental barrier permeability of drugs.
Collapse
|