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Application of Computational Methods in Drug Design

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Medicinal Chemistry".

Deadline for manuscript submissions: closed (15 November 2018) | Viewed by 41092

Special Issue Editors

Kragujevac Center for Computational Biochemistry, Department of Chemistry, Faculty of Science, University of Kragujevac, Radoja Domanovića 12, 34000 Kragujevac, P.O. Box 60, Serbia
Interests: biochemistry; computer aided drug design; cheminformatics; bioinformatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The proposed workshop, entitled “DesignIT-TO-LEAD: 1st Computational Medicinal Chemistry WorkShop” is intended as a first trial to establish regular workshops in drug design on a biennual based frequency. The DesignIT-TO-LEAD will be organized at the Faculty of Science, University of Kragujevac, Republic of Serbia, from from September 3rd to September 8th, 2018.

The contribution of computational methodologies to drug discovery is no longer a matter of dispute, and all major world pharmaceutical and biotechnology companies use computational design tools. Computer-aided drug design encompasses computational methods and resources that are used to facilitate the design and discovery of new bioactive chemical entities.

This workshop “DesignIT-TO-LEAD: 1st Computational Medicinal Chemistry WorkShop” will cover the main computational techniques currently used in the drug discovery process, supplying a basic level of knowledge of this field. All the presented computational approaches will focus mainly on the development of three-dimensional quantitative structure–activity relationships (3-D QSAR) and related tools.

The course will be divided into theoretical lesson and practical sessions with the aim of allowing participants to independently apply the computational techniques to their own projects.

Prof. Rino Ragno
Prof. Milan Mladenović
Guest Editors

Manuscript Submission Information

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Keywords

  • 3-D QSAR
  • Drug Design
  • Molecular Docking
  • Ligand-based alignment
  • Computational Medicinal Chemistry

Published Papers (9 papers)

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Research

20 pages, 5868 KiB  
Article
Identifying Protein Features Responsible for Improved Drug Repurposing Accuracies Using the CANDO Platform: Implications for Drug Design
by William Mangione and Ram Samudrala
Molecules 2019, 24(1), 167; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules24010167 - 04 Jan 2019
Cited by 16 | Viewed by 4024
Abstract
Drug repurposing is a valuable tool for combating the slowing rates of novel therapeutic discovery. The Computational Analysis of Novel Drug Opportunities (CANDO) platform performs shotgun repurposing of 2030 indications/diseases using 3733 drugs/compounds to predict interactions with 46,784 proteins and relating them via [...] Read more.
Drug repurposing is a valuable tool for combating the slowing rates of novel therapeutic discovery. The Computational Analysis of Novel Drug Opportunities (CANDO) platform performs shotgun repurposing of 2030 indications/diseases using 3733 drugs/compounds to predict interactions with 46,784 proteins and relating them via proteomic interaction signatures. The accuracy is calculated by comparing interaction similarities of drugs approved for the same indications. We performed a unique subset analysis by breaking down the full protein library into smaller subsets and then recombining the best performing subsets into larger supersets. Up to 14% improvement in accuracy is seen upon benchmarking the supersets, representing a 100–1000-fold reduction in the number of proteins considered relative to the full library. Further analysis revealed that libraries comprised of proteins with more equitably diverse ligand interactions are important for describing compound behavior. Using one of these libraries to generate putative drug candidates against malaria, tuberculosis, and large cell carcinoma results in more drugs that could be validated in the biomedical literature compared to using those suggested by the full protein library. Our work elucidates the role of particular protein subsets and corresponding ligand interactions that play a role in drug repurposing, with implications for drug design and machine learning approaches to improve the CANDO platform. Full article
(This article belongs to the Special Issue Application of Computational Methods in Drug Design)
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15 pages, 2959 KiB  
Article
Design of a Novel and Selective IRAK4 Inhibitor Using Topological Water Network Analysis and Molecular Modeling Approaches
by Myeong Hwi Lee, Anand Balupuri, Ye-rim Jung, Sungwook Choi, Areum Lee, Young Sik Cho and Nam Sook Kang
Molecules 2018, 23(12), 3136; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules23123136 - 29 Nov 2018
Cited by 9 | Viewed by 4640
Abstract
Protein kinases are deeply involved in immune-related diseases and various cancers. They are a potential target for structure-based drug discovery, since the general structure and characteristics of kinase domains are relatively well-known. However, the ATP binding sites in protein kinases, which serve as [...] Read more.
Protein kinases are deeply involved in immune-related diseases and various cancers. They are a potential target for structure-based drug discovery, since the general structure and characteristics of kinase domains are relatively well-known. However, the ATP binding sites in protein kinases, which serve as target sites, are highly conserved, and thus it is difficult to develop selective kinase inhibitors. To resolve this problem, we performed molecular dynamics simulations on 26 kinases in the aqueous solution, and analyzed topological water networks (TWNs) in their ATP binding sites. Repositioning of a known kinase inhibitor in the ATP binding sites of kinases that exhibited a TWN similar to interleukin-1 receptor-associated kinase 4 (IRAK4) allowed us to identify a hit molecule. Another hit molecule was obtained from a commercial chemical library using pharmacophore-based virtual screening and molecular docking approaches. Pharmacophoric features of the hit molecules were hybridized to design a novel compound that inhibited IRAK4 at low nanomolar levels in the in vitro assay. Full article
(This article belongs to the Special Issue Application of Computational Methods in Drug Design)
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11 pages, 2654 KiB  
Article
Discovery of a Natural Syk Inhibitor from Chinese Medicine through a Docking-Based Virtual Screening and Biological Assay Study
by Xing Wang, Junfang Guo, Zhongqi Ning and Xia Wu
Molecules 2018, 23(12), 3114; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules23123114 - 28 Nov 2018
Cited by 8 | Viewed by 3708
Abstract
Spleen tyrosine kinase (Syk) is a critical target protein for treating immunoreceptor signalling-mediated allergies. In this study, a virtual screening of an in-house Chinese medicine database followed by biological assays was carried out to identify novel Syk inhibitors. A molecular docking method was [...] Read more.
Spleen tyrosine kinase (Syk) is a critical target protein for treating immunoreceptor signalling-mediated allergies. In this study, a virtual screening of an in-house Chinese medicine database followed by biological assays was carried out to identify novel Syk inhibitors. A molecular docking method was employed to screen for compounds with potential Syk inhibitory activity. Then, an in vitro kinase inhibition assay was performed to verify the Syk inhibitory activity of the virtual screening hits. Subsequently, a β-hexosaminidase release assay was conducted to evaluate the anti-mast cell degranulation activity of the active compounds. Finally, tanshinone I was confirmed as a Syk inhibitor (IC50 = 1.64 μM) and exhibited anti-mast cell degranulation activity in vitro (IC50 = 2.76 μM). Docking studies showed that Pro455, Gln462, Leu377, and Lys458 were key amino acid residues for Syk inhibitory activity. This study demonstrated that tanshinone I is a Syk inhibitor with mast cell degranulation inhibitory activity. Tanshinone I may be a potential lead compound for developing effective and safe Syk-inhibiting drugs. Full article
(This article belongs to the Special Issue Application of Computational Methods in Drug Design)
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14 pages, 5107 KiB  
Article
Investigation of New Orexin 2 Receptor Modulators Using In Silico and In Vitro Methods
by Jana Janockova, Rafael Dolezal, Eugenie Nepovimova, Tereza Kobrlova, Marketa Benkova, Kamil Kuca, Jan Konecny, Eva Mezeiova, Michaela Melikova, Vendula Hepnarova, Avi Ring, Ondrej Soukup and Jan Korabecny
Molecules 2018, 23(11), 2926; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules23112926 - 09 Nov 2018
Cited by 8 | Viewed by 5614
Abstract
The neuropeptides, orexin A and orexin B (also known as hypocretins), are produced in hypothalamic neurons and belong to ligands for orphan G protein-coupled receptors. Generally, the primary role of orexins is to act as excitatory neurotransmitters and regulate the sleep process. Lack [...] Read more.
The neuropeptides, orexin A and orexin B (also known as hypocretins), are produced in hypothalamic neurons and belong to ligands for orphan G protein-coupled receptors. Generally, the primary role of orexins is to act as excitatory neurotransmitters and regulate the sleep process. Lack of orexins may lead to sleep disorder narcolepsy in mice, dogs, and humans. Narcolepsy is a neurological disorder of alertness characterized by a decrease of ability to manage sleep-wake cycles, excessive daytime sleepiness, and other symptoms, such as cataplexy, vivid hallucinations, and paralysis. Thus, the discovery of orexin receptors, modulators, and their causal implication in narcolepsy is the most important advance in sleep-research. The presented work is focused on the evaluation of compounds L1L11 selected by structure-based virtual screening for their ability to modulate orexin receptor type 2 (OX2R) in comparison with standard agonist orexin-A together with their blood-brain barrier permeability and cytotoxicity. We can conclude that the studied compounds possess an affinity towards the OX2R. However, the compounds do not have intrinsic activity and act as the antagonists of this receptor. It was shown that L4 was the most potent antagonistic ligand to orexin A and displayed an IC50 of 2.2 µM, offering some promise mainly for the treatment of insomnia. Full article
(This article belongs to the Special Issue Application of Computational Methods in Drug Design)
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19 pages, 4737 KiB  
Article
In Silico Prediction of O6-Methylguanine-DNA Methyltransferase Inhibitory Potency of Base Analogs with QSAR and Machine Learning Methods
by Guohui Sun, Tengjiao Fan, Xiaodong Sun, Yuxing Hao, Xin Cui, Lijiao Zhao, Ting Ren, Yue Zhou, Rugang Zhong and Yongzhen Peng
Molecules 2018, 23(11), 2892; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules23112892 - 06 Nov 2018
Cited by 25 | Viewed by 4025
Abstract
O6-methylguanine-DNA methyltransferase (MGMT), a unique DNA repair enzyme, can confer resistance to DNA anticancer alkylating agents that modify the O6-position of guanine. Thus, inhibition of MGMT activity in tumors has a great interest for cancer researchers because it can [...] Read more.
O6-methylguanine-DNA methyltransferase (MGMT), a unique DNA repair enzyme, can confer resistance to DNA anticancer alkylating agents that modify the O6-position of guanine. Thus, inhibition of MGMT activity in tumors has a great interest for cancer researchers because it can significantly improve the anticancer efficacy of such alkylating agents. In this study, we performed a quantitative structure activity relationship (QSAR) and classification study based on a total of 134 base analogs related to their ED50 values (50% inhibitory concentration) against MGMT. Molecular information of all compounds were described by quantum chemical descriptors and Dragon descriptors. Genetic algorithm (GA) and multiple linear regression (MLR) analysis were combined to develop QSAR models. Classification models were generated by seven machine-learning methods based on six types of molecular fingerprints. Performances of all developed models were assessed by internal and external validation techniques. The best QSAR model was obtained with Q2Loo = 0.83, R2 = 0.87, Q2ext = 0.67, and R2ext = 0.69 based on 84 compounds. The results from QSAR studies indicated topological charge indices, polarizability, ionization potential (IP), and number of primary aromatic amines are main contributors for MGMT inhibition of base analogs. For classification studies, the accuracies of 10-fold cross-validation ranged from 0.750 to 0.885 for top ten models. The range of accuracy for the external test set ranged from 0.800 to 0.880 except for PubChem-Tree model, suggesting a satisfactory predictive ability. Three models (Ext-SVM, Ext-Tree and Graph-RF) showed high and reliable predictive accuracy for both training and external test sets. In addition, several representative substructures for characterizing MGMT inhibitors were identified by information gain and substructure frequency analysis method. Our studies might be useful for further study to design and rapidly identify potential MGMT inhibitors. Full article
(This article belongs to the Special Issue Application of Computational Methods in Drug Design)
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10 pages, 5966 KiB  
Article
Design of a New α-1-C-Alkyl-DAB Derivative Acting as a Pharmacological Chaperone for β-Glucocerebrosidase Using Ligand Docking and Molecular Dynamics Simulation
by Izumi Nakagome, Atsushi Kato, Noriyuki Yamaotsu, Tomoki Yoshida, Shin-ichiro Ozawa, Isao Adachi and Shuichi Hirono
Molecules 2018, 23(10), 2683; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules23102683 - 18 Oct 2018
Cited by 10 | Viewed by 3493
Abstract
Some point mutations in β-glucocerebrosidase cause either improper folding or instability of this protein, resulting in Gaucher disease. Pharmacological chaperones bind to the mutant enzyme and stabilize this enzyme; thus, pharmacological chaperone therapy was proposed as a potential treatment for Gaucher disease. The [...] Read more.
Some point mutations in β-glucocerebrosidase cause either improper folding or instability of this protein, resulting in Gaucher disease. Pharmacological chaperones bind to the mutant enzyme and stabilize this enzyme; thus, pharmacological chaperone therapy was proposed as a potential treatment for Gaucher disease. The binding affinities of α-1-C-alkyl 1,4-dideoxy-1,4-imino-d-arabinitol (DAB) derivatives, which act as pharmacological chaperones for β-glucocerebrosidase, abruptly increased upon elongation of their alkyl chain. In this study, the primary causes of such an increase in binding affinity were analyzed using protein–ligand docking and molecular dynamics simulations. We found that the activity cliff between α-1-C-heptyl-DAB and α-1-C-octyl-DAB was due to the shape and size of the hydrophobic binding site accommodating the alkyl chains, and that the interaction with this hydrophobic site controlled the binding affinity of the ligands well. Furthermore, based on the aromatic/hydrophobic properties of the binding site, a 7-(tetralin-2-yl)-heptyl-DAB compound was designed and synthesized. This compound had significantly enhanced activity. The design strategy in consideration of aromatic interactions in the hydrophobic pocket was useful for generating effective pharmacological chaperones for the treatment of Gaucher disease. Full article
(This article belongs to the Special Issue Application of Computational Methods in Drug Design)
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37 pages, 13068 KiB  
Article
The Targeted Pesticides as Acetylcholinesterase Inhibitors: Comprehensive Cross-Organism Molecular Modelling Studies Performed to Anticipate the Pharmacology of Harmfulness to Humans In Vitro
by Milan Mladenović, Biljana B. Arsić, Nevena Stanković, Nezrina Mihović, Rino Ragno, Andrew Regan, Jelena S. Milićević, Tatjana M. Trtić-Petrović and Ružica Micić
Molecules 2018, 23(9), 2192; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules23092192 - 30 Aug 2018
Cited by 35 | Viewed by 5823
Abstract
Commercially available pesticides were examined as Mus musculus and Homo sapiens acetylcholinesterase (mAChE and hAChE) inhibitors by means of ligand-based (LB) and structure-based (SB) in silico approaches. Initially, the crystal structures of simazine, monocrotophos, dimethoate, and acetamiprid were reproduced using [...] Read more.
Commercially available pesticides were examined as Mus musculus and Homo sapiens acetylcholinesterase (mAChE and hAChE) inhibitors by means of ligand-based (LB) and structure-based (SB) in silico approaches. Initially, the crystal structures of simazine, monocrotophos, dimethoate, and acetamiprid were reproduced using various force fields. Subsequently, LB alignment rules were assessed and applied to determine the inter synaptic conformations of atrazine, propazine, carbofuran, carbaryl, tebufenozide, imidacloprid, diuron, monuron, and linuron. Afterwards, molecular docking and dynamics SB studies were performed on either mAChE or hAChE, to predict the listed pesticides’ binding modes. Calculated energies of global minima (Eglob_min) and free energies of binding (∆Gbinding) were correlated with the pesticides’ acute toxicities (i.e., the LD50 values) against mice, as well to generate the model that could predict the LD50s against humans. Although for most of the pesticides the low Eglob_min correlates with the high acute toxicity, it is the ∆Gbinding that conditions the LD50 values for all the evaluated pesticides. Derived pLD50 = f(∆Gbinding) mAChE model may predict the pLD50 against hAChE, too. The hAChE inhibition by atrazine, propazine, and simazine (the most toxic pesticides) was elucidated by SB quantum mechanics (QM) DFT mechanistic and concentration-dependent kinetic studies, enriching the knowledge for design of less toxic pesticides. Full article
(This article belongs to the Special Issue Application of Computational Methods in Drug Design)
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16 pages, 6113 KiB  
Article
Investigations of Structural Requirements for BRD4 Inhibitors through Ligand- and Structure-Based 3D QSAR Approaches
by Adeena Tahir, Rima D. Alharthy, Saadia Naseem, Natasha Mahmood, Mahmood Ahmed, Khuram Shahzad, Malik Nadeem Akhtar, Abdul Hameed, Irfan Sadiq, Haq Nawaz and Muhammad Muddassar
Molecules 2018, 23(7), 1527; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules23071527 - 25 Jun 2018
Cited by 12 | Viewed by 4000
Abstract
The bromodomain containing protein 4 (BRD4) recognizes acetylated histone proteins and plays numerous roles in the progression of a wide range of cancers, due to which it is under intense investigation as a novel anti-cancer drug target. In the present study, we performed [...] Read more.
The bromodomain containing protein 4 (BRD4) recognizes acetylated histone proteins and plays numerous roles in the progression of a wide range of cancers, due to which it is under intense investigation as a novel anti-cancer drug target. In the present study, we performed three-dimensional quantitative structure activity relationship (3D-QSAR) molecular modeling on a series of 60 inhibitors of BRD4 protein using ligand- and structure-based alignment and different partial charges assignment methods by employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The developed models were validated using various statistical methods, including non-cross validated correlation coefficient (r2), leave-one-out (LOO) cross validated correlation coefficient (q2), bootstrapping, and Fisher’s randomization test. The highly reliable and predictive CoMFA (q2 = 0.569, r2 = 0.979) and CoMSIA (q2 = 0.500, r2 = 0.982) models were obtained from a structure-based 3D-QSAR approach using Merck molecular force field (MMFF94). The best models demonstrate that electrostatic and steric fields play an important role in the biological activities of these compounds. Hence, based on the contour maps information, new compounds were designed, and their binding modes were elucidated in BRD4 protein’s active site. Further, the activities and physicochemical properties of the designed molecules were also predicted using the best 3D-QSAR models. We believe that predicted models will help us to understand the structural requirements of BRD4 protein inhibitors that belong to quinolinone and quinazolinone classes for the designing of better active compounds. Full article
(This article belongs to the Special Issue Application of Computational Methods in Drug Design)
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14 pages, 3498 KiB  
Article
New Chromane-Based Derivatives as Inhibitors of Mycobacterium tuberculosis Salicylate Synthase (MbtI): Preliminary Biological Evaluation and Molecular Modeling Studies
by Elena Pini, Giulio Poli, Tiziano Tuccinardi, Laurent Roberto Chiarelli, Matteo Mori, Arianna Gelain, Luca Costantino, Stefania Villa, Fiorella Meneghetti and Daniela Barlocco
Molecules 2018, 23(7), 1506; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules23071506 - 21 Jun 2018
Cited by 30 | Viewed by 4720
Abstract
Tuberculosis is the leading cause of death from a single infectious agent worldwide; therefore, the need for new antitubercular drugs is desperate. The recently validated target salicylate synthase MbtI is the first enzyme involved in the biosynthesis of mycobactins, compounds able to chelate [...] Read more.
Tuberculosis is the leading cause of death from a single infectious agent worldwide; therefore, the need for new antitubercular drugs is desperate. The recently validated target salicylate synthase MbtI is the first enzyme involved in the biosynthesis of mycobactins, compounds able to chelate iron, an essential cofactor for the survival of Mycobacterium tuberculosis in the host. Here, we report on the synthesis and biological evaluation of chromane-based compounds as new potential inhibitors of MbtI. Our approach successfully allowed the identification of a novel lead compound (1), endowed with a promising activity against this enzyme (IC50 = 55 μM). Molecular modeling studies were performed in order to evaluate the binding mode of 1 and rationalize the preliminary structure-activity relationships, thus providing crucial information to carry out further optimization studies. Full article
(This article belongs to the Special Issue Application of Computational Methods in Drug Design)
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