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Special Issue "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)

Special Issue Editors

Guest Editor
Prof. Rino Ragno

Rome Center for Molecular Design, Dipartimento di Chimica e Tecnologie del Farmaco, Sapienza Università di Roma, P. le A. Moro 5, 00185 Roma, Italy
Website | E-Mail
Interests: design and synthesis of bioactive compounds; development of new 3-D QSAR procedures and their application in drug design; molecular docking in drug design; extraction of bioactive compounds from natural sources
Guest Editor
Prof. Milan Mladenović

Kragujevac Center for Computational Biochemistry, University of Kragujevac, Faculty of Science, Radoja Domanovića 12, 34000 Kragujevac, Republic of Serbia
Website | E-Mail
Interests: design and synthesis of bioactive compounds; development of new 3-D QSAR procedures and their application in drug design; structure-based and ligand-based drug design; in vitro–in vivo assays in drug design

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

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

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

Published Papers (8 papers)

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Research

Open AccessArticle Design of a Novel and Selective IRAK4 Inhibitor Using Topological Water Network Analysis and Molecular Modeling Approaches
Molecules 2018, 23(12), 3136; https://doi.org/10.3390/molecules23123136
Received: 7 November 2018 / Revised: 28 November 2018 / Accepted: 28 November 2018 / Published: 29 November 2018
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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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Open AccessArticle Discovery of a Natural Syk Inhibitor from Chinese Medicine through a Docking-Based Virtual Screening and Biological Assay Study
Molecules 2018, 23(12), 3114; https://doi.org/10.3390/molecules23123114
Received: 5 November 2018 / Revised: 20 November 2018 / Accepted: 26 November 2018 / Published: 28 November 2018
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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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Open AccessArticle Investigation of New Orexin 2 Receptor Modulators Using In Silico and In Vitro Methods
Molecules 2018, 23(11), 2926; https://doi.org/10.3390/molecules23112926
Received: 5 October 2018 / Revised: 2 November 2018 / Accepted: 8 November 2018 / Published: 9 November 2018
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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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Open AccessFeature PaperArticle In Silico Prediction of O6-Methylguanine-DNA Methyltransferase Inhibitory Potency of Base Analogs with QSAR and Machine Learning Methods
Molecules 2018, 23(11), 2892; https://doi.org/10.3390/molecules23112892
Received: 21 October 2018 / Revised: 4 November 2018 / Accepted: 6 November 2018 / Published: 6 November 2018
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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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Open AccessArticle 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
Molecules 2018, 23(10), 2683; https://doi.org/10.3390/molecules23102683
Received: 10 September 2018 / Revised: 11 October 2018 / Accepted: 18 October 2018 / Published: 18 October 2018
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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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Open AccessFeature PaperArticle The Targeted Pesticides as Acetylcholinesterase Inhibitors: Comprehensive Cross-Organism Molecular Modelling Studies Performed to Anticipate the Pharmacology of Harmfulness to Humans In Vitro
Molecules 2018, 23(9), 2192; https://doi.org/10.3390/molecules23092192
Received: 6 August 2018 / Revised: 24 August 2018 / Accepted: 24 August 2018 / Published: 30 August 2018
Cited by 1 | PDF Full-text (13068 KB) | HTML Full-text | XML Full-text | Supplementary Files
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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Open AccessArticle Investigations of Structural Requirements for BRD4 Inhibitors through Ligand- and Structure-Based 3D QSAR Approaches
Molecules 2018, 23(7), 1527; https://doi.org/10.3390/molecules23071527
Received: 17 May 2018 / Revised: 15 June 2018 / Accepted: 18 June 2018 / Published: 25 June 2018
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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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Open AccessArticle New Chromane-Based Derivatives as Inhibitors of Mycobacterium tuberculosis Salicylate Synthase (MbtI): Preliminary Biological Evaluation and Molecular Modeling Studies
Molecules 2018, 23(7), 1506; https://doi.org/10.3390/molecules23071506
Received: 22 May 2018 / Revised: 15 June 2018 / Accepted: 19 June 2018 / Published: 21 June 2018
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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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