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Drug Discovery and Molecular Docking

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

Deadline for manuscript submissions: closed (30 June 2020) | Viewed by 38108

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Prof. Dr. Maria Cristina De Rosa

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Institute of Chemical Sciences and Technologies "Giulio Natta" (SCITEC) – Rome, CNR, 00185 Rome, Italy
Interests: molecular modelling; molecular dynamics simulations; molecular docking; computational drug discovery
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The process of drug development is complex, expensive, and time-consuming. In this scenario, computer-based methodologies for drug design have been demonstrated to have the predictive power useful to speed up the discovery of novel drug candidates. Among the several methodologies of computational chemistry for identification of biologically active molecules, molecular docking is being used increasingly in the pharmaceutical industry. Molecular docking evaluates ligand–target interactions and tries to reproduce native binding modes, thus accelerating estimations of binding affinity and ligand optimization techniques. The process of drug discovery mainly focuses on protein–ligand and, more recently, protein–protein docking. Indeed, many challenges still remain to be addressed such as protein flexibility, role of water molecules, and entropic effects. The goal of this Special Issue is, therefore, to solicit and publish the latest advances in molecular docking and to inform researchers in related fields of its potential.

Dr. Maria Cristina De Rosa
Guest Editor

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Keywords

shape complementarity
binding mode
molecular recognition
virtual screening
hot-spot residues
molecular docking

Published Papers (10 papers)

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Research

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18 pages, 4807 KiB

Open AccessArticle

Molecular Dynamic Simulations to Probe Stereoselectivity of Tiagabine Binding with Human GAT1

by Sadia Zafar and Ishrat Jabeen

Molecules 2020, 25(20), 4745; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules25204745 - 16 Oct 2020

Cited by 5 | Viewed by 2213

Abstract

The human gamma aminobutyric acid transporter subtype 1 (hGAT1) located in the nerve terminals is known to catalyze the neuronal function by the electrogenic reuptake of γ-aminobutyric acid (GABA) with the co-transport of Na⁺ and Cl⁻ ions. In the past, there has been a major research drive focused on the dysfunction of hGAT1 in several neurological disorders. Thus, hGAT1 of the GABAergic system has been well established as an attractive target for such diseased conditions. Till date, there are various reports about stereo selectivity of –COOH group of tiagabine, a Food and Drug Administration (FDA)-approved hGAT1-selective antiepileptic drug. However, the effect of the stereochemistry of the protonated –NH group of tiagabine has never been scrutinized. Therefore, in this study, tiagabine has been used to explore the binding hypothesis of different enantiomers of tiagabine. In addition, the impact of axial and equatorial configuration of the–COOH group attached at the meta position of the piperidine ring of tiagabine enantiomers was also investigated. Further, the stability of the finally selected four hGAT1–tiagabine enantiomers namely entries 3, 4, 6, and 9 was evaluated through 100 ns molecular dynamics (MD) simulations for the selection of the best probable tiagabine enantiomer. The results indicate that the protonated –NH group in the R-conformation and the –COOH group of Tiagabine in the equatorial configuration of entry 4 provide maximum strength in terms of interaction within the hGAT1 binding pocket to prevent the change in hGAT1 conformational state, i.e., from open-to-out to open-to-in as compared to other selected tiagabine enantiomers 3, 6, and 9. Full article

(This article belongs to the Special Issue Drug Discovery and Molecular Docking)

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21 pages, 3577 KiB

Open AccessFeature PaperArticle

Targeting the Protein Tunnels of the Urease Accessory Complex: A Theoretical Investigation

by Matteo Masetti, Federico Falchi, Dario Gioia, Maurizio Recanatini, Stefano Ciurli and Francesco Musiani

Molecules 2020, 25(12), 2911; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules25122911 - 24 Jun 2020

Cited by 10 | Viewed by 3603

Abstract

Urease is a nickel-containing enzyme that is essential for the survival of several and often deadly pathogenic bacterial strains, including Helicobacter pylori. Notwithstanding several attempts, the development of direct urease inhibitors without side effects for the human host remains, to date, elusive. The recently solved X-ray structure of the HpUreDFG accessory complex involved in the activation of urease opens new perspectives for structure-based drug discovery. In particular, the quaternary assembly and the presence of internal tunnels for nickel translocation offer an intriguing possibility to target the HpUreDFG complex in the search of indirect urease inhibitors. In this work, we adopted a theoretical framework to investigate such a hypothesis. Specifically, we searched for putative binding sites located at the protein–protein interfaces on the HpUreDFG complex, and we challenged their druggability through structure-based virtual screening. We show that, by virtue of the presence of tunnels, some protein–protein interfaces on the HpUreDFG complex are intrinsically well suited for hosting small molecules, and, as such, they possess good potential for future drug design endeavors. Full article

(This article belongs to the Special Issue Drug Discovery and Molecular Docking)

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27 pages, 5498 KiB

Open AccessArticle

Design, Synthesis, Antitumor Activity and Molecular Docking Study of Novel 5-Deazaalloxazine Analogs

by Sawsan Mahmoud, Doaa Samaha, Mosaad S. Mohamed, Nageh A. Abou Taleb, Mohamed A. Elsawy, Tomohisa Nagamatsu and Hamed I. Ali

Molecules 2020, 25(11), 2518; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules25112518 - 28 May 2020

Cited by 4 | Viewed by 2700

Abstract

Protein tyrosine kinases (PTKs) are the most potential therapeutic targets for cancer. Herein, we present a sound rationale for synthesis of a series of novel 2-(methylthio), 2-(substituted alkylamino), 2-(heterocyclic substituted), 2-amino, 2,4-dioxo and 2-deoxo-5-deazaalloxazine derivatives by applying structure-based drug design (SBDD) using AutoDock 4.2. Their antitumor activities against human CCRF-HSB-2, KB, MCF-7 and HeLa have been investigated in vitro. Many 5-deazaalloxazine analogs revealed high selective activities against MCF-7 tumor cell lines (IC₅₀: 0.17–2.17 µM) over HeLa tumor cell lines (IC₅₀ > 100 µM). Protein kinase profiling revealed that compound 3h induced multi- targets kinase inhibition including −43% against (FAK), −40% against (CDKI) and −36% against (SCR). Moreover, the Annexin-V/PI apoptotic assay elucidate that compound 3h showed 33% and potentially 140% increase in early and late apoptosis to MCF-7 cells respectively, compared to the control. The structure-activity relationship (SAR) and molecular docking study using PTK as a target enzyme for the synthesized 7-deazaalloaxazine derivatives were investigated as potential antitumor agents. The AutoDock binding affinities of the 5-deazaalloxazine analogs into c-kit PTK (PDB code: 1t46) revealed reasonable correlations between their AutoDock binding free energy and IC₅₀. Full article

(This article belongs to the Special Issue Drug Discovery and Molecular Docking)

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12 pages, 1029 KiB

Open AccessArticle

A Deep-Learning Approach toward Rational Molecular Docking Protocol Selection

by José Jiménez-Luna, Alberto Cuzzolin, Giovanni Bolcato, Mattia Sturlese and Stefano Moro

Molecules 2020, 25(11), 2487; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules25112487 - 27 May 2020

Cited by 14 | Viewed by 4533

Abstract

While a plethora of different protein–ligand docking protocols have been developed over the past twenty years, their performances greatly depend on the provided input protein–ligand pair. In this study, we developed a machine-learning model that uses a combination of convolutional and fully connected neural networks for the task of predicting the performance of several popular docking protocols given a protein structure and a small compound. We also rigorously evaluated the performance of our model using a widely available database of protein–ligand complexes and different types of data splits. We further open-source all code related to this study so that potential users can make informed selections on which protocol is best suited for their particular protein–ligand pair. Full article

(This article belongs to the Special Issue Drug Discovery and Molecular Docking)

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24 pages, 2624 KiB

Open AccessArticle

Combined Machine Learning and Molecular Modelling Workflow for the Recognition of Potentially Novel Fungicides

by Ozren Jović and Tomislav Šmuc

Molecules 2020, 25(9), 2198; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules25092198 - 08 May 2020

Cited by 2 | Viewed by 2720

Abstract

Novel machine learning and molecular modelling filtering procedures for drug repurposing have been carried out for the recognition of the novel fungicide targets of Cyp51 and Erg2. Classification and regression approaches on molecular descriptors have been performed using stepwise multilinear regression (FS-MLR), uninformative-variable elimination partial-least square regression, and a non-linear method called Forward Stepwise Limited Correlation Random Forest (FS-LM-RF). Altogether, 112 prediction models from two different approaches have been built for the descriptor recognition of fungicide hit compounds. Aiming at the fungal targets of sterol biosynthesis in membranes, antifungal hit compounds have been selected for docking experiments from the Drugbank database using the Autodock4 molecular docking program. The results were verified by Gold Protein-Ligand Docking Software. The best-docked conformation, for each high-scored ligand considered, was submitted to quantum mechanics/molecular mechanics (QM/MM) gradient optimization with final single point calculations taking into account both the basis set superposition error and thermal corrections (with frequency calculations). Finally, seven Drugbank lead compounds were selected based on their high QM/MM scores for the Cyp51 target, and three were selected for the Erg2 target. These lead compounds could be recommended for further in vitro studies. Full article

(This article belongs to the Special Issue Drug Discovery and Molecular Docking)

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29 pages, 8717 KiB

Open AccessArticle

Discovery of Novel Imidazopyridine GSK-3β Inhibitors Supported by Computational Approaches

by Rosa Buonfiglio, Federica Prati, Martina Bischetti, Claudia Cavarischia, Guido Furlotti and Rosella Ombrato

Molecules 2020, 25(9), 2163; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules25092163 - 05 May 2020

Cited by 14 | Viewed by 3252

Abstract

The interest of research groups and pharmaceutical companies to discover novel GSK-3β inhibitors has increased over the years considering the involvement of this enzyme in many pathophysiological processes and diseases. Along this line, we recently reported on 1H-indazole-3-carboxamide (INDZ) derivatives 1–6, showing good GSK-3β inhibition activity. However, they suffered from generally poor central nervous system (CNS) permeability. Here, we describe the design, synthesis, and in vitro characterization of novel imidazo[1,5-a]pyridine-1-carboxamide (IMID 1) and imidazo[1,5-a]pyridine-3-carboxamide (IMID 2) compounds (7–18) to overcome such liability. In detail, structure-based approaches and fine-tuning of physicochemical properties guided the design of derivatives 7–18 resulting in ameliorated absorption, distribution, metabolism, and excretion (ADME) properties. A crystal structure of 16 in complex with GSK-3β enzyme (PDB entry 6Y9S) confirmed the in silico models. Despite the nanomolar inhibition activity, the new core compounds showed a reduction in potency with respect to INDZ derivatives 1–6. In this context, Molecular Dynamics (MD) and Quantum Mechanics (QM) based approaches along with NMR investigation helped to rationalize the observed structure activity relationship (SAR). With these findings, the key role of the acidic hydrogen of the central core for a tight interaction within the ATP pocket of the enzyme reflecting in good GSK-3β affinity was demonstrated. Full article

(This article belongs to the Special Issue Drug Discovery and Molecular Docking)

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17 pages, 4367 KiB

Open AccessArticle

Discovery of Novel Inhibitor for WNT/β-Catenin Pathway by Tankyrase 1/2 Structure-Based Virtual Screening

by Bo Li, Jinxia Liang, Feng Lu, Guandi Zeng, Jindao Zhang, Yinxing Ma, Peng Liu, Qin Wang, Qian Zhou and Liang Chen

Molecules 2020, 25(7), 1680; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules25071680 - 06 Apr 2020

Cited by 16 | Viewed by 3975

Abstract

Aberrant activation of the WNT/β-catenin signaling pathway is implicated in various types of cancers. Inhibitors targeting the Wnt signaling pathway are intensively studied in the current cancer research field, the outcomes of which remain to be determined. In this study, we have attempted to discover novel potent WNT/β-catenin pathway inhibitors through tankyrase 1/2 structure-based virtual screening. After screening more than 13.4 million compounds through molecular docking, we experimentally verified one compound, LZZ-02, as the most potent inhibitor out of 11 structurally representative top hits. LiCl-induced HEK293 cells containing TOPFlash reporter showed that LZZ-02 inhibited the transcriptional activity of β-catenin with an IC₅₀ of 10 ± 1.2 μM. Mechanistically, LZZ-02 degrades the expression of β-catenin by stabilizing axin 2, thereby diminishing downstream proteins levels, including c-Myc and cyclin D1. LZZ-02 also inhibits the growth of colonic carcinoma cell harboring constitutively active β-catenin. More importantly, LZZ-02 effectively shrinks tumor xenograft derived from colonic cell lines. Our study successfully identified a novel tankyrase 1/2 inhibitor and shed light on a novel strategy for developing inhibitors targeting the WNT/β-catenin signaling axis. Full article

(This article belongs to the Special Issue Drug Discovery and Molecular Docking)

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19 pages, 10615 KiB

Open AccessArticle

Large-Scale Virtual Screening Against the MET Kinase Domain Identifies a New Putative Inhibitor Type

by Emmanuel Bresso, Alessandro Furlan, Philippe Noel, Vincent Leroux, Flavio Maina, Rosanna Dono and Bernard Maigret

Molecules 2020, 25(4), 938; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules25040938 - 19 Feb 2020

Cited by 5 | Viewed by 3305

Abstract

By using an ensemble-docking strategy, we undertook a large-scale virtual screening campaign in order to identify new putative hits against the MET kinase target. Following a large molecular dynamics sampling of its conformational space, a set of 45 conformers of the kinase was retained as docking targets to take into account the flexibility of the binding site moieties. Our screening funnel started from about 80,000 chemical compounds to be tested in silico for their potential affinities towards the kinase binding site. The top 100 molecules selected—thanks to the molecular docking results—were further analyzed for their interactions, and 25 of the most promising ligands were tested for their ability to inhibit MET activity in cells. F0514-4011 compound was the most efficient and impaired this scattering response to HGF (Hepatocyte Growth Factor) with an IC

_{50}

of 7.2

μ

M. Interestingly, careful docking analysis of this molecule with MET suggests a possible conformation halfway between classical type-I and type-II MET inhibitors, with an additional region of interaction. This compound could therefore be an innovative seed to be repositioned from its initial antiviral purpose towards the field of MET inhibitors. Altogether, these results validate our ensemble docking strategy as a cost-effective functional method for drug development. Full article

(This article belongs to the Special Issue Drug Discovery and Molecular Docking)

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11 pages, 2348 KiB

Open AccessFeature PaperArticle

Design of Disruptors of the Hsp90–Cdc37 Interface

by Ilda D’Annessa, Naama Hurwitz, Valentina Pirota, Giovanni Luca Beretta, Stella Tinelli, Mark Woodford, Mauro Freccero, Mehdi Mollapour, Nadia Zaffaroni, Haim Wolfson and Giorgio Colombo

Molecules 2020, 25(2), 360; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules25020360 - 15 Jan 2020

Cited by 14 | Viewed by 3553

Abstract

The molecular chaperone Hsp90 is a ubiquitous ATPase-directed protein responsible for the activation and structural stabilization of a large clientele of proteins. As such, Hsp90 has emerged as a suitable candidate for the treatment of a diverse set of diseases, such as cancer and neurodegeneration. The inhibition of the chaperone through ATP-competitive inhibitors, however, was shown to lead to undesirable side effects. One strategy to alleviate this problem is the development of molecules that are able to disrupt specific protein–protein interactions, thus modulating the activity of Hsp90 only in the particular cellular pathway that needs to be targeted. Here, we exploit novel computational and theoretical approaches to design a set of peptides that are able to bind Hsp90 and compete for its interaction with the co-chaperone Cdc37, which is found to be responsible for the promotion of cancer cell proliferation. In spite of their capability to disrupt the Hsp90–Cdc37 interaction, no important cytotoxicity was observed in human cancer cells exposed to designed compounds. These findings imply the need for further optimization of the compounds, which may lead to new ways of interfering with the Hsp90 mechanisms that are important for tumour growth. Full article

(This article belongs to the Special Issue Drug Discovery and Molecular Docking)

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Review

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18 pages, 1430 KiB

Open AccessReview

Antibody-Drug Conjugates and Targeted Treatment Strategies for Hepatocellular Carcinoma: A Drug-Delivery Perspective

by David Dahlgren and Hans Lennernäs

Molecules 2020, 25(12), 2861; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules25122861 - 21 Jun 2020

Cited by 14 | Viewed by 7245

Abstract

Increased understanding of cancer biology, pharmacology and drug delivery has provided a new framework for drug discovery and product development that relies on the unique expression of specific macromolecules (i.e., antigens) on the surface of tumour cells. This has enabled the development of anti-cancer treatments that combine the selectivity of antibodies with the efficacy of highly potent chemotherapeutic small molecules, called antibody-drug conjugates (ADCs). ADCs are composed of a cytotoxic drug covalently linked to an antibody which then selectively binds to a highly expressed antigen on a cancer cell; the conjugate is then internalized by the cell where it releases the potent cytotoxic drug and efficiently kills the tumour cell. There are, however, many challenges in the development of ADCs, mainly around optimizing the therapeutic/safety benefits. These challenges are discussed in this review; they include issues with the plasma stability and half-life of the ADC, its transport from blood into and distribution throughout the tumour compartment, cancer cell antigen expression and the ADC binding affinity to the target antigen, the cell internalization process, cleaving of the cytotoxic drug from the ADC, and the cytotoxic effect of the drug on the target cells. Finally, we present a summary of some of the experimental ADC strategies used in the treatment of hepatocellular carcinoma, from the recent literature. Full article

(This article belongs to the Special Issue Drug Discovery and Molecular Docking)

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