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Topical Collection "Molecular Docking"

A topical collection in Molecules (ISSN 1420-3049). This collection belongs to the section "Medicinal Chemistry".

Editor

Collection Editor
Prof. Dr. 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

Topical Collection Information

Dear Colleagues,

Following the success of the Special Issue entitled “Molecular Docking in Drug Design” ( http://www.mdpi.com/journal/molecules/special_issues/molecular_docking_drug ), where a number of papers have been published, it was decided to widen the issue and convert it to a Topical Collection under the name of “Molecular Docking”.

Molecular docking is an invaluable tool to study how two different molecular entities can recognize each to other. This tool is, not only used in modern drug discovery and design, but also in other fields, such as protein–protein interaction characterization to drive biological investigations.

Although many algorithms have been disclosed, and new docking programs are constantly released, there is still a lot to do. Many authors have proposed different scoring function approaches, such as consensus scoring, consensus docking and external independent scoring, others have proposed different poses generation methods or different conformation generators. Many methods have been reported to work better than others; nevertheless, we are still very far away from the ideal molecular docking software.

Therefore, there is still the need to continue the improvement of actual molecular docking procedures and this represent the main goal of this collection where manuscript will be accepted for publication if reporting newest approaches in molecular docking application and development.

The “Molecular Docking Topical Collection” will embrace several molecular docking related topics, such as:

  • Small Molecule Reversible Docking Application
  • Small Molecule Covalent Docking Application
  • Virtual Screening
  • De Novo Design
  • Molecular Docking Software Development
  • Molecular Docking Software Comparison
  • Protein-Protein docking
  • Scoring Function Development
  • Scoring Function Comparison
  • Drug Design
  • Host-Guest Studies
  • Molecular Dynamics as molecular Docking Tools
  • Reviews

Prof. Dr. Rino Ragno
Collection Editor

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 collection 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.

Related Special Issue

Published Papers (22 papers)

2017

Jump to: 2016, 2015

Open AccessArticle Synthesis of New Hydrazone Derivatives for MAO Enzymes Inhibitory Activity
Molecules 2017, 22(8), 1381; doi:10.3390/molecules22081381 (registering DOI)
Received: 26 July 2017 / Revised: 2 August 2017 / Accepted: 15 August 2017 / Published: 20 August 2017
PDF Full-text (3283 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In the present work, 14 new 1-substituted-2-phenylhydrazone derivatives were synthesized to evaluate their inhibitory activity against hMAO enzymes. The structures of the newly synthesized hydrazones 2a–2n were characterized by IR, 1H-NMR, 13C-NMR, HR-MS spectroscopic methods. The inhibitory activity of compounds 2a–2n against hMAO-A
[...] Read more.
In the present work, 14 new 1-substituted-2-phenylhydrazone derivatives were synthesized to evaluate their inhibitory activity against hMAO enzymes. The structures of the newly synthesized hydrazones 2a–2n were characterized by IR, 1H-NMR, 13C-NMR, HR-MS spectroscopic methods. The inhibitory activity of compounds 2a–2n against hMAO-A and hMAO-B enzymes was elucidated by using an in-vitro Amplex Red® reagent assay based on fluorometric methods. According to the activity studies, 2a and 2b were found to be the most active compounds against hMAO-A enzyme, with IC50 values of 0.342 µM and 0.028 µM, respectively. The most active compounds 2a–2b were evaluated by means of enzyme kinetics and docking studies. Moreover, these compounds were subjected to cytotoxicity and genotoxicity tests to establish their preliminary toxicological profiles and were found to be non-cytotoxic and non-genotoxic. Consequently, the findings of this study display the biological importance of compounds 2a, 2b as selective, irreversible and competitive inhibitors of hMAO-A. Docking studies revealed that there is a strong interaction between hMAO-A and the most active compound 2b. Full article
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Figure 1

Open AccessReview Recent Advances and Applications of Molecular Docking to G Protein-Coupled Receptors
Molecules 2017, 22(2), 340; doi:10.3390/molecules22020340
Received: 12 December 2016 / Revised: 27 January 2017 / Accepted: 15 February 2017 / Published: 22 February 2017
Cited by 1 | PDF Full-text (873 KB) | HTML Full-text | XML Full-text
Abstract
The growing number of studies on G protein-coupled receptors (GPCRs) family are a source of noticeable improvement in our understanding of the functioning of these proteins. GPCRs are responsible for a vast part of signaling in vertebrates and, as such, invariably remain in
[...] Read more.
The growing number of studies on G protein-coupled receptors (GPCRs) family are a source of noticeable improvement in our understanding of the functioning of these proteins. GPCRs are responsible for a vast part of signaling in vertebrates and, as such, invariably remain in the spotlight of medicinal chemistry. A deeper insight into the underlying mechanisms of interesting phenomena observed in GPCRs, such as biased signaling or allosteric modulation, can be gained with experimental and computational studies. The latter play an important role in this process, since they allow for observations on scales inaccessible for most other methods. One of the key steps in such studies is proper computational reconstruction of actual ligand-receptor or protein-protein interactions, a process called molecular docking. A number of improvements and innovative applications of this method were documented recently. In this review, we focus particularly on innovations in docking to GPCRs. Full article
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2016

Jump to: 2017, 2015

Open AccessArticle AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking
Molecules 2016, 21(11), 1604; doi:10.3390/molecules21111604
Received: 12 October 2016 / Revised: 15 November 2016 / Accepted: 16 November 2016 / Published: 23 November 2016
Cited by 2 | PDF Full-text (5935 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Water plays a significant role in the binding process between protein and ligand. However, the thermodynamics of water molecules are often underestimated, or even ignored, in protein-ligand docking. Usually, the free energies of active-site water molecules are substantially different from those of waters
[...] Read more.
Water plays a significant role in the binding process between protein and ligand. However, the thermodynamics of water molecules are often underestimated, or even ignored, in protein-ligand docking. Usually, the free energies of active-site water molecules are substantially different from those of waters in the bulk region. The binding of a ligand to a protein causes a displacement of these waters from an active site to bulk, and this displacement process substantially contributes to the free energy change of protein-ligand binding. The free energy of active-site water molecules can be calculated by grid inhomogeneous solvation theory (GIST), using molecular dynamics (MD) and the trajectory of a target protein and water molecules. Here, we show a case study of the combination of GIST and a docking program and discuss the effectiveness of the displacing gain of unfavorable water in protein-ligand docking. We combined the GIST-based desolvation function with the scoring function of AutoDock4, which is called AutoDock-GIST. The proposed scoring function was assessed employing 51 ligands of coagulation factor Xa (FXa), and results showed that both scoring accuracy and docking success rate were improved. We also evaluated virtual screening performance of AutoDock-GIST using FXa ligands in the directory of useful decoys-enhanced (DUD-E), thus finding that the displacing gain of unfavorable water is effective for a successful docking campaign. Full article
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Open AccessArticle Molecular Docking Optimization in the Context of Multi-Drug Resistant and Sensitive EGFR Mutants
Molecules 2016, 21(11), 1575; doi:10.3390/molecules21111575
Received: 26 September 2016 / Revised: 13 November 2016 / Accepted: 15 November 2016 / Published: 19 November 2016
PDF Full-text (3945 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The human Epidermal Growth Factor (EGFR) plays an important role in signaling pathways, such as cell proliferation and migration. Mutations like G719S, L858R, T790M, G719S/T790M or T790M/L858R can alter its conformation, and, therefore, drug responses from lung cancer patients. In this context, candidate
[...] Read more.
The human Epidermal Growth Factor (EGFR) plays an important role in signaling pathways, such as cell proliferation and migration. Mutations like G719S, L858R, T790M, G719S/T790M or T790M/L858R can alter its conformation, and, therefore, drug responses from lung cancer patients. In this context, candidate drugs are being tested and in silico studies are necessary to know how these mutations affect the ligand binding site. This problem can be tackled by using a multi-objective approach applied to the molecular docking problem. According to the literature, few studies are related to the application of multi-objective approaches by minimizing two or more objectives in drug discovery. In this study, we have used four algorithms (NSGA-II, GDE3, SMPSO and MOEA/D) to minimize two objectives: the ligand–receptor intermolecular energy and the RMSD score. We have prepared a set of instances that includes the wild-type EGFR kinase domain and the same receptor with somatic mutations, and then we assessed the performance of the algorithms by applying a quality indicator to evaluate the convergence and diversity of the reference fronts. The MOEA/D algorithm yields the best solutions to these docking problems. The obtained solutions were analyzed, showing promising results to predict candidate EGFR inhibitors by using this multi-objective approach. Full article
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Figure 1a

Open AccessArticle Molecular Modeling Studies of 11β-Hydroxysteroid Dehydrogenase Type 1 Inhibitors through Receptor-Based 3D-QSAR and Molecular Dynamics Simulations
Molecules 2016, 21(9), 1222; doi:10.3390/molecules21091222
Received: 13 July 2016 / Revised: 21 August 2016 / Accepted: 9 September 2016 / Published: 19 September 2016
Cited by 2 | PDF Full-text (4438 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
11β-Hydroxysteroid dehydrogenase type 1 (11β-HSD1) is a potential target for the treatment of numerous human disorders, such as diabetes, obesity, and metabolic syndrome. In this work, molecular modeling studies combining molecular docking, 3D-QSAR, MESP, MD simulations and free energy calculations were performed on
[...] Read more.
11β-Hydroxysteroid dehydrogenase type 1 (11β-HSD1) is a potential target for the treatment of numerous human disorders, such as diabetes, obesity, and metabolic syndrome. In this work, molecular modeling studies combining molecular docking, 3D-QSAR, MESP, MD simulations and free energy calculations were performed on pyridine amides and 1,2,4-triazolopyridines as 11β-HSD1 inhibitors to explore structure-activity relationships and structural requirement for the inhibitory activity. 3D-QSAR models, including CoMFA and CoMSIA, were developed from the conformations obtained by docking strategy. The derived pharmacophoric features were further supported by MESP and Mulliken charge analyses using density functional theory. In addition, MD simulations and free energy calculations were employed to determine the detailed binding process and to compare the binding modes of inhibitors with different bioactivities. The binding free energies calculated by MM/PBSA showed a good correlation with the experimental biological activities. Free energy analyses and per-residue energy decomposition indicated the van der Waals interaction would be the major driving force for the interactions between an inhibitor and 11β-HSD1. These unified results may provide that hydrogen bond interactions with Ser170 and Tyr183 are favorable for enhancing activity. Thr124, Ser170, Tyr177, Tyr183, Val227, and Val231 are the key amino acid residues in the binding pocket. The obtained results are expected to be valuable for the rational design of novel potent 11β-HSD1 inhibitors. Full article
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Open AccessArticle Predicting Protein-Protein Interactions Using BiGGER: Case Studies
Molecules 2016, 21(8), 1037; doi:10.3390/molecules21081037
Received: 10 June 2016 / Revised: 3 August 2016 / Accepted: 4 August 2016 / Published: 9 August 2016
Cited by 2 | PDF Full-text (3467 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The importance of understanding interactomes makes preeminent the study of protein interactions and protein complexes. Traditionally, protein interactions have been elucidated by experimental methods or, with lower impact, by simulation with protein docking algorithms. This article describes features and applications of the BiGGER
[...] Read more.
The importance of understanding interactomes makes preeminent the study of protein interactions and protein complexes. Traditionally, protein interactions have been elucidated by experimental methods or, with lower impact, by simulation with protein docking algorithms. This article describes features and applications of the BiGGER docking algorithm, which stands at the interface of these two approaches. BiGGER is a user-friendly docking algorithm that was specifically designed to incorporate experimental data at different stages of the simulation, to either guide the search for correct structures or help evaluate the results, in order to combine the reliability of hard data with the convenience of simulations. Herein, the applications of BiGGER are described by illustrative applications divided in three Case Studies: (Case Study A) in which no specific contact data is available; (Case Study B) when different experimental data (e.g., site-directed mutagenesis, properties of the complex, NMR chemical shift perturbation mapping, electron tunneling) on one of the partners is available; and (Case Study C) when experimental data are available for both interacting surfaces, which are used during the search and/or evaluation stage of the docking. This algorithm has been extensively used, evidencing its usefulness in a wide range of different biological research fields. Full article
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Open AccessArticle Bioactive Molecule Prediction Using Extreme Gradient Boosting
Molecules 2016, 21(8), 983; doi:10.3390/molecules21080983
Received: 1 May 2016 / Revised: 19 July 2016 / Accepted: 22 July 2016 / Published: 28 July 2016
Cited by 2 | PDF Full-text (379 KB) | HTML Full-text | XML Full-text
Abstract
Following the explosive growth in chemical and biological data, the shift from traditional methods of drug discovery to computer-aided means has made data mining and machine learning methods integral parts of today’s drug discovery process. In this paper, extreme gradient boosting (Xgboost), which
[...] Read more.
Following the explosive growth in chemical and biological data, the shift from traditional methods of drug discovery to computer-aided means has made data mining and machine learning methods integral parts of today’s drug discovery process. In this paper, extreme gradient boosting (Xgboost), which is an ensemble of Classification and Regression Tree (CART) and a variant of the Gradient Boosting Machine, was investigated for the prediction of biological activity based on quantitative description of the compound’s molecular structure. Seven datasets, well known in the literature were used in this paper and experimental results show that Xgboost can outperform machine learning algorithms like Random Forest (RF), Support Vector Machines (LSVM), Radial Basis Function Neural Network (RBFN) and Naïve Bayes (NB) for the prediction of biological activities. In addition to its ability to detect minority activity classes in highly imbalanced datasets, it showed remarkable performance on both high and low diversity datasets. Full article
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2015

Jump to: 2017, 2016

Open AccessArticle Identification of Hydrophobic Interfaces in Protein-Ligand Complexes by Selective Saturation Transfer NMR Spectroscopy
Molecules 2015, 20(12), 21992-21999; doi:10.3390/molecules201219824
Received: 6 May 2015 / Revised: 17 September 2015 / Accepted: 26 November 2015 / Published: 9 December 2015
PDF Full-text (3299 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The proper characterization of protein-ligand interfaces is essential for structural biology, with implications ranging from the fundamental understanding of biological processes to pharmacology. Nuclear magnetic resonance is a powerful technique for such studies. We propose a novel approach to the direct determination of
[...] Read more.
The proper characterization of protein-ligand interfaces is essential for structural biology, with implications ranging from the fundamental understanding of biological processes to pharmacology. Nuclear magnetic resonance is a powerful technique for such studies. We propose a novel approach to the direct determination of the likely pose of a peptide ligand onto a protein partner, by using frequency-selective cross-saturation with a low stringency isotopic labeling methods. Our method illustrates a complex of the Src homology 3 domain of C-terminal Src kinase with a peptide from the proline-enriched tyrosine phosphatase. Full article
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Open AccessReview Charting a Path to Success in Virtual Screening
Molecules 2015, 20(10), 18732-18758; doi:10.3390/molecules201018732
Received: 13 August 2015 / Revised: 7 October 2015 / Accepted: 12 October 2015 / Published: 15 October 2015
Cited by 7 | PDF Full-text (7136 KB) | HTML Full-text | XML Full-text
Abstract
Docking is commonly applied to drug design efforts, especially high-throughput virtual screenings of small molecules, to identify new compounds that bind to a given target. Despite great advances and successful applications in recent years, a number of issues remain unsolved. Most of the
[...] Read more.
Docking is commonly applied to drug design efforts, especially high-throughput virtual screenings of small molecules, to identify new compounds that bind to a given target. Despite great advances and successful applications in recent years, a number of issues remain unsolved. Most of the challenges and problems faced when running docking experiments are independent of the specific software used, and can be ascribed to either improper input preparation or to the simplified approaches applied to achieve high-throughput speed. Being aware of approximations and limitations of such methods is essential to prevent errors, deal with misleading results, and increase the success rate of virtual screening campaigns. In this review, best practices and most common issues of docking and virtual screening will be discussed, covering the journey from the design of the virtual experiment to the hit identification. Full article
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Open AccessReview Evolution of Macromolecular Docking Techniques: The Case Study of Nickel and Iron Metabolism in Pathogenic Bacteria
Molecules 2015, 20(8), 14265-14292; doi:10.3390/molecules200814265
Received: 28 April 2015 / Revised: 23 July 2015 / Accepted: 28 July 2015 / Published: 5 August 2015
Cited by 1 | PDF Full-text (10313 KB) | HTML Full-text | XML Full-text
Abstract
The interaction between macromolecules is a fundamental aspect of most biological processes. The computational techniques used to study protein-protein and protein-nucleic acid interactions have evolved in the last few years because of the development of new algorithms that allow the a priori incorporation,
[...] Read more.
The interaction between macromolecules is a fundamental aspect of most biological processes. The computational techniques used to study protein-protein and protein-nucleic acid interactions have evolved in the last few years because of the development of new algorithms that allow the a priori incorporation, in the docking process, of experimentally derived information, together with the possibility of accounting for the flexibility of the interacting molecules. Here we review the results and the evolution of the techniques used to study the interaction between metallo-proteins and DNA operators, all involved in the nickel and iron metabolism of pathogenic bacteria, focusing in particular on Helicobacter pylori (Hp). In the first part of the article we discuss the methods used to calculate the structure of complexes of proteins involved in the activation of the nickel-dependent enzyme urease. In the second part of the article, we concentrate on two applications of protein-DNA docking conducted on the transcription factors HpFur (ferric uptake regulator) and HpNikR (nickel regulator). In both cases we discuss the technical expedients used to take into account the conformational variability of the multi-domain proteins involved in the calculations. Full article
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Open AccessReview Molecular Docking and Structure-Based Drug Design Strategies
Molecules 2015, 20(7), 13384-13421; doi:10.3390/molecules200713384
Received: 13 May 2015 / Revised: 14 July 2015 / Accepted: 20 July 2015 / Published: 22 July 2015
Cited by 55 | PDF Full-text (4565 KB) | HTML Full-text | XML Full-text
Abstract
Pharmaceutical research has successfully incorporated a wealth of molecular modeling methods, within a variety of drug discovery programs, to study complex biological and chemical systems. The integration of computational and experimental strategies has been of great value in the identification and development of
[...] Read more.
Pharmaceutical research has successfully incorporated a wealth of molecular modeling methods, within a variety of drug discovery programs, to study complex biological and chemical systems. The integration of computational and experimental strategies has been of great value in the identification and development of novel promising compounds. Broadly used in modern drug design, molecular docking methods explore the ligand conformations adopted within the binding sites of macromolecular targets. This approach also estimates the ligand-receptor binding free energy by evaluating critical phenomena involved in the intermolecular recognition process. Today, as a variety of docking algorithms are available, an understanding of the advantages and limitations of each method is of fundamental importance in the development of effective strategies and the generation of relevant results. The purpose of this review is to examine current molecular docking strategies used in drug discovery and medicinal chemistry, exploring the advances in the field and the role played by the integration of structure- and ligand-based methods. Full article
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Open AccessArticle Molecular Docking and Multivariate Analysis of Xanthones as Antimicrobial and Antiviral Agents
Molecules 2015, 20(7), 13165-13204; doi:10.3390/molecules200713165
Received: 1 April 2015 / Revised: 10 May 2015 / Accepted: 21 May 2015 / Published: 21 July 2015
Cited by 2 | PDF Full-text (4535 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Xanthones are secondary metabolites which have drawn considerable interest over the last decades due to their antimicrobial properties, among others. A great number of this kind of compounds has been therefore reported, but there is a limited amount of studies on screening for
[...] Read more.
Xanthones are secondary metabolites which have drawn considerable interest over the last decades due to their antimicrobial properties, among others. A great number of this kind of compounds has been therefore reported, but there is a limited amount of studies on screening for biological activity. Thus, as part of our research on antimicrobial agents of natural origin, a set of 272 xanthones were submitted to molecular docking (MD) calculations with a group of seven fungal and two viral enzymes. The results indicated that prenylated xanthones are important hits for inhibition of the analyzed enzymes. The MD scores were also analyzed by multivariate statistics. Important structural details were found to be crucial for the inhibition of the tested enzymes by the xanthones. In addition, the classification of active xanthones can be achieved by statistical analysis on molecular docking scores by an affinity-antifungal activity relationship approach. The obtained results therefore are a suitable starting point for the development of antifungal and antiviral agents based on xanthones. Full article
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Open AccessReview Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps
Molecules 2015, 20(7), 12045-12060; doi:10.3390/molecules200712045
Received: 1 April 2015 / Revised: 8 June 2015 / Accepted: 17 June 2015 / Published: 1 July 2015
Cited by 2 | PDF Full-text (2813 KB) | HTML Full-text | XML Full-text
Abstract
In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available,
[...] Read more.
In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions. Full article
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Open AccessReview Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors
Molecules 2015, 20(6), 11569-11603; doi:10.3390/molecules200611569
Received: 27 March 2015 / Revised: 2 June 2015 / Accepted: 15 June 2015 / Published: 23 June 2015
Cited by 5 | PDF Full-text (2526 KB) | HTML Full-text | XML Full-text
Abstract
Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases
[...] Read more.
Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers. Full article
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Open AccessArticle Coarse-Grained Modeling of Peptide Docking Associated with Large Conformation Transitions of the Binding Protein: Troponin I Fragment–Troponin C System
Molecules 2015, 20(6), 10763-10780; doi:10.3390/molecules200610763
Received: 31 March 2015 / Revised: 14 May 2015 / Accepted: 21 May 2015 / Published: 11 June 2015
Cited by 5 | PDF Full-text (6164 KB) | HTML Full-text | XML Full-text
Abstract
Most of the current docking procedures are focused on fine conformational adjustments of assembled complexes and fail to reproduce large-scale protein motion. In this paper, we test a new modeling approach developed to address this problem. CABS-dock is a versatile and efficient tool
[...] Read more.
Most of the current docking procedures are focused on fine conformational adjustments of assembled complexes and fail to reproduce large-scale protein motion. In this paper, we test a new modeling approach developed to address this problem. CABS-dock is a versatile and efficient tool for modeling the structure, dynamics and interactions of protein complexes. The docking protocol employs a coarse-grained representation of proteins, a simplified model of interactions and advanced protocols for conformational sampling. CABS-dock is one of the very few tools that allow unrestrained docking with large conformational freedom of the receptor. In an example application we modeled the process of complex assembly between two proteins: Troponin C (TnC) and the N-terminal helix of Troponin I (TnI N-helix), which occurs in vivo during muscle contraction. Docking simulations illustrated how the TnC molecule undergoes significant conformational transition on complex formation, a phenomenon that can be modeled only when protein flexibility is properly accounted for. This way our procedure opens up a new possibility for studying mechanisms of protein complex assembly, which may be a supporting tool for rational drug design. Full article
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Open AccessArticle Computational Studies of Benzoxazinone Derivatives as Antiviral Agents against Herpes Virus Type 1 Protease
Molecules 2015, 20(6), 10689-10704; doi:10.3390/molecules200610689
Received: 28 February 2015 / Revised: 27 May 2015 / Accepted: 1 June 2015 / Published: 10 June 2015
PDF Full-text (2684 KB) | HTML Full-text | XML Full-text
Abstract
Herpes simplex virus infections have been described in the medical literature for centuries, yet the the drugs available nowadays for therapy are largely ineffective and low oral bioavailability plays an important role on the inefficacy of the treatments. Additionally, the details of the
[...] Read more.
Herpes simplex virus infections have been described in the medical literature for centuries, yet the the drugs available nowadays for therapy are largely ineffective and low oral bioavailability plays an important role on the inefficacy of the treatments. Additionally, the details of the inhibition of Herpes Virus type 1 are still not fully understood. Studies have shown that several viruses encode one or more proteases required for the production new infectious virions. This study presents an analysis of the interactions between HSV-1 protease and benzoxazinone derivatives through a combination of structure-activity relationships, comparative modeling and molecular docking studies. The structure activity relationship results showed an important contribution of hydrophobic and polarizable groups and limitations for bulky groups in specific positions. Two Herpes Virus type 1 protease models were constructed and compared to achieve the best model which was obtained by MODELLER. Molecular docking results pointed to an important interaction between the most potent benzoxazinone derivative and Ser129, consistent with previous mechanistic data. Moreover, we also observed hydrophobic interactions that may play an important role in the stabilization of inhibitors in the active site. Finally, we performed druglikeness and drugscore studies of the most potent derivatives and the drugs currently used against Herpes virus. Full article
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Open AccessArticle Solving Molecular Docking Problems with Multi-Objective Metaheuristics
Molecules 2015, 20(6), 10154-10183; doi:10.3390/molecules200610154
Received: 30 March 2015 / Accepted: 21 May 2015 / Published: 2 June 2015
Cited by 5 | PDF Full-text (3354 KB) | HTML Full-text | XML Full-text
Abstract
Molecular docking is a hard optimization problem that has been tackled in the past with metaheuristics, demonstrating new and challenging results when looking for one objective: the minimum binding energy. However, only a few papers can be found in the literature that deal
[...] Read more.
Molecular docking is a hard optimization problem that has been tackled in the past with metaheuristics, demonstrating new and challenging results when looking for one objective: the minimum binding energy. However, only a few papers can be found in the literature that deal with this problem by means of a multi-objective approach, and no experimental comparisons have been made in order to clarify which of them has the best overall performance. In this paper, we use and compare, for the first time, a set of representative multi-objective optimization algorithms applied to solve complex molecular docking problems. The approach followed is focused on optimizing the intermolecular and intramolecular energies as two main objectives to minimize. Specifically, these algorithms are: two variants of the non-dominated sorting genetic algorithm II (NSGA-II), speed modulation multi-objective particle swarm optimization (SMPSO), third evolution step of generalized differential evolution (GDE3), multi-objective evolutionary algorithm based on decomposition (MOEA/D) and S-metric evolutionary multi-objective optimization (SMS-EMOA). We assess the performance of the algorithms by applying quality indicators intended to measure convergence and the diversity of the generated Pareto front approximations. We carry out a comparison with another reference mono-objective algorithm in the problem domain (Lamarckian genetic algorithm (LGA) provided by the AutoDock tool). Furthermore, the ligand binding site and molecular interactions of computed solutions are analyzed, showing promising results for the multi-objective approaches. In addition, a case study of application for aeroplysinin-1 is performed, showing the effectiveness of our multi-objective approach in drug discovery. Full article
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Open AccessArticle DockBench: An Integrated Informatic Platform Bridging the Gap between the Robust Validation of Docking Protocols and Virtual Screening Simulations
Molecules 2015, 20(6), 9977-9993; doi:10.3390/molecules20069977
Received: 31 March 2015 / Revised: 5 May 2015 / Accepted: 21 May 2015 / Published: 29 May 2015
Cited by 10 | PDF Full-text (1203 KB) | HTML Full-text | XML Full-text
Abstract
Virtual screening (VS) is a computational methodology that streamlines the drug discovery process by reducing costs and required resources through the in silico identification of potential drug candidates. Structure-based VS (SBVS) exploits knowledge about the three-dimensional (3D) structure of protein targets and uses
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Virtual screening (VS) is a computational methodology that streamlines the drug discovery process by reducing costs and required resources through the in silico identification of potential drug candidates. Structure-based VS (SBVS) exploits knowledge about the three-dimensional (3D) structure of protein targets and uses the docking methodology as search engine for novel hits. The success of a SBVS campaign strongly depends upon the accuracy of the docking protocol used to select the candidates from large chemical libraries. The identification of suitable protocols is therefore a crucial step in the setup of SBVS experiments. Carrying out extensive benchmark studies, however, is usually a tangled task that requires users’ proficiency in handling different file formats and philosophies at the basis of the plethora of existing software packages. We present here DockBench 1.0, a platform available free of charge that eases the pipeline by automating the entire procedure, from docking benchmark to VS setups. In its current implementation, DockBench 1.0 handles seven docking software packages and offers the possibility to test up to seventeen different protocols. The main features of our platform are presented here and the results of the benchmark study of human Checkpoint kinase 1 (hChk1) are discussed as validation test. Full article
Open AccessArticle S4MPLE—Sampler for Multiple Protein-Ligand Entities: Methodology and Rigid-Site Docking Benchmarking
Molecules 2015, 20(5), 8997-9028; doi:10.3390/molecules20058997
Received: 5 March 2015 / Revised: 27 April 2015 / Accepted: 11 May 2015 / Published: 19 May 2015
Cited by 2 | PDF Full-text (3643 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes the development of the unified conformational sampling and docking tool called Sampler for Multiple Protein-Ligand Entities (S4MPLE). The main novelty in S4MPLE is the unified dealing with intra- and intermolecular degrees of freedom (DoF). While classically programs are either designed
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This paper describes the development of the unified conformational sampling and docking tool called Sampler for Multiple Protein-Ligand Entities (S4MPLE). The main novelty in S4MPLE is the unified dealing with intra- and intermolecular degrees of freedom (DoF). While classically programs are either designed for folding or docking, S4MPLE transcends this artificial specialization. It supports folding, docking of a flexible ligand into a flexible site and simultaneous docking of several ligands. The trick behind it is the formal assimilation of inter-molecular to intra-molecular DoF associated to putative inter-molecular contact axes. This is implemented within the genetic operators powering a Lamarckian Genetic Algorithm (GA). Further novelty includes differentiable interaction fingerprints to control population diversity, and fitting a simple continuum solvent model and favorable contact bonus terms to the AMBER/GAFF force field. Novel applications—docking of fragment-like compounds, simultaneous docking of multiple ligands, including free crystallographic waters—were published elsewhere. This paper discusses: (a) methodology, (b) set-up of the force field energy functions and (c) their validation in classical redocking tests. More than 80% success in redocking was achieved (RMSD of top-ranked pose < 2.0 Å). Full article
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Open AccessArticle Development and Validation of a Docking-Based Virtual Screening Platform for the Identification of New Lactate Dehydrogenase Inhibitors
Molecules 2015, 20(5), 8772-8790; doi:10.3390/molecules20058772
Received: 3 March 2015 / Revised: 6 May 2015 / Accepted: 11 May 2015 / Published: 15 May 2015
Cited by 1 | PDF Full-text (1402 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The human muscle isoform of lactate dehydrogenase (hLDH5) is one of the key enzymes of the glycolytic process. It is overexpressed in metastatic cancer cells and is linked to the vitality of tumors in hypoxic conditions. With the aim of identifying
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The human muscle isoform of lactate dehydrogenase (hLDH5) is one of the key enzymes of the glycolytic process. It is overexpressed in metastatic cancer cells and is linked to the vitality of tumors in hypoxic conditions. With the aim of identifying new hLDH5 inhibitors, a fully automated docking-based virtual screening platform was developed by considering different protein conformations and the consensus docking strategy. In order to verify the reliability of the reported platform, a small database of about 10,000 compounds was filtered by using this method, and the top-ranked compounds were tested for their hLDH5 inhibition activity. Enzymatic assays revealed that, among the ten selected compounds, two proved to efficiently inhibit enzyme activity with IC50 values in the micromolar range. These results demonstrate the validity of the methodologies we followed, encouraging the application of larger virtual screening studies and further refinements of the platform. Furthermore, the two active compounds herein described may be considered as interesting leads for the development of new and more efficient LDH inhibitors. Full article
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Open AccessArticle Reduction of False Positives in Structure-Based Virtual Screening When Receptor Plasticity Is Considered
Molecules 2015, 20(3), 5152-5164; doi:10.3390/molecules20035152
Received: 5 February 2015 / Revised: 9 March 2015 / Accepted: 16 March 2015 / Published: 19 March 2015
Cited by 4 | PDF Full-text (2414 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Structure-based virtual screening for selecting potential drug candidates is usually challenged by how numerous false positives in a molecule library are excluded when receptor plasticity is considered. In this study, based on the binding energy landscape theory, a hypothesis that a true inhibitor
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Structure-based virtual screening for selecting potential drug candidates is usually challenged by how numerous false positives in a molecule library are excluded when receptor plasticity is considered. In this study, based on the binding energy landscape theory, a hypothesis that a true inhibitor can bind to different conformations of the binding site favorably was put forth, and related strategies to defeat this challenge were devised; reducing false positives when receptor plasticity is considered. The receptor in the study is the influenza A nucleoprotein, whose oligomerization is a requirement for RNA binding. The structural flexibility of influenza A nucleoprotein was explored by molecular dynamics simulations. The resultant distinctive structures and the crystal structure were used as receptor models in docking exercises in which two binding sites, the tail-loop binding pocket and the RNA binding site, were targeted with the Otava PrimScreen1 diversity-molecule library using the GOLD software. The intersection ligands that were listed in the top-ranked molecules from all receptor models were selected. Such selection strategy successfully distinguished high-affinity and low-affinity control molecules added to the molecule library. This work provides an applicable approach for reducing false positives and selecting true ligands from molecule libraries. Full article
Open AccessReview Theory and Applications of Covalent Docking in Drug Discovery: Merits and Pitfalls
Molecules 2015, 20(2), 1984-2000; doi:10.3390/molecules20021984
Received: 12 November 2014 / Revised: 19 December 2014 / Accepted: 12 January 2015 / Published: 27 January 2015
Cited by 24 | PDF Full-text (1935 KB) | HTML Full-text | XML Full-text
Abstract
he present art of drug discovery and design of new drugs is based on suicidal irreversible inhibitors. Covalent inhibition is the strategy that is used to achieve irreversible inhibition. Irreversible inhibitors interact with their targets in a time-dependent fashion, and the reaction proceeds
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he present art of drug discovery and design of new drugs is based on suicidal irreversible inhibitors. Covalent inhibition is the strategy that is used to achieve irreversible inhibition. Irreversible inhibitors interact with their targets in a time-dependent fashion, and the reaction proceeds to completion rather than to equilibrium. Covalent inhibitors possessed some significant advantages over non-covalent inhibitors such as covalent warheads can target rare, non-conserved residue of a particular target protein and thus led to development of highly selective inhibitors, covalent inhibitors can be effective in targeting proteins with shallow binding cleavage which will led to development of novel inhibitors with increased potency than non-covalent inhibitors. Several computational approaches have been developed to simulate covalent interactions; however, this is still a challenging area to explore. Covalent molecular docking has been recently implemented in the computer-aided drug design workflows to describe covalent interactions between inhibitors and biological targets. In this review we highlight: (i) covalent interactions in biomolecular systems; (ii) the mathematical framework of covalent molecular docking; (iii) implementation of covalent docking protocol in drug design workflows; (iv) applications covalent docking: case studies and (v) shortcomings and future perspectives of covalent docking. To the best of our knowledge; this review is the first account that highlights different aspects of covalent docking with its merits and pitfalls. We believe that the method and applications highlighted in this study will help future efforts towards the design of irreversible inhibitors. Full article
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