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Special Issue "New Avenues in Molecular Docking for Drug Design 2020"

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: 31 August 2020.

Special Issue Editor

Prof. Dr. Giulio Vistoli
Website
Guest Editor
Department of Pharmaceutical Sciences Università degli Studi di Milano, via Mangiagalli 25, 20133 Milano, Italy
Interests: computational chemistry; drug design; cheminformatics; molecular docking; ADME predictions; lipophilicity
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Molecular docking is gaining increased interest in drug design approaches, especially considering its noteworthy potentialities in performing successful virtual screening campaigns. Currently available computing resources allow for simulations involving huge molecular libraries on extended panels of targets in a reasonable time, and these extremely extended simulations appear to be particularly fruitful in the field of multi-target ligand design as well as in the repurposing studies. Clearly, these powerful simulations require new algorithms and new methodological approaches to optimize their performances and to match the advancements in the hardware architectures. Molecular docking requires continuous improvements especially focused on the algorithms for scoring function and pose evaluation. Molecular docking is often combined with other computational approaches to further improve the reliability of the obtained results in terms of both computed complexes and predictive power, and, in this context, machine learning techniques can offer new avenues with which to improve docking simulations and virtual screening campaigns.

On these grounds, this Special Issue seeks manuscripts dealing with novel approaches of molecular docking in drug design by considering both methodological and applicative studies with a view to offering a picture of the areas in which docking simulations can have an ever-increasing impact in the drug discovery pipeline, as well as with the new trends that will impact on such a field in the next future.

Prof. Dr. Giulio Vistoli
Guest 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 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. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. 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

  • Structure-based drug design
  • Molecular targets
  • Molecular recognition
  • Ligand binding
  • Virtual screening
  • Drug repositioning
  • Multi-target ligands
  • Scoring function
  • Pose generation and evaluation
  • Big data

Published Papers (3 papers)

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Research

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Open AccessArticle
Combining Molecular Dynamics and Docking Simulations to Develop Targeted Protocols for Performing Optimized Virtual Screening Campaigns on The hTRPM8 Channel
Int. J. Mol. Sci. 2020, 21(7), 2265; https://doi.org/10.3390/ijms21072265 (registering DOI) - 25 Mar 2020
Abstract
Background: There is an increasing interest in TRPM8 ligands of medicinal interest, the rational design of which can be nowadays supported by structure-based in silico studies based on the recently resolved TRPM8 structures. Methods: The study involves the generation of a [...] Read more.
Background: There is an increasing interest in TRPM8 ligands of medicinal interest, the rational design of which can be nowadays supported by structure-based in silico studies based on the recently resolved TRPM8 structures. Methods: The study involves the generation of a reliable hTRPM8 homology model, the reliability of which was assessed by a 1.0 μs MD simulation which was also used to generate multiple receptor conformations for the following structure-based virtual screening (VS) campaigns; docking simulations utilized different programs and involved all monomers of the selected frames; the so computed docking scores were combined by consensus approaches based on the EFO algorithm. Results: The obtained models revealed very satisfactory performances; LiGen™ provided the best results among the tested docking programs; the combination of docking results from the four monomers elicited a markedly beneficial effect on the computed consensus models. Conclusions: The generated hTRPM8 model appears to be amenable for successful structure-based VS studies; cross-talk modulating effects between interacting monomers on the binding sites can be accounted for by combining docking simulations as performed on all the monomers; this strategy can have general applicability for docking simulations involving quaternary protein structures with multiple identical binding pockets. Full article
(This article belongs to the Special Issue New Avenues in Molecular Docking for Drug Design 2020)
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Open AccessArticle
Structural Requirements of N-alpha-Mercaptoacetyl Dipeptide (NAMdP) Inhibitors of Pseudomonas Aeruginosa Virulence Factor LasB: 3D-QSAR, Molecular Docking, and Interaction Fingerprint Studies
Int. J. Mol. Sci. 2019, 20(24), 6133; https://doi.org/10.3390/ijms20246133 - 05 Dec 2019
Cited by 1
Abstract
The zinc metallopeptidase Pseudomonas elastase (LasB) is a virulence factor of Pseudomonas aeruginosa (P. aeruginosa), a pathogenic bacterium that can cause nosocomial infections. The present study relates the structural analysis of 118 N-alpha-mercaptoacetyl dipeptides (NAMdPs) as LasB inhibitors. Field-based 3D-QSAR [...] Read more.
The zinc metallopeptidase Pseudomonas elastase (LasB) is a virulence factor of Pseudomonas aeruginosa (P. aeruginosa), a pathogenic bacterium that can cause nosocomial infections. The present study relates the structural analysis of 118 N-alpha-mercaptoacetyl dipeptides (NAMdPs) as LasB inhibitors. Field-based 3D-QSAR and molecular docking methods were employed to describe the essential interactions between NAMdPs and LasB binding sites, and the chemical features that determine their differential activities. We report a predictive 3D-QSAR model that was developed according to the internal and external validation tests. The best model, including steric, electrostatic, hydrogen bond donor, hydrogen bond acceptor, and hydrophobic fields, was found to depict a three-dimensional map with the local positive and negative effects of these chemotypes on the LasB inhibitory activities. Furthermore, molecular docking experiments yielded bioactive conformations of NAMdPs inside the LasB binding site. The series of NAMdPs adopted a similar orientation with respect to phosphoramidon within the LasB binding site (crystallographic reference), where the backbone atoms of NAMdPs are hydrogen-bonded to the LasB residues N112, A113, and R198, similarly to phosphoramidon. Our study also included a deep description of the residues involved in the protein–ligand interaction patterns for the whole set of NAMdPs, through the use of interaction fingerprints (IFPs). Full article
(This article belongs to the Special Issue New Avenues in Molecular Docking for Drug Design 2020)
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Review

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Open AccessReview
Computer-Aided Drug Design of β-Secretase, γ-Secretase and Anti-Tau Inhibitors for the Discovery of Novel Alzheimer’s Therapeutics
Int. J. Mol. Sci. 2020, 21(3), 703; https://doi.org/10.3390/ijms21030703 - 21 Jan 2020
Cited by 1
Abstract
Aging-associated neurodegenerative diseases, which are characterized by progressive neuronal death and synapses loss in human brain, are rapidly growing affecting millions of people globally. Alzheimer’s is the most common neurodegenerative disease and it can be caused by genetic and environmental risk factors. This [...] Read more.
Aging-associated neurodegenerative diseases, which are characterized by progressive neuronal death and synapses loss in human brain, are rapidly growing affecting millions of people globally. Alzheimer’s is the most common neurodegenerative disease and it can be caused by genetic and environmental risk factors. This review describes the amyloid-β and Tau hypotheses leading to amyloid plaques and neurofibrillary tangles, respectively which are the predominant pathways for the development of anti-Alzheimer’s small molecule inhibitors. The function and structure of the druggable targets of these two pathways including β-secretase, γ-secretase, and Tau are discussed in this review article. Computer-Aided Drug Design including computational structure-based design and ligand-based design have been employed successfully to develop inhibitors for biomolecular targets involved in Alzheimer’s. The application of computational molecular modeling for the discovery of small molecule inhibitors and modulators for β-secretase and γ-secretase is summarized. Examples of computational approaches employed for the development of anti-amyloid aggregation and anti-Tau phosphorylation, proteolysis and aggregation inhibitors are also reported. Full article
(This article belongs to the Special Issue New Avenues in Molecular Docking for Drug Design 2020)
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