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Special Issue "Protein–Ligand Interactions: Deciphering the Molecular Targets and the Mechanisms of Action of Drugs and Natural Compounds 2.0"

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

Deadline for manuscript submissions: closed (31 December 2020).

Special Issue Editor

Prof. Dr. Fabio Altieri
E-Mail Website
Guest Editor
Department of Biochemical Sciences “A. RossiFanelli”, La Sapienza University, 00185 Rome, Italy
Interests: oxidative stress; cellular biochemistry; signal transduction; protein–ligand interaction; bioactive compounds
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Drug discovery is a process where bioactive compounds are designed and screened either on the basis of specific molecular targets, by the identification of active ingredients from traditional medicine, or by serendipitous discovery. Both forward and reverse pharmacology approaches not only require a deep knowledge of the molecular processes involved in each pathological condition and disease but also the specific protein targets and the effects of drug binding on the conformation and activity of the proteins involved. The understanding of how drugs can modify and modulate specific cellular pathways and functions will be helpful during the process of drug development and clinical trials.

This Special Issue is the second volume of our previous Special Issue, “Protein–Ligand Interactions: Deciphering the Molecular Targets and the Mechanisms of Action of Drugs and Natural Compounds”. It will focus on recent studies aimed to investigate protein–ligand interactions with a special aim to elucidate molecular modes of action and the protein targets of drugs as well as natural compounds, and the cellular pathways involved. Protein–ligand interactions may affect both protein conformation and biological activity. However, for many bioactive compounds, knowledge is lacking of their molecular targets, their effects on protein structure, and how they can modulate different cellular pathways and functions. Studies providing such information are welcomed and will help to elucidate the molecular bases for many drugs activity and the development of new drugs.

Prof. Dr. Fabio Altieri
Guest Editor

Manuscript Submission Information

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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.

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Keywords

  • protein–ligand interaction
  • molecular mode of actions
  • target identification
  • drug discovery
  • bioactive agents

Published Papers (8 papers)

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Research

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Article
Biochemical and Computational Studies of the Interaction between a Glucosamine Derivative, NAPA, and the IKKα Kinase
Int. J. Mol. Sci. 2021, 22(4), 1643; https://doi.org/10.3390/ijms22041643 - 06 Feb 2021
Viewed by 748
Abstract
The glucosamine derivative 2-(N-Acetyl)-L-phenylalanylamido-2-deoxy-β-D-glucose (NAPA), was shown to inhibit the kinase activity of IKKα, one of the two catalytic subunits of IKK complex, decreasing the inflammatory status in osteoarthritis chondrocytes. In the present work we have investigated the inhibition [...] Read more.
The glucosamine derivative 2-(N-Acetyl)-L-phenylalanylamido-2-deoxy-β-D-glucose (NAPA), was shown to inhibit the kinase activity of IKKα, one of the two catalytic subunits of IKK complex, decreasing the inflammatory status in osteoarthritis chondrocytes. In the present work we have investigated the inhibition mechanism of IKKα by NAPA by combining computational simulations, in vitro assays and Mass Spectrometry (MS) technique. The kinase in vitro assay was conducted using a recombinant IKKα and IKKtide, a 20 amino acid peptide substrate derived from IkBα kinase protein and containing the serine residues Ser32 and Ser36. Phosphorylated peptide production was measured by Ultra Performance Liquid Chromatography coupled with Mass Spectrometry (UPLC-MS), and the atomic interaction between IKKα and NAPA has been studied by molecular docking and Molecular Dynamics (MD) approaches. Here we report that NAPA was able to inhibit the IKKα kinase activity with an IC50 of 0.5 mM, to decrease the Km value from 0.337 mM to 0.402 mM and the Vmax from 0.0257 mM·min1 to 0.0076 mM·min1. The computational analyses indicate the region between the KD, ULD and SDD domains of IKKα as the optimal binding site explored by NAPA. Biochemical data indicate that there is a non-significant difference between Km and Ki whereas there is a statistically significant difference between the two Vmax values. This evidence, combined with computational results, consistently indicates that the inhibition is non-competitive, and that the NAPA binding site is different than that of ATP or IKKtide. Full article
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Article
Predicting Potential SARS-COV-2 Drugs—In Depth Drug Database Screening Using Deep Neural Network Framework SSnet, Classical Virtual Screening and Docking
Int. J. Mol. Sci. 2021, 22(4), 1573; https://doi.org/10.3390/ijms22041573 - 04 Feb 2021
Cited by 6 | Viewed by 1338
Abstract
Severe Acute Respiratory Syndrome Corona Virus 2 has altered life on a global scale. A concerted effort from research labs around the world resulted in the identification of potential pharmaceutical treatments for CoVID-19 using existing drugs, as well as the discovery of multiple [...] Read more.
Severe Acute Respiratory Syndrome Corona Virus 2 has altered life on a global scale. A concerted effort from research labs around the world resulted in the identification of potential pharmaceutical treatments for CoVID-19 using existing drugs, as well as the discovery of multiple vaccines. During an urgent crisis, rapidly identifying potential new treatments requires global and cross-discipline cooperation, together with an enhanced open-access research model to distribute new ideas and leads. Herein, we introduce an application of a deep neural network based drug screening method, validating it using a docking algorithm on approved drugs for drug repurposing efforts, and extending the screen to a large library of 750,000 compounds for de novo drug discovery effort. The results of large library screens are incorporated into an open-access web interface to allow researchers from diverse fields to target molecules of interest. Our combined approach allows for both the identification of existing drugs that may be able to be repurposed and de novo design of ACE2-regulatory compounds. Through these efforts we demonstrate the utility of a new machine learning algorithm for drug discovery, SSnet, that can function as a tool to triage large molecular libraries to identify classes of molecules with possible efficacy. Full article
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Article
SSnet: A Deep Learning Approach for Protein-Ligand Interaction Prediction
Int. J. Mol. Sci. 2021, 22(3), 1392; https://doi.org/10.3390/ijms22031392 - 30 Jan 2021
Cited by 8 | Viewed by 1893
Abstract
Computational prediction of Protein-Ligand Interaction (PLI) is an important step in the modern drug discovery pipeline as it mitigates the cost, time, and resources required to screen novel therapeutics. Deep Neural Networks (DNN) have recently shown excellent performance in PLI prediction. However, the [...] Read more.
Computational prediction of Protein-Ligand Interaction (PLI) is an important step in the modern drug discovery pipeline as it mitigates the cost, time, and resources required to screen novel therapeutics. Deep Neural Networks (DNN) have recently shown excellent performance in PLI prediction. However, the performance is highly dependent on protein and ligand features utilized for the DNN model. Moreover, in current models, the deciphering of how protein features determine the underlying principles that govern PLI is not trivial. In this work, we developed a DNN framework named SSnet that utilizes secondary structure information of proteins extracted as the curvature and torsion of the protein backbone to predict PLI. We demonstrate the performance of SSnet by comparing against a variety of currently popular machine and non-Machine Learning (ML) models using various metrics. We visualize the intermediate layers of SSnet to show a potential latent space for proteins, in particular to extract structural elements in a protein that the model finds influential for ligand binding, which is one of the key features of SSnet. We observed in our study that SSnet learns information about locations in a protein where a ligand can bind, including binding sites, allosteric sites and cryptic sites, regardless of the conformation used. We further observed that SSnet is not biased to any specific molecular interaction and extracts the protein fold information critical for PLI prediction. Our work forms an important gateway to the general exploration of secondary structure-based Deep Learning (DL), which is not just confined to protein-ligand interactions, and as such will have a large impact on protein research, while being readily accessible for de novo drug designers as a standalone package. Full article
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Article
Investigation of Receptor Heteromers Using NanoBRET Ligand Binding
Int. J. Mol. Sci. 2021, 22(3), 1082; https://doi.org/10.3390/ijms22031082 - 22 Jan 2021
Cited by 2 | Viewed by 1340
Abstract
Receptor heteromerization is the formation of a complex involving at least two different receptors with pharmacology that is distinct from that exhibited by its constituent receptor units. Detection of these complexes and monitoring their pharmacology is crucial for understanding how receptors function. The [...] Read more.
Receptor heteromerization is the formation of a complex involving at least two different receptors with pharmacology that is distinct from that exhibited by its constituent receptor units. Detection of these complexes and monitoring their pharmacology is crucial for understanding how receptors function. The Receptor-Heteromer Investigation Technology (Receptor-HIT) utilizes ligand-dependent modulation of interactions between receptors and specific biomolecules for the detection and profiling of heteromer complexes. Previously, the interacting biomolecules used in Receptor-HIT assays have been intracellular proteins, however in this study we have for the first time used bioluminescence resonance energy transfer (BRET) with fluorescently-labeled ligands to investigate heteromerization of receptors on the cell surface. Using the Receptor-HIT ligand binding assay with NanoBRET, we have successfully investigated heteromers between the angiotensin II type 1 (AT1) receptor and the β2 adrenergic receptor (AT12AR heteromer), as well as between the AT1 and angiotensin II type 2 receptor (AT1-AT2 heteromer). Full article
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Article
Low Basicity as a Characteristic for Atypical Ligands of Serotonin Receptor 5-HT2
Int. J. Mol. Sci. 2021, 22(3), 1035; https://doi.org/10.3390/ijms22031035 - 21 Jan 2021
Cited by 2 | Viewed by 653
Abstract
Serotonin receptors are extensively examined by academic and industrial researchers, due to their vital roles, which they play in the organism and constituting therefore important drug targets. Up to very recently, it was assumed that the basic nitrogen in compound structure is a [...] Read more.
Serotonin receptors are extensively examined by academic and industrial researchers, due to their vital roles, which they play in the organism and constituting therefore important drug targets. Up to very recently, it was assumed that the basic nitrogen in compound structure is a necessary component to make it active within this receptor system. Such nitrogen interacts in its protonated form with the aspartic acid from the third transmembrane helix (D3x32) forming a hydrogen bond tightly fitting the ligand in the protein binding site. However, there are several recent studies that report strong serotonin receptor affinity also for compounds without a basic moiety in their structures. In the study, we carried out a comprehensive in silico analysis of the low-basicity phenomenon of the selected serotonin receptor ligands. We focused on the crystallized representatives of the proteins of 5-HT1B, 5-HT2A, 5-HT2B, and 5-HT2C receptors, and examined the problem both from the ligand- and structure-based perspectives. The study was performed for the native proteins, and for D3x32A mutants. The investigation resulted in the determination of nonstandard structural requirements for activity towards serotonin receptors, which can be used in the design of new nonbasic ligands. Full article
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Article
In Silico Finding of Key Interaction Mediated α3β4 and α7 Nicotinic Acetylcholine Receptor Ligand Selectivity of Quinuclidine-Triazole Chemotype
Int. J. Mol. Sci. 2020, 21(17), 6189; https://doi.org/10.3390/ijms21176189 - 27 Aug 2020
Viewed by 863
Abstract
The selective binding of six (S)-quinuclidine-triazoles and their (R)-enantiomers to nicotinic acetylcholine receptor (nAChR) subtypes α3β4 and α7, respectively, were analyzed by in silico docking to provide the insight into the molecular basis for the observed stereospecific subtype discrimination. [...] Read more.
The selective binding of six (S)-quinuclidine-triazoles and their (R)-enantiomers to nicotinic acetylcholine receptor (nAChR) subtypes α3β4 and α7, respectively, were analyzed by in silico docking to provide the insight into the molecular basis for the observed stereospecific subtype discrimination. Homology modeling followed by molecular docking and molecular dynamics (MD) simulations revealed that unique amino acid residues in the complementary subunits of the nAChR subtypes are involved in subtype-specific selectivity profiles. In the complementary β4-subunit of the α3β4 nAChR binding pocket, non-conserved AspB173 through a salt bridge was found to be the key determinant for the α3β4 selectivity of the quinuclidine-triazole chemotype, explaining the 47–327-fold affinity of the (S)-enantiomers as compared to their (R)-enantiomer counterparts. Regarding the α7 nAChR subtype, the amino acids promoting a however significantly lower preference for the (R)-enantiomers were the conserved TyrA93, TrpA149 and TrpB55 residues. The non-conserved amino acid residue in the complementary subunit of nAChR subtypes appeared to play a significant role for the nAChR subtype-selective binding, particularly at the heteropentameric subtype, whereas the conserved amino acid residues in both principal and complementary subunits are essential for ligand potency and efficacy. Full article
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Review

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Review
Paroxetine—Overview of the Molecular Mechanisms of Action
Int. J. Mol. Sci. 2021, 22(4), 1662; https://doi.org/10.3390/ijms22041662 - 07 Feb 2021
Cited by 2 | Viewed by 1201
Abstract
In the 21st century and especially during a pandemic, the diagnosis and treatment of depression is an essential part of the daily practice of many family doctors. It mainly affects patients in the age category 15–44 years, regardless of gender. Anxiety disorders are [...] Read more.
In the 21st century and especially during a pandemic, the diagnosis and treatment of depression is an essential part of the daily practice of many family doctors. It mainly affects patients in the age category 15–44 years, regardless of gender. Anxiety disorders are often diagnosed in children and adolescents. Social phobias can account for up to 13% of these diagnoses. Social anxiety manifests itself in fear of negative social assessment and humiliation, which disrupts the quality of social functioning. Treatment of the above-mentioned disorders is based on psychotherapy and pharmacotherapy. Serious side effects or mortality from antidepressant drug overdose are currently rare. Recent studies indicate that paroxetine (ATC code: N06AB), belonging to the selective serotonin reuptake inhibitors, has promising therapeutic effects and is used off-label in children and adolescents. The purpose of this review is to describe the interaction of paroxetine with several molecular targets in various points of view including the basic chemical and pharmaceutical properties. The central point of the review is focused on the pharmacodynamic analysis based on the molecular mechanism of binding paroxetine to various therapeutic targets. Full article
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Review
Nucleophosmin in Its Interaction with Ligands
Int. J. Mol. Sci. 2020, 21(14), 4885; https://doi.org/10.3390/ijms21144885 - 10 Jul 2020
Cited by 10 | Viewed by 1528
Abstract
Nucleophosmin (NPM1) is a mainly nucleolar protein that shuttles between nucleoli, nucleoplasm and cytoplasm to fulfill its many functions. It is a chaperone of both nucleic acids and proteins and plays a role in cell cycle control, centrosome duplication, ribosome maturation and export, [...] Read more.
Nucleophosmin (NPM1) is a mainly nucleolar protein that shuttles between nucleoli, nucleoplasm and cytoplasm to fulfill its many functions. It is a chaperone of both nucleic acids and proteins and plays a role in cell cycle control, centrosome duplication, ribosome maturation and export, as well as the cellular response to a variety of stress stimuli. NPM1 is a hub protein in nucleoli where it contributes to nucleolar organization through heterotypic and homotypic interactions. Furthermore, several alterations, including overexpression, chromosomal translocations and mutations are present in solid and hematological cancers. Recently, novel germline mutations that cause dyskeratosis congenita have also been described. This review focuses on NPM1 interactions and inhibition. Indeed, the list of NPM1 binding partners is ever-growing and, in recent years, many studies contributed to clarifying the structural basis for NPM1 recognition of both nucleic acids and several proteins. Intriguingly, a number of natural and synthetic ligands that interfere with NPM1 interactions have also been reported. The possible role of NPM1 inhibitors in the treatment of multiple cancers and other pathologies is emerging as a new therapeutic strategy. Full article
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