International Journal of Molecular Sciences

Research

12 pages, 3176 KiB

Open AccessArticle

1,2-Dibenzoylhydrazine as a Multi-Inhibitor Compound: A Morphological and Docking Study

by Vincenzo Patamia, Giuseppe Floresta, Chiara Zagni, Venerando Pistarà, Francesco Punzo and Antonio Rescifina

Int. J. Mol. Sci. 2023, 24(2), 1425; https://doi.org/10.3390/ijms24021425 - 11 Jan 2023

Cited by 7 | Viewed by 1426

Abstract

In the framework of the multitarget inhibitor study, we report an in silico analysis of 1,2-dibenzoylhydrazine (DBH) with respect to three essential receptors such as the ecdysone receptor (EcR), urease, and HIV-integrase. Starting from a crystallographic structural study of accidentally harvested crystals of [...] Read more.

In the framework of the multitarget inhibitor study, we report an in silico analysis of 1,2-dibenzoylhydrazine (DBH) with respect to three essential receptors such as the ecdysone receptor (EcR), urease, and HIV-integrase. Starting from a crystallographic structural study of accidentally harvested crystals of this compound, we performed docking studies to evaluate the inhibitory capacity of DBH toward three selected targets. A crystal morphology prediction was then performed. The results of our molecular modeling calculations indicate that DBH is an excellent candidate as a ligand to inhibit the activity of EcR receptors and urease. Docking studies also revealed the activity of DBH on the HIV integrase receptor, providing an excellent starting point for developing novel inhibitors using this molecule as a starting lead compound. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Informatics in Italy)

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17 pages, 5267 KiB

Open AccessArticle

Alvascience: A New Software Suite for the QSAR Workflow Applied to the Blood–Brain Barrier Permeability

by Andrea Mauri and Matteo Bertola

Int. J. Mol. Sci. 2022, 23(21), 12882; https://doi.org/10.3390/ijms232112882 - 25 Oct 2022

Cited by 18 | Viewed by 4847

Abstract

Quantitative structure–activity relationship (QSAR) and quantitative structure–property relationship (QSPR) are established techniques to relate endpoints to molecular features. We present the Alvascience software suite that takes care of the whole QSAR/QSPR workflow necessary to use models to predict endpoints for untested molecules. The [...] Read more.

Quantitative structure–activity relationship (QSAR) and quantitative structure–property relationship (QSPR) are established techniques to relate endpoints to molecular features. We present the Alvascience software suite that takes care of the whole QSAR/QSPR workflow necessary to use models to predict endpoints for untested molecules. The first step, data curation, is covered by alvaMolecule. Features such as molecular descriptors and fingerprints are generated by using alvaDesc. Models are built and validated with alvaModel. The models can then be deployed and used on new molecules by using alvaRunner. We use these software tools on a real case scenario to predict the blood–brain barrier (BBB) permeability. The resulting predictive models have accuracy equal or greater than 0.8. The models are bundled in an alvaRunner project available on the Alvascience website. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Informatics in Italy)

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21 pages, 6659 KiB

Open AccessArticle

Exploring Ligand Binding Domain Dynamics in the NRs Superfamily

by Giulia D’Arrigo, Ida Autiero, Eleonora Gianquinto, Lydia Siragusa, Massimo Baroni, Gabriele Cruciani and Francesca Spyrakis

Int. J. Mol. Sci. 2022, 23(15), 8732; https://doi.org/10.3390/ijms23158732 - 5 Aug 2022

Cited by 3 | Viewed by 2103

Abstract

Nuclear receptors (NRs) are transcription factors that play an important role in multiple diseases, such as cancer, inflammation, and metabolic disorders. They share a common structural organization composed of five domains, of which the ligand-binding domain (LBD) can adopt different conformations in response [...] Read more.

Nuclear receptors (NRs) are transcription factors that play an important role in multiple diseases, such as cancer, inflammation, and metabolic disorders. They share a common structural organization composed of five domains, of which the ligand-binding domain (LBD) can adopt different conformations in response to substrate, agonist, and antagonist binding, leading to distinct transcription effects. A key feature of NRs is, indeed, their intrinsic dynamics that make them a challenging target in drug discovery. This work aims to provide a meaningful investigation of NR structural variability to outline a dynamic profile for each of them. To do that, we propose a methodology based on the computation and comparison of protein cavities among the crystallographic structures of NR LBDs. First, pockets were detected with the FLAPsite algorithm and then an “all against all” approach was applied by comparing each pair of pockets within the same sub-family on the basis of their similarity score. The analysis concerned all the detectable cavities in NRs, with particular attention paid to the active site pockets. This approach can guide the investigation of NR intrinsic dynamics, the selection of reference structures to be used in drug design and the easy identification of alternative binding sites. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Informatics in Italy)

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14 pages, 1102 KiB

Open AccessArticle

Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel

by Silvia Gervasoni, Carmine Talarico, Candida Manelfi, Alessandro Pedretti, Giulio Vistoli and Andrea R. Beccari

Int. J. Mol. Sci. 2022, 23(14), 7558; https://doi.org/10.3390/ijms23147558 - 8 Jul 2022

Cited by 1 | Viewed by 1511

Abstract

(1) Background: Virtual screening campaigns require target structures in which the pockets are properly arranged for binding. Without these, MD simulations can be used to relax the available target structures, optimizing the fine architecture of their binding sites. Among the generated frames, the [...] Read more.

(1) Background: Virtual screening campaigns require target structures in which the pockets are properly arranged for binding. Without these, MD simulations can be used to relax the available target structures, optimizing the fine architecture of their binding sites. Among the generated frames, the best structures can be selected based on available experimental data. Without experimental templates, the MD trajectories can be filtered by energy-based criteria or sampled by systematic analyses. (2) Methods: A blind and methodical analysis was performed on the already reported MD run of the hTRPM8 tetrameric structures; a total of 50 frames underwent docking simulations by using a set of 1000 ligands including 20 known hTRPM8 modulators. Docking runs were performed by LiGen program and involved the frames as they are and after optimization by SCRWL4.0. For each frame, all four monomers were considered. Predictive models were developed by the EFO algorithm based on the sole primary LiGen scores. (3) Results: On average, the MD simulation progressively enhances the performance of the extracted frames, and the optimized structures perform better than the non-optimized frames (EF1% mean: 21.38 vs. 23.29). There is an overall correlation between performances and volumes of the explored pockets and the combination of the best performing frames allows to develop highly performing consensus models (EF1% = 49.83). (4) Conclusions: The systematic sampling of the entire MD run provides performances roughly comparable with those previously reached by using rationally selected frames. The proposed strategy appears to be helpful when the lack of experimental data does not allow an easy selection of the optimal structures for docking simulations. Overall, the reported docking results confirm the relevance of simulating all the monomers of an oligomer structure and emphasize the efficacy of the SCRWL4.0 method to optimize the protein structures for docking calculations. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Informatics in Italy)

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15 pages, 889 KiB

Open AccessArticle

Monte Carlo Models for Sub-Chronic Repeated-Dose Toxicity: Systemic and Organ-Specific Toxicity

by Gianluca Selvestrel, Giovanna J. Lavado, Alla P. Toropova, Andrey A. Toropov, Domenico Gadaleta, Marco Marzo, Diego Baderna and Emilio Benfenati

Int. J. Mol. Sci. 2022, 23(12), 6615; https://doi.org/10.3390/ijms23126615 - 14 Jun 2022

Cited by 6 | Viewed by 1654

Abstract

The risk-characterization of chemicals requires the determination of repeated-dose toxicity (RDT). This depends on two main outcomes: the no-observed-adverse-effect level (NOAEL) and the lowest-observed-adverse-effect level (LOAEL). These endpoints are fundamental requirements in several regulatory frameworks, such as the Registration, Evaluation, Authorization and Restriction [...] Read more.

The risk-characterization of chemicals requires the determination of repeated-dose toxicity (RDT). This depends on two main outcomes: the no-observed-adverse-effect level (NOAEL) and the lowest-observed-adverse-effect level (LOAEL). These endpoints are fundamental requirements in several regulatory frameworks, such as the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) and the European Regulation of 1223/2009 on cosmetics. The RDT results for the safety evaluation of chemicals are undeniably important; however, the in vivo tests are time-consuming and very expensive. The in silico models can provide useful input to investigate sub-chronic RDT. Considering the complexity of these endpoints, involving variable experimental designs, this non-testing approach is challenging and attractive. Here, we built eight in silico models for the NOAEL and LOAEL predictions, focusing on systemic and organ-specific toxicity, looking into the effects on the liver, kidney and brain. Starting with the NOAEL and LOAEL data for oral sub-chronic toxicity in rats, retrieved from public databases, we developed and validated eight quantitative structure-activity relationship (QSAR) models based on the optimal descriptors calculated by the Monte Carlo method, using the CORAL software. The results obtained with these models represent a good achievement, to exploit them in a safety assessment, considering the importance of organ-related toxicity. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Informatics in Italy)

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8 pages, 1644 KiB

Open AccessCommunication

PLATO: A Predictive Drug Discovery Web Platform for Efficient Target Fishing and Bioactivity Profiling of Small Molecules

by Fulvio Ciriaco, Nicola Gambacorta, Daniela Trisciuzzi and Orazio Nicolotti

Int. J. Mol. Sci. 2022, 23(9), 5245; https://doi.org/10.3390/ijms23095245 - 8 May 2022

Cited by 16 | Viewed by 2505

Abstract

PLATO (Polypharmacology pLATform predictiOn) is an easy-to-use drug discovery web platform, which has been designed with a two-fold objective: to fish putative protein drug targets and to compute bioactivity values of small molecules. Predictions are based on the similarity principle, through a reverse [...] Read more.

PLATO (Polypharmacology pLATform predictiOn) is an easy-to-use drug discovery web platform, which has been designed with a two-fold objective: to fish putative protein drug targets and to compute bioactivity values of small molecules. Predictions are based on the similarity principle, through a reverse ligand-based screening, based on a collection of 632,119 compounds known to be experimentally active on 6004 protein targets. An efficient backend implementation allows to speed-up the process that returns results for query in less than 20 s. The graphical user interface is intuitive to give practitioners easy input and transparent output, which is available as a standard report in portable document format. PLATO has been validated on thousands of external data, with performances better than those of other parallel approaches. PLATO is available free of charge (http://plato.uniba.it/ accessed on 13 April 2022). Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Informatics in Italy)

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13 pages, 5201 KiB

Open AccessArticle

Focused Design of Novel Cyclic Peptides Endowed with GABARAP-Inhibiting Activity

by Enrico Mario Alessandro Fassi, Mariangela Garofalo, Jacopo Sgrignani, Michele Dei Cas, Matteo Mori, Gabriella Roda, Andrea Cavalli and Giovanni Grazioso

Int. J. Mol. Sci. 2022, 23(9), 5070; https://doi.org/10.3390/ijms23095070 - 3 May 2022

Cited by 3 | Viewed by 1833

Abstract

(1) Background: Disfunctions in autophagy machinery have been identified in various conditions, including neurodegenerative diseases, cancer, and inflammation. Among mammalian autophagy proteins, the Atg8 family member GABARAP has been shown to be greatly involved in the autophagy process of prostate cancer cells, supporting [...] Read more.

(1) Background: Disfunctions in autophagy machinery have been identified in various conditions, including neurodegenerative diseases, cancer, and inflammation. Among mammalian autophagy proteins, the Atg8 family member GABARAP has been shown to be greatly involved in the autophagy process of prostate cancer cells, supporting the idea that GABARAP inhibitors could be valuable tools to fight the progression of tumors. (2) Methods: In this paper, starting from the X-ray crystal structure of GABARAP in a complex with an AnkirinB-LIR domain, we identify two new peptides by applying in silico drug design techniques. The two ligands are synthesized, biophysically assayed, and biologically evaluated to ascertain their potential anticancer profile. (3) Results: Two cyclic peptides (WC8 and WC10) displayed promising biological activity, high conformational stability (due to the presence of disulfide bridges), and K_d values in the low micromolar range. The anticancer assays, performed on PC-3 cells, proved that both peptides exhibit antiproliferative effects comparable to those of peptide K1, a known GABARAP inhibitor. (4) Conclusions: WC8 and WC10 can be considered new GABARAP inhibitors to be employed as pharmacological tools or even templates for the rational design of new small molecules. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Informatics in Italy)

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Graphical abstract

16 pages, 2297 KiB

Open AccessArticle

Critical Assessment of a Structure-Based Screening Campaign for IDO1 Inhibitors: Tips and Pitfalls

by Andrea Mammoli, Elisa Bianconi, Luana Ruta, Alessandra Riccio, Carlo Bigiotti, Maria Souma, Andrea Carotti, Sofia Rossini, Chiara Suvieri, Maria Teresa Pallotta, Ursula Grohmann, Emidio Camaioni and Antonio Macchiarulo

Int. J. Mol. Sci. 2022, 23(7), 3981; https://doi.org/10.3390/ijms23073981 - 2 Apr 2022

Cited by 6 | Viewed by 2566

Abstract

Over the last two decades, indoleamine 2,3-dioxygenase 1 (IDO1) has attracted wide interest as a key player in immune regulation, fostering the design and development of small molecule inhibitors to restore immune response in tumor immunity. In this framework, biochemical, structural, and pharmacological [...] Read more.

Over the last two decades, indoleamine 2,3-dioxygenase 1 (IDO1) has attracted wide interest as a key player in immune regulation, fostering the design and development of small molecule inhibitors to restore immune response in tumor immunity. In this framework, biochemical, structural, and pharmacological studies have unveiled peculiar structural plasticity of IDO1, with different conformations and functional states that are coupled to fine regulation of its catalytic activity and non-enzymic functions. The large plasticity of IDO1 may affect its ligand recognition process, generating bias in structure-based drug design campaigns. In this work, we report a screening campaign of a fragment library of compounds, grounding on the use of three distinct conformations of IDO1 that recapitulate its structural plasticity to some extent. Results are instrumental to discuss tips and pitfalls that, due to the large plasticity of the enzyme, may influence the identification of novel and differentiated chemical scaffolds of IDO1 ligands in structure-based screening campaigns. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Informatics in Italy)

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