Docking, Interaction Fingerprint, and Three-Dimensional Quantitative Structure-Activity Relationship (3D-QSAR) of Sigma1 Receptor Ligands, Analogs of the Neuroprotective Agent RC-33

Novel S1R agonists counteracting NMDA excitotoxicity and oxidative stress: A step forward in the discovery of neuroprotective agents

Sigma-1 receptor (S1R) has been considered a promising therapeutic target for several neurodegenerative diseases and S1R agonists have shown neuroprotective activity against glutamate excitotoxicity and oxidative stress. Starting from a previously identified low nanomolar S1R agonist, in this work we prepared and tested novel benzylpiperidine/benzylpiperazine-based compounds designed by applying a ring opening strategy. Among them, 4-benzyl-1-(2-phenoxyethyl)piperidine 6b (S1R Ki = 0.93 nM) and 4-benzyl-1-(3-phenoxypropyl)piperidine 8b (S1R Ki = 1.1 nM) emerged as high affinity S1R ligands and showed selectivity over S2R and N-methyl-d-aspartate receptor (NMDAR). Candidate compounds behaved as potent S1R agonists being able to enhance the neurite outgrowth induced by nerve growth factor (NGF) in PC12 cell lines. In SH-SY5Y neuroblastoma cell lines they exhibited a neuroprotective effect against rotenone- and NMDA-mediated toxic insults. The neuroprotective activity of 6b and 8b was reverted by co-treatment with an S1R antagonist, PB212. Compounds 6b and 8b were tested for cytotoxicity in-vitro against three human cancer cell lines (A549, LoVo and Panc-1) and in-vivo zebrafish model, resulting in a good efficacy/safety profile, comparable or superior to the reference drug memantine. Overall, these results encourage further preclinical investigations of 6b and 8b on in-vivo models of neurodegenerative diseases.

Dammarane triterpenes targeting α-synuclein: biological activity and evaluation of binding sites by molecular docking

Parkinson's disease (PD) is a neurodegenerative disorder that affects adult people whose treatment is palliative. Thus, we decided to test three dammarane triterpenes 1, 1a, 1b, and we determined that 1 and 1a inhibit β-aggregation through thioflavine T rather than 1b. Since compound 1 was most active, we determined the interaction between α-synuclein and 1 at 50 µM (Kd) through microscale thermophoresis. Also, we observed differences in height and diameter of aggregates, and α-synuclein remains unfolded in the presence of 1. Also, aggregates treated with 1 do not provoke neurites' retraction in N2a cells previously induced by retinoic acid. Finally, we studied the potential sites of interaction between 1 with α-synuclein fibrils using molecular modelling. Docking experiments suggest that 1 preferably interact with the site 2 of α-synuclein through hydrogen bonds with residues Y39 and T44.

Bitopic Sigma 1 Receptor Modulators to Shed Light on Molecular Mechanisms Underpinning Ligand Binding and Receptor Oligomerization

The sigma 1 receptor (S1R) is an enigmatic ligand-operated chaperone involved in many important biological processes, and its functions are not fully understood yet. Herein, we developed a novel series of bitopic S1R ligands as versatile tools to investigate binding processes, allosteric modulation, and the oligomerization mechanism. These molecules have been prepared in the enantiopure form and subjected to a preliminary biological evaluation, while in silico investigations helped to rationalize the results. Compound 7 emerged as the first bitopic S1R ligand endowed with low nanomolar affinity (Ki = 2.6 nM) reported thus far. Computational analyses suggested that 7 may stabilize the open conformation of the S1R by simultaneously binding the occluded primary binding site and a peripheral site on the cytosol-exposed surface. These findings pave the way to new S1R ligands with enhanced activity and/or selectivity, which could also be used as probes for the identification of a potential allosteric site.

In Vitro Confirmation of Siramesine as a Novel Antifungal Agent with In Silico Lead Proposals of Structurally Related Antifungals

The limited number of medicinal products available to treat of fungal infections makes control of fungal pathogens problematic, especially since the number of fungal resistance incidents increases. Given the high costs and slow development of new antifungal treatment options, repurposing of already known compounds is one of the proposed strategies. The objective of this study was to perform in vitro experimental tests of already identified lead compounds in our previous in silico drug repurposing study, which had been conducted on the known Drugbank database using a seven-step procedure which includes machine learning and molecular docking. This study identifies siramesine as a novel antifungal agent. This novel indication was confirmed through in vitro testing using several yeast species and one mold. The results showed susceptibility of Candida species to siramesine with MIC at concentration 12.5 µg/mL, whereas other candidates had no antifungal activity. Siramesine was also effective against in vitro biofilm formation and already formed biofilm was reduced following 24 h treatment with a MBEC range of 50-62.5 µg/mL. Siramesine is involved in modulation of ergosterol biosynthesis in vitro, which indicates it is a potential target for its antifungal activity. This implicates the possibility of siramesine repurposing, especially since there are already published data about nontoxicity. Following our in vitro results, we provide additional in depth in silico analysis of siramesine and compounds structurally similar to siramesine, providing an extended lead set for further preclinical and clinical investigation, which is needed to clearly define molecular targets and to elucidate its in vivo effectiveness as well.

Involvement of Chaperone Sigma1R in the Anxiolytic Effect of Fabomotizole

Sigma-1 receptor (chaperone Sigma1R) is an intracellular protein with chaperone functions, which is expressed in various organs, including the brain. Sigma1R participates in the regulation of physiological mechanisms of anxiety (Su, T. P. et al., 2016) and reactions to emotional stress (Hayashi, T., 2015). In 2006, fabomotizole (ethoxy-2-[2-(morpholino)-ethylthio]benzimidazole dihydrochloride) was registered in Russia as an anxiolytic (Seredenin S. and Voronin M., 2009). The molecular targets of fabomotizole are Sigma1R, NRH: quinone reductase 2 (NQO2), and monoamine oxidase A (MAO-A) (Seredenin S. and Voronin M., 2009). The current study aimed to clarify the dependence of fabomotizole anxiolytic action on its interaction with Sigma1R and perform a docking analysis of fabomotizole interaction with Sigma1R. An elevated plus maze (EPM) test revealed that the anxiolytic-like effect of fabomotizole (2.5 mg/kg i.p.) administered to male BALB/c mice 30 min prior EPM exposition was blocked by Sigma1R antagonists BD-1047 (1.0 mg/kg i.p.) and NE-100 (1.0 mg/kg i.p.) pretreatment. Results of initial in silico study showed that fabomotizole locates in the active center of Sigma1R, reproducing the interactions with the site's amino acids common for established Sigma1R ligands, with the ΔGbind value closer to that of agonist (+)-pentazocine in the 6DK1 binding site.

The latest automated docking technologies for novel drug discovery

INTRODUCTION

Molecular docking has been consolidated as one of the most important methods in the molecular modeling field. It has been recognized as a prominent tool in the study of protein-ligand complexes, to describe intermolecular interactions, to accurately predict poses of multiple ligands, to discover novel promising bioactive compounds. Molecular docking methods have evolved in terms of their accuracy and reliability; but there are pending issues to solve for improving the connection between the docking results and the experimental evidence.

AREAS COVERED

In this article, the author reviews very recent innovative molecular docking applications with special emphasis on reverse docking, treatment of protein flexibility, the use of experimental data to guide the selection of docking poses, the application of Quantum mechanics(QM) in docking, and covalent docking.

EXPERT OPINION

There are several issues being worked on in recent years that will lead to important breakthroughs in molecular docking methods in the near future These developments are related to more efficient exploration of large datasets and receptor conformations, advances in electronic description, and the use of structural information for guiding the selection of results.

Identification of the naphthoquinone derivative inhibitors binding site in heat shock protein 90: an induced-fit docking, molecular dynamics and 3D-QSAR study

The combination of molecular modeling methods to identify the putative binding site of inhibitors constitutes an important tool in drug discovery. In this work, we used these analyses to understand the potent inhibitory effect of naphthoquinone derivatives on heat shock protein 90 (Hsp90), one of the proteins involved in many types of cancer. Molecular docking results indicated that some favorable interactions of key amino acid residues at the binding site of Hsp90 with these quinones would be responsible for the inhibition of Hsp90 activity. Molecular docking and molecular dynamics simulation were carried out to further understand the binding modes and the interactions between the protein and these inhibitors. The main residues of the internal cavity were Val136, Phe138, Tyr139, Val150, Trp162 and Val186. The high concordance between the docking results and 3D-QSAR contour maps gives us helpful information about the environment of the binding site. Our results provide the bases for a rational modification of new molecules based in quinone scaffold, in order to design more potent Hsp90 inhibitors, which would exhibit highly potent antitumor activity.Communicated by Ramaswamy H. Sarma.

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

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

Considerations for Docking of Selective Angiotensin-Converting Enzyme Inhibitors

The angiotensin-converting enzyme (ACE) is a two-domain dipeptidylcarboxypeptidase, which has a direct involvement in the control of blood pressure by performing the hydrolysis of angiotensin I to produce angiotensin II. At the same time, ACE hydrolyzes other substrates such as the vasodilator peptide bradykinin and the anti-inflammatory peptide N-acetyl-SDKP. In this sense, ACE inhibitors are bioactive substances with potential use as medicinal products for treatment or prevention of hypertension, heart failures, myocardial infarction, and other important diseases. This review examined the most recent literature reporting ACE inhibitors with the help of molecular modeling. The examples exposed here demonstrate that molecular modeling methods, including docking, molecular dynamics (MD) simulations, quantitative structure-activity relationship (QSAR), etc, are essential for a complete structural picture of the mode of action of ACE inhibitors, where molecular docking has a key role. Examples show that too many works identified ACE inhibitory activities of natural peptides and peptides obtained from hydrolysates. In addition, other works report non-peptide compounds extracted from natural sources and synthetic compounds. In all these cases, molecular docking was used to provide explanation of the chemical interactions between inhibitors and the ACE binding sites. For docking applications, most of the examples exposed here do not consider that: (i) ACE has two domains (nACE and cACE) with available X-ray structures, which are relevant for the design of selective inhibitors, and (ii) nACE and cACE binding sites have large dimensions, which leads to non-reliable solutions during docking calculations. In support of the solution of these problems, the structural information found in Protein Data Bank (PDB) was used to perform an interaction fingerprints (IFPs) analysis applied on both nACE and cACE domains. This analysis provides plots that identify the chemical interactions between ligands and both ACE binding sites, which can be used to guide docking experiments in the search of selective natural components or novel drugs. In addition, the use of hydrogen bond constraints in the S₂ and S₂′ subsites of nACE and cACE are suggested to guarantee that docking solutions are reliable.

Structural Requirements of N-alpha-Mercaptoacetyl Dipeptide (NAMdP) Inhibitors of Pseudomonas Aeruginosa Virulence Factor LasB: 3D-QSAR, Molecular Docking, and Interaction Fingerprint Studies

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).