Molecular Modeling Research Articles

Unveiling Resistance and Virulence Mechanisms under Darwinian Positive Selection for Novel Drug Discovery for Gardnerella vaginalis

Gardnerella vaginalis is a Gram-variable bacillus capable of causing bacterial vaginosis, a condition prevalent in reproductive-age women, this bacterium is present in almost 100% of cases and is also considered a gateway to various sexually transmitted infections. This organism exhibits high pathogenicity linked to virulence and resistance genes acquired throughout evolution, showcasing elevated resistance to a broad spectrum of drug classes. This study conducted comparative genomic analyses to identify these genes and correlate their presence with positive Darwinian selection. Additionally, new drug targets were selected through docking and molecular modeling, guided by the heightened antimicrobial resistance exhibited by this microbial species. The available genomes of G. vaginalis were analyzed, and the orthologous genes were delineated and positively selected, whereby 29 groups were found. Of these genes, one of great importance was predicted, Mef(A), which is related to resistance to the macrolide group of antibiotics, which are one of the main choices for the treatment of sexually transmitted infections. Additionally, two potential protein candidates were selected as drug targets. These proteins were linked with a natural compound each and are considered good potential drug targets. The analyses in this study contribute to analyzing the evolution of the species and how resistance genes are related to their permanence as a potential pathogen.

Exploration of cytotoxicity of iodoquinazoline derivatives as inhibitors of both VEGFR-2 and EGFRT790M: Molecular docking, ADMET, design, and syntheses.

Novel inhibitors of epidermal growth factor receptor (EGFR)T790M/vascular endothelial growth factor receptor-2 (VEGFR-2) were synthesized based on the iodoquinazoline scaffold linked to different heteroaromatic, aromatic, and/or aliphatic moieties. The novel derivatives were in vitro examined for anticancer activities against A549, HCT116, michigan cancer foundation-7 (MCF-7), and HepG2 cells. Molecular modeling was applied to discover their orientation of binding with both VEGFR-2 and EGFR active sites. Compounds 8d, 8c, 6d, and 6c indicated the highest cytotoxicity with IC50 = 6.00, 6.90, 6.12 and 6.24 µM, 7.05, 7.35, 6.80, and 6.80 µM, 5.75, 7.50, 6.90, and 6.95 µM, and 6.55, 7.88, 7.44, and 7.10 µM against the A549, HepG2, HCT116, and MCF-7 cell lines, correspondingly. The cytotoxicity against normal VERO (normal african green monkey kidney cells) of the extremely active eight compounds 6a-d and 8a-d was evaluated. Our compounds exhibited low toxicity concerning normal VERO cells with IC50 = 45.66-51.83 μM. Furthermore, inhibition assays for both the EGFRT790M and VEGFR-2 enzymes were done for all compounds. Remarkable inhibition of EGFRT790M activity was achieved with compounds 6d, 8d, 6c, and 8c at IC50 = 0.35, 0.42, 0.48, and 0.50 µM correspondingly. Moreover, remarkable inhibition of VEGFR-2 activity was achieved with compounds 8d, 8c, 6d, and 6c at IC50 = 0.92, 0.95, 1.00, and 1.20 µM correspondingly. As planned, derivatives 6d, 8d, 6c, and 8c presented exceptional inhibition of both EGFRT790M/VEGFR-2 activities. Finally, in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) studies were made for the highly active four compounds 6c, 6d, 8c, and 8d in comparison with erlotinib and sorafenib as reference standards.

Clinical and genetic spectrum of Ataxia Telangiectasia Tunisian patients: Bioinformatic analysis unveil mechanisms of ATM variants pathogenicity

Ataxia Telangiectasia (AT) is a rare multisystemic neurodegenerative disease caused by biallelic mutations in the ATM gene. Few clinical studies on AT disease have been conducted in Tunisia, however, the mutational landscape is still undefined. Our aim is to determine the clinical and genetic spectrum of AT Tunisian patients and to explore the potential underlying mechanism of variant pathogenicity.Sanger sequencing was performed for nine AT patients. A comprehensive computational analysis was conducted to evaluate the possible pathogenic effect of ATM identified variants. Genetic screening of ATM gene has identified nine different variants from which six have not been previously reported. In silico analysis have predicted a pathogenic effect of identified mutations. This was corroborated by a structural bioinformatics study based on molecular modeling and docking for novel missense mutations. Our findings suggest a profound impact of identified mutations not only on the ATM protein stability, but also on the ATM-ligand interactions.Our study characterizes the mutational landscape of AT Tunisian patients which will allow to set up genetic counseling and prenatal diagnosis for families at risk and expand the spectrum of ATM variants worldwide. Furthermore, understanding the mechanism that underpin variant pathogenicity could provide further insights into disease pathogenesis.

Combining Machine Learning, Molecular Dynamics, and Free Energy Analysis for (5HT)-2A Receptor Modulator Classification

The 5-Hydroxytryptamine (5HT)-2A receptor, a key target in psychoactive drug development, presents significant challenges in the design of selective compounds. Here, we describe the construction, evaluation and validation of two machine learning (ML) models for the classification of bioactivity mechanisms against the (5HT)-2A receptor. Employing neural networks and XGBoost models, we achieved an overall accuracy of around 87%, which was further enhanced through molecular modelling (MM) (e.g. molecular dynamics simulations) and binding free energy analysis. This ML-MM integration provided insights into the mechanisms of direct modulators and prodrugs. A significant outcome of the current study is the development of a 'binding free energy fingerprint' specific to (5HT)-2A modulators, offering a novel metric for evaluating drug efficacy against this target. Our study demonstrates the prospective of employing a successful workflow combining AI with structural biology, offering a powerful tool for advancing psychoactive drug discovery.

Design, synthesis, molecular modeling, in vitro evaluation of novel piperidine-containing hydrazone derivatives as cholinesterase inhibitors.

In an effort to develop new and effective therapeutic agents for Alzheimer's disease, a series of hydrazone derivatives bearing piperidine rings have been designed and synthesized. The chemical structures of the compounds were characterized by various spectroscopic techniques. In vitro antioxidant and cholinesterase activities of the compounds were evaluated. Among the compounds, N12 exhibited the most antioxidant activity in all methods (CUPRAC, FRAP, DPPH, ABTS). In vitro acetylcholinesterase (AChE) activity results of the compounds showed good IC50 values between 14.124 ± 0.084 and 49.680 ± 0.110 µM were obtained (IC50 = 38.842 ± 0.053 µM for Donepezil). Among the compounds, N7 and N6 are much more effective derivatives than the standard compound donepezil with IC50 values of 14.124 ± 0.084 and 17.968 ± 0.072 µM, respectively. In vitro, butyrylcholinesterase (BChE) inhibition values of the compounds were between 13.505 ± 0.025 and 52.230 ± 0.027 μm. Among the compounds, N6 has the highest BChE inhibition with an IC50 value of 13.505 μm in the series. The cytotoxicity and AChE inhibitory activity of the compounds on SH-SY5Y cell lines were also evaluated. Kinetic studies were also performed to determine the behavior of the compounds as competitive or noncompetitive inhibitors. The binding modes of N6, which was determined to be highly effective according to in vitro analyses, with AChE and BChE were investigated using molecular docking studies, and the stability of the complexes was determined by molecular dynamics simulations. These findings indicated that AChE and BChE enzymes maintained their overall structural stability and compactness during interactions with compound N6.

Investigating flavonoids derived from Tribulus terrestris L. as prospective candidates for Alzheimer's disease treatment: Molecular docking modeling of their interactions with physiological system receptors

Alzheimer's disease (AD) stands as the primary cause of dementia, marked by its neurodegenerative essence, which results in cognitive impairment associated with memory and a decline in functionality. Currently there is no drug which can permanently cure the nervous lesions as well as completely eradicate this pathogenesis. The aim of this research is to examine the acetylcholinesterase activity of flavonoids identified in Tribulus terrestris L. (Tt) by predicting ligand-receptor binding. The research process begins with the preparation of protein and ligand structures. Subsequently, docking is performed, interaction between protein-ligands is then analyzed and visualized. Four phytoconstituents of Tt were chosen, and molecular docking simulations revealed that all four compounds exhibited good binding affinities. Based on the predicted ADMET values using the Lipinski rule, compounds with potentially good activity were identified. The results suggest that these compounds may exhibit anti-acetylcholinesterase activity.

Potential (co-)contamination of dairy milk with AFM1 and MC-LR and their synergistic interaction in inducing mitochondrial dysfunction in HepG2 cells

Several toxic metabolites, such as aflatoxin M1 (AFM1), are known to contaminate dairy milk. However, as mentioned in an external EFSA report, there is a knowledge gap regarding the carry-over of certain emerging toxins such as microcystin-LR (MC-LR). Therefore, this work aimed to develop an LC-MS/MS method for MC-LR quantification in dairy milk. Also, the method included AFM1 as a common fungal metabolite and applied to analyze 113 dairy milk samples collected directly after the end of the summer peak. Both toxins were below their LODs, keeping the question on MC-LR carry-over still unanswered. Moreover, an in silico analysis, using a 3D molecular modeling was performed, pointing to a possible interaction between MC-LR and milk proteins, especially β-lactoglobulin.Since AFM1 and MC-LR are hepatotoxic, their interaction in inducing mitochondrial dysfunction in HepG2 cells was investigated at low (subcytotoxic) concentrations. Live cell imaging-based assays showed an inhibition in cell viability, without involvement of caspase-3/7, and a hyperpolarization in the mitochondrial membrane potential after the exposure to a mixture of 100 ng mL-1 AFM1 and 1000 ng mL-1 MC-LR for 48h. Extracellular flux analysis revealed inhibitions of several key parameters of mitochondrial function (basal respiration, ATP-linked respiration, and spare respiratory capacity).

A Visual Environment for Data Driven Protein Modeling and Validation.

In structural biology, validation and verification of new atomic models are crucial and necessary steps which limit the production of reliable molecular models for publications and databases. An atomic model is the result of meticulous modeling and matching and is evaluated using a variety of metrics that provide clues to improve and refine the model so it fits our understanding of molecules and physical constraints. In cryo electron microscopy (cryo-EM) the validation is also part of an iterative modeling process in which there is a need to judge the quality of the model during the creation phase. A shortcoming is that the process and results of the validation are rarely communicated using visual metaphors. This work presents a visual framework for molecular validation. The framework was developed in close collaboration with domain experts in a participatory design process. Its core is a novel visual representation based on 2D heatmaps that shows all available validation metrics in a linear fashion, presenting a global overview of the atomic model and provide domain experts with interactive analysis tools. Additional information stemming from the underlying data, such as a variety of local quality measures, is used to guide the user's attention toward regions of higher relevance. Linked with the heatmap is a three-dimensional molecular visualization providing the spatial context of the structures and chosen metrics. Additional views of statistical properties of the structure are included in the visual framework. We demonstrate the utility of the framework and its visual guidance with examples from cryo-EM.

Design, development of pyrazole-linked spirocyclopropyl oxindole-carboxamides as potential cytotoxic agents and Type III allosteric VEGFR-2 inhibitors.

Tumor progression depends on angiogenesis, which is stimulated by growth factors like VEGF, targeting VEGFR kinase with small molecules is an effective anti-angiogenic therapeutic approach. Sunitinib was rationally modified to spirocyclopropyloxindoline carboxamides and their in vitro cytotoxic profiling were evaluated. The molecular modelling studies enabled the screening of designed analogues and identified possible interactions within the type III allosteric inhibitor binding site of VEGFR-2. The biological screening of compounds 15a-y, revealed the ability of compound 15w to inhibit the cell growth in MCF-7 cells with IC50 value of 3.87 ± 0.19 μM and alongside inhibition of VEGFR-2 kinase at a IC50 concentration of 4.34 ± 0.13 μM was observed. VEGFR-2 inhibition was validated through HUVEC tube formation inhibition assay. 15w also inhibited cell migration in wound healing assay. The qualitative assessment of apoptosis induction by 15w in MCF-7 cells was evaluated through AO/EB and DAPI staining studies, whereas apoptotic quantification and cell cycle analysis were performed through FACS analysis. The current study strives to sequentially optimize the structural attributes of 3-alkenyl oxindole core to surpass the existing challenges of well-known VEGFR-2 inhibitors and compound 15w was identified to be a prominent lead towards the development of clinical drug candidates.

Optical Properties of H-Bonded Heterotriangulene Supramolecular Polymers: Charge-Transfer Excitations Matter.

H-bonded N-heterotriangulene (NHT) supramolecular polymers offer a nice playground to explore the nature and dynamics of electronic excitations in low-dimensional organic nanostructures. Here, we report on a comprehensive molecular modeling of the excited-state electronic structure and optical properties of model NHT stacks, highlighting the important role of intermolecular charge-transfer (CT) excitations in shaping their optical absorption and emission lineshapes. Most importantly, we show that the coupling between the local and CT excitations, modulated by the electric fields induced by the presence of polar amide groups forming H-bonded arrays along the stacks, significantly increases the resulting hybrid exciton bandwidth. We discuss these findings in the context of the efficient transport of singlet excitons over the μm length scale reported experimentally on individual self-assembled nanofibers with molecular-scale diameter.

Interfacial Electrochemistry of Catalyst-Coordinated Graphene Nanoribbons.

The immobilization of molecular electrocatalysts on conductive electrodes is an appealing strategy for enhancing their overall activity relative to those of analogous molecular compounds. In this study, we report on the interfacial electrochemistry of self-assembled two-dimensional nanosheets of graphene nanoribbons (GNR-2DNS) and analogs containing a Rh-based hydrogen evolution reaction (HER) catalyst (RhGNR-2DNS) immobilized on conductive electrodes. Proton-coupled electron transfer (PCET) taking place at N-centers of the nanoribbons was utilized as an indirect reporter of the interfacial electric fields experienced by the monolayer nanosheet located within the electric double layer. The experimental Pourbaix diagrams were compared with a theoretical model, which derives the experimental Pourbaix slopes as a function of parameter f, a fraction of the interfacial potential drop experienced by the redox-active group. Interestingly, our study revealed that GNR-2DNS was strongly coupled to glassy carbon electrodes (f = 1), while RhGNR-2DNS was not (f = 0.15). We further investigated the HER mechanism by RhGNR-2DNS using electrochemical and X-ray absorption spectroelectrochemical methods and compared it to homogeneous molecular model compounds. RhGNR-2DNS was found to be an active HER electrocatalyst over a broader set of aqueous pH conditions than its molecular analogs. We find that the improved HER performance in the immobilized catalyst arises due to two factors. First, redox-active bipyrimidine-based ligands were shown to dramatically alter the activity of Rh sites by increasing the electron density at the active Rh center and providing RhGNR-2DNS with improved catalysis. Second, catalyst immobilization was found to prevent catalyst aggregation that was found to occur for the molecular analog in the basic pH. Overall, this study provides valuable insights into the mechanism by which catalyst immobilization can affect the overall electrocatalytic performance.

Identification of a novel RHCE*Ce (829G > A) allele associated with absence of C and e antigens expression.

The Rh blood group antigens are encoded by the RHD and RHCE genes, which possess a remarkable degree of polymorphism owing to their high homologous structures. These variants of the RH genes can lead to absence or weak expression of antigens. Analysis of RHCE genotyping by Polymerase Chain Reaction (PCR-SSP) method specific to detect c.48G, c.48C, 109 bp insertion of IVS2, c.201A and c.307C and RhCE phenotyping, were conducted in 316 Chinese patients in previous study. One patient with discrepancy typing result was collected for further RhCE serologic typing using microcolumn gel method and tube method in saline using monoclonal antibodies. PacBio sequencing was performed for RHCE, RHD and RHAG complete sequence analysis. 3D molecular models of the protein with the wild-type and mutant residue were generated using the DynaMut web server. The effect of the mutation on the protein function was predicted by PolyPhen-2 software. One male patient of Chinese Han was detected with RHCE*C allele showed by PCR-SSP method but ccEE phenotype. Further PacBio sequencing identified one normal RHCE*cE allele and one RHCE*Ce allele carried a novel c.829G > A (p.Gly277Arg) variant, which the encoded amino acid located in the ninth transmembrane segment of RhCE protein. Crystallisation analysis of 3D molecular models revealed that the substitution at Arg277 leads to the formation of additional hydrogen bonds, including weak hydrogen bonds between multiple atoms. It also results in hydrophobic ion interactions between Arg277 and Ala244. This mutation is predicted to have a damaging effect on protein function. One novel RHCE*Ce allele with c.829G > A (p.Gly277Arg) variant was identified to resulting in the absence or weak expression of C and e antigens.

Molecular Modeling Studies to mimic the Binding Hypothesis of NEU3 Sialidase aand EGFR in Non-small Cell Lung Carcinoma

Molecular Modeling Studies to mimic the Binding Hypothesis of NEU3 Sialidase aand EGFR in Non-small Cell Lung Carcinoma

Unveiling Therapeutic Avenues for Crohn's Disease Management: Exploring Inhibitors for Adherent-Invasive Escherichia coli Propanediol Dehydratase.

Inflammatory Bowel Disease (IBD) encompasses a group of chronic disorders distinguished by inflammation of the gastrointestinal tract. Among these, Crohn's Disease (CD) stands out as a complex and impactful condition due to challenges for both diagnosis and management, making it a cynosure of research. In CD, there is the predominance of proinflammatory bacteria, including the Adherentinvasive Escherichia coli (AIEC) with virulence-associated metabolic enzyme Propanediol Dehydratase (pduC), which has been identified as a therapeutic target for the management of CD. Herein, molecular modeling techniques, including molecular docking, Molecular Mechanics with Generalized Born and Surface Area (MMGBSA), drug-likeness, and pharmacokinetics profiling, were utilized to probe the potentials of eighty antibacterial compounds to serve as inhibitors of pduC. The results of this study led to the identification of five compounds with promising potentials; the results of the molecular docking simulation revealed the compounds as possessing better binding affinities for the target compared to the standard drug (sulfasalazine), while Lipinski's rule of five-based assessment of their drug-likeness properties revealed them as potential oral drugs. MMGBSA free energy calculation and Molecular Dynamics (MD) simulation of the complexes formed a sequel to molecular docking, revealing the compounds as stable binders in the active site of the protein. Ultimately, the results of this study have revealed five compounds to possess the potential to serve as inhibitors of pduC of AIEC. However, experimental studies are still needed to validate the findings of this study.

Discovery of Novel Isatin Encompassing Oxadiazoles as Potential Inhibitors against New Delhi Metallo-β-lactamase-1: Synthesis, Spectral Analysis, Antimicrobial, and Molecular Modeling Studies

Discovery of Novel Isatin Encompassing Oxadiazoles as Potential Inhibitors against New Delhi Metallo-β-lactamase-1: Synthesis, Spectral Analysis, Antimicrobial, and Molecular Modeling Studies

Revolutionizing Drug Discovery: A Comprehensive Review of Computer-Aided Drug Design Approaches

Abstract: Computer-Aided Drug Design (CADD) has significantly advanced the drug discovery process, offering tools to enhance efficiency and reduce costs. This review explores essential CADD methodologies, including molecular docking, virtual screening, ADMET profiling, homology modeling, and Quantitative Structure-Activity Relationship (QSAR) models. Molecular docking predicts interactions between drugs and targets, while virtual screening evaluates large compound libraries to identify promising candidates. ADMET profiling assesses pharmacokinetic and toxicological properties early in development. Homology modeling constructs three-dimensional protein models to aid target identification, and QSAR models predict biological activities based on chemical structures. These integrated approaches streamline drug development, providing a robust framework for modern pharmaceutical research.

Multi-Template-Guided Synthesis of High-Dimensional Molecular Assemblies for Humidity Gradient-Based Power Generators.

Systematically orchestrating fundamental building blocks into intricate high-dimensional molecular assemblies at molecular level is imperative for multifunctionality integration. However, this remains a formidable task in crystal engineering due to the dynamic nature of inorganic building blocks. Herein, we develop a multi-template-guided strategy to control building blocks. The coordination modes of ligands and the spatial hindrance of anionic templates are pivotal in dictating the overall structures. Flexible multi-dentate linkers selectively promote the formation of oligomeric assembly ([TeO3(Mo2O2S2)3O2(OH)(C5O2H7)3]4- {TeMo6}) into tetrahedral cages ([(TeO3)4(Mo2O2S2)12(OH)12(C9H9O4P)6]8- {Te4Mo24} and [(AsO4)4(Mo2O2S2)12(OH)12(C9H9O6)4]12- {As4Mo24}), while steric hindrance from anionic templates further assists in assembling cages into an open quadruply twisted Möbius nanobelt ([(C6H5O3P)8(Mo2O2S2)24(OH)24(C8H10O4)12]16- {P8Mo48}). Among these structures, the hydrophilic-hydrophobic hybrid cage {Te4Mo24} emerges as an exemplary molecular model for proton conduction and serves as a prototype for humidity gradient-based power generators (HGPGs). The Te4Mo24-PVDF-based HGPG (PVDF = Poly(vinylidene fluoride)) exhibits notable stability and power generation, yielding an open-circuit voltage of 0.51 V and a current density of 77.8 nA cm-2 at room temperature and 90% relative humidity (RH). Further insights into the interactions between water molecules and microscale molecules within the generator are achieved through molecular dynamics simulations. This endeavor unveils a universal strategy for synthesizing multifunctional integration molecules.

Multi‐Template‐Guided Synthesis of High‐Dimensional Molecular Assemblies for Humidity Gradient‐Based Power Generators

Systematically orchestrating fundamental building blocks into intricate high‐dimensional molecular assemblies at molecular level is imperative for multifunctionality integration. However, this remains a formidable task in crystal engineering due to the dynamic nature of inorganic building blocks. Herein, we develop a multi‐template‐guided strategy to control building blocks. The coordination modes of ligands and the spatial hindrance of anionic templates are pivotal in dictating the overall structures. Flexible multi‐dentate linkers selectively promote the formation of oligomeric assembly ([TeO3(Mo2O2S2)3O2(OH)(C5O2H7)3]4‐ {TeMo6}) into tetrahedral cages ([(TeO3)4(Mo2O2S2)12(OH)12(C9H9O4P)6]8‐ {Te4Mo24} and [(AsO4)4(Mo2O2S2)12(OH)12(C9H9O6)4]12‐ {As4Mo24}), while steric hindrance from anionic templates further assists in assembling cages into an open quadruply twisted Möbius nanobelt ([(C6H5O3P)8(Mo2O2S2)24(OH)24(C8H10O4)12]16‐ {P8Mo48}). Among these structures, the hydrophilic‐hydrophobic hybrid cage {Te4Mo24} emerges as an exemplary molecular model for proton conduction and serves as a prototype for humidity gradient‐based power generators (HGPGs). The Te4Mo24‐PVDF‐based HGPG (PVDF = Poly(vinylidene fluoride)) exhibits notable stability and power generation, yielding an open‐circuit voltage of 0.51 V and a current density of 77.8 nA cm‐2 at room temperature and 90% relative humidity (RH). Further insights into the interactions between water molecules and microscale molecules within the generator are achieved through molecular dynamics simulations. This endeavor unveils a universal strategy for synthesizing multifunctional integration molecules.

In silico insights into the design of novel NR2B-selective NMDA receptor antagonists: QSAR modeling, ADME-toxicity predictions, molecular docking, and molecular dynamics investigations

Based on a structural family of thirty-two NR2B-selective N-Methyl-D-Aspartate receptor (NMDAR) antagonists, two phenylpiperazine derivatives labeled C37 and C39 were conceived thanks to molecular modeling techniques, as novel NMDAR inhibitors exhibiting the highest analgesic activities (of pIC50 order) against neuropathic pain, with excellent ADME-toxicity profiles, and good levels of molecular stability towards the targeted protein of NMDA receptor. Initially, the quantitative structure-activity relationships (QSARs) models were developed using multiple linear regression (MLR), partial least square regression (PLSR), multiple non-linear regression (MNLR), and artificial neural network (ANN) techniques, revealing that analgesic activity was strongly correlated with dipole moment, octanol/water partition coefficient, Oxygen mass percentage, electronegativity, and energy of the lowest unoccupied molecular orbital, whose the correlation coefficients of generated models were: 0.860, 0.758, 0.885 and 0.977, respectively. The predictive capacity of each model was evaluated by an external validation with correlation coefficients of 0.703, 0.851, 0.778, and 0.981 respectively, followed by a cross-validation technique with the leave-one-out procedure (CVLOO) with Q2cv of 0.785, more than Y-randomization test, and applicability domain (AD), in addition to Fisher’s and Student’s statistical tests. Thereafter, ten novel molecules were designed based on MLR QSAR model, then predicted with their ADME-Toxicity profiles and subsequently examined for their similarity to the drug candidates. Finally, two of the most active compounds (C37 and C39) were chosen for molecular docking and molecular dynamics (MD) investigations during 100 ns of MD simulation time in complex with the targeted protein of NMDA receptor (5EWJ.pdb).

Halogen Bonding Hot Spots as a Constraint in Virtual Screening: A Case Study of 5-HT7R.

The recently developed and used molecular modeling approach to search for privileged amino acids for halogen bonding (XB hot spots) through XSAR sets has been applied to 5-HT7R. Herein, among all identified 5-HT7R XB hot spots, the S5x42 was employed in a virtual screening protocol as a constraint. Through a designed virtual screening protocol, 63 XSAR sets (156 compounds) were selected from more than 8 million commercially available compounds and examined using in vitro assay toward 5-HT7R. A 68% accuracy was found in predicting halogenated derivatives with higher affinity for 5-HT7R than their unsubstituted analogs. Moreover, it was observed that a halogen bond formed between S5x42 and a chlorine atom at the 3-position of the arylpiperazine fragment caused the most remarkable, 35.4-fold increase in binding affinity for 5-HT7R when compared to the nonhalogenated analog. Interestingly, molecular dynamics simulations showed the formation of a bifurcated halogen bond with S5x42.