Identification Of Binding Sites Research Articles

Binding Networks Identify Targetable Protein Pockets for Mechanism-Based Drug Design.

The human genome codes only a few thousand druggable proteins, mainly receptors and enzymes. While this pool of available drug targets is limited, there is an untapped potential for discovering new drug-binding mechanisms and modes. For example, enzymes with long binding cavities offer numerous prerequisite binding sites that may be visited by an inhibitor during migration from a bulk solution to the destination site. Drug design can use these prerequisite sites as new structural targets. However, identifying these ephemeral sites is challenging. Here, we introduce a new method called NetBinder for the systematic identification and classification of prerequisite binding sites at atomic resolution. NetBinder is based on atomistic simulations of the full inhibitor binding process and provides a networking framework on which to select the most important binding modes and uncover the entire binding mechanism, including previously undiscovered events. NetBinder was validated by a study of the binding mechanism of blebbistatin (a potent inhibitor) to myosin 2 (a promising target for cancer chemotherapy). Myosin 2 is a good test enzyme because, like other potential targets, it has a long internal binding cavity that provides blebbistatin with numerous potential prerequisite binding sites. The mechanism proposed by NetBinder of myosin 2 structural changes during blebbistatin binding shows excellent agreement with experimentally determined binding sites and structural changes. While NetBinder was tested on myosin 2, it may easily be adopted to other proteins with long internal cavities, such as G-protein-coupled receptors or ion channels, the most popular current drug targets. NetBinder provides a new paradigm for drug design by a network-based elucidation of binding mechanisms at an atomic resolution.

BLSSpeller to discover novel regulatory motifs in maize.

With the decreasing cost of sequencing and availability of larger numbers of sequenced genomes, comparative genomics is becoming increasingly attractive to complement experimental techniques for the task of transcription factor (TF) binding site identification. In this study, we redesigned BLSSpeller, a motif discovery algorithm, to cope with larger sequence datasets. BLSSpeller was used to identify novel motifs in Zea mays in a comparative genomics setting with 16 monocot lineages. We discovered 61 motifs of which 20 matched previously described motif models in Arabidopsis. In addition, novel, yet uncharacterized motifs were detected, several of which are supported by available sequence-based and/or functional data. Instances of the predicted motifs were enriched around transcription start sites and contained signatures of selection. Moreover, the enrichment of the predicted motif instances in open chromatin and TF binding sites indicates their functionality, supported by the fact that genes carrying instances of these motifs were often found to be co-expressed and/or enriched in similar GO functions. Overall, our study unveiled several novel candidate motifs that might help our understanding of the genotype to phenotype association in crops.

Art v 1 IgE epitopes of patients and humanized mice are conformational

Worldwide, pollen of the weed mugwort (Artemisiavulgaris) is a major cause of severe respiratory allergy, with its major allergen, Art v 1, being the key pathogenic molecule for millions of patients. Humanized mice transgenic for a human T-cell receptor specific for the major Art v 1 T-cell epitope and thecorresponding HLA have been made. We sought to characterize IgE epitopes of Art v 1-sensitized patients and humanized mice for molecular immunotherapy of mugwort allergy. Four overlapping peptides incorporating surface-exposed amino acids representing the full-length Art v 1 sequence were synthesized and used to search for IgE reactivity to sequential epitopes. For indirect mapping, peptide-specific rabbit antibodies were raised to block IgE against surface-exposed epitopes on folded Art v 1. IgE reactivity and basophil activation studies were performed in clinically defined mugwort-allergic patients. Secondary structure of recombinant (r) Art v 1 and peptides was determined by circular dichroism spectroscopy. Mugwort-allergic patients and humanized mice sensitized by allergen inhalation showed IgE reactivity and/or basophil activation mainly to folded, complete Art v 1 but not to unfolded, sequential peptide epitopes. Blocking of allergic patients' IgE with peptide-specific rabbit antisera identified a hitherto unknown major conformational IgE binding site in the C-terminal Art v 1 domain. Identification of the new major conformational IgE binding site on Art v 1, which can be blocked with IgG raised against non-IgE reactive Art v 1 peptides, is an important basis for the development of a hypoallergenic peptide vaccine for mugwort allergy.

Genome-Wide Identification of Binding Sites for SmTCP7a Transcription Factors of Eggplant during Bacterial Wilt Resistance by ChIP-Seq.

Teosinte branched 1/cycloidea/proliferating cell factor (TCP) transcription factors play a key role in the regulation of plant biotic and abiotic stresses. In this study, our results show that SmTCP7a positively regulated bacterial wilt that was caused by Ralstonia solanacearum. ChIP-seq was conducted to analyze the transcriptional regulation mechanism of SmTCP7a before (R0 h) and 48 h after infection (R48 h). SmTCP7a regulated a total of 92 and 91 peak-associated genes in R0 h and R48 h, respectively. A KEGG (Kyoto encyclopedia of genes and genomes) pathway analysis showed that phenylpropanoid biosynthesis, MAPK (mitogen-activated protein kinas) signaling pathway, plant hormone signal transduction and plant-pathogen interactions were involved. The difference in peaks between R0 h and R48 h showed that there were three peak-associated genes that were modulated by infection. A better understanding of the potential target genes of SmTCP7a in response to R. solanacearum will provide a comprehensive understanding of the SmTCP7a regulatory mechanism during the eggplant defense response to bacterial wilt.

Abstract 1552: Deciphering the mechanism of action of Long non-coding RNA fer1l4 in the suppression of invasion, migration and metastasis of colon cell carcinoma

Abstract Introduction: p73 transcription factor belongs to the p53 tumor suppressor family. Recent studies revealed that p73 wields its tumor suppressor properties by inhibiting metastasis. Although the literature on the p73 transcriptional circuit has chiefly concentrated on protein-coding genes, it has been progressively pointed out that p73 is also able to transcriptionally modulate non-coding RNA (ncRNA) members. These involve microRNAs (miRNAs) and many p53-regulated long non-coding RNAs (lncRNAs). Methods: Identification of p73 binding sites in the FER1L4 promoter region was made by JASPER and TF BIND which was further confirmed by chromatin immunoprecipitation (ChIP) and site-directed mutagenesis experiments. Effect of FER1L4 in p73 mediated cell cycle arrest and apoptosis was checked by cell cycle analysis, Annexin-V/PI, and TUNEL apoptosis assays. Depletion of FER1L4 enhanced cell proliferation, migration, and invasion in a p73-dependent manner. Furthermore, RNA-In situ hybridization (RNA-ISH) analysis of non-metastatic and metastatic human colon cancer tissue samples was carried out to compare the levels of FER1L4 and p73 in metastatic and non-metastatic tumor tissue samples. We also checked the expression of different miRNA including miR1273g-3p and its effect on PTEN expression. Results: We have identified lncRNA FER1L4 as a novel p73 transcriptional target that gets induced as a result of genotoxic stress. The binding of p73 to FER1L4 promoter was established by bioinformatics analysis, luciferase reporter, and ChIP assays. Both FER1L4 and p73 knockdown enhanced the migration and invasion rate of colorectal cancer cells. FER1L4 knockdown reduced E-cadherin expression and enhanced the expression of N-cadherin, Vimentin, Snail, and Fibronectin. Cell cycle assays revealed that FER1L4 induces a G2/M cell cycle arrest in a p73-dependent manner. Annexin V/PI and TUNEL assays revealed FER1L4 induced apoptosis in HCT116p53-/-p73+/+ colon cancer cells under genotoxic stress and FER1L4 knockdown inhibited apoptosis even in the presence of p73. The expression of pro-apoptotic markers such as Bad, Bax, Bik, Bim, Bid, Bak and PUMA decreased upon FER1L4 and p73 knockdown. FER1L4 sponges the expression of miR-1273g-3p, which in turn increases PTEN expression leading to cell cycle arrest. RNA In-situ hybridization revealed the down-regulation of both p73 and FER1L4 expression in metastatic colon cancer tissue as compared to non-metastatic tissue. Conclusion: We provide conclusive proof that p73 exerts its anti-metastatic properties by inducing lncRNA FER1L4 in response to genotoxic stress which in turn sponges the expression of miR1273g-3p, a regulator of PTEN. Citation Format: Daman Saluja, Apoorva Uboveja, Yatendra kumar Satija, Fouzia Siraj. Deciphering the mechanism of action of Long non-coding RNA fer1l4 in the suppression of invasion, migration and metastasis of colon cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1552.

Abstract 1560: Elucidating the differential regulation of novel long non coding RNAs and their mechanism of action in p73 dependent manner

Abstract INTRODUCTION: The p53 tumor suppressor family is classically activated after DNA damage and plays a central role in cell fate decisions. Although, the p53 family activates many of the same genes in response to DNA damage, p73 plays distinct biological functions in development and metastasis. It is likely that p73 activates a unique transcriptional network which is critical for its anti-metastatic and anti-invasive action. Long non-coding RNAs (lncRNAs) are a class of mRNA-like transcripts longer than 200 nucleotides. They lack protein-coding ability and are believed to be involved in various kinds of biological processes. Increasing evidence suggests that lncRNA are frequently aberrantly expressed in cancers. Therefore, the roles of dysregulated functional lncRNA in human malignant tumors have attracted considerable scientific interest. The objective of our study is to find out novel long non-coding RNAs that can act as transcriptional targets of p73 and to delineate their role in p73-mediated anti-metastatic response. METHODS: For this purpose, we performed transcriptome sequencing in HCT116p73wt and HCT116p73KD cells and screened the data for modulation of expression of lncRNAs in differential manner. Quantitative Real Time PCR was further carried out to validate the data obtained after screening RNA seq Data. Promoter analysis was carried out for the identification of p73 binding sites in the selected upregulated or downregulated lncRNAs which was further confirmed by Luciferase reporter, ChIP and site directed mutagenesis assays. RESULTS: About six lncRNAs were observed to be significantly upregulated while four were down-regulated upon knockdown of p73. The promoters of selected lncRNAs were analysed in silico using TF Bind and JASPAR software for p73 binding sites and luciferase reporter assays suggested regulation of lncRNAs by p73. Chromatin immunoprecipitation showed promoter enrichment of the selected lncRNAs. Site directed mutagenesis further confirmed the exact binding sites of p73 onto the promoters of these novel long non coding RNAs. CONCLUSION: Together, our study provides insights into the differential regulation of long non-coding RNAs in p73 dependent manner which further will provide the mechanism of their action at the genome level. Citation Format: Chanchal Bareja, Apoorva Uboveja, Daman Saluja. Elucidating the differential regulation of novel long non coding RNAs and their mechanism of action in p73 dependent manner [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1560.

Abstract 2136: Prediction of small molecule-protein binding events for BRD4 and EGFR inhibitors using HR-LiP, a novel structural proteomics approach

Abstract Background: Beyond phenotypic efficacy and safety categorization, high resolution profiling of drug-protein interactions and binding mechanisms remains a major hurdle during lead selection and optimization. A key milestone in structure-based drug design is compound binding site identification and characterization. Structure-activity relationship (SAR) studies utilize techniques such as nuclear magnetic resonance (NMR), x-ray crystallography (X-ray), cryo-electron microscopy (cryo-EM) and the mass spectrometry-based hydrogen-deuterium exchange (HDX) to address these hurdles but they are labor, time and cost intensive. Further, SAR studies are often complicated by protein size (i.e. large proteins) and location (i.e. membrane proteins), which can lead to protocol adaptations (e.g. recombinant protein usage and/or protein truncation) that can introduce artifacts. Using limited proteolysis (LiP) coupled to next-generation mass spectrometry we have developed a high-throughput, high-resolution approach (HR-LiP) that utilizes peptide-level resolution to characterize drug-protein interactions including for proteins that hindered by the previously mentioned limitations. Methods: To boost protein abundance in their native environment, proteins of interest were overexpressed in HEK293 cells using a simple plasmid construct. Cell lysates were incubated with the compounds of interest at increasing concentrations. Samples were then subjected to a limited digest using proteinase K and further processed for data independent acquisition (DIA)-MS analysis using trypsin. Data was analyzed using a directDIA workflow in Spectronaut. Results: Two well-characterized drug target proteins, bromodomain-containing protein 4 (BRD4) and epidermal growth factor receptor (EGFR), were selected for analysis. Using HR-LiP we identify the binding site of the BRD4 inhibitor JQ1 in the full-length protein, which is typically too large to be used directly in with conventional methods. Further, we map the intracellular binding location of both gefitinib and afatinib, two inhibitors of the membrane protein EGFR. Our data for both proteins are in good accordance with orthogonal data obtained by HDX-MS, NMR and X-ray studies. Conclusions: We demonstrate that HR-LiP can be used to dissect small molecule-protein binding events, including compound binding site prediction for protein targets classically considered to be difficult. Given its biological power, broad applicability and ease of implementation, we envision the use of HR-LiP as a routine approach for target validation and lead optimization in small molecule drug discovery pipelines. Citation Format: Nigel Beaton, Jagat Adhikari, Roland Bruderer, Ron Tomlinson, Yuehan Feng, Ivan Cornella-Taracido, Lukas Reiter. Prediction of small molecule-protein binding events for BRD4 and EGFR inhibitors using HR-LiP, a novel structural proteomics approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2136.

Identification of Transcription Factor Binding Sites by Cleavage Under Target and Release Using Nuclease in Zebrafish.

Cleavage Under Targets and Release Using Nuclease (CUT&RUN) has emerged as a chromatin profiling strategy that excels traditional methods. Although CUT&RUN has been widely utilized in mammalian cells, its use in the zebrafish is at its early stages. In this study, we have developed a protocol to successfully perform CUT&RUN to map transcription factor (TF) binding sites in embryonic, adult tissues, and FACS-sorted zebrafish cells. We also provide a detailed workflow for the identification of predicted TF binding sites that can be utilized in any animal species. Altogether, our strategy will expand this invaluable tool to the zebrafish community, improving the epigenetic resolution that can be achieved in this model organism.

PointSite: A Point Cloud Segmentation Tool for Identification of Protein Ligand Binding Atoms.

Accurate identification of ligand binding sites (LBS) on a protein structure is critical for understanding protein function and designing structure-based drugs. As the previous pocket-centric methods are usually based on the investigation of pseudo-surface-points outside the protein structure, they cannot fully take advantage of the local connectivity of atoms within the protein, as well as the global 3D geometrical information from all the protein atoms. In this paper, we propose a novel point clouds segmentation method, PointSite, for accurate identification of protein ligand binding atoms, which performs protein LBS identification at the atom-level in a protein-centric manner. Specifically, we first transfer the original 3D protein structure to point clouds and then conduct segmentation through Submanifold Sparse Convolution based U-Net. With the fine-grained atom-level binding atoms representation and enhanced feature learning, PointSite can outperform previous methods in atom Intersection over Union (atom-IoU) by a large margin. Furthermore, our segmented binding atoms, that is, atoms with high probability predicted by our model can work as a filter on predictions achieved by previous pocket-centric approaches, which significantly decreases the false-positive of LBS candidates. Besides, we further directly extend PointSite trained on bound proteins for LBS identification on unbound proteins, which demonstrates the superior generalization capacity of PointSite. Through cascaded filter and reranking aided by the segmented atoms, state-of-the-art performance can be achieved over various canonical benchmarks, CAMEO hard targets, and unbound proteins in terms of the commonly used DCA criteria.

CB-Dock2: improved protein-ligand blind docking by integrating cavity detection, docking and homologous template fitting.

Protein-ligand blind docking is a powerful method for exploring the binding sites of receptors and the corresponding binding poses of ligands. It has seen wide applications in pharmaceutical and biological researches. Previously, we proposed a blind docking server, CB-Dock, which has been under heavy use (over 200 submissions per day) by researchers worldwide since 2019. Here, we substantially improved the docking method by combining CB-Dock with our template-based docking engine to enhance the accuracy in binding site identification and binding pose prediction. In the benchmark tests, it yielded the success rate of ∼85% for binding pose prediction (RMSD < 2.0 Å), which outperformed original CB-Dock and most popular blind docking tools. This updated docking server, named CB-Dock2, reconfigured the input and output web interfaces, together with a highly automatic docking pipeline, making it a particularly efficient and easy-to-use tool for the bioinformatics and cheminformatics communities. The web server is freely available at https://cadd.labshare.cn/cb-dock2/.

CSM-Potential: mapping protein interactions and biological ligands in 3D space using geometric deep learning.

Recent advances in protein structural modelling have enabled the accurate prediction of the holo 3D structures of almost any protein, however protein function is intrinsically linked to the interactions it makes. While a number of computational approaches have been proposed to explore potential biological interactions, they have been limited to specific interactions, and have not been readily accessible for non-experts or use in bioinformatics pipelines. Here we present CSM-Potential, a geometric deep learning approach to identify regions of a protein surface that are likely to mediate protein-protein and protein–ligand interactions in order to provide a link between 3D structure and biological function. Our method has shown robust performance, outperforming existing methods for both predictive tasks. By assessing the performance of CSM-Potential on independent blind tests, we show that our method was able to achieve ROC AUC values of up to 0.81 for the identification of potential protein-protein binding sites, and up to 0.96 accuracy on biological ligand classification. Our method is freely available as a user-friendly and easy-to-use web server and API at http://biosig.unimelb.edu.au/csm_potential.

Agonistic and potentiating effects of perfluoroalkyl substances (PFAS) on the Atlantic cod (Gadus morhua) peroxisome proliferator-activated receptors (Ppars)

Toxicity mediated by per- and polyfluoroalkyl substances (PFAS), and especially perfluoroalkyl acids (PFAAs), has been linked to activation of peroxisome proliferator-activated receptors (Ppar) in many vertebrates. Here, we present the primary structures, phylogeny, and tissue-specific distributions of the Atlantic cod (Gadus morhua) gmPpara1, gmPpara2, gmPparb, and gmPparg, and demonstrate that the carboxylic acids PFHxA, PFOA, PFNA, as well as the sulfonic acid PFHxS, activate gmPpara1 in vitro, which was also supported by in silico analyses. Intriguingly, a binary mixture of PFOA and the non-activating PFOS produced a higher activation of gmPpara1 compared to PFOA alone, suggesting that PFOS has a potentiating effect on receptor activation. Supporting the experimental data, docking and molecular dynamics simulations of single and double-ligand complexes led to the identification of a putative allosteric binding site, which upon binding of PFOS stabilizes an active conformation of gmPpara1. Notably, binary exposures of gmPpara1, gmPpara2, and gmPparb to model-agonists and PFAAs produced similar potentiating effects. This study provides novel mechanistic insights into how PFAAs may modulate the Ppar signaling pathway by either binding the canonical ligand-binding pocket or by interacting with an allosteric binding site. Thus, individual PFAAs, or mixtures, could potentially modulate the Ppar-signaling pathway in Atlantic cod by interfering with at least one gmPpar subtype.

Transcriptome-wide identification of RNA-binding protein binding sites using seCLIP-seq.

Discovery of interaction sites between RNA-binding proteins (RBPs) and their RNA targets plays a critical role in enabling our understanding of how these RBPs control RNA processing and regulation. Cross-linking and immunoprecipitation (CLIP) provides a generalizable, transcriptome-wide method by which RBP/RNA complexes are purified and sequenced to identify sites of intermolecular contact. By simplifying technical challenges in prior CLIP methods and incorporating the generation of and quantitative comparison against size-matched input controls, the single-end enhanced CLIP (seCLIP) protocol allows for the profiling of these interactions with high resolution, efficiency and scalability. Here, we present a step-by-step guide to the seCLIP method, detailing critical steps and offering insights regarding troubleshooting and expected results while carrying out the ~4-d protocol. Furthermore, we describe a comprehensive bioinformatics pipeline that offers users the tools necessary to process two replicate datasets and identify reproducible and significant peaks for an RBP of interest in ~2 d.

Computer Aided Drug Design

Computational approaches in drug style, discovery and admiration. Generally, drug discovery takes an extended Duration of your time amount Ni twelve year and billon of capital. It includes the making of recent molecules, docking Molecules to focus on macromolecule, analyzing molecular interaction, estimating binding strength and drug properties. Computer power-assisted Drug planning (CADD) is value effective and freed from some biological trials. It mainly consists of 2 styles of drug style that’s structure -based drug style and ligand-based drug style. Through it we are able to comprehend the drug receptor interaction. Structure primarily based Drug style includes binding Site identification, arrival and stocking, virtual screening, compound choice, lead optimization. Ligand Based Drug style includes quantitative structure activity relationship, medicine modelling and steps Followed as structure- primarily based drug style. As we are able to see CADD facilitate to acknowledge appropriate characteristics of a Drug and its compatibility to induce a straightforward hand in pre- clinical trials.

Molecular modelling studies and identification of novel phytochemical inhibitor of DLL3

Prostate cancer has been recently considered the most diagnosed cancer in male. DLL3 is overexpressed in CRPC-NE but not in localised prostate cancer or BPH. There are no effective treatments for neuroendocrine differentiated prostate cancer due to a lack of understanding of DLL3 structure and function. The structure of DLL3 is not yet determined using any experimental techniques. Hence, the structure-based drug discovery approach against prostate cancer has not shown great success. In present study, molecular modelling techniques were employed to generate three-dimensional structure of DLL3 and performed its thorough structural analysis. Further, all-atom molecular dynamics simulation was performed to obtain energetically favourable conformation. Further, we used a virtual screening using a library of >13800 phytochemicals from the IMPPAT database and other literature to select the best possible phytochemical inhibitor for DLL3 and identified the top five compounds. Relative binding affinity was calculated using the MM-PBSA approach. ADMET properties of the screened compounds reveal the toxic effect of Gnemonol C. We believe these studied physicochemical properties, functional domain identification, and binding site identification would be very useful to gain more structural and functional insights of DLL3; also, it can be used to infer their pharmacodynamics properties of DLL3 which was recently reported as an important prostate cancer target. The current study also proposes that Ergosterol Peroxide, Dioslupecin A, Mulberrofuran K, and Caracurine V have strong affinities and could serve as plausible inhibitors against DLL3. We believe this study would further help develop better drug candidates against neuroendocrine prostate cancer. Communicated by Ramaswamy H. Sarma

Production and Preparation of Isotopically Labeled Human Membrane Proteins in Pichia pastoris for Fast-MAS-NMR Analyses.

Membrane proteins (MPs) comprise about one-third of the human proteome, playing critical roles in many physiological processes and associated disorders. Consistently, they represent one of the largest classes of targets for the pharmaceutical industry. Their study at the molecular level is however particularly challenging, resulting in a severe lack of structural and dynamic information that is hindering their detailed functional characterization and the identification of novel potent drug candidates.Magic Angle Spinning (MAS) NMR is a reliable and efficient method for the determination of protein structures and dynamics and for the identification of ligand binding sites and equilibria. MAS-NMR is particularly well suited for MPs since they can be directly analysed in a native-like lipid bilayer environment but used to require aggravating large amounts of isotope enriched material. The frequent toxicity of human MP overexpression in bacterial cultures poses an additional hurdle, resulting in the need for alternative (and often more costly) expression systems. The recent development of very fast (up to 150kHz) MAS probes has revolutionized the field of biomolecular solid-state NMR enabling higher spectral resolution with significant reduction of the required sample, rendering eukaryotic expression systems cost-effective.Here is presented a set of accessible procedures validated for the production and preparation of eukaryotic MPs for Fast-MAS 1H-detected NMR analysis. The methodology is illustrated with the human copper uptake protein hCTR1 recombinantly produced and 13C-15N uniformly labeled with the versatile and affordable Pichia pastoris system. Subsequent purification procedures allow the recovery of mg amounts that are then reconstituted into liposome formulations compatible with solid-state NMR handling and analysis.

Separation and Characterization of Protein-DNA Complexes by EMSA and In-Gel Footprinting.

In-gel footprinting enables the precise identification of protein binding sites on the DNA after separation of free and protein-bound DNA molecules by gel electrophoresis in native conditions and subsequent digestion by the nuclease activity of the 1,10-phenanthroline-copper ion [(OP)2-Cu+] within the gel matrix. Hence, the technique combines the resolving power of protein-DNA complexes in the electrophoretic mobility shift assay (EMSA) with the precision of target site identification by chemical footprinting. This approach is particularly well suited to characterize distinct molecular assemblies in a mixture of protein-DNA complexes and to identify individual binding sites within composite operators, when the concentration-dependent occupation of binding sites, with a different affinity, results in the generation of complexes with a distinct stoichiometry and migration velocity in gel electrophoresis.

Binding site identification of G protein-coupled receptors through a 3D Zernike polynomials-based method: application to C. elegans olfactory receptors

Studying the binding processes of G protein-coupled receptors (GPCRs) proteins is of particular interest both to better understand the molecular mechanisms that regulate the signaling between the extracellular and intracellular environment and for drug design purposes. In this study, we propose a new computational approach for the identification of the binding site for a specific ligand on a GPCR. The method is based on the Zernike polynomials and performs the ligand-GPCR association through a shape complementarity analysis of the local molecular surfaces. The method is parameter-free and it can distinguish, working on hundreds of experimentally GPCR-ligand complexes, binding pockets from randomly sampled regions on the receptor surface, obtaining an Area Under ROC curve of 0.77. Given its importance both as a model organism and in terms of applications, we thus investigated the olfactory receptors of the C. elegans, building a list of associations between 21 GPCRs belonging to its olfactory neurons and a set of possible ligands. Thus, we can not only carry out rapid and efficient screenings of drugs proposed for GPCRs, key targets in many pathologies, but also we laid the groundwork for computational mutagenesis processes, aimed at increasing or decreasing the binding affinity between ligands and receptors.

Search for Structural Basis of Interactions of Biogenic Amines with Human TAAR1 and TAAR6 Receptors.

The identification and characterization of ligand-receptor binding sites are important for drug development. Trace amine-associated receptors (TAARs, members of the class A GPCR family) can interact with different biogenic amines and their metabolites, but the structural basis for their recognition by the TAARs is not well understood. In this work, we have revealed for the first time a group of conserved motifs (fingerprints) characterizing TAARs and studied the docking of aromatic (β-phenylethylamine, tyramine) and aliphatic (putrescine and cadaverine) ligands, including gamma-aminobutyric acid, with human TAAR1 and TAAR6 receptors. We have identified orthosteric binding sites for TAAR1 (Asp68, Asp102, Asp284) and TAAR6 (Asp78, Asp112, Asp202). By analyzing the binding results of 7500 structures, we determined that putrescine and cadaverine bind to TAAR1 at one site, Asp68 + Asp102, and to TAAR6 at two sites, Asp78 + Asp112 and Asp112 + Asp202. Tyramine binds to TAAR6 at the same two sites as putrescine and cadaverine and does not bind to TAAR1 at the selected Asp residues. β-Phenylethylamine and gamma-aminobutyric acid do not bind to the TAAR1 and TAAR6 receptors at the selected Asp residues. The search for ligands targeting allosteric and orthosteric sites of TAARs has excellent pharmaceutical potential.

Molecular Docking of Mangostin and Sinensetin Derivatives on SUR1-Pancreatic KATP Channel Target as Antidiabetic

Background: Diabetes Mellitus (DM) is a complex chronic disease characterized by increased blood glucose. The incidence of this disease is rising, especially type 2 diabetes which is caused by insulin resistance in the body. SUR1-Pancreatic KATP Channel is a receptor as an antidiabetic target because its inhibition process can increase insulin production so that it can reduce blood glucose in people with type 2 diabetes. Objective: This study aims to identify the in-silico activity of the SUR1-Pancreatic KATP Channel macromolecules. Methods: Identification of macromolecular binding sites using Protein Plus software, then carried out molecular docking using AutoDock software, where the formed molecular interactions are further identified using the BIOVIA Discovery Studio software. Results: After determining the macromolecular binding site, the RMSD value was 1.253, allowing for further molecular docking. Molecular docking showed that the Ligands of mangostin (α, β, γ-mangostin) and sinensetin derivatives had a good affinity, namely α-mangostin -6,31 kcal/mol; β-mangostin -5.78 kcal/mol; γ-mangostin -6.17 kcal/mol and sinensetin -4.75 kcal/mol. Conclusion: The affinity sequence in the docking process for the SUR1 KATP channel macromolecules is α-mangostin &gt; γ-mangostin &gt; β-mangostin &gt; sinensetin. The highest affinity for the docking process on the macromolecule SUR1 KATP channel was α-mangostin with a value of ΔG -6.31 kcal/mol Ki 23.65 μM.