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Articles de revues sur le sujet « Target binding »

Auteur : Grafiati

Publié le 11 mars 2023

Mis à jour le 31 juillet 2025

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1

Park, Keunwan, Young-Joon Ko, Prasannavenkatesh Durai, and Cheol-Ho Pan. "Machine learning-based chemical binding similarity using evolutionary relationships of target genes." Nucleic Acids Research 47, no. 20 (2019): e128-e128. http://dx.doi.org/10.1093/nar/gkz743.

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Abstract Chemical similarity searching is a basic research tool that can be used to find small molecules which are similar in shape to known active molecules. Despite its popularity, the retrieval of local molecular features that are critical to functional activity related to target binding often fails. To overcome this limitation, we developed a novel machine learning-based chemical binding similarity score by using various evolutionary relationships of binding targets. The chemical similarity was defined by the probability of chemical compounds binding to identical targets. Comprehensive and

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Cheung, S. H., G. E. Legge, S. T. L. Chung, and B. S. Tjan. "Target-flanker binding releases crowding." Journal of Vision 6, no. 6 (2010): 807. http://dx.doi.org/10.1167/6.6.807.

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JOHNSTON, Angus, and Eva VAN DER MAREL. "How Binding are the EU’s ‘Binding’ Renewables Targets?" Cambridge Yearbook of European Legal Studies 18 (August 9, 2016): 176–214. http://dx.doi.org/10.1017/cel.2016.7.

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AbstractThe EU’s current renewable energy legislation sets a binding EU target for renewables as a share of overall energy consumption, allied with binding national targets for renewables as well. Yet the precise implications of having imposed such ‘mandatory’ binding targets have received little attention to date. This contribution examines the history and evolution of such targets, the context within which they must be pursued and applied, and some of the problems in and prospects for their enforcement and effectiveness. Comparisons are drawn with other areas of EU law where appropriate and

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POOLSAP, UNYANEE, YUKI KATO, KENGO SATO, and TATSUYA AKUTSU. "USING BINDING PROFILES TO PREDICT BINDING SITES OF TARGET RNAs." Journal of Bioinformatics and Computational Biology 09, no. 06 (2011): 697–713. http://dx.doi.org/10.1142/s0219720011005628.

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Prediction of RNA–RNA interaction is a key to elucidating possible functions of small non-coding RNAs, and a number of computational methods have been proposed to analyze interacting RNA secondary structures. In this article, we focus on predicting binding sites of target RNAs that are expected to interact with regulatory antisense RNAs in a general form of interaction. For this purpose, we propose bistaRNA, a novel method for predicting multiple binding sites of target RNAs. bistaRNA employs binding profiles that represent scores for hybridized structures, leading to reducing the computationa

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Molina, Daniel Martinez, Rozbeh Jafari, Marina Ignatushchenko, et al. "Monitoring Drug Target Engagement in Cells and Tissues Using the Cellular Thermal Shift Assay." Science 341, no. 6141 (2013): 84–87. http://dx.doi.org/10.1126/science.1233606.

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The efficacy of therapeutics is dependent on a drug binding to its cognate target. Optimization of target engagement by drugs in cells is often challenging, because drug binding cannot be monitored inside cells. We have developed a method for evaluating drug binding to target proteins in cells and tissue samples. This cellular thermal shift assay (CETSA) is based on the biophysical principle of ligand-induced thermal stabilization of target proteins. Using this assay, we validated drug binding for a set of important clinical targets and monitored processes of drug transport and activation, off

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Briskin, Daniel, Peter Y. Wang, and David P. Bartel. "The biochemical basis for the cooperative action of microRNAs." Proceedings of the National Academy of Sciences 117, no. 30 (2020): 17764–74. http://dx.doi.org/10.1073/pnas.1920404117.

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In cells, closely spaced microRNA (miRNA) target sites within a messenger RNA (mRNA) can act cooperatively, leading to more repression of the target mRNA than expected by independent action at each site. Using purified miRNA-Argonaute (AGO2) complexes, synthetic target RNAs, and a purified domain of TNRC6B (GW182 in flies) that is able to simultaneously bind multiple AGO proteins, we examined both the occupancies and binding affinities of miRNA-AGO2 complexes and target RNAs with either one site or two cooperatively spaced sites. On their own, miRNA-AGO2 complexes displayed little if any coope

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KUMAR, YOGESH, and FEROZ KHAN. "Detection of aroma compound’s binding mode conformations on anticancer target DNA topoisomerase II." Journal of Medicinal and Aromatic Plant Sciences 40, no. 3 (2018): 40–48. http://dx.doi.org/10.62029/jmaps.v40i3.kumar.

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Cancer is one of the most common, devastating class of disease affecting millions of people causing large number of death every year. It is therefore considered to be the second leading cause of death in developing countries next to cardiovascular diseases. Recent molecular studies have focussed on the most targeted gene for cancer i.e. DNA topoisomerase II (DNA TOP2), an enzyme that controls and alters the topological states of DNA during transcription. DNA TOP2 is also a target of known anticancer drugs like etoposide, doxorubicin, daunorubicin, amsacrine, amrubicin, and many others. These d

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Jadhav, Sagar Ashok, Payal Chavan, Supriya Suresh Shete, et al. "In Silico ADMET and Docking Study of Selected Drug Used in Therapy of COVID-19." Journal of Pharmaceutical Technology, Research and Management 10, no. 1 (2022): 47–73. http://dx.doi.org/10.15415/jptrm.2022.101006.

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Docking is one of the most widely utilized technique used method in structure -based drug design because of its capability to predict the binding conformation of ligands to appropriate target. Ability of binding/ affinity towards the target i.e., bioactive peptides or specific receptor provides strong evidence of binding conformation pattern and affinity for further investigation. Aim- The present study was conducted for evaluation of current API’s potential used in COVID-19. Methods: In-silico molecular docking was performed using softwares such as SWISS ADME, MOLSOFT, MOLINSPIRATION, PYMOL,

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Tan, Zhixin Cyrillus, Brian T. Orcutt-Jahns, and Aaron S. Meyer. "A quantitative view of strategies to engineer cell-selective ligand binding." Integrative Biology 13, no. 11 (2021): 269–82. http://dx.doi.org/10.1093/intbio/zyab019.

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Abstract A critical property of many therapies is their selective binding to target populations. Exceptional specificity can arise from high-affinity binding to surface targets expressed exclusively on target cell types. In many cases, however, therapeutic targets are only expressed at subtly different levels relative to off-target cells. More complex binding strategies have been developed to overcome this limitation, including multi-specific and multivalent molecules, creating a combinatorial explosion of design possibilities. Guiding strategies for developing cell-specific binding are critic

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Lipovsek, D. "Adnectins: engineered target-binding protein therapeutics." Protein Engineering Design and Selection 24, no. 1-2 (2010): 3–9. http://dx.doi.org/10.1093/protein/gzq097.

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Lv, Shuang-Qing, Xin Zeng, Guang-Peng Su, Wen-Feng Du, Yi Li, and Meng-Liang Wen. "Improving Identification of Drug-Target Binding Sites Based on Structures of Targets Using Residual Graph Transformer Network." Biomolecules 15, no. 2 (2025): 221. https://doi.org/10.3390/biom15020221.

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Improving identification of drug-target binding sites can significantly aid in drug screening and design, thereby accelerating the drug development process. However, due to challenges such as insufficient fusion of multimodal information from targets and imbalanced datasets, enhancing the performance of drug-target binding sites prediction models remains exceptionally difficult. Leveraging structures of targets, we proposed a novel deep learning framework, RGTsite, which employed a Residual Graph Transformer Network to improve the identification of drug-target binding sites. First, a residual

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Liao, Jianbo, Qinyu Wang, Fengxu Wu, and Zunnan Huang. "In Silico Methods for Identification of Potential Active Sites of Therapeutic Targets." Molecules 27, no. 20 (2022): 7103. http://dx.doi.org/10.3390/molecules27207103.

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Target identification is an important step in drug discovery, and computer-aided drug target identification methods are attracting more attention compared with traditional drug target identification methods, which are time-consuming and costly. Computer-aided drug target identification methods can greatly reduce the searching scope of experimental targets and associated costs by identifying the diseases-related targets and their binding sites and evaluating the druggability of the predicted active sites for clinical trials. In this review, we introduce the principles of computer-based active s

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Mohebbi, Mohammad, Liang Ding, Russell L. Malmberg, Cory Momany, Khaled Rasheed, and Liming Cai. "Accurate prediction of human miRNA targets via graph modeling of the miRNA-target duplex." Journal of Bioinformatics and Computational Biology 16, no. 04 (2018): 1850013. http://dx.doi.org/10.1142/s0219720018500130.

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miRNAs are involved in many critical cellular activities through binding to their mRNA targets, e.g. in cell proliferation, differentiation, death, growth control, and developmental timing. Accurate prediction of miRNA targets can assist efficient experimental investigations on the functional roles of miRNAs. Their prediction, however, remains a challengeable task due to the lack of experimental data about the tertiary structure of miRNA-target binding duplexes. In particular, correlations of nucleotides in the binding duplexes may not be limited to the canonical Watson Crick base pairs (BPs)

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Lee and Kim. "In-Silico Molecular Binding Prediction for Human Drug Targets Using Deep Neural Multi-Task Learning." Genes 10, no. 11 (2019): 906. http://dx.doi.org/10.3390/genes10110906.

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In in-silico prediction for molecular binding of human genomes, promising results have been demonstrated by deep neural multi-task learning due to its strength in training tasks with imbalanced data and its ability to avoid over-fitting. Although the interrelation between tasks is known to be important for successful multi-task learning, its adverse effect has been underestimated. In this study, we used molecular interaction data of human targets from ChEMBL to train and test various multi-task and single-task networks and examined the effectiveness of multi-task learning for different composi

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Robers, M. B., R. Friedman-Ohana, K. V. M. Huber, et al. "Quantifying Target Occupancy of Small Molecules Within Living Cells." Annual Review of Biochemistry 89, no. 1 (2020): 557–81. http://dx.doi.org/10.1146/annurev-biochem-011420-092302.

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The binding affinity and kinetics of target engagement are fundamental to establishing structure–activity relationships (SARs) for prospective therapeutic agents. Enhancing these binding parameters for operative targets, while minimizing binding to off-target sites, can translate to improved drug efficacy and a widened therapeutic window. Compound activity is typically assessed through modulation of an observed phenotype in cultured cells. Quantifying the corresponding binding properties under common cellular conditions can provide more meaningful interpretation of the cellular SAR analysis. C

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Schulmeyer, Kayley H., Manisha R. Diaz, Thomas B. Bair, et al. "Primary and Secondary Sequence Structure Requirements for Recognition and Discrimination of Target RNAs by Pseudomonas aeruginosa RsmA and RsmF." Journal of Bacteriology 198, no. 18 (2016): 2458–69. http://dx.doi.org/10.1128/jb.00343-16.

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ABSTRACTCsrA family RNA-binding proteins are widely distributed in bacteria and regulate gene expression at the posttranscriptional level.Pseudomonas aeruginosahas a canonical member of the CsrA family (RsmA) and a novel, structurally distinct variant (RsmF). To better understand RsmF binding properties, we performed parallel systematic evolution of ligands by exponential enrichment (SELEX) experiments for RsmA and RsmF. The initial target library consisted of 62-nucleotide (nt) RNA transcripts with central cores randomized at 15 sequential positions. Most targets selected by RsmA and RsmF wer

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Bandorowicz-Pikuła, J., M. Danieluk, A. Wrzosek, R. Buś, R. Buchet, and S. Pikuła. "Annexin VI: an intracellular target for ATP." Acta Biochimica Polonica 46, no. 3 (1999): 801–12. http://dx.doi.org/10.18388/abp.1999_4152.

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Annexin VI (AnxVI), an Ca2+- and phospholipid-binding protein, interacts in vitro with ATP in a calcium-dependent manner. Experimental evidence indicates that its nucleotide-binding domain which is localized in the C-terminal half of the protein differs structurally from ATP/GTP-binding motifs found in other nucleotide-binding proteins. The amino-acid residues of AnxVI directly involved in ATP binding have not been yet defined. Binding of ATP to AnxVI induces changes in the secondary and tertiary structures of protein, affecting the affinity of AnxVI for Ca2+ and, in consequence, influencing t

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Schmidt, Denis, Magdalena M. Scharf, Dominique Sydow, et al. "Analyzing Kinase Similarity in Small Molecule and Protein Structural Space to Explore the Limits of Multi-Target Screening." Molecules 26, no. 3 (2021): 629. http://dx.doi.org/10.3390/molecules26030629.

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While selective inhibition is one of the key assets for a small molecule drug, many diseases can only be tackled by simultaneous inhibition of several proteins. An example where achieving selectivity is especially challenging are ligands targeting human kinases. This difficulty arises from the high structural conservation of the kinase ATP binding sites, the area targeted by most inhibitors. We investigated the possibility to identify novel small molecule ligands with pre-defined binding profiles for a series of kinase targets and anti-targets by in silico docking. The candidate ligands origin

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Chen, Zihao, Long Hu, Bao-Ting Zhang, et al. "Artificial Intelligence in Aptamer–Target Binding Prediction." International Journal of Molecular Sciences 22, no. 7 (2021): 3605. http://dx.doi.org/10.3390/ijms22073605.

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Aptamers are short single-stranded DNA, RNA, or synthetic Xeno nucleic acids (XNA) molecules that can interact with corresponding targets with high affinity. Owing to their unique features, including low cost of production, easy chemical modification, high thermal stability, reproducibility, as well as low levels of immunogenicity and toxicity, aptamers can be used as an alternative to antibodies in diagnostics and therapeutics. Systematic evolution of ligands by exponential enrichment (SELEX), an experimental approach for aptamer screening, allows the selection and identification of in vitro

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Ganotra, Gaurav K., and Rebecca C. Wade. "Prediction of Drug–Target Binding Kinetics by Comparative Binding Energy Analysis." ACS Medicinal Chemistry Letters 9, no. 11 (2018): 1134–39. http://dx.doi.org/10.1021/acsmedchemlett.8b00397.

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Henrich, Stefan, Isabella Feierberg, Ting Wang, Niklas Blomberg, and Rebecca C. Wade. "Comparative binding energy analysis for binding affinity and target selectivity prediction." Proteins: Structure, Function, and Bioinformatics 78, no. 1 (2009): 135–53. http://dx.doi.org/10.1002/prot.22579.

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Klimentová, Eva, Václav Hejret, Ján Krčmář, Katarína Grešová, Ilektra-Chara Giassa, and Panagiotis Alexiou. "miRBind: A Deep Learning Method for miRNA Binding Classification." Genes 13, no. 12 (2022): 2323. http://dx.doi.org/10.3390/genes13122323.

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The binding of microRNAs (miRNAs) to their target sites is a complex process, mediated by the Argonaute (Ago) family of proteins. The prediction of miRNA:target site binding is an important first step for any miRNA target prediction algorithm. To date, the potential for miRNA:target site binding is evaluated using either co-folding free energy measures or heuristic approaches, based on the identification of binding ‘seeds’, i.e., continuous stretches of binding corresponding to specific parts of the miRNA. The limitations of both these families of methods have produced generations of miRNA tar

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Sarmoko, Sarmoko, Afif Hariawan Pratama, Nur Amalia Choironi, and Muhammad Salman Fareza. "Bioinformatic Study of the Active Compound of Morusin in Mulberry (Morus alba) against Breast Cancer." Indonesian Journal of Cancer Chemoprevention 14, no. 1 (2023): 60. http://dx.doi.org/10.14499/indonesianjcanchemoprev14iss1pp60-71.

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Morusin, an active constituent of the mulberry plant (Morus alba), exhibits inhibitory effects on several types of cancer cells in vitro, including breast cancer. This study aimed to identify potential target proteins of morusin, investigate the binding energy, and explore type of interactions between morusin and the target protein. Morusin target was searched using the PubMed, STITCH, STRING, and Cytoscape databases. Subsequently, the obtained morusin target protein data underwent processing using Autodock Tools and DS BIOVIA to facilate the simulation of molecular docking between morusin and

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Xiong, Li, Junfeng Cao, Yixin Qiu, et al. "Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics." Evidence-Based Complementary and Alternative Medicine 2022 (August 12, 2022): 1–11. http://dx.doi.org/10.1155/2022/9828518.

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Purpose. The research aims to investigate the mechanism of action of aspirin in the treatment of Kawasaki disease. Methods. We predicted the targets of aspirin with the help of the Drugbank and PharmMapper databases, the target genes of Kawasaki disease were mined in the GeneCards and Disgenet databases, the intersection targets were processed in the Venny database, and the gene expression differences were observed in the GEO database. The Drugbank and PharmMapper databases were used to predict the target of aspirin, and the target genes of Kawasaki disease were explored in the GeneCards and D

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Kim, Minjee, and Young Bong Kim. "Uncovering Quercetin’s Effects against Influenza A Virus Using Network Pharmacology and Molecular Docking." Processes 9, no. 9 (2021): 1627. http://dx.doi.org/10.3390/pr9091627.

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(1) Background: Re-emerging influenza threats continue to challenge medical and public health systems. Quercetin is a ubiquitous flavonoid found in food and is recognized to possess antioxidant, anti-inflammatory, antiviral, and anticancer activities. (2) Methods: To elucidate the targets and mechanisms underlying the action of quercetin as a therapeutic agent for influenza, network pharmacology and molecular docking were employed. Biological targets of quercetin and target genes associated with influenza were retrieved from public databases. Compound–disease target (C-D) networks were constru

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Sneha, Nandeshwar* Sapan Shah Rida Saiyad Nikita Gaikwad Pooja Wankhade. "In-Silico Evaluation of Flavone Derivatives for Cardioprotective Effects: A Comparative Molecular Docking Approach." International Journal of Pharmaceutical Sciences 3, no. 3 (2025): 2543–56. https://doi.org/10.5281/zenodo.15087478.

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Background: In this study, we used molecular docking to explore the binding affinity, ADME, and toxicity of flavone derivatives on several receptors associated with cardioprotective action. The binding affinity of several flavone derivatives to various receptors involved in cardioprotective action was determined. Auto Dock Vina, PyMol, Discovery Studio, AutoDock Tools, ChemSketch, Swiss ADME, and PROTOX 3.0. Methods: Molecular docking. Results: The binding results of the selected plant compounds and target proteins, namely 1o86, 7Q29, 5JMY, 4DLI, 2YCW, and 1CX2, showed that the good binding af

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Julio, Ashley R., and Keriann M. Backus. "New approaches to target RNA binding proteins." Current Opinion in Chemical Biology 62 (June 2021): 13–23. http://dx.doi.org/10.1016/j.cbpa.2020.12.006.

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Kadonosono, Tetsuya. "A smart design of target-binding molecules." Japanese Journal of Pesticide Science 46, no. 2 (2021): 168–72. http://dx.doi.org/10.1584/jpestics.w21-33.

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Holmberg, Eric, Kazuo Maruyama, Stephen Kennel, et al. "Target-Specific Binding of Immunoliposomes in Vivo." Journal of Liposome Research 1, no. 4 (1990): 393–406. http://dx.doi.org/10.3109/08982109009036003.

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Wu, Yung-Peng, Chee Ying Chew, Tian-Neng Li, et al. "Target-activated streptavidin–biotin controlled binding probe." Chemical Science 9, no. 3 (2018): 770–76. http://dx.doi.org/10.1039/c7sc04014h.

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The streptavidin–biotin controlled binding probe has several advantages for the detection of enzymes and reactive small molecules, such as minimal background, multiple signal amplification steps, and wide selection of the optimal dyes for detection.

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GuhaThakurta, D., and G. D. Stormo. "Identifying target sites for cooperatively binding factors." Bioinformatics 17, no. 7 (2001): 608–21. http://dx.doi.org/10.1093/bioinformatics/17.7.608.

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Öztürk, Hakime, Arzucan Özgür, and Elif Ozkirimli. "DeepDTA: deep drug–target binding affinity prediction." Bioinformatics 34, no. 17 (2018): i821—i829. http://dx.doi.org/10.1093/bioinformatics/bty593.

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de la Rosa, Mario A. Diaz, Elena F. Koslover, Peter J. Mulligan, and Andrew J. Spakowitz. "Target-Site Search of DNA-Binding Proteins." Biophysical Journal 98, no. 3 (2010): 221a. http://dx.doi.org/10.1016/j.bpj.2009.12.1194.

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Oğul, Hasan, Sinan U. Umu, Y. Yener Tuncel, and Mahinur S. Akkaya. "A probabilistic approach to microRNA-target binding." Biochemical and Biophysical Research Communications 413, no. 1 (2011): 111–15. http://dx.doi.org/10.1016/j.bbrc.2011.08.065.

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Loach, Daniel, and Paloma Marí-Beffa. "Post-target inhibition: A temporal binding mechanism?" Visual Cognition 10, no. 5 (2003): 513–26. http://dx.doi.org/10.1080/13506280244000203.

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Drwal, Malgorzata N., Guillaume Bret, and Esther Kellenberger. "Multi-target Fragments Display Versatile Binding Modes." Molecular Informatics 36, no. 10 (2017): 1700042. http://dx.doi.org/10.1002/minf.201700042.

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Smith, F. Donelson, Robert H. Pierce, Thomas Thisted, and Edward H. van der Horst. "Conditionally Active, pH-Sensitive Immunoregulatory Antibodies Targeting VISTA and CTLA-4 Lead an Emerging Class of Cancer Therapeutics." Antibodies 12, no. 3 (2023): 55. http://dx.doi.org/10.3390/antib12030055.

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Immune checkpoints and other immunoregulatory targets can be difficult to precisely target due to expression on non-tumor immune cells critical to maintaining immune homeostasis in healthy tissues. On-target/off-tumor binding of therapeutics results in significant pharmacokinetic and pharmacodynamic problems. Target-mediated drug disposition (TMDD) significantly limits effective intratumoral drug levels and adversely affects anti-tumor efficacy. Target engagement outside the tumor environment may lead to severe immune-related adverse events (irAEs), resulting in a narrowing of the therapeutic

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Yim, Hyung-Soon, and Jae-Hak Lee. "Prediction of Hypoxia-inducible Factor Binding Site in Whale Genome and Analysis of Target Genes Regulated by Predicted Sites." Journal of Marine Bioscience and Biotechnology 7, no. 2 (2015): 35–41. http://dx.doi.org/10.15433/ksmb.2015.7.2.035.

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Re, Suyong, Hiraku Oshima, Kento Kasahara, Motoshi Kamiya, and Yuji Sugita. "Encounter complexes and hidden poses of kinase-inhibitor binding on the free-energy landscape." Proceedings of the National Academy of Sciences 116, no. 37 (2019): 18404–9. http://dx.doi.org/10.1073/pnas.1904707116.

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Modern drug discovery increasingly focuses on the drug-target binding kinetics which depend on drug (un)binding pathways. The conventional molecular dynamics simulation can observe only a few binding events even using the fastest supercomputer. Here, we develop 2D gREST/REUS simulation with enhanced flexibility of the ligand and the protein binding site. Simulation (43 μs in total) applied to an inhibitor binding to c-Src kinase covers 100 binding and unbinding events. On the statistically converged free-energy landscapes, we succeed in predicting the X-ray binding structure, including water p

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Eriksson, Mikael, Guenther Leitz, Erik Fällman, et al. "Inhibitory Receptors Alter Natural Killer Cell Interactions with Target Cells Yet Allow Simultaneous Killing of Susceptible Targets." Journal of Experimental Medicine 190, no. 7 (1999): 1005–12. http://dx.doi.org/10.1084/jem.190.7.1005.

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Inhibitory receptors expressed on natural killer (NK) cells abrogate positive signals upon binding corresponding major histocompatibility complex (MHC) class I molecules on various target cells. By directly micromanipulating the effector–target cell encounter using an optical tweezers system which allowed temporal and spatial control, we demonstrate that Ly49–MHC class I interactions prevent characteristic cellular responses in NK cells upon binding to target cells. Furthermore, using this system, we directly demonstrate that an NK cell already bound to a resistant target cell may simultaneous

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Soller, Matthias, Min Li, and Irmgard U. Haussmann. "Determinants of ELAV gene-specific regulation." Biochemical Society Transactions 38, no. 4 (2010): 1122–24. http://dx.doi.org/10.1042/bst0381122.

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How RNA-binding proteins recognize their complement of targets in a complex cellular environment remains poorly understood. Sequence degeneracy and redundancy of short motifs at genomic scales have mostly eluded predictions of specific target genes for gene-specific ELAV (embryonic lethal abnormal visual system)/Hu proteins that bind ubiquitous AU-rich motifs. Using the genetic tools of Drosophila, we have analysed binding properties of ELAV in vitro and ELAV-dependent regulation of its major target ewg (erect wing) in neurons. These studies reveal that an integral part of ELAV gene-specific r

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Talukder, Amlan, Xiaoman Li, and Haiyan Hu. "Position-wise binding preference is important for miRNA target site prediction." Bioinformatics 36, no. 12 (2020): 3680–86. http://dx.doi.org/10.1093/bioinformatics/btaa195.

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Abstract Motivation It is a fundamental task to identify microRNAs (miRNAs) targets and accurately locate their target sites. Genome-scale experiments for miRNA target site detection are still costly. The prediction accuracies of existing computational algorithms and tools are often not up to the expectation due to a large number of false positives. One major obstacle to achieve a higher accuracy is the lack of knowledge of the target binding features of miRNAs. The published high-throughput experimental data provide an opportunity to analyze position-wise preference of miRNAs in terms of targ

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Jhanwar-Uniyal, Meena, Sabrina L. Zeller, Eris Spirollari, Mohan Das, Simon J. Hanft, and Chirag D. Gandhi. "Discrete Mechanistic Target of Rapamycin Signaling Pathways, Stem Cells, and Therapeutic Targets." Cells 13, no. 5 (2024): 409. http://dx.doi.org/10.3390/cells13050409.

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The mechanistic target of rapamycin (mTOR) is a serine/threonine kinase that functions via its discrete binding partners to form two multiprotein complexes, mTOR complex 1 and 2 (mTORC1 and mTORC2). Rapamycin-sensitive mTORC1, which regulates protein synthesis and cell growth, is tightly controlled by PI3K/Akt and is nutrient-/growth factor-sensitive. In the brain, mTORC1 is also sensitive to neurotransmitter signaling. mTORC2, which is modulated by growth factor signaling, is associated with ribosomes and is insensitive to rapamycin. mTOR regulates stem cell and cancer stem cell characteristi

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Zhou, Delong, Sonia Couture, Michelle S. Scott, and Sherif Abou Elela. "RBFOX2 alters splicing outcome in distinct binding modes with multiple protein partners." Nucleic Acids Research 49, no. 14 (2021): 8370–83. http://dx.doi.org/10.1093/nar/gkab595.

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Abstract RBFOX2 controls the splicing of a large number of transcripts implicated in cell differentiation and development. Parsing RNA-binding protein datasets, we uncover that RBFOX2 can interact with hnRNPC, hnRNPM and SRSF1 to regulate splicing of a broad range of splicing events using different sequence motifs and binding modes. Using immunoprecipitation, specific RBP knockdown, RNA-seq and splice-sensitive PCR, we show that RBFOX2 can target splice sites using three binding configurations: single, multiple or secondary modes. In the single binding mode RBFOX2 is recruited to its target sp

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Trezza, Alfonso, Anna Visibelli, Bianca Roncaglia, et al. "Unveiling Dynamic Hotspots in Protein–Ligand Binding: Accelerating Target and Drug Discovery Approaches." International Journal of Molecular Sciences 26, no. 9 (2025): 3971. https://doi.org/10.3390/ijms26093971.

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Computational methods have transformed target and drug discovery, significantly accelerating the identification of biological targets and lead compounds. Despite its limitations, in silico molecular docking represents a foundational tool. Molecular Dynamics (MD) simulations, employing accurate force fields, provide near-realistic insights into a compound’s behavior within a biological target. However, docking and MD predictions may be unreliable without precise knowledge of the target binding site. Through MD simulations, we investigated 100 co-crystal structures of biological targets complexe

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Faquetti, M. L., F. Grisoni, P. Schneider, G. Schneider, and A. M. Burden. "POS0091 OFF-TARGET PROFILING OF JANUS KINASE (JAK) INHIBITORS IN RHEUMATOID ARTHRITIS: A COMPUTER-BASED APPROACH FOR DRUG SAFETY STUDIES AND REPURPOSING." Annals of the Rheumatic Diseases 80, Suppl 1 (2021): 255.2–255. http://dx.doi.org/10.1136/annrheumdis-2021-eular.982.

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Background:The JAK inhibitors (JAKi’s) tofacitinib and baricitinib are new alternatives for treating rheumatoid arthritis. Safety concerns associated with JAKi’s, such as the increased risk for thrombosis and viral infections, have emerged worldwide. The underlying explanatory mechanisms remain unknown, suggesting the elevated risk is likely due to underlying confounding or an off-target binding effect. Computational approaches can explore the potential for a small molecule drug to interact with previously unknown biological targets and identify potential safety-related concerns, and open door

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Li, Shiyuan, Duyu Chen, Qingtong Zhou, et al. "A General Chemiluminescence Strategy for Measuring Aptamer–Target Binding and Target Concentration." Analytical Chemistry 86, no. 11 (2014): 5559–66. http://dx.doi.org/10.1021/ac501061c.

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Gijsen, Matthias, Erwin Dreesen, Ruth Van Daele, et al. "Pharmacokinetic/Pharmacodynamic Target Attainment Based on Measured versus Predicted Unbound Ceftriaxone Concentrations in Critically Ill Patients with Pneumonia: An Observational Cohort Study." Antibiotics 10, no. 5 (2021): 557. http://dx.doi.org/10.3390/antibiotics10050557.

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The impact of ceftriaxone pharmacokinetic alterations on protein binding and PK/PD target attainment still remains unclear. We evaluated pharmacokinetic/pharmacodynamic (PK/PD) target attainment of unbound ceftriaxone in critically ill patients with severe community-acquired pneumonia (CAP). Besides, we evaluated the accuracy of predicted vs. measured unbound ceftriaxone concentrations, and its impact on PK/PD target attainment. A prospective observational cohort study was carried out in adult patients admitted to the intensive care unit with severe CAP. Ceftriaxone 2 g q24h intermittent infus

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Shlyakhtenko, Luda S., Alexander Y. Lushnikov, Atsushi Miyagi, and Yuri L. Lyubchenko. "Specificity of Binding of Single-Stranded DNA-Binding Protein to Its Target." Biochemistry 51, no. 7 (2012): 1500–1509. http://dx.doi.org/10.1021/bi201863z.

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Brokx, Richard D., Maria M. Lopez, Hans J. Vogel, and George I. Makhatadze. "Energetics of Target Peptide Binding by Calmodulin Reveals Different Modes of Binding." Journal of Biological Chemistry 276, no. 17 (2001): 14083–91. http://dx.doi.org/10.1074/jbc.m011026200.

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