In Silico Approaches for TRP Channel Modulation

Nikolaeva-Koleva, Magdalena; Fernández‐Ballester, Gregorio

doi:10.1007/978-1-4939-9446-5_12

Cited by 5 publications

(4 citation statements)

References 67 publications

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“…All of the software differs in the conformational search algorithms and in the scoring functions that they are composed of. There are many examples of the use of these applications, and the ability of docking methods to bind ligands into protein has been extensively reviewed [29,30] and adapted for soluble or membrane proteins, including ion channels and receptors [57,88,89]. Nonetheless, there is no one docking application that is superior to others [90].…”

Section: Computational Approaches Based On Structural Data: Virtual S...mentioning

confidence: 99%

Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening

et al. 2022

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The rapid advances of 3D techniques for the structural determination of proteins and the development of numerous computational methods and strategies have led to identifying highly active compounds in computer drug design. Molecular docking is a method widely used in high-throughput virtual screening campaigns to filter potential ligands targeted to proteins. A great variety of docking programs are currently available, which differ in the algorithms and approaches used to predict the binding mode and the affinity of the ligand. All programs heavily rely on scoring functions to accurately predict ligand binding affinity, and despite differences in performance, none of these docking programs is preferable to the others. To overcome this problem, consensus scoring methods improve the outcome of virtual screening by averaging the rank or score of individual molecules obtained from different docking programs. The successful application of consensus docking in high-throughput virtual screening highlights the need to optimize the predictive power of molecular docking methods.

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Section: Computational Approaches Based On Structural Data: Virtual S...mentioning

confidence: 99%

Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening

et al. 2022

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“…To the best of our knowledge, molecular docking and MD simulations have not been applied yet to study the binding of photoswitchable lipids to TRP channels. However, these two computational techniques have been extensively used to investigate channel modulation by other TRP ligands [ 58 , 59 , 60 , 61 , 62 ] and thus their use could be easily extended to photopharmacological applications.…”

Section: Computational Modeling Of Photoswitchable Ligands Targeting Voltage-gated Ion Channelsmentioning

confidence: 99%

Photopharmacology of Ion Channels through the Light of the Computational Microscope

Nin‐Hill

Mueller

Molteni

et al. 2021

IJMS

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The optical control and investigation of neuronal activity can be achieved and carried out with photoswitchable ligands. Such compounds are designed in a modular fashion, combining a known ligand of the target protein and a photochromic group, as well as an additional electrophilic group for tethered ligands. Such a design strategy can be optimized by including structural data. In addition to experimental structures, computational methods (such as homology modeling, molecular docking, molecular dynamics and enhanced sampling techniques) can provide structural insights to guide photoswitch design and to understand the observed light-regulated effects. This review discusses the application of such structure-based computational methods to photoswitchable ligands targeting voltage- and ligand-gated ion channels. Structural mapping may help identify residues near the ligand binding pocket amenable for mutagenesis and covalent attachment. Modeling of the target protein in a complex with the photoswitchable ligand can shed light on the different activities of the two photoswitch isomers and the effect of site-directed mutations on photoswitch binding, as well as ion channel subtype selectivity. The examples presented here show how the integration of computational modeling with experimental data can greatly facilitate photoswitchable ligand design and optimization. Recent advances in structural biology, both experimental and computational, are expected to further strengthen this rational photopharmacology approach.

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“…Multiple omics-based approaches can be combined to yield quick and precise insights into credible bioactive candidates ("hits"). With the use of bioinformatic analysis tools, gene structure and functional annotation provide a clue to the potential of the drug-like gene, which could be coupled to pathway analysis and, finally, virtually confirmed by structure-based (SB) or ligand-based (LB) approach using chemoinformatic tools [158].…”

Section: Bioinformatics and Chemoinformatics Crosstalk In Drug Discovery From Bacteria And Microalgaementioning

confidence: 99%

“…The paradigm shift from single to multidisciplinary approaches intersecting biosciences, chemistry, and physics has the potential to revolutionize drug discovery and development, and accelerate the accuracy of drug discovery endeavor. As of today, computational science, through what is known as machine learning and artificial intelligence, can facilitate de novo drug design and propel the process of analysis faster than the human brain could perform [158]. In the near future, most challenges related to drug toxicity may be resolved through antibody and nanotechnology, which have emerged as methods to curtail chemotherapeutic toxicity by improving targeted drug delivery.…”

Section: Future Prospectsmentioning

confidence: 99%

Omics for Bioprospecting and Drug Discovery from Bacteria and Microalgae

et al. 2020

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“Omics” represent a combinatorial approach to high-throughput analysis of biological entities for various purposes. It broadly encompasses genomics, transcriptomics, proteomics, lipidomics, and metabolomics. Bacteria and microalgae exhibit a wide range of genetic, biochemical and concomitantly, physiological variations owing to their exposure to biotic and abiotic dynamics in their ecosystem conditions. Consequently, optimal conditions for adequate growth and production of useful bacterial or microalgal metabolites are critically unpredictable. Traditional methods employ microbe isolation and ‘blind’-culture optimization with numerous chemical analyses making the bioprospecting process laborious, strenuous, and costly. Advances in the next generation sequencing (NGS) technologies have offered a platform for the pan-genomic analysis of microbes from community and strain downstream to the gene level. Changing conditions in nature or laboratory accompany epigenetic modulation, variation in gene expression, and subsequent biochemical profiles defining an organism’s inherent metabolic repertoire. Proteome and metabolome analysis could further our understanding of the molecular and biochemical attributes of the microbes under research. This review provides an overview of recent studies that have employed omics as a robust, broad-spectrum approach for screening bacteria and microalgae to exploit their potential as sources of drug leads by focusing on their genomes, secondary metabolite biosynthetic pathway genes, transcriptomes, and metabolomes. We also highlight how recent studies have combined molecular biology with analytical chemistry methods, which further underscore the need for advances in bioinformatics and chemoinformatics as vital instruments in the discovery of novel bacterial and microalgal strains as well as new drug leads.

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In Silico Approaches for TRP Channel Modulation

Cited by 5 publications

References 67 publications

Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening

Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening

Photopharmacology of Ion Channels through the Light of the Computational Microscope

Omics for Bioprospecting and Drug Discovery from Bacteria and Microalgae

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