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Journal articles on the topic 'In silico methodologies'

Author: Grafiati

Published: 14 March 2023

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1

Hasan, Doaa Mohamed, Ahmed Sharaf Eldin, Ayman Elsayed Khedr, and Hanan Fahmy. "In-Silico Methodologies for Cancer Multidrug Optimization." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 17, no. 2 (2018): 7186–205. http://dx.doi.org/10.24297/ijct.v17i2.7168.

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Drug combinations is considered as an effective strategy designed to control complex diseases like cancer. Combinations of drugs can effectively decrease side effects and enhance adaptive resistance. Therefore, increasing the likelihood of defeating complex diseases in a synergistic way. This is due to overcoming factors such as off-target activities, network robustness, bypass mechanisms, cross-talk across compensatory escape pathways and the mutational heterogeneity which results in alterations within multiple molecular pathways. The plurality of effective drug combinations used in clinic we

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Scotti, Luciana, Jahan Ghasemi, and Marcus T. Scotti. "Editorial: In Silico Methodologies Applied to Drug Discovery." Combinatorial Chemistry & High Throughput Screening 21, no. 3 (2018): 150–51. http://dx.doi.org/10.2174/138620732103180423125817.

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Scotti, Luciana, and Marcus T. Scotti. "In Silico Methodologies Applied to Anti-infections Drug Discovery." Combinatorial Chemistry & High Throughput Screening 23, no. 6 (2020): 456–57. http://dx.doi.org/10.2174/138620732306200612101828.

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Remtulla, Raheem, Sanjoy Kumar Das, and Leonard A. Levin. "Predicting Absorption-Distribution Properties of Neuroprotective Phosphine-Borane Compounds Using In Silico Modeling and Machine Learning." Molecules 26, no. 9 (2021): 2505. http://dx.doi.org/10.3390/molecules26092505.

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Phosphine-borane complexes are novel chemical entities with preclinical efficacy in neuronal and ophthalmic disease models. In vitro and in vivo studies showed that the metabolites of these compounds are capable of cleaving disulfide bonds implicated in the downstream effects of axonal injury. A difficulty in using standard in silico methods for studying these drugs is that most computational tools are not designed for borane-containing compounds. Using in silico and machine learning methodologies, the absorption-distribution properties of these unique compounds were assessed. Features examine

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Uysal, Sengul, Abdurrahman Aktumsek, Carene M. N. Picot, et al. "A comparative in vitro and in silico study of the biological potential and chemical fingerprints of Dorcycinum pentapyllum subsp. haussknechtii using three extraction procedures." New Journal of Chemistry 41, no. 22 (2017): 13952–60. http://dx.doi.org/10.1039/c7nj03497k.

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Moura, Ana S., Amit K. Halder, and M. Natália DS Cordeiro. "From biomedicinal to in silico models and back to therapeutics: a review on the advancement of peptidic modeling." Future Medicinal Chemistry 11, no. 17 (2019): 2313–31. http://dx.doi.org/10.4155/fmc-2018-0365.

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Bioactive peptides participate in numerous metabolic functions of living organisms and have emerged as potential therapeutics on a diverse range of diseases. Albeit peptide design does not go without challenges, overwhelming advancements on in silico methodologies have increased the scope of peptide-based drug design and discovery to an unprecedented amount. Within an in silico model versus an experimental validation scenario, this review aims to summarize and discuss how different in silico techniques contribute at present to the design of peptide-based molecules. Published in silico results

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Ball, Nicholas, Remi Bars, Philip A. Botham, et al. "A framework for chemical safety assessment incorporating new approach methodologies within REACH." Archives of Toxicology 96, no. 3 (2022): 743–66. http://dx.doi.org/10.1007/s00204-021-03215-9.

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AbstractThe long-term investment in new approach methodologies (NAMs) within the EU and other parts of the world is beginning to result in an emerging consensus of how to use information from in silico, in vitro and targeted in vivo sources to assess the safety of chemicals. However, this methodology is being adopted very slowly for regulatory purposes. Here, we have developed a framework incorporating in silico, in vitro and in vivo methods designed to meet the requirements of REACH in which both hazard and exposure can be assessed using a tiered approach. The outputs from each tier are class

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Gimeno, Aleix, María Ojeda-Montes, Sarah Tomás-Hernández, et al. "The Light and Dark Sides of Virtual Screening: What Is There to Know?" International Journal of Molecular Sciences 20, no. 6 (2019): 1375. http://dx.doi.org/10.3390/ijms20061375.

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Virtual screening consists of using computational tools to predict potentially bioactive compounds from files containing large libraries of small molecules. Virtual screening is becoming increasingly popular in the field of drug discovery as in silico techniques are continuously being developed, improved, and made available. As most of these techniques are easy to use, both private and public organizations apply virtual screening methodologies to save resources in the laboratory. However, it is often the case that the techniques implemented in virtual screening workflows are restricted to thos

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Kothandan, Gugan, Changdev G. Gadhe, Thirumurthy Madhavan, and Seung J. Cho. "Binding Site Analysis of CCR2 Through In Silico Methodologies: Docking, CoMFA, and CoMSIA." Chemical Biology & Drug Design 78, no. 1 (2011): 161–74. http://dx.doi.org/10.1111/j.1747-0285.2011.01095.x.

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Gadhe, Changdev G., Gugan Kothandan, and Seung Joo Cho. "Binding site exploration of CCR5 using in silico methodologies: a 3D-QSAR approach." Archives of Pharmacal Research 36, no. 1 (2013): 6–31. http://dx.doi.org/10.1007/s12272-013-0001-1.

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Halder, Amit Kumar, and M. Natália Dias Soeiro Cordeiro. "Advanced in Silico Methods for the Development of Anti- Leishmaniasis and Anti-Trypanosomiasis Agents." Current Medicinal Chemistry 27, no. 5 (2020): 697–718. http://dx.doi.org/10.2174/0929867325666181031093702.

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Leishmaniasis and trypanosomiasis occur primarily in undeveloped countries and account for millions of deaths and disability-adjusted life years. Limited therapeutic options, high toxicity of chemotherapeutic drugs and the emergence of drug resistance associated with these diseases demand urgent development of novel therapeutic agents for the treatment of these dreadful diseases. In the last decades, different in silico methods have been successfully implemented for supporting the lengthy and expensive drug discovery process. In the current review, we discuss recent advances pertaining to in s

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Cezário, Stephanie Priscila de Sousa, Gabriel Veloso Correa, and Luiz Frederico Motta. "<em>In silico</em> pharmacokinetic and toxicological study of Flavone analogues." Brazilian Journal of Development 8, no. 12 (2022): 80782–99. http://dx.doi.org/10.34117/bjdv8n12-263.

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Flavone analogs are natural compounds of the flavonoid class that have a wide range of biological activities. The present study aimed to predict, with the aid of in silico methodologies, the oral bioavailability and pharmacokinetic and toxicological analyzes for three flavone analogues (apigenin, chrysin and luteonlin). The study revealed that the analogues have good oral availability, favorable pharmacokinetic and toxicological parameters. The Virtual Screening performed to predict oral bioavailability revealed that all analogues did not violate Lipinski's Rule. The in silico pharmacokinetic

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Firman, James W., Mark T. D. Cronin, Philip H. Rowe, Elizaveta Semenova, and John E. Doe. "The use of Bayesian methodology in the development and validation of a tiered assessment approach towards prediction of rat acute oral toxicity." Archives of Toxicology 96, no. 3 (2022): 817–30. http://dx.doi.org/10.1007/s00204-021-03205-x.

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AbstractThere exists consensus that the traditional means by which safety of chemicals is assessed—namely through reliance upon apical outcomes obtained following in vivo testing—is increasingly unfit for purpose. Whilst efforts in development of suitable alternatives continue, few have achieved levels of robustness required for regulatory acceptance. An array of “new approach methodologies” (NAM) for determining toxic effect, spanning in vitro and in silico spheres, have by now emerged. It has been suggested, intuitively, that combining data obtained from across these sources might serve to e

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Araujo, Laura Faria, Cacio Henrique de Souza Pinto, and Luiz Frederico Motta. "<em>In silico</em> pharmacokinetic and toxicological study of Cinnamic Acid analogues." Brazilian Journal of Development 8, no. 12 (2022): 80800–80817. http://dx.doi.org/10.34117/bjdv8n12-264.

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Cinnamic acid analogs are natural phenolic compounds that have a wide range of biological and therapeutic activities. The present work aimed to predict, through in silico methodologies, the oral bioavailability and pharmacokinetic and toxicological analyzes for four cinnamic acid analogues (caffeic acid, ferulic acid, p-coumaric acid and synaptic acid). The study revealed that the analogues have good oral bioavailability, favorable pharmacokinetic and toxicological parameters. The Virtual Screening performed to predict oral bioavailability indicated that all analogues do not violate Lipinski's

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Tsiaka, Thalia, Eftichia Kritsi, Konstantinos Tsiantas, Paris Christodoulou, Vassilia J. Sinanoglou, and Panagiotis Zoumpoulakis. "Design and Development of Novel Nutraceuticals: Current Trends and Methodologies." Nutraceuticals 2, no. 2 (2022): 71–90. http://dx.doi.org/10.3390/nutraceuticals2020006.

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Over the past few years, nutraceuticals have gained substantial attention due to the health-promoting and disease-preventing functions behind their nutritional value. The global prevalence of nutraceuticals is reflected in the increasing number of commercially available nutraceuticals and their wide range of applications. Therefore, a unique opportunity emerges for their further exploration using innovative, reliable, accurate, low cost, and high hit rate methods to design and develop next generation nutraceuticals. Towards this direction, computational techniques constitute an influential tre

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Johnson, David, Anthony J. Connor, Steve Mckeever, et al. "Semantically Linking in Silico Cancer Models." Cancer Informatics 13s1 (January 2014): CIN.S13895. http://dx.doi.org/10.4137/cin.s13895.

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Multiscale models are commonplace in cancer modeling, where individual models acting on different biological scales are combined within a single, cohesive modeling framework. However, model composition gives rise to challenges in understanding interfaces and interactions between them. Based on specific domain expertise, typically these computational models are developed by separate research groups using different methodologies, programming languages, and parameters. This paper introduces a graph-based model for semantically linking computational cancer models via domain graphs that can help us

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Pereira, Florbela, and Joao Aires-de-Sousa. "Computational Methodologies in the Exploration of Marine Natural Product Leads." Marine Drugs 16, no. 7 (2018): 236. http://dx.doi.org/10.3390/md16070236.

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Computational methodologies are assisting the exploration of marine natural products (MNPs) to make the discovery of new leads more efficient, to repurpose known MNPs, to target new metabolites on the basis of genome analysis, to reveal mechanisms of action, and to optimize leads. In silico efforts in drug discovery of NPs have mainly focused on two tasks: dereplication and prediction of bioactivities. The exploration of new chemical spaces and the application of predicted spectral data must be included in new approaches to select species, extracts, and growth conditions with maximum probabili

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Botton, Andrea, Gianmarco Barberi, and Pierantonio Facco. "Data Augmentation to Support Biopharmaceutical Process Development through Digital Models—A Proof of Concept." Processes 10, no. 9 (2022): 1796. http://dx.doi.org/10.3390/pr10091796.

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In recent years, monoclonal antibodies (mAbs) are gaining a wide market share as the most impactful bioproducts. The development of mAbs requires extensive experimental campaigns which may last several years and cost billions of dollars. Following the paradigm of Industry 4.0 digitalization, data-driven methodologies are now used to accelerate the development of new biopharmaceutical products. For instance, predictive models can be built to forecast the productivity of the cell lines in the culture in such a way as to anticipate the identification of the cell lines to be progressed in the scal

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Azzam, Khaldun AL. "SwissADME and pkCSM Webservers Predictors: an integrated Online Platform for Accurate and Comprehensive Predictions for In Silico ADME/T Properties of Artemisinin and its Derivatives." Kompleksnoe Ispolʹzovanie Mineralʹnogo syrʹâ/Complex Use of Mineral Resources/Mineraldik Shikisattardy Keshendi Paidalanu 325, no. 2 (2022): 14–21. http://dx.doi.org/10.31643/2023/6445.13.

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In vivo ADME testing is costly, time-consuming, and puts animal lives at risk, whereas in silico ADME testing is safer, simpler, and faster. This study will use in silico methodologies from SwissADME and pkCSM as an integrated online platform for accurate and comprehensive predictions to determine In Silico ADME/T Properties of Artemisinin and its Derivatives. The investigated compounds' structures were translated into canonical SMILES format and then submitted to the SwissADME and pkCSM webserver tools, which provide free access to different properties of compounds. A compound's ADME/T charac

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Grumetto, Lucia, та Giacomo Russo. "cΔlog kwIAM: can we afford estimation of small molecules’ blood-brain barrier passage based upon in silico phospholipophilicity?" ADMET and DMPK 9, № 4 (2021): 267–81. http://dx.doi.org/10.5599/admet.1034.

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56 compounds, whose log BB values were known from the scientific literature, were considered and their phospholipophilicity values were calculated in silico. These values, along with either experimentally determined or calculated lipophilicity values, were used to extract cΔ/Δ’log kwIAM parameters. cΔ/Δ’log kwIAM values were found inversely related to data of blood-brain barrier passage, especially in the < -0.20 log BB range and on the IAM.PC.DD2 phase (r2 = 0.79). In multiple linear regression, satisfactory statistic models (r2 (n-1) = 0.76), based on cD/D’log kwIAM.MG along with other in

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Albuquerque, Pedro, Inês Ribeiro, Sofia Correia, et al. "Complete Genome Sequence of Two Deep-Sea Streptomyces Isolates from Madeira Archipelago and Evaluation of Their Biosynthetic Potential." Marine Drugs 19, no. 11 (2021): 621. http://dx.doi.org/10.3390/md19110621.

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The deep-sea constitutes a true unexplored frontier and a potential source of innovative drug scaffolds. Here, we present the genome sequence of two novel marine actinobacterial strains, MA3_2.13 and S07_1.15, isolated from deep-sea samples (sediments and sponge) and collected at Madeira archipelago (NE Atlantic Ocean; Portugal). The de novo assembly of both genomes was achieved using a hybrid strategy that combines short-reads (Illumina) and long-reads (PacBio) sequencing data. Phylogenetic analyses showed that strain MA3_2.13 is a new species of the Streptomyces genus, whereas strain S07_1.1

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Gupta, Pawan, Prabha Garg, and Nilanjan Roy. "In silico screening for identification of novel HIV-1 integrase inhibitors using QSAR and docking methodologies." Medicinal Chemistry Research 22, no. 10 (2013): 5014–28. http://dx.doi.org/10.1007/s00044-013-0490-y.

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Barlow, D. J., A. Buriani, T. Ehrman, E. Bosisio, I. Eberini, and P. J. Hylands. "In-silico studies in Chinese herbal medicines’ research: Evaluation of in-silico methodologies and phytochemical data sources, and a review of research to date." Journal of Ethnopharmacology 140, no. 3 (2012): 526–34. http://dx.doi.org/10.1016/j.jep.2012.01.041.

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Araújo, Gabrielle Luck de, Maria Augusta Amaral Campos, Maria Anete Santana Valente, et al. "Alternative methods in toxicity testing: the current approach." Brazilian Journal of Pharmaceutical Sciences 50, no. 1 (2014): 55–62. http://dx.doi.org/10.1590/s1984-82502011000100005.

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Alternative methods are being developed to reduce, refine, and replace (3Rs) animals used in experiments, aimed at protecting animal welfare. The present study reports alternative tests which are based on the principles of the 3Rs and the efforts made to validate these tests. In Europe, several methodologies have already been implemented, such as tests of irritability, cell viability, and phototoxicity as well as in vitro mathematical models together with the use of in silico tools. This is a complex process that spans from development to regulatory approval and subsequent adoption by various

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Hussain, Michelle, Kun Tian, Luciano Mutti, Marija Krstic-Demonacos, and Jean-Marc Schwartz. "The Expanded p53 Interactome as a Predictive Model for Cancer Therapy." Genomics and Computational Biology 1, no. 1 (2015): 20. http://dx.doi.org/10.18547/gcb.2015.vol1.iss1.e20.

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The tumor suppressor gene TP53 is implicated in the majority of all human cancers, thus pivotal to genomic integrity. There are more than 72,000 scientific publications describing p53’s function, yet, due to the complexity of its interactions we are still far from fully elucidating p53’s role in tumorigenesis. Computational methodologies are novel tools to depict and dissect complex disease networks. The Boolean PKT206 p53 – DNA damage model has previously demonstrated good predictive capability for p53 wild-type and null tumors in various in silico knockouts. Here, we have expanded PKT206 to

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Aminpour, Maral, Carlo Montemagno, and Jack A. Tuszynski. "An Overview of Molecular Modeling for Drug Discovery with Specific Illustrative Examples of Applications." Molecules 24, no. 9 (2019): 1693. http://dx.doi.org/10.3390/molecules24091693.

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In this paper we review the current status of high-performance computing applications in the general area of drug discovery. We provide an introduction to the methodologies applied at atomic and molecular scales, followed by three specific examples of implementation of these tools. The first example describes in silico modeling of the adsorption of small molecules to organic and inorganic surfaces, which may be applied to drug delivery issues. The second example involves DNA translocation through nanopores with major significance to DNA sequencing efforts. The final example offers an overview

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Bisel, Blaine, Francesco S. Pavone, and Martino Calamai. "GM1 and GM2 gangliosides: recent developments." BioMolecular Concepts 5, no. 1 (2014): 87–93. http://dx.doi.org/10.1515/bmc-2013-0039.

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AbstractGM1 and GM2 gangliosides are important components of the cell membrane and play an integral role in cell signaling and metabolism. In this conceptual overview, we discuss recent developments in our understanding of the basic biological functions of GM1 and GM2 and their involvement in several diseases. In addition to a well-established spectrum of disorders known as gangliosidoses, such as Tay-Sachs disease, more and more evidence points at an involvement of GM1 in Alzheimer’s and Parkinson’s diseases. New emerging methodologies spanning from single-molecule imaging in vivo to simulati

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Furxhi, Irini, Finbarr Murphy, Martin Mullins, Athanasios Arvanitis, and Craig A. Poland. "Practices and Trends of Machine Learning Application in Nanotoxicology." Nanomaterials 10, no. 1 (2020): 116. http://dx.doi.org/10.3390/nano10010116.

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Machine Learning (ML) techniques have been applied in the field of nanotoxicology with very encouraging results. Adverse effects of nanoforms are affected by multiple features described by theoretical descriptors, nano-specific measured properties, and experimental conditions. ML has been proven very helpful in this field in order to gain an insight into features effecting toxicity, predicting possible adverse effects as part of proactive risk analysis, and informing safe design. At this juncture, it is important to document and categorize the work that has been carried out. This study investi

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Piñeiro-Yáñez, Elena, María José Jiménez-Santos, Gonzalo Gómez-López, and Fátima Al-Shahrour. "In Silico Drug Prescription for Targeting Cancer Patient Heterogeneity and Prediction of Clinical Outcome." Cancers 11, no. 9 (2019): 1361. http://dx.doi.org/10.3390/cancers11091361.

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In silico drug prescription tools for precision cancer medicine can match molecular alterations with tailored candidate treatments. These methodologies require large and well-annotated datasets to systematically evaluate their performance, but this is currently constrained by the lack of complete patient clinicopathological data. Moreover, in silico drug prescription performance could be improved by integrating additional tumour information layers like intra-tumour heterogeneity (ITH) which has been related to drug response and tumour progression. PanDrugs is an in silico drug prescription met

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Iwaniak, Anna, Małgorzata Darewicz, Damir Mogut, and Piotr Minkiewicz. "Elucidation of the role of in silico methodologies in approaches to studying bioactive peptides derived from foods." Journal of Functional Foods 61 (October 2019): 103486. http://dx.doi.org/10.1016/j.jff.2019.103486.

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Ayaz, Shahid, and Vivek Asati. "In silico study for the identification of potential compounds as PIM-1 kinase inhibitors." Pharmaspire 14, no. 01 (2022): 01–09. http://dx.doi.org/10.56933/pharmaspire.2022.14101.

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PIM kinases are a group of serine/threonine kinases that are classified into three isoforms: PIM1, PIM2, and PIM3. Pim-1 kinase is a critical enzyme that is involved in cell growth, cell survival, differentiation, apoptosis, senescence and drug resistance. The PUBMED database has been taken for the screening of PIM-1 kinase inhibitor. This database, further, screened by Lipinski Rule of five, HTVS, standard precision (SP), and extra precision (XP) methodologies. 2OJF protein of PIM-1 kinase was taken for molecular docking. The compound 1a showed good docking scores, SP = −7.244 and XP = −8.6,

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Arooj, Qudsia, Gregory J. Wilson, and Feng Wang. "Methodologies in Spectral Tuning of DSSC Chromophores through Rational Design and Chemical-Structure Engineering." Materials 12, no. 24 (2019): 4024. http://dx.doi.org/10.3390/ma12244024.

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The investigation of new photosensitizers for Grätzel-type organic dye-sensitized solar cells (DSSCs) remains a topic of interest for researchers of alternative solar cell materials. Over the past 20 years, considerable and increasing research efforts have been devoted to the design and synthesis of new materials, based on “donor, π-conjugated bridge, acceptor” (D–π–A) organic dye photosensitizers. In this paper, the computational chemistry methods are outlined and the design of organic sensitizers (compounds, dyes) is discussed. With reference to recent literature reports, rational molecular

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Chikhale, Hemant U. "PERSPECTIVE INSIGHT AND APPLICATION OF IN-SILICO TOOL AS VIRTUAL SCREENING METHOD FOR LEAD DESIGNING AND DEVELOPMENT." Journal of Medical pharmaceutical and allied sciences 11, no. 6 (2021): 16–24. http://dx.doi.org/10.22270/jmpas.v10i6.1908.

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Humans are now in a bioinformatics and chemo informatics century, where we can foresee data across domains like as healthcare, the environmental, technology, and public health. The use of information sharing in silico methodologies has impacted sickness administration by predicting the absorption, distribution, metabolism, excretion, and toxicity (ADMET) patterns of synthetic compounds and efficient and environmentally succeeding pharmaceuticals upfront. The purpose of lead discovery and design is to create the appearance of novel drug candidates that can attach to a specific illness cause. Th

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Drummond, Michael L., Andrew Henry, Huifang Li, and Christopher I. Williams. "Improved Accuracy for Modeling PROTAC-Mediated Ternary Complex Formation and Targeted Protein Degradation via New In Silico Methodologies." Journal of Chemical Information and Modeling 60, no. 10 (2020): 5234–54. http://dx.doi.org/10.1021/acs.jcim.0c00897.

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Santos, Joana, Miguel Cardoso, Irina S. Moreira, et al. "Integrated in Silico and Experimental Approach towards the Design of a Novel Recombinant Protein Containing an Anti-HER2 scFv." International Journal of Molecular Sciences 22, no. 7 (2021): 3547. http://dx.doi.org/10.3390/ijms22073547.

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Biological therapies, such as recombinant proteins, are nowadays amongst the most promising approaches towards precision medicine. One of the most innovative methodologies currently available aimed at improving the production yield of recombinant proteins with minimization of costs relies on the combination of in silico studies to predict and deepen the understanding of the modified proteins with an experimental approach. The work described herein aims at the design and production of a biomimetic vector containing the single-chain variable domain fragment (scFv) of an anti-HER2 antibody fragme

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Yadav, Tara Chand, Amit Kumar Srivastava, Arpita Dey, Naresh Kumar, Navdeep Raghuwanshi, and Vikas Pruthi. "Application of Computational Techniques to Unravel Structure-Function Relationship and their Role in Therapeutic Development." Current Topics in Medicinal Chemistry 18, no. 20 (2018): 1769–91. http://dx.doi.org/10.2174/1568026619666181120142141.

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Application of computational tools and techniques has emerged as an invincible instrument to unravel the structure-function relationship and offered better mechanistic insights in the designing and development of new drugs along with the treatment regime. The use of in silico tools equipped modern chemist with armamentarium of extensive methods to meticulously comprehend the structural tenacity of receptor-ligand interactions and their dynamics. In silico methods offers a striking property of being less resource intensive and economically viable as compared to experimental evaluation. These te

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Di Lorenzo, Chiara, Mario Dell'Agli, Elisa Colombo, Enrico Sangiovanni, and Patrizia Restani. "Metabolic Syndrome and Inflammation: A Critical Review ofIn Vitroand Clinical Approaches for Benefit Assessment of Plant Food Supplements." Evidence-Based Complementary and Alternative Medicine 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/782461.

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Metabolic syndrome is defined as the clustering in an individual of several metabolic abnormalities associated with insulin resistance, type 2 diabetes, and obesity, in which low-grade chronic inflammatory activity is commonly observed. Part of the European Project PlantLIBRA is concerned with methods to assess the benefits of plant food supplements (PFSs) in countering inflammatory activity and metabolic syndrome. This paper summarizes the current methods used for benefit assessment of PFS, taking into consideration onlyin vitro, in silico, and clinical methodologies used to investigate the a

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Schaack, Dominik, Markus A. Weigand, and Florian Uhle. "Comparison of machine-learning methodologies for accurate diagnosis of sepsis using microarray gene expression data." PLOS ONE 16, no. 5 (2021): e0251800. http://dx.doi.org/10.1371/journal.pone.0251800.

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We investigate the feasibility of molecular-level sample classification of sepsis using microarray gene expression data merged by in silico meta-analysis. Publicly available data series were extracted from NCBI Gene Expression Omnibus and EMBL-EBI ArrayExpress to create a comprehensive meta-analysis microarray expression set (meta-expression set). Measurements had to be obtained via microarray-technique from whole blood samples of adult or pediatric patients with sepsis diagnosed based on international consensus definition immediately after admission to the intensive care unit. We aggregate tr

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Chen, Qi, Xianwen Meng, Qi Liao, and Ming Chen. "Versatile interactions and bioinformatics analysis of noncoding RNAs." Briefings in Bioinformatics 20, no. 5 (2019): 1781–94. http://dx.doi.org/10.1093/bib/bby050.

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Abstract Advances in RNA sequencing technologies and computational methodologies have provided a huge impetus to noncoding RNA (ncRNA) study. Once regarded as inconsequential results of transcriptional promiscuity, ncRNAs were later found to exert great roles in various aspects of biological functions. They are emerging as key players in gene regulatory networks by interacting with other biomolecules (DNA, RNA or protein). Here, we provide an overview of ncRNA repertoire and highlight recent discoveries of their versatile interactions. To better investigate the ncRNA-mediated regulation, it is

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Agarwal, A., P. N. Pushparaj, G. Ahmad, et al. "Deciphering the sperm proteins associated with infertility in men with hodgkin’s disease using mass spectrometry and in silico methodologies." Fertility and Sterility 108, no. 3 (2017): e192. http://dx.doi.org/10.1016/j.fertnstert.2017.07.567.

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Brogi, Simone, Mark Tristan Quimque, Kin Israel Notarte, et al. "Virtual Combinatorial Library Screening of Quinadoline B Derivatives against SARS-CoV-2 RNA-Dependent RNA Polymerase." Computation 10, no. 1 (2022): 7. http://dx.doi.org/10.3390/computation10010007.

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The unprecedented global health threat of SARS-CoV-2 has sparked a continued interest in discovering novel anti-COVID-19 agents. To this end, we present here a computer-based protocol for identifying potential compounds targeting RNA-dependent RNA polymerase (RdRp). Starting from our previous study wherein, using a virtual screening campaign, we identified a fumiquinazolinone alkaloid quinadoline B (Q3), an antiviral fungal metabolite with significant activity against SARS-CoV-2 RdRp, we applied in silico combinatorial methodologies for generating and screening a library of anti-SARS-CoV-2 can

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Shukla, Pratibha, Deepa Deswal, Chandra S. Azad та Anudeep K. Narula. "Novel nucleosides as potential inhibitors of fungal lanosterol 14α-demethylase: an in vitro and in silico study". Future Medicinal Chemistry 11, № 20 (2019): 2663–86. http://dx.doi.org/10.4155/fmc-2019-0014.

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Aim: The global burden of fungal infections has transitioned from a case–specific observation to a major cause of high human mortality. Therefore, novel compounds with innovative methodologies need to be synthesized and evaluated for their antifungal potential to keep pace with the current clinical demands. Results: An efficient synthetic pathway was developed for the synthesis of 21 synthetic novel nucleosides. Two compounds had significant antifungal effect on Aspergillus fumigatus 3007, which was comparable to fluconazole. The experimental data (confocal microscopy, ultrahigh-performance li

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Ribeiro, Frederico F., Francisco J. B. M. Junior, Marcelo S. da Silva, Marcus Tullius Scotti, and Luciana Scotti. "Computational and Investigative Study of Flavonoids Active against Trypanosoma cruzi and Leishmania spp." Natural Product Communications 10, no. 6 (2015): 1934578X1501000. http://dx.doi.org/10.1177/1934578x1501000630.

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Flavonoid compounds active against Trypanosoma cruzi and Leishmania species were submitted to several methodologies in silico: docking with the enzymes cruzain and trypanothione reductase (from T. cruzi), and N-myristoyltransferase, dihydroorotate dehydrogenase, and trypanothiona reductase (from Leishmania spp). Molecular maps of the complexes and the ligands were calculated. In order to compare and evaluate the antioxidant activity of the flavonoids with their antiprotozoal activity, quantum parameters were calculated. Considering the energies, interactions, and hydrophobic surfaces calculate

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Ram, Rebecca N., Domenico Gadaleta, and Timothy E. H. Allen. "The role of ‘big data’ and ‘in silico’ New Approach Methodologies (NAMs) in ending animal use – A commentary on progress." Computational Toxicology 23 (August 2022): 100232. http://dx.doi.org/10.1016/j.comtox.2022.100232.

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Lee, Kyeonghee Monica, Richard Corley, Annie M. Jarabek, et al. "Advancing New Approach Methodologies (NAMs) for Tobacco Harm Reduction: Synopsis from the 2021 CORESTA SSPT—NAMs Symposium." Toxics 10, no. 12 (2022): 760. http://dx.doi.org/10.3390/toxics10120760.

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New approach methodologies (NAMs) are emerging chemical safety assessment tools consisting of in vitro and in silico (computational) methodologies intended to reduce, refine, or replace (3R) various in vivo animal testing methods traditionally used for risk assessment. Significant progress has been made toward the adoption of NAMs for human health and environmental toxicity assessment. However, additional efforts are needed to expand their development and their use in regulatory decision making. A virtual symposium was held during the 2021 Cooperation Centre for Scientific Research Relative to

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Cicaloni, Vittoria, Alfonso Trezza, Francesco Pettini, and Ottavia Spiga. "Applications of in Silico Methods for Design and Development of Drugs Targeting Protein-Protein Interactions." Current Topics in Medicinal Chemistry 19, no. 7 (2019): 534–54. http://dx.doi.org/10.2174/1568026619666190304153901.

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Background:Identification of Protein-Protein Interactions (PPIs) is a major challenge in modern molecular biology and biochemistry research, due to the unquestionable role of proteins in cells, biological process and pathological states. Over the past decade, the PPIs have evolved from being considered a highly challenging field of research to being investigated and examined as targets for pharmacological intervention.Objective:Comprehension of protein interactions is crucial to known how proteins come together to build signalling pathways, to carry out their functions, or to cause diseases, w

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Parladé, Eloi, Eric Voltà-Durán, Olivia Cano-Garrido, et al. "An In Silico Methodology That Facilitates Decision Making in the Engineering of Nanoscale Protein Materials." International Journal of Molecular Sciences 23, no. 9 (2022): 4958. http://dx.doi.org/10.3390/ijms23094958.

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Under the need for new functional and biocompatible materials for biomedical applications, protein engineering allows the design of assemblable polypeptides, which, as convenient building blocks of supramolecular complexes, can be produced in recombinant cells by simple and scalable methodologies. However, the stability of such materials is often overlooked or disregarded, becoming a potential bottleneck in the development and viability of novel products. In this context, we propose a design strategy based on in silico tools to detect instability areas in protein materials and to facilitate th

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Wu, Xunxun, Xiaokun Li, Chunxue Yang, and Yong Diao. "Target Characterization of Kaempferol against Myocardial Infarction Using Novel In Silico Docking and DARTS Prediction Strategy." International Journal of Molecular Sciences 22, no. 23 (2021): 12908. http://dx.doi.org/10.3390/ijms222312908.

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Target identification is a crucial process for advancing natural products and drug leads development, which is often the most challenging and time-consuming step. However, the putative biological targets of natural products obtained from traditional prediction studies are also informatively redundant. Thus, how to precisely identify the target of natural products is still one of the major challenges. Given the shortcomings of current target identification methodologies, herein, a novel in silico docking and DARTS prediction strategy was proposed. Concretely, the possible molecular weight was d

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Johnson, Dale. "Biotherapeutics: Challenges and Opportunities for Predictive Toxicology of Monoclonal Antibodies." International Journal of Molecular Sciences 19, no. 11 (2018): 3685. http://dx.doi.org/10.3390/ijms19113685.

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Biotherapeutics are a rapidly growing portion of the total pharmaceutical market accounting for almost one-half of recent new drug approvals. A major portion of these approvals each year are monoclonal antibodies (mAbs). During development, non-clinical pharmacology and toxicology testing of mAbs differs from that done with chemical entities since these biotherapeutics are derived from a biological source and therefore the animal models must share the same epitopes (targets) as humans to elicit a pharmacological response. Mechanisms of toxicity of mAbs are both pharmacological and non-pharmaco

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Zhou, Ying, Guoyou Gan, Jianhong Yi, et al. "Research status of the rare and precious metals’ Materials Genome Initiative." Journal of Micromechanics and Molecular Physics 05, no. 02 (2020): 2040002. http://dx.doi.org/10.1142/s2424913020400020.

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The core philosophy of Materials Genome Initiative (MGI) is the transition of the way of new materials design from the traditional “trial-and-error” approach to the in-silico materials design approach which employs intensive computing and material informatics. In June 2011, President Barack Obama launched MGI alongside the Advanced Manufacturing Partnership to help businesses discover, develop and deploy new materials twice as fast. In this paper, the concept of rare and precious genome is presented first, followed by the progress of MGI. After that, we focus on the research status of the rare

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