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Journal articles on the topic 'In silico design'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

DeWitt, Natalie. "In silico vaccine design?" Nature Biotechnology 17, no. 6 (1999): 523. http://dx.doi.org/10.1038/9813.

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2

Kotz, Joanne. "In silico drug design." Science-Business eXchange 6, no. 3 (2013): 50. http://dx.doi.org/10.1038/scibx.2013.50.

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Rees-Garbutt, Joshua, Jake Rightmyer, Jonathan R. Karr, Claire Grierson, and Lucia Marucci. "Furthering genome design using models and algorithms." Current Opinion in Systems Biology 24 (October 16, 2020): 120–26. https://doi.org/10.1016/j.coisb.2020.10.007.

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<strong>Highlights</strong> Models can investigate many more genome designs than laboratory research. Algorithms can search for genomes that optimise specific criteria. Together, models and algorithms can help engineers to design genomes. Algorithm-driven whole-cell model <em>in silico</em> designs could be viable <em>in vivo</em>. The genome design ecosystem needs improved modelling and design tools. <strong>Abstract</strong> Large-scale <em>in silico</em> genome designs are on the brink of being engineered <em>in vivo</em>, offering a potential paradig

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4

Triveni, S., C. Naresh Babu, E. Bhargav, and M. Vijaya Jyothi. "in silico Design, ADME Prediction, Molecular Docking, Synthesis of Novel Triazoles, Indazoles & Aminopyridines and in vitro Evaluation of Antitubercular Activity." Asian Journal of Chemistry 32, no. 11 (2020): 2713–21. http://dx.doi.org/10.14233/ajchem.2020.22790.

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To design and synthesize novel triazoles, indazoles and aminopyridines from various (thiophene-2-yl)prop-2-en-1-one derivatives as antitubercular leads by in silico and in vitro methods. in silco Drug design, ADME prediction and molecular docking studies were performed to assess drug likeliness and antitubercular potential of all 30 novel triazoles, indazoles and aminopyridines. in silico Drug design studies revealed that the synthetic routes applied were appropriate according to the calculations of Swiss-ADME that measure synthetic accessibility. Most of the synthesized compounds found to hav

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5

Zhao, Jun, Ruth Nussinov, Wen-Jin Wu, and Buyong Ma. "In Silico Methods in Antibody Design." Antibodies 7, no. 3 (2018): 22. http://dx.doi.org/10.3390/antib7030022.

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6

Konteatis, Zenon D. "In silico fragment-based drug design." Expert Opinion on Drug Discovery 5, no. 11 (2010): 1047–65. http://dx.doi.org/10.1517/17460441.2010.523697.

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7

Dahiyat, Bassil I. "In silico design for protein stabilization." Current Opinion in Biotechnology 10, no. 4 (1999): 387–90. http://dx.doi.org/10.1016/s0958-1669(99)80070-6.

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8

Boetker, Johan, Dhara Raijada, Johanna Aho, et al. "In silico product design of pharmaceuticals." Asian Journal of Pharmaceutical Sciences 11, no. 4 (2016): 492–99. http://dx.doi.org/10.1016/j.ajps.2016.02.010.

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9

Baginski, Maciej, and Katarzyna Serbakowska. "In silico design of telomerase inhibitors." Drug Discovery Today 25, no. 7 (2020): 1213–22. http://dx.doi.org/10.1016/j.drudis.2020.04.024.

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10

Islam, Rainul, Sumit Maji, Souparna Kabiraj, et al. "Role of in silico Drug Design in Pharmaceutical Sciences." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 2358–67. http://dx.doi.org/10.22214/ijraset.2022.42836.

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Abstract: In silico drug design is the study to identify, develop, analyze, optimize drugs or biologically cum pharmaceutically active compounds by using computerized software programs as well web servers. In silico drug design is commonly known as computer aided drug design or CADD in short. This technique shows a vital role in preclinical drug design and development. CADD can improve the speed of drug design. It reduces time as well as total cost of the experiments. Potent cum suitable molecules are prepared after performing in silico drug design including CADD. Various applications like con

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11

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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12

Nikam, Priya V., Sanjay Kumar, Sachinkumar D. Gunjal, Mrunalini H. Kulkarni, and Surya P. Singh. "Unlocking the Potential of In-silico Approaches: Drug Development and Vaccine Design." INTERNATIONAL JOURNAL OF DRUG DELIVERY TECHNOLOGY 13, no. 04 (2023): 1606–10. http://dx.doi.org/10.25258/ijddt.13.4.74.

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Unmatched in its field, bioinformatics combines several academic fields such as statistics, computer science, mathematics, and biology to create state-of-the-art techniques for biological data retrieval, storage, and analysis that lead to a thorough understanding of the biological world. Countless options currently accessible in field of living sciences by the expansion of in-silico biology. Paradigm of life sciences has changed as a result of in-silico technologies, which offer researchers a valuable and affordable way to focus on in-silico techniques like homology modeling, epitope predictio

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13

Kleynhans, Janke, Hendrik Gerhardus Kruger, Theunis Cloete, Jan Rijn Zeevaart, and Thomas Ebenhan. "In Silico Modelling in the Development of Novel Radiolabelled Peptide Probes." Current Medicinal Chemistry 27, no. 41 (2020): 7048–63. http://dx.doi.org/10.2174/0929867327666200504082256.

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This review describes the usefulness of in silico design approaches in the design of new radiopharmaceuticals, especially peptide-based radiotracers (including peptidomimetics). Although not part of the standard arsenal utilized during radiopharmaceutical design, the use of in silico strategies is steadily increasing in the field of radiochemistry as it contributes to a more rational and scientific approach. The development of new peptide-based radiopharmaceuticals as well as a short introduction to suitable computational approaches are provided in this review. The first section comprises a co

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14

Avihoo, Assaf, Idan Gabdank, Michal Shapira, and Danny Barash. "In Silico Design of Small RNA Switches." IEEE Transactions on NanoBioscience 6, no. 1 (2007): 4–11. http://dx.doi.org/10.1109/tnb.2007.891894.

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15

Bulacu, Monica, Xavier Périole, and Siewert J. Marrink. "In Silico Design of Robust Bolalipid Membranes." Biomacromolecules 13, no. 1 (2011): 196–205. http://dx.doi.org/10.1021/bm201454j.

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16

Foscato, Marco, and Vidar R. Jensen. "Automated in Silico Design of Homogeneous Catalysts." ACS Catalysis 10, no. 3 (2020): 2354–77. http://dx.doi.org/10.1021/acscatal.9b04952.

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17

Rodrigo, Guillermo, Javier Carrera, and Santiago F. Elena. "Network design meets in silico evolutionary biology." Biochimie 92, no. 7 (2010): 746–52. http://dx.doi.org/10.1016/j.biochi.2010.04.003.

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18

Chang, Yiqun, Bryson A. Hawkins, Jonathan J. Du, Paul W. Groundwater, David E. Hibbs, and Felcia Lai. "A Guide to In Silico Drug Design." Pharmaceutics 15, no. 1 (2022): 49. http://dx.doi.org/10.3390/pharmaceutics15010049.

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The drug discovery process is a rocky path that is full of challenges, with the result that very few candidates progress from hit compound to a commercially available product, often due to factors, such as poor binding affinity, off-target effects, or physicochemical properties, such as solubility or stability. This process is further complicated by high research and development costs and time requirements. It is thus important to optimise every step of the process in order to maximise the chances of success. As a result of the recent advancements in computer power and technology, computer-aid

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19

Lewis, Daniel R., Vladyslav Kholodovych, Michael D. Tomasini, et al. "In silico design of anti-atherogenic biomaterials." Biomaterials 34, no. 32 (2013): 7950–59. http://dx.doi.org/10.1016/j.biomaterials.2013.07.011.

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20

Hamada, Michiaki. "In silico approaches to RNA aptamer design." Biochimie 145 (February 2018): 8–14. http://dx.doi.org/10.1016/j.biochi.2017.10.005.

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21

Geris, L., R. Schugart, and H. Van Oosterwyck. "In silico design of treatment strategies in wound healing and bone fracture healing." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1920 (2010): 2683–706. http://dx.doi.org/10.1098/rsta.2010.0056.

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Wound and bone fracture healing are natural repair processes initiated by trauma. Over the last decade, many mathematical models have been established to investigate the healing processes in silico , in addition to ongoing experimental work. In recent days, the focus of the mathematical models has shifted from simulation of the healing process towards simulation of the impaired healing process and the in silico design of treatment strategies. This review describes the most important causes of failure of the wound and bone fracture healing processes and the experimental models and methods used

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22

Yurina, Valentina, and Oktavia Rahayu Adianingsih. "Predicting epitopes for vaccine development using bioinformatics tools." Therapeutic Advances in Vaccines and Immunotherapy 10 (January 2022): 251513552211002. http://dx.doi.org/10.1177/25151355221100218.

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Epitope-based DNA vaccine development is one application of bioinformatics or in silico studies, that is, computational methods, including mathematical, chemical, and biological approaches, which are widely used in drug development. Many in silico studies have been conducted to analyze the efficacy, safety, toxicity effects, and interactions of drugs. In the vaccine design process, in silico studies are performed to predict epitopes that could trigger T-cell and B-cell reactions that would produce both cellular and humoral immune responses. Immunoinformatics is the branch of bioinformatics use

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23

Pradhananga, Sarbendra, William Rayner, and Alan Berry. "De novo protein design: Evaluation of an in silico design method." Biochemical Society Transactions 28, no. 3 (2000): A69. http://dx.doi.org/10.1042/bst028a069c.

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24

Jukič, Marko, Sebastjan Kralj, Anja Kolarič, and Urban Bren. "Design of Tetra-Peptide Ligands of Antibody Fc Regions Using In Silico Combinatorial Library Screening." Pharmaceuticals 16, no. 8 (2023): 1170. http://dx.doi.org/10.3390/ph16081170.

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Peptides, or short chains of amino-acid residues, are becoming increasingly important as active ingredients of drugs and as crucial probes and/or tools in medical, biotechnological, and pharmaceutical research. Situated at the interface between small molecules and larger macromolecular systems, they pose a difficult challenge for computational methods. We report an in silico peptide library generation and prioritization workflow using CmDock for identifying tetrapeptide ligands that bind to Fc regions of antibodies that is analogous to known in vitro recombinant peptide libraries’ display and

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25

Wang, Yulan, Jing Xing, Yuan Xu, et al. "In silico ADME/T modelling for rational drug design." Quarterly Reviews of Biophysics 48, no. 4 (2015): 488–515. http://dx.doi.org/10.1017/s0033583515000190.

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AbstractIn recent decades, in silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) modelling as a tool for rational drug design has received considerable attention from pharmaceutical scientists, and various ADME/T-related prediction models have been reported. The high-throughput and low-cost nature of these models permits a more streamlined drug development process in which the identification of hits or their structural optimization can be guided based on a parallel investigation of bioavailability and safety, along with activity. However, the effectiveness of these

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26

Katti, Suvarna A. "Design, Synthesis and In Silico Evaluation of 1,3,4-Oxadiazole Derivatives for Their Nootropic Activity." Chettinad Health City Medical Journal 13, no. 04 (2024): 43–54. https://doi.org/10.24321/2278.2044.202458.

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27

Joshua, Magezi, Semawule Syrus, Namuswe Magdalene, and Janice Adaeze Nwankwo. "Recent Advances in the development of User-friendly Software Tools for Computational Protein Design, Modeling, and Molecular Docking." International Journal of Environment, Agriculture and Biotechnology 9, no. 5 (2024): 326–36. http://dx.doi.org/10.22161/ijeab.95.38.

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Computational protein design, modeling, and Molecular Docking represent a group of vital in-silico methods employed in predicting protein sequences with desired functions, predicting protein structures, and several molecular interactions with proteins. The application of such in silico methods is seen in the screening of potential targets during new drug designs, the discovery of novel protein sequences that could play new and vital functions such as industrial processes, understanding of protein function by studying its residues, and understanding of the effects of position mutations to the s

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28

V, Vani, Fathimathul Nafiya, Harshad A, Mahima Krishnan M M, Naisam N, and Sneha Saji. "In-Silico Design of Thiadiazole Derivatives as Anticonvulsant Agents." Asian Journal of Pharmaceutical Research and Development 12, no. 4 (2024): 85–91. http://dx.doi.org/10.22270/ajprd.v12i4.1445.

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This study focuses on the in-silico design and molecular docking of thiadiazole and its derivatives to evaluate their potential as anticonvulsant agents.Thiadiazoles are heterocyclic compounds known for their diverse biological activities, including anticonvulsant properties.The molecular structures were subjected to various in-silico screening methods to predict their drug-like properties and pharmacokinetic profiles. Molecular docking studies were performed to assess the binding affinity and interactions of the designed compounds with key targets associated with anticonvulsant activity, part

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29

Anić, Miloš, Miljan Milošević, Dalibor Nikolic, et al. "Computational Modeling for Mechanical Testing of Bioresorbable Stents." Ipsi Transactions on Internet research 18, no. 1 (2022): 34–43. http://dx.doi.org/10.58245/ipsi.tir.22jr.07.

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Development of plaques compositions caused by atherosclerosis inside of coronary arteries is known as coronary artery disease. Its treatment includes the possibility of stent deployment through operation called percutaneous transluminal coronary angioplasty. In this procedure stent is delivered using a balloon catheter and then inserted across the lesion. The new stent design development or optimization of existing ones requires the performance of many expensive mechanical tests which are always followed by their time-consuming analysis. Thus, the possibility of those tests to be performed on

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30

Mousavi, Sarah, Shima Zare, Mahmoud Mirzaei, and Awat Feizi. "Novel Drug Design for Treatment of COVID-19: A Systematic Review of Preclinical Studies." Canadian Journal of Infectious Diseases and Medical Microbiology 2022 (September 25, 2022): 1–70. http://dx.doi.org/10.1155/2022/2044282.

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Background. Since the beginning of the novel coronavirus (SARS-CoV-2) disease outbreak, there has been an increasing interest in discovering potential therapeutic agents for this disease. In this regard, we conducted a systematic review through an overview of drug development (in silico, in vitro, and in vivo) for treating COVID-19. Methods. A systematic search was carried out in major databases including PubMed, Web of Science, Scopus, EMBASE, and Google Scholar from December 2019 to March 2021. A combination of the following terms was used: coronavirus, COVID-19, SARS-CoV-2, drug design, dru

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31

Richards, William D., Yan Wang, Lincoln J. Miara, Jae Chul Kim, and Gerbrand Ceder. "Design of Li1+2xZn1−xPS4, a new lithium ion conductor." Energy & Environmental Science 9, no. 10 (2016): 3272–78. http://dx.doi.org/10.1039/c6ee02094a.

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32

Ulfa, Evi Umayah. "In Silico Design Gene Encoding CYP71AV1 for Expression in Escherichia coli." Journal of Bio-Molecule Research and Engineering 1, no. 1 (2022): 1–6. http://dx.doi.org/10.20473/jbiome.v1i1.35856.

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Cytochrome P450 monooxygenase (CYP71AV1) is a crucial enzyme in the artemisinin biosynthesis pathway. This enzyme oxidized Amorpha 4,11 diene to produce artemisinic acid. This study aimed to in silico design high-level expression of CYP71AV1 in the E.coli system. In silico techniques are highly suitable for designing protein recombinant production before entering the laboratory. The amino acid sequence of CYP71AV1 was back-translated to the DNA sequence and adapt to E.coli codon usage by using Gene Designer. The DNA sequence of optimized CYP71AV1 was analyzed using Rare Codon Analysis to asses

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33

Winiwarter, Susanne, Ernst Ahlberg, Edmund Watson, et al. "In silico ADME in drug design – enhancing the impact." ADMET and DMPK 6, no. 1 (2018): 15. http://dx.doi.org/10.5599/admet.6.1.470.

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<p>Each year the pharmaceutical industry makes thousands of compounds, many of which do not meet the desired efficacy or pharmacokinetic properties, describing the absorption, distribution, metabolism and excretion (ADME) behavior. Parameters such as lipophilicity, solubility and metabolic stability can be measured in high throughput in vitro assays. However, a compound needs to be synthesized in order to be tested. In silico models for these endpoints exist, although with varying quality. Such models can be used before synthesis and, together with a potency estimation, influence the dec

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34

Martinelli, Dominic D. "In silico vaccine design: A tutorial in immunoinformatics." Healthcare Analytics 2 (November 2022): 100044. http://dx.doi.org/10.1016/j.health.2022.100044.

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35

Prabhakar, Yenamandra. "Chemical Structure Indices in In Silico Molecular Design." Scientia Pharmaceutica 76, no. 2 (2008): 101–32. http://dx.doi.org/10.3797/scipharm.0804-12.

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36

Baumeier, Björn, Falk May, Christian Lennartz, and Denis Andrienko. "Challenges for in silico design of organic semiconductors." Journal of Materials Chemistry 22, no. 22 (2012): 10971. http://dx.doi.org/10.1039/c2jm30182b.

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37

Roy, Ankit, Sanjana Nair, Neeladri Sen, Neelesh Soni, and M. S. Madhusudhan. "In silico methods for design of biological therapeutics." Methods 131 (December 2017): 33–65. http://dx.doi.org/10.1016/j.ymeth.2017.09.008.

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38

Findeiß, Sven, Stefan Hammer, Michael T. Wolfinger, Felix Kühnl, Christoph Flamm, and Ivo L. Hofacker. "In silico design of ligand triggered RNA switches." Methods 143 (July 2018): 90–101. http://dx.doi.org/10.1016/j.ymeth.2018.04.003.

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39

Pieraccini, Stefano, Giorgio Saladino, Graziella Cappelletti, et al. "In silico design of tubulin-targeted antimitotic peptides." Nature Chemistry 1, no. 8 (2009): 642–48. http://dx.doi.org/10.1038/nchem.401.

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40

Shiragannavar, Shilpa, and Shivakumar Madagi. "In Silico Vaccine Design against Mycoplasma hominis Infections." Biomedical and Pharmacology Journal 13, no. 1 (2020): 457–68. http://dx.doi.org/10.13005/bpj/1906.

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41

Sanz-Herrera, J. A., E. Reina-Romo, and A. R. Boccaccini. "In silico design of magnesium implants: Macroscopic modeling." Journal of the Mechanical Behavior of Biomedical Materials 79 (March 2018): 181–88. http://dx.doi.org/10.1016/j.jmbbm.2017.12.016.

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42

Marchand, Jean-Rémy, and Amedeo Caflisch. "In silico fragment-based drug design with SEED." European Journal of Medicinal Chemistry 156 (August 2018): 907–17. http://dx.doi.org/10.1016/j.ejmech.2018.07.042.

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43

Rahal, Mahmoud, Mira Abdallah, Thanh-Tuân Bui, et al. "Design of new phenothiazine derivatives as visible light photoinitiators." Polymer Chemistry 11, no. 19 (2020): 3349–59. http://dx.doi.org/10.1039/d0py00497a.

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44

De, Baishakhi, Koushik Bhandari, Francisco J. B. Mendonça, Marcus T. Scotti, and Luciana Scotti. "Computational Studies in Drug Design Against Cancer." Anti-Cancer Agents in Medicinal Chemistry 19, no. 5 (2019): 587–91. http://dx.doi.org/10.2174/1871520618666180911125700.

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Background: The application of in silico tools in the development of anti cancer drugs. Objective: The summing of different computer aided drug design approaches that have been applied in the development of anti cancer drugs. Methods: Structure based, ligand based, hybrid protein-ligand pharmacophore methods, Homology modeling, molecular docking aids in different steps of drug discovery pipeline with considerable saving in time and expenditure. In silico tools also find applications in the domain of cancer drug development. Results: Structure-based pharmacophore modeling aided in the identific

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45

Wang, Ye, Chengkai Zhang, Song An, Xuexun Fang, and Dahai Yu. "Engineering substrate promiscuity in 2,4-dichlorophenol hydroxylase by in silico design." RSC Advances 8, no. 38 (2018): 21184–90. http://dx.doi.org/10.1039/c8ra03229g.

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46

García-Machorro, Jazmín, Gema Lizbeth Ramírez-Salinas, Marlet Martinez-Archundia, and José Correa-Basurto. "The Advantage of Using Immunoinformatic Tools on Vaccine Design and Development for Coronavirus." Vaccines 10, no. 11 (2022): 1844. http://dx.doi.org/10.3390/vaccines10111844.

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After the outbreak of SARS-CoV-2 by the end of 2019, the vaccine development strategies became a worldwide priority. Furthermore, the appearances of novel SARS-CoV-2 variants challenge researchers to develop new pharmacological or preventive strategies. However, vaccines still represent an efficient way to control the SARS-CoV-2 pandemic worldwide. This review describes the importance of bioinformatic and immunoinformatic tools (in silico) for guide vaccine design. In silico strategies permit the identification of epitopes (immunogenic peptides) which could be used as potential vaccines, as we

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47

HANDA, Susumu, Ken-ichiro TSUDA, Takashi IKEDA, and Yoshiaki TSUWA. "Integrated Environments for in silico Drug Design and Visualization." Journal of the Visualization Society of Japan 26, no. 101 (2006): 130–34. http://dx.doi.org/10.3154/jvs.26.130.

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48

Buglak, Andrey A., Alexey V. Samokhvalov, Anatoly V. Zherdev, and Boris B. Dzantiev. "Methods and Applications of In Silico Aptamer Design and Modeling." International Journal of Molecular Sciences 21, no. 22 (2020): 8420. http://dx.doi.org/10.3390/ijms21228420.

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Aptamers are nucleic acid analogues of antibodies with high affinity to different targets, such as cells, viruses, proteins, inorganic materials, and coenzymes. Empirical approaches allow the design of in vitro aptamers that bind particularly to a target molecule with high affinity and selectivity. Theoretical methods allow significant expansion of the possibilities of aptamer design. In this study, we review theoretical and joint theoretical-experimental studies dedicated to aptamer design and modeling. We consider aptamers with different targets, such as proteins, antibiotics, organophosphat

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49

Chandan, Kumar, Bharadwaj Soumya, Kumar Singh Shivam, et al. "Synthesis and In-silico Design of Gallic Acid Derivatives." International Journal of Innovative Science and Research Technology 8, no. 5 (2023): 224–32. https://doi.org/10.5281/zenodo.7937869.

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One of the most widespread phenolic acids in the plant world is gallic acid, also known as 3,4,5- trihydroxybenzoic acid. It is a crystalline substance that can be white or slightly yellow and finds extensive use in the food and pharmaceutical sectors. In the current study, three gallic acid compounds were created and then assessed for in silico investigations employing (PDB ID: 3VMP). When compared to common drugs like norfloxacin, it was shown that the three synthesised gallic acid derivatives with various aromatic aldehydes as schiff bases had a higher docking score and glide energy. In add

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50

Cerchia, Carmen, and Antonio Lavecchia. "In Silico Drug Design and Discovery: Big Data for Small Molecule Design." Biomolecules 13, no. 1 (2022): 44. http://dx.doi.org/10.3390/biom13010044.

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