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Relevant bibliographies by topics / Computer-aided drug discovery, in silico methodologies, ligand-based, structure-based / Journal articles

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Journal articles on the topic 'Computer-aided drug discovery, in silico methodologies, ligand-based, structure-based'

Author: Grafiati

Published: 14 March 2023

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1

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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de Sousa Luis, José A., Normando A. da Silva Costa, Cristiane C. S. Luis, et al. "Synthesis of New Cyclic Imides Derived From Safrole, Structure- and Ligand-based Approaches to Evaluate Potential New Multitarget Agents Against Species of Leishmania." Medicinal Chemistry 16, no. 1 (2020): 39–51. http://dx.doi.org/10.2174/1573406415666190430144950.

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Background: Leishmaniasis is a neglected disease that does not have adequate treatment. It affects around 12 million people around the world and is classified as a neglected disease by the World Health Organization. In this context, strategies to obtain new, more active and less toxic drugs should be stimulated. Sources of natural products combined with synthetic and chemoinformatic methodologies are strategies used to obtain molecules that are most likely to be effective against a specific disease. Computer-Aided Drug Design has become an indispensable tool in the pharmaceutical industry and

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Cerdan, Adrien H., Marion Sisquellas, Gilberto Pereira, Diego E. Barreto Gomes, Jean-Pierre Changeux, and Marco Cecchini. "The Glycine Receptor Allosteric Ligands Library (GRALL)." Bioinformatics 36, no. 11 (2020): 3379–84. http://dx.doi.org/10.1093/bioinformatics/btaa170.

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Abstract Motivation Glycine receptors (GlyRs) mediate fast inhibitory neurotransmission in the brain and have been recognized as key pharmacological targets for pain. A large number of chemically diverse compounds that are able to modulate GlyR function both positively and negatively have been reported, which provides useful information for the development of pharmacological strategies and models for the allosteric modulation of these ion channels. Results Based on existing literature, we have collected 218 unique chemical entities with documented modulatory activities at homomeric GlyR-α1 and

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Nero, Tracy L., Michael W. Parker, and Craig J. Morton. "Protein structure and computational drug discovery." Biochemical Society Transactions 46, no. 5 (2018): 1367–79. http://dx.doi.org/10.1042/bst20180202.

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The first protein structures revealed a complex web of weak interactions stabilising the three-dimensional shape of the molecule. Small molecule ligands were then found to exploit these same weak binding events to modulate protein function or act as substrates in enzymatic reactions. As the understanding of ligand–protein binding grew, it became possible to firstly predict how and where a particular small molecule might interact with a protein, and then to identify putative ligands for a specific protein site. Computer-aided drug discovery, based on the structure of target proteins, is now a w

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Sehgal, Vijay Kumar, Supratik Das, and Anand Vardhan. "Computer Aided Drug Designing." International Journal of Medical and Dental Sciences 6, no. 1 (2017): 1433. http://dx.doi.org/10.18311/ijmds/2017/18804.

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Designing of drugs and their development are a time and resource consuming process. There is an increasing effort to introduce the role of computational approach to chemical and biological space in order to organise the design and development of drugs and their optimisation. The role of Computer Aided Drug Designing (CADD) are nowadays expressed in Nanotechnology, Molecular biology, Biochemistry etc. It is a diverse discipline where various forms of applied and basic researches are interlinked with each other. Computer aided or in Silico drug designing is required to detect hits and leads. Opt

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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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Sanyal, Saptarshi, Sk Abdul Amin, Nilanjan Adhikari, and Tarun Jha. "Ligand-based design of anticancer MMP2 inhibitors: a review." Future Medicinal Chemistry 13, no. 22 (2021): 1987–2013. http://dx.doi.org/10.4155/fmc-2021-0262.

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MMP2, a Zn2+-dependent metalloproteinase, is related to cancer and angiogenesis. Inhibition of this enzyme might result in a potential antimetastatic drug to leverage the anticancer drug armory. In silico or computer-aided ligand-based drug design is a method of rational drug design that takes multiple chemometrics (i.e., multi-quantitative structure–activity relationship methods) into account for virtually selecting or developing a series of probable selective MMP2 inhibitors. Though existing matrix metalloproteinase inhibitors have shown plausible pan-matrix metalloproteinase (MMP) activity,

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Leelananda, Sumudu P., and Steffen Lindert. "Computational methods in drug discovery." Beilstein Journal of Organic Chemistry 12 (December 12, 2016): 2694–718. http://dx.doi.org/10.3762/bjoc.12.267.

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The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power ha

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Samanta, Pabitra Narayan, Supratik Kar, and Jerzy Leszczynski. "Recent Advances of In-Silico Modeling of Potent Antagonists for the Adenosine Receptors." Current Pharmaceutical Design 25, no. 7 (2019): 750–73. http://dx.doi.org/10.2174/1381612825666190304123545.

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The rapid advancement of computer architectures and development of mathematical algorithms offer a unique opportunity to leverage the simulation of macromolecular systems at physiologically relevant timescales. Herein, we discuss the impact of diverse structure-based and ligand-based molecular modeling techniques in designing potent and selective antagonists against each adenosine receptor (AR) subtype that constitutes multitude of drug targets. The efficiency and robustness of high-throughput empirical scoring function-based approaches for hit discovery and lead optimization in the AR family

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Ramesh, Muthusamy, and Arunachalam Muthuraman. "Computer-Aided Drug Discovery (CADD) Approaches for the Management of Neuropathic Pain." Current Topics in Medicinal Chemistry 21, no. 32 (2021): 2856–68. http://dx.doi.org/10.2174/1568026621666211122161932.

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Neuropathic pain occurs due to physical damage, injury, or dysfunction of neuronal fibers. The pathophysiology of neuropathic pain is too complex. Therefore, an accurate and reliable prediction of the appropriate hits/ligands for the treatment of neuropathic pain is a challenging process. However, computer-aided drug discovery approaches contributed significantly to discovering newer hits/ligands for the treatment of neuropathic pain. The computational approaches like homology modeling, induced-fit molecular docking, structure-activity relationships, metadynamics, and virtual screening were ci

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Rudrapal, Mithun, and Dipak Chetia. "Virtual Screening, Molecular Docking and QSAR Studies in Drug Discovery and Development Programme." Journal of Drug Delivery and Therapeutics 10, no. 4 (2020): 225–33. http://dx.doi.org/10.22270/jddt.v10i4.4218.

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Structure-based drug design (SBDD) and ligand-based drug design (LBDD) are the two basic approaches of computer-aided drug design (CADD) used in modern drug discovery and development programme. Virtual screening (or in silico screening) has been used in drug discovery program as a complementary tool to high throughput screening (HTS) to identify bioactive compounds. It is a preliminary tool of CADD that has gained considerable interest in the pharmaceutical research as a productive and cost-effective technology in search for novel molecules of medicinal interest. Docking is also used for virtu

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Nakarin, Fahsai, Kajjana Boonpalit, Jiramet Kinchagawat, Patcharapol Wachiraphan, Thanyada Rungrotmongkol, and Sarana Nutanong. "Assisting Multitargeted Ligand Affinity Prediction of Receptor Tyrosine Kinases Associated Nonsmall Cell Lung Cancer Treatment with Multitasking Principal Neighborhood Aggregation." Molecules 27, no. 4 (2022): 1226. http://dx.doi.org/10.3390/molecules27041226.

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A multitargeted therapeutic approach with hybrid drugs is a promising strategy to enhance anticancer efficiency and overcome drug resistance in nonsmall cell lung cancer (NSCLC) treatment. Estimating affinities of small molecules against targets of interest typically proceeds as a preliminary action for recent drug discovery in the pharmaceutical industry. In this investigation, we employed machine learning models to provide a computationally affordable means for computer-aided screening to accelerate the discovery of potential drug compounds. In particular, we introduced a quantitative struct

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Pandey, Surabhi, and B. K. Singh. "De-novo Drug Design, Molecular Docking and In-Silico Molecular Prediction of AChEI Analogues through CADD Approaches as Anti-Alzheimer’s Agents." Current Computer-Aided Drug Design 16, no. 1 (2020): 54–72. http://dx.doi.org/10.2174/1573409915666190301124210.

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Background: There are over 44 million persons who suffer with Alzheimer’s disease (AD) worldwide, no existence of cure and only symptomatic treatments are available for it. The aim of this study is to evaluate the anti-Alzheimer potential of designed AChEI analogues using computer simulation docking studies. AChEIs are the most potential standards for treatment of AD, because they have proven efficacy. Among all AChEIs donepezil possesses lowest adverse effects, it can treat mildmoderate- severe AD and only once-daily dosing is required. Therefore, donepezil is recognized as a significant prot

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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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Osman, Doaa A., Mario A. Macías, Lamya H. Al-Wahaibi та ін. "Structural Insights and Docking Analysis of Adamantane-Linked 1,2,4-Triazole Derivatives as Potential 11β-HSD1 Inhibitors". Molecules 26, № 17 (2021): 5335. http://dx.doi.org/10.3390/molecules26175335.

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The solid-state structural analysis and docking studies of three adamantane-linked 1,2,4-triazole derivatives are presented. Crystal structure analyses revealed that compound 2 crystallizes in the triclinic P-1 space group, while compounds 1 and 3 crystallize in the same monoclinic P21/c space group. Since the only difference between them is the para substitution on the aryl group, the electronic nature of these NO2 and halogen groups seems to have no influence over the formation of the solid. However, a probable correlation with the size of the groups is not discarded due to the similar inter

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Sokolova, K. V., V. V. Stavytskyi, S. О. Konovalova, O. A. Podpletnya, S. I. Kovalenko, and A. P. Avdeenko. "Design and search for prospective diuretics (CA II Inhibitors) among aroylhydrazones of esters quinone oxime using in silico and in vivo methodology." Medicni perspektivi 27, no. 4 (2022): 27–37. http://dx.doi.org/10.26641/2307-0404.2022.4.271120.

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The design and search for new selective inhibitors of CA II with a better pharmacological profile, which would cause minimal electrolyte disturbances in the body, remains an urgent problem of medical chemistry and pharmacology today. It is important that the discovered new classes of inhibitors do not always contain the main “pharmacophoric” function (sulfamide), which is characteristic of “classic” drugs (Acetazolamide, Methazolamide, Ethoxzolamide, Dorzolamide and others), but are derivatives of phenols, polyamines, coumarins/thiocoumarins, ureas, thioureas, hydroxamates, etc. These molecule

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Moreira, Bernardo Pereira, Izabella Cristina Andrade Batista, Naiara Clemente Tavares, et al. "Docking-Based Virtual Screening Enables Prioritizing Protein Kinase Inhibitors With In Vitro Phenotypic Activity Against Schistosoma mansoni." Frontiers in Cellular and Infection Microbiology 12 (July 5, 2022). http://dx.doi.org/10.3389/fcimb.2022.913301.

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Schistosomiasis is a parasitic neglected disease with praziquantel (PZQ) utilized as the main drug for treatment, despite its low effectiveness against early stages of the worm. To aid in the search for new drugs to tackle schistosomiasis, computer-aided drug design has been proved a helpful tool to enhance the search and initial identification of schistosomicidal compounds, allowing fast and cost-efficient progress in drug discovery. The combination of high-throughput in silico data followed by in vitro phenotypic screening assays allows the assessment of a vast library of compounds with the

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Simoben, Conrad V., Fidele Ntie-Kang, Dina Robaa, and Wolfgang Sippl. "Case studies on computer-based identification of natural products as lead molecules." Physical Sciences Reviews 5, no. 10 (2020). http://dx.doi.org/10.1515/psr-2018-0119.

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AbstractThe development and application of computer-aided drug design/discovery (CADD) techniques (such as structured-base virtual screening, ligand-based virtual screening and neural networks approaches) are on the point of disintermediation in the pharmaceutical drug discovery processes. The application of these CADD methods are standing out positively as compared to other experimental approaches in the identification of hits. In order to venture into new chemical spaces, research groups are exploring natural products (NPs) for the search and identification of new hits and more efficient lea

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Rahman, Md Mominur, Md Rezaul Islam, Shopnil Akash, et al. "In silico investigation and potential therapeutic approaches of natural products for COVID-19: Computer-aided drug design perspective." Frontiers in Cellular and Infection Microbiology 12 (August 22, 2022). http://dx.doi.org/10.3389/fcimb.2022.929430.

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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a substantial number of deaths around the world, making it a serious and pressing public health hazard. Phytochemicals could thus provide a rich source of potent and safer anti-SARS-CoV-2 drugs. The absence of approved treatments or vaccinations continues to be an issue, forcing the creation of new medicines. Computer-aided drug design has helped to speed up the drug research and development process by decreasing costs and time. Natural compounds like terpenoids, alkaloids, polyphenols, and flavonoid derivatives have a

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Proj, Matic, Steven De Jonghe, Tom Van Loy, et al. "A Set of Experimentally Validated Decoys for the Human CC Chemokine Receptor 7 (CCR7) Obtained by Virtual Screening." Frontiers in Pharmacology 13 (March 18, 2022). http://dx.doi.org/10.3389/fphar.2022.855653.

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We present a state-of-the-art virtual screening workflow aiming at the identification of novel CC chemokine receptor 7 (CCR7) antagonists. Although CCR7 is associated with a variety of human diseases, such as immunological disorders, inflammatory diseases, and cancer, this target is underexplored in drug discovery and there are no potent and selective CCR7 small molecule antagonists available today. Therefore, computer-aided ligand-based, structure-based, and joint virtual screening campaigns were performed. Hits from these virtual screenings were tested in a CCL19-induced calcium signaling as

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Sahu, Ankita, Saurabh Verma, Dibyabhaba Pradhan, Khalid Raza, Sahar Qazi, and A. K. Jain. "Computational screening for finding new potent cox-2 inhibitors as anticancer agents." Letters in Drug Design & Discovery 19 (January 28, 2022). http://dx.doi.org/10.2174/1570180819666220128122553.

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Background: Breast cancer ranks first in women and the second most common type of cancer overall. It is the most important barrier to the rise of life expectancy, globally affecting disease modalities. Cyclooxygenase-2 (COX-2) has become a prominent hallmark as inhibition target for breast cancer, and this therapeutic target for anti-inflammatory drugs regulates cell proliferation, angiogenesis, tumor growth and apoptosis. There is a need to explore new anti-cancerous drugs for searching the best possible hit candidates for cancer treatment. The computer-aided drug design approach was conducte

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Gahbauer, Stefan, Galen J. Correy, Marion Schuller, et al. "Iterative computational design and crystallographic screening identifies potent inhibitors targeting the Nsp3 macrodomain of SARS-CoV-2." Proceedings of the National Academy of Sciences 120, no. 2 (2023). http://dx.doi.org/10.1073/pnas.2212931120.

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The nonstructural protein 3 (NSP3) of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) contains a conserved macrodomain enzyme (Mac1) that is critical for pathogenesis and lethality. While small-molecule inhibitors of Mac1 have great therapeutic potential, at the outset of the COVID-19 pandemic, there were no well-validated inhibitors for this protein nor, indeed, the macrodomain enzyme family, making this target a pharmacological orphan. Here, we report the structure-based discovery and development of several different chemical scaffolds exhibiting low- to sub-micromolar affin

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