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Journal articles on the topic 'Computer-Aided Drug Discovery and Design (CADD)'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Niazi, Sarfaraz K., and Zamara Mariam. "Computer-Aided Drug Design and Drug Discovery: A Prospective Analysis." Pharmaceuticals 17, no. 1 (2023): 22. http://dx.doi.org/10.3390/ph17010022.

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In the dynamic landscape of drug discovery, Computer-Aided Drug Design (CADD) emerges as a transformative force, bridging the realms of biology and technology. This paper overviews CADDs historical evolution, categorization into structure-based and ligand-based approaches, and its crucial role in rationalizing and expediting drug discovery. As CADD advances, incorporating diverse biological data and ensuring data privacy become paramount. Challenges persist, demanding the optimization of algorithms and robust ethical frameworks. Integrating Machine Learning and Artificial Intelligence amplifie

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Apurva, Patel1 Astha Sachdeva2. "Computer Aided Drug Design." International Journal of Pharmaceutical Sciences 3, no. 5 (2025): 2645–51. https://doi.org/10.5281/zenodo.15432398.

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Computer-Aided Drug Design (CADD) has emerged as a transformative approach in pharmaceutical research, integrating computational tools and molecular modeling techniques to accelerate and optimize the drug discovery process. This review provides a comprehensive overview of the fundamental principles, methodologies, and applications of CADD, including structure-based and ligand-based drug design, molecular docking, pharmacophore modeling, and virtual screening. Advances in bioinformatics, artificial intelligence, and high- performance computing have significantly enhanced the accuracy and effici

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Ugariogu, Sylvester Nnaemeka. "Natural Product Chemistry and Computer Aided Drug Design an Approach to Drug Discovery: A Review Article." International Journal of Pharmacognosy & Chinese Medicine 4, no. 3 (2020): 1–8. http://dx.doi.org/10.23880/ipcm-16000207.

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Natural products have been an inherent part of sustaining acculturation because of their medicinal properties. Past discoveries of bioactive natural products have relied on serendipity and accidental experience, and these compounds serve as inspiration for the generation of analogs with desired physicochemical properties. Bioactive natural products with therapeutic potential are abundantly available in nature and some of them are beyond exploration by conventional methods. However there has been a great breakthrough in the study of computer aided drug design (CADD) as many unfruitful lab resea

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KIRBOĞA, Kevser Kübra, and Ecir KÜÇÜKSİLLE. "Bilgisayar Destekli İlaç Keşfi Üzerine Bakışlar." Dicle Üniversitesi Fen Bilimleri Enstitüsü Dergisi 11, no. 2 (2022): 1. http://dx.doi.org/10.55007/dufed.1103457.

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The drug development and discovery process are challenging, take 15 to 20 years, and require approximately 1.5-2 billion dollars, from the critical selection of the target molecule to post-clinical market application. Several computational drug design methods identify and optimize target biologically lead compounds. Given the complexity and cost of the drug discovery process in recent years, computer-assisted drug discovery (CADD) has spread over a broad spectrum. CADD methods support the discovery of target molecules, optimization of small target molecules, analysis, and development processes

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Wang, Ge, Yuhao Bai, Jiarui Cui, Zirui Zong, Yuan Gao, and Zhen Zheng. "Computer-Aided Drug Design Boosts RAS Inhibitor Discovery." Molecules 27, no. 17 (2022): 5710. http://dx.doi.org/10.3390/molecules27175710.

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The Rat Sarcoma (RAS) family (NRAS, HRAS, and KRAS) is endowed with GTPase activity to regulate various signaling pathways in ubiquitous animal cells. As proto-oncogenes, RAS mutations can maintain activation, leading to the growth and proliferation of abnormal cells and the development of a variety of human cancers. For the fight against tumors, the discovery of RAS-targeted drugs is of high significance. On the one hand, the structural properties of the RAS protein make it difficult to find inhibitors specifically targeted to it. On the other hand, targeting other molecules in the RAS signal

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Pranali R. Bhujade, Khemutai G. Shedame, Pooja R. Hatwar, Dr. Ravindra L. Bakal, Krushnali N. Nehar, and Ankita Y.Gawai. "A Review on Computer Aided Drug Design – In Silico." Asian Journal of Pharmaceutical Research and Development 12, no. 6 (2024): 80–85. https://doi.org/10.22270/ajprd.v12i6.1467.

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The process of drug discovery takes a long time and costs a lot of money. Computer-Aided Drug Design (CADD) has become an important part of modern drug discovery because it speeds up the process and lowers prices. CADD includes many methods, such as Structure-Based Drug Design (SBDD) and Ligand-Based Drug Design (LBDD). These use computer programs to do things like molecular docking, virtual screening, QSAR, pharmacophore modeling, and molecular dynamics. LBDD is used when the shapes of receptors are unknown, while SBDD uses machine learning. This review provides a comprehensive overview of CA

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Dorahy, Georgia, Jake Zheng Chen, and Thomas Balle. "Computer-Aided Drug Design towards New Psychotropic and Neurological Drugs." Molecules 28, no. 3 (2023): 1324. http://dx.doi.org/10.3390/molecules28031324.

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Central nervous system (CNS) disorders are a therapeutic area in drug discovery where demand for new treatments greatly exceeds approved treatment options. This is complicated by the high failure rate in late-stage clinical trials, resulting in exorbitant costs associated with bringing new CNS drugs to market. Computer-aided drug design (CADD) techniques minimise the time and cost burdens associated with drug research and development by ensuring an advantageous starting point for pre-clinical and clinical assessments. The key elements of CADD are divided into ligand-based and structure-based m

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Sharma, Anu, Lalubhai Jangid, Nusrat Shaikh, and Jitendra Bhangale. "Computer-Aided Drug Design Boon in Drug Discovery." Asian Journal of Organic & Medicinal Chemistry 7, no. 1 (2022): 55–64. http://dx.doi.org/10.14233/ajomc.2022.ajomc-p361.

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An innovative sequential step of detecting new medicines or drugs dependent on the information of a target is called drug design. The drug is a small molecule that alters the capacity of a bimolecular, example, protein, receptor or catalyst that leads to restorative incentive for patients. Designing of drug by computational method helped steady use of computational science to find, improve and study drugs as well as biologically related active molecules. The displaying examines like the structure-based plan; ligand-based drugs structure; database looking and restricting partiality dependent on

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Namitha K N and V Velmurugan. "Review of bioinformatic tools used in Computer Aided Drug Design (CADD)." World Journal of Advanced Research and Reviews 14, no. 2 (2022): 453–65. http://dx.doi.org/10.30574/wjarr.2022.14.2.0394.

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Drug discovery is а time consuming рrосess of finding out a new drug molecule. The process takes many years to complete and needs human resource. These is difficulties have been overcome by introducing computer programmes in drug discovery (CADD) which includes target identification, hit identification, and molecular modification of а lead compound to optimize desired effects and minimize side effects, based on the knowledge of their biological targets. Molecular modelling is the process of designing a molecule with a computer-based collection of programmes (in-silico design) for deriving, rep

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Namitha, K. N., and Velmurugan V. "Review of bioinformatic tools used in Computer Aided Drug Design (CADD)." World Journal of Advanced Research and Reviews 14, no. 2 (2022): 453–65. https://doi.org/10.5281/zenodo.7298898.

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Drug discovery is а time consuming рrосess of finding out a new drug molecule. The process takes many years to complete and needs human resource. These is difficulties have been overcome by introducing computer programmes in drug discovery (CADD) which includes target identification, hit identification, and molecular modification of а lead compound to optimize desired effects and minimize side effects, based on the knowledge of their biological targets. Molecular modelling is the process of designing a molecule with a computer-based collection of programmes (in-silico design) for deriving, rep

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Natolotriniavo Tendrinarisoa RANDRIAMAMISOLONIRINA, Olivier Fridolin MAMINIAINA, Andriambandaina Abel ANDRIANTSIMAHAVANDY, and Mirantsoa Suzanne RAZAFINDRAFARA. "Application of computer-aided drug design in drug discovery and development: Updating knowledge." GSC Advanced Research and Reviews 21, no. 1 (2024): 209–27. http://dx.doi.org/10.30574/gscarr.2024.21.1.0360.

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Coronavirus (CoV) diseases are widespread throughout the world and have caused considerable socio-economic disruptions. For this reason, efforts have been made to develop a direct or indirect antiviral drugs against these diseases. However, no specific antiviral drug has yet been approved by the Food and Drug Administration (FDA) for CoV infections. Thus, the challenge in discovering therapeutic molecules against these infections remains pertinent. Computer-aided drug design (CADD) is one of the modern techniques for drug discovery and development. It accelerates the process, minimizes costs,

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Surabhi, Surabhi, and BK Singh. "COMPUTER AIDED DRUG DESIGN: AN OVERVIEW." Journal of Drug Delivery and Therapeutics 8, no. 5 (2018): 504–9. http://dx.doi.org/10.22270/jddt.v8i5.1894.

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Discovery and development of a new drug is generally known as a very complex process which takes a lot of time and resources. So now a day’s computer aided drug design approaches are used very widely to increase the efficiency of the drug discovery and development course. Various approaches of CADD are evaluated as promising techniques according to their need, in between all these structure-based drug design and ligand-based drug design approaches are known as very efficient and powerful techniques in drug discovery and development. These both methods can be applied with molecular docking to v

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Niranjan, Divya, Simran Gill, Deepali Shrivastava, Aakash Jain, and Om Prakash Agrawal. "Quantitative Structure Activity Relationships in Computer Aided Drug Design: A Review." Journal of Drug Delivery and Therapeutics 9, no. 3 (2019): 645–49. http://dx.doi.org/10.22270/jddt.v9i3.2662.

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The process of processing a drug and reaching to the market consists of various steps. In the early times of Drug Discovery, researchers faced with little or no Structure Activity Relationships information regarding any chemical moiety. Computer Aided Drug Designing (CADD) is a discipline allowing various aspects of research to merge together and stimulate each other. CADD acts as a tunnel in Drug Discovery and accelerates finding new lead compounds. The theoretical basis of CADD involves quantum mechanics and molecular modelling studies like Structure-based design, Ligand-based design, databa

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Guo, Jiao, Yang Bai, Yan Guo, Meihua Wang, Xinxin Ji, and Yang Wang. "Drug Discovery for SARS-CoV-2 Utilizing Computer-Aided Drug Design Approaches." COVID 5, no. 3 (2025): 32. https://doi.org/10.3390/covid5030032.

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive-sense RNA virus with an unusually large genome of approximately 30 kb. It is highly transmissible and exhibits broad tissue tropism. The third most pathogenic of all known coronaviruses, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is responsible for the clinical manifestation known as coronavirus disease 2019 (COVID-19), which has resulted in the loss of millions of lives on a global scale. This pandemic has prompted significant efforts to develop therapeutic strategies that target the virus and/or hum

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Oli, Bharti. "Revolutionizing Drug Discovery: A Comprehensive Review of Computer-Aided Drug Design Approaches." International Journal for Research in Applied Science and Engineering Technology 12, no. 7 (2024): 308–17. http://dx.doi.org/10.22214/ijraset.2024.63563.

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Abstract: Computer-Aided Drug Design (CADD) has significantly advanced the drug discovery process, offering tools to enhance efficiency and reduce costs. This review explores essential CADD methodologies, including molecular docking, virtual screening, ADMET profiling, homology modeling, and Quantitative Structure-Activity Relationship (QSAR) models. Molecular docking predicts interactions between drugs and targets, while virtual screening evaluates large compound libraries to identify promising candidates. ADMET profiling assesses pharmacokinetic and toxicological properties early in developm

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Shi, Peiyang. "Research on the application of computer in drug design." Applied and Computational Engineering 34, no. 1 (2024): 18–22. http://dx.doi.org/10.54254/2755-2721/34/20230289.

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Virtual screening by computer is of great scientific significance for drug research and development. In recent years, a large number of computer simulation methods have been developed and applied to drug development for a variety of diseases. This paper summarized and prospected the application progress of computer aided drug design (CADD) in the research and development of new drugs, focusing on the working principle of CADD, related algorithms, and the advantages and disadvantages of existing methods. Although CADD has been successfully applied to a number of drug development projects, the a

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Kumar, Nilandu, Yash Shrivastava, and Dr Shilpa Sivashankar. "Insilico Simulation Studies for Tuberculosis Drug Discovery and its Response." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 008 (2024): 1–4. http://dx.doi.org/10.55041/ijsrem37244.

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From high treatment and with such precaution measures TB (Tuberculosis) came with leading cause of deaths in the world. For Tuberculosis it increasing drug resistance for different kind of TB like Multidrug-resistant TB and Extensively drug-resistant TB, increasing relapse and in efficiency of drug for TB pathogen.it take longer duration, it affect on human body with infection from HIV and other autoimmune disorder have pushed it to a lethal level and for this we need more effective drugs. With the help of CADD technology we can findout more viable drug molecules for the better treatment of My

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Sachin, Wankhede1 Komal Bonde2 Chetan Kedari 3. Wavhal Ramesh4 Akash Tiwari5 Pratiksha Patil6*. "Computer-Aided Drug Design, Synthesis, and Evaluation of New Anti-Cancer Drugs." International Journal of Pharmaceutical Sciences 3, no. 3 (2025): 822–37. https://doi.org/10.5281/zenodo.15004258.

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Computer-aided drug design (CADD) has become a transformative tool in the discovery, synthesis, and evaluation of new anti-cancer drugs. By leveraging advanced computational techniques, CADD enables the efficient identification of potential drug candidates by simulating the interactions between drugs and biological targets, optimizing molecular structures, and predicting drug properties such as absorption, distribution, metabolism, excretion, and toxicity (ADMET). The integration of artificial intelligence (AI) and machine learning (ML) further accelerates the design of novel therapeutic molec

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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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Yu, Dahai, Linlin Wang, and Ye Wang. "Recent Advances in Application of Computer-Aided Drug Design in Anti-Influenza A Virus Drug Discovery." International Journal of Molecular Sciences 23, no. 9 (2022): 4738. http://dx.doi.org/10.3390/ijms23094738.

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Influenza A is an acute respiratory infectious disease caused by the influenza A virus, which seriously threatens global human health and causes substantial economic losses every year. With the emergence of new viral strains, anti-influenza drugs remain the most effective treatment for influenza A. Research on traditional, innovative small-molecule drugs faces many challenges, while computer-aided drug design (CADD) offers opportunities for the rapid and effective development of innovative drugs. This literature review describes the general process of CADD, the viral proteins that play an esse

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Yu, Dahai, Linlin Wang, and Ye Wang. "Recent Advances in Application of Computer-Aided Drug Design in Anti-Influenza A Virus Drug Discovery." International Journal of Molecular Sciences 23, no. 9 (2022): 4738. http://dx.doi.org/10.3390/ijms23094738.

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Influenza A is an acute respiratory infectious disease caused by the influenza A virus, which seriously threatens global human health and causes substantial economic losses every year. With the emergence of new viral strains, anti-influenza drugs remain the most effective treatment for influenza A. Research on traditional, innovative small-molecule drugs faces many challenges, while computer-aided drug design (CADD) offers opportunities for the rapid and effective development of innovative drugs. This literature review describes the general process of CADD, the viral proteins that play an esse

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Rakesh, Palepu Narasimha. "A Data Science Approach to Bioinformatics." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (2021): 3860–69. http://dx.doi.org/10.22214/ijraset.2021.37221.

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Computer aided drug design (CADD) which uses the computational advance towards to develop, discover and scrutinize and examine drugs and alike biologically agile molecules. CADD is a specialized stream which uses the computational techniques to mimic drug-receptor interactions. CADD procedures are so much dependent on the tools of bioinformatics, databases & applications. There are so many advantages of computer aided drug discovery; it saves lot of time which is one of the main advantages followed by low cost and more accuracy. CADD required less manpower to work. There are different type

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Kanwar, Gurtej, Anish Kumar, and Anshika Mahajan. "Open source software tools for computer aided drug design." International Journal of Research in Pharmaceutical Sciences 9, no. 1 (2018): 86. http://dx.doi.org/10.26452/ijrps.v9i1.1191.

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Computer-aided drug design (CADD) has revolutionized the drug discovery arena and it has reduced the costs associated with finding novel compounds which are having pharmaceutical importance. In CADD, the scientists use the computer software to discover biological active compounds. Molecular docking and energy minimization tools are essential components of structure based drug design. It is a significant tool in structural molecular biology and computer-assisted drug design. It reduces the laboratory workload of the end user and allows researchers to restrict their docking studies to the smalle

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Kiran, Kumari* Muskan Thakur Sahil Dhiman Shubham Dhiman. "ROLE OF COMPUTER AIDED DRUG DESIGN IN MODERN DRUG DISCOVERY." International Journal in Pharmaceutical Sciences 2, no. 5 (2024): 157–62. https://doi.org/10.5281/zenodo.11114895.

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When combined with modern chemical biology screening techniques, computer assisted drug design is a potent tool for finding viable drug candidates. Despite the limitations and approximations it employs, CADD has emerged as a crucial step in the drug design process because of its capacity to expedite the discovery of new drugs by drawing on existing knowledge and theories about receptor-ligand interactions, energy and structural optimization, and synthesis. However, there is still potential for advancements, particularly with regard to scoring functions, taking into account solvent and molecula

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Sobral, Patrícia S., Tiago Carvalho, Shiva Izadi, et al. "Advancements in drug discovery: integrating CADD tools and drug repurposing for PD-1/PD-L1 axis inhibition." RSC Advances 15, no. 4 (2025): 2298–316. https://doi.org/10.1039/d4ra08245a.

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A pioneering strategy to expedite drug discovery for PD-1/PD-L1 axis inhibition is offered by an integrated approach combining computer-aided drug design (CADD) tools, QSAR modelling, drug repurposing, and molecular docking.

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Ahirwar, Hemant, Gabbar Kurmi, Rubeena Khan, et al. "Review on QSAR using Anticancer Drug." Asian Journal of Dental and Health Sciences 2, no. 4 (2022): 59–63. http://dx.doi.org/10.22270/ajdhs.v2i4.27.

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New drug discovery has been acknowledged as a complicated, expensive, time-consuming, and challenging project. It has been estimated that around 12 years and 2.7 billion USD, on average, are demanded for a new drug discovery via traditional drug development pipeline. How to reduce the research cost and speed up the development process of new drug discovery has become a challenging, urgent question for the pharmaceutical industry. Computer-aided drug discovery (CADD) has emerged as a powerful and promising technology for faster, cheaper and more effective drug design. Recently, the rapid growth

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Kumar, Sanjiv. "ROLE OF COMPUTER-AIDED DRUG DESIGN IN THE DISCOVERY AND DEVELOPMENT OF NEW MEDICINAL AGENTS A REVIEW." Journal of medical pharmaceutical and allied sciences 11, no. 3 (2022): 4794–801. http://dx.doi.org/10.55522/jmpas.v11i3.2300.

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Drug design and development is a time consuming and costly process. Nowadays, computer-aided drug design approaches are usually used to improve drug discovery and advancement efficiency. The role of Computer-Aided Drug Design (CADD) is a diverse discipline in which various versions of applied and basic analysis are interlinked. It is being implemented in various fields including biochemistry, molecular biology, nanotechnology etc. Various employed computational approaches includes ligand-based drug design, structure-based drug design, quantitative structure-property relationships and quantitat

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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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Radan, Milica, Jelena Bošković, Vladimir Dobričić, Olivera Čudina, and Katarina Nikolić. "Current computer-aided drug design methodologies in discovery of novel drug candidates for neuropsychiatric and inflammatory diseases." Arhiv za farmaciju 71, no. 4 (2021): 225–56. http://dx.doi.org/10.5937/arhfarm71-32523.

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Drug discovery and development is a very challenging, expensive and time-consuming process. Impressive technological advances in computer sciences and molecular biology have made it possible to use computer-aided drug design (CADD) methods in various stages of the drug discovery and development pipeline. Nowadays, CADD presents an efficacious and indispensable tool, widely used in medicinal chemistry, to lead rational drug design and synthesis of novel compounds. In this article, an overview of commonly used CADD approaches from hit identification to lead optimization was presented. Moreover,

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Li, Linwei, Songtao Liu, Bi Wang, et al. "An Updated Review on Developing Small Molecule Kinase Inhibitors Using Computer-Aided Drug Design Approaches." International Journal of Molecular Sciences 24, no. 18 (2023): 13953. http://dx.doi.org/10.3390/ijms241813953.

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Small molecule kinase inhibitors (SMKIs) are of heightened interest in the field of drug research and development. There are 79 (as of July 2023) small molecule kinase inhibitors that have been approved by the FDA and hundreds of kinase inhibitor candidates in clinical trials that have shed light on the treatment of some major diseases. As an important strategy in drug design, computer-aided drug design (CADD) plays an indispensable role in the discovery of SMKIs. CADD methods such as docking, molecular dynamic, quantum mechanics/molecular mechanics, pharmacophore, virtual screening, and quant

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Sachin, S. Padole, J. Asnani Alpana, R. Chaple Dinesh, and G. Katre Soumya. "A review of approaches in computer-aided drug design in drug discovery." GSC Biological and Pharmaceutical Sciences 19, no. 2 (2022): 075–83. https://doi.org/10.5281/zenodo.6627446.

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The process of discovering and developing a new medication is often seen as a lengthy and expensive endeavors. As a result, computer-aided drug design methods are now frequently utilized to improve the efficiency of the drug discovery and development process. Various CADD approaches are regarded as potential techniques based on their needs; nevertheless, structure-based drug design and ligand-based drug design approaches are well-known as highly efficient and powerful strategies in drug discovery and development. Both of these approaches may be used in conjunction with molecular docking to con

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Bassani, Davide, and Stefano Moro. "Past, Present, and Future Perspectives on Computer-Aided Drug Design Methodologies." Molecules 28, no. 9 (2023): 3906. http://dx.doi.org/10.3390/molecules28093906.

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The application of computational approaches in drug discovery has been consolidated in the last decades. These families of techniques are usually grouped under the common name of “computer-aided drug design” (CADD), and they now constitute one of the pillars in the pharmaceutical discovery pipelines in many academic and industrial environments. Their implementation has been demonstrated to tremendously improve the speed of the early discovery steps, allowing for the proficient and rational choice of proper compounds for a desired therapeutic need among the extreme vastness of the drug-like che

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Gurung, Arun Bahadur, Mohammad Ajmal Ali, Joongku Lee, Mohammad Abul Farah, and Khalid Mashay Al-Anazi. "An Updated Review of Computer-Aided Drug Design and Its Application to COVID-19." BioMed Research International 2021 (June 24, 2021): 1–18. http://dx.doi.org/10.1155/2021/8853056.

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The recent outbreak of the deadly coronavirus disease 19 (COVID-19) pandemic poses serious health concerns around the world. The lack of approved drugs or vaccines continues to be a challenge and further necessitates the discovery of new therapeutic molecules. Computer-aided drug design has helped to expedite the drug discovery and development process by minimizing the cost and time. In this review article, we highlight two important categories of computer-aided drug design (CADD), viz., the ligand-based as well as structured-based drug discovery. Various molecular modeling techniques involved

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Sachin S Padole, Alpana J Asnani, Dinesh R Chaple, and Soumya G Katre. "A review of approaches in computer-aided drug design in drug discovery." GSC Biological and Pharmaceutical Sciences 19, no. 2 (2022): 075–83. http://dx.doi.org/10.30574/gscbps.2022.19.2.0161.

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The process of discovering and developing a new medication is often seen as a lengthy and expensive endeavors. As a result, computer-aided drug design methods are now frequently utilized to improve the efficiency of the drug discovery and development process. Various CADD approaches are regarded as potential techniques based on their needs; nevertheless, structure-based drug design and ligand-based drug design approaches are well-known as highly efficient and powerful strategies in drug discovery and development. Both of these approaches may be used in conjunction with molecular docking to con

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Yadav, Manoj Kumar, Triloki Prasad, Rubal Rathi, et al. "An overview of Quinazolines: Applicability of molecular docking in Cancer therapy." International Journal of Pharma Professional’s Research (IJPPR) 14, no. 2 (2023): 36–54. http://dx.doi.org/10.48165/ijppronline.2023.14204.

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Medicinal chemistry is distracted with the elaboration, discovery, confirmation of physical and chemical approaches, and the synthesis in laboratory. Quinazoline derivatives occupy crucial positions in modern medicinal chemistry and possess established application as medicine. Several researches have been accomplished on derivatives of the quinazoline for different many pharmacological activity are reported recently. The most important process molecular docking modification is the preliminary step in the drug designing of novel drugs. The main aim of this review is to quiz or examine recently

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Paiman, Arif, Ahmad Mohammad, and Mubashar Rehman. "Role of Computer Aided Drug Design in Modern Drug Discovery and Pharmacokinetic Prediction." Global Drug Design & Development Review II, no. I (2017): 1–8. http://dx.doi.org/10.31703/gdddr.2017(ii-i).01.

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In modern day, Data on different diseases and drug substances with their properties like modification, side effects, and dose requires documentation data and building library exploring, such library with vast information in every aspect needs computational methods used in CADD. Recognition of specific targets for the drug tested and defining pharmacological activity of a drug candidate based on the structure of both drug and its target, finding outside effects of drugs at the molecular level and calculation of toxicity caused by metabolism of drug applications of Computer aided drug design in

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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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Lin, Yipeng. "Review of Modern Computer-aided Drug Design Methods." International Journal of Biology and Life Sciences 1, no. 1 (2022): 47–50. http://dx.doi.org/10.54097/ijbls.v1i1.3230.

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Computer technology has developed rapidly in recent decades, and it is also widely used in the field of drug research and development. Computer-aided drug design (CADD) has appeared in the form of assistance to drug discovery process in this background. Computer-aided drug design can save time which is spent in the experimental process in the real world. Since appearance of computer-based drug design strategies, the concepts of HTS, structure-based and ligand-based drug design (SBDD and LBDD), and virtual screening (VS) have been proposed. These technologies have their own advantages and disad

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Bafna, Divya, Fuqiang Ban, Paul S. Rennie, Kriti Singh, and Artem Cherkasov. "Computer-Aided Ligand Discovery for Estrogen Receptor Alpha." International Journal of Molecular Sciences 21, no. 12 (2020): 4193. http://dx.doi.org/10.3390/ijms21124193.

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Breast cancer (BCa) is one of the most predominantly diagnosed cancers in women. Notably, 70% of BCa diagnoses are Estrogen Receptor α positive (ERα+) making it a critical therapeutic target. With that, the two subtypes of ER, ERα and ERβ, have contrasting effects on BCa cells. While ERα promotes cancerous activities, ERβ isoform exhibits inhibitory effects on the same. ER-directed small molecule drug discovery for BCa has provided the FDA approved drugs tamoxifen, toremifene, raloxifene and fulvestrant that all bind to the estrogen binding site of the receptor. These ER-directed inhibitors ar

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Makhouri, Farahnaz R., and Jahan B. Ghasemi. "Combating Diseases with Computational Strategies Used for Drug Design and Discovery." Current Topics in Medicinal Chemistry 18, no. 32 (2019): 2743–73. http://dx.doi.org/10.2174/1568026619666190121125106.

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Computer-aided drug discovery (CADD) tools have provided an effective way in the drug discovery pipeline for expediting of this long process and economizing the cost of research and development. Due to the dramatic increase in the availability of human proteins as drug targets and small molecule information due to the advances in bioinformatics, cheminformatics, genomics, proteomics, and structural information, the applicability of in silico drug discovery has been extended. Computational approaches have been used at almost all stages in the drug discovery pipeline including target identificat

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de Araújo, Rodrigo Santos Aquino, Edeildo Ferreira da Silva-Junior, Thiago Mendonça de Aquino, et al. "Computer-Aided Drug Design Applied to Secondary Metabolites as Anticancer Agents." Current Topics in Medicinal Chemistry 20, no. 19 (2020): 1677–703. http://dx.doi.org/10.2174/1568026620666200607191838.

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: Computer-Aided Drug Design (CADD) techniques have garnered a great deal of attention in academia and industry because of their great versatility, low costs, possibilities of cost reduction in in vitro screening and in the development of synthetic steps; these techniques are compared with highthroughput screening, in particular for candidate drugs. The secondary metabolism of plants and other organisms provide substantial amounts of new chemical structures, many of which have numerous biological and pharmacological properties for virtually every existing disease, including cancer. In oncology

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Garg, Pankaj, Gargi Singhal, Prakash Kulkarni, David Horne, Ravi Salgia, and Sharad S. Singhal. "Artificial Intelligence–Driven Computational Approaches in the Development of Anticancer Drugs." Cancers 16, no. 22 (2024): 3884. http://dx.doi.org/10.3390/cancers16223884.

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The integration of AI has revolutionized cancer drug development, transforming the landscape of drug discovery through sophisticated computational techniques. AI-powered models and algorithms have enhanced computer-aided drug design (CADD), offering unprecedented precision in identifying potential anticancer compounds. Traditionally, cancer drug design has been a complex, resource-intensive process, but AI introduces new opportunities to accelerate discovery, reduce costs, and optimize efficiency. This manuscript delves into the transformative applications of AI-driven methodologies in predict

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Gaudêncio, Susana P., and Florbela Pereira. "A Computer-Aided Drug Design Approach to Predict Marine Drug-Like Leads for SARS-CoV-2 Main Protease Inhibition." Marine Drugs 18, no. 12 (2020): 633. http://dx.doi.org/10.3390/md18120633.

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The investigation of marine natural products (MNPs) as key resources for the discovery of drugs to mitigate the COVID-19 pandemic is a developing field. In this work, computer-aided drug design (CADD) approaches comprising ligand- and structure-based methods were explored for predicting SARS-CoV-2 main protease (Mpro) inhibitors. The CADD ligand-based method used a quantitative structure–activity relationship (QSAR) classification model that was built using 5276 organic molecules extracted from the ChEMBL database with SARS-CoV-2 screening data. The best model achieved an overall predictive ac

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Aditee, Kagde* Dr. Mrunal Shirsat Anjali Zende. "Drug Design: A Comprehensive Review." International Journal of Pharmaceutical Sciences 3, no. 1 (2025): 2548–52. https://doi.org/10.5281/zenodo.14774296.

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Drug design is a systematic and innovative process aimed at creating pharmaceutical compounds that interact with biological targets to treat or manage diseases. With recent advancements in computational biology and artificial intelligence, traditional methods of drug discovery are now complemented by highly efficient Computer-Aided Drug Design (CADD). This evolution has minimized resource expenditure, accelerated timelines, and enabled the exploration of complex disease mechanisms. This review elaborates on the principles, methodologies, applications, and the role of advanced software in drug

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Kumari, Uma, Nehal Balhara, and Ojas Singh. "Computer Aided Drug Designing Approach for Prospective Human Metastatic Cancer." International Journal for Research in Applied Science and Engineering Technology 11, no. 7 (2023): 1874–79. http://dx.doi.org/10.22214/ijraset.2023.550014.

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Abstract: It is well known that finding new drugs is a difficult, expensive, time-consuming, and expensive project. According to a study, the typical time and cost for developing a new medicine through the conventional drug development pipeline is 12 years and 2.7 billion dollars. The pharmaceutical industry is grappling with the difficult and pressing challenge of how to find new drugs faster and at lower research costs.Insilico,The field of computer-aided drug discovery (CADD) has shown significant promise as an advanced technology for secure, cost-effective, and efficient drug design. In re

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Zhu, Siyu, Meixian Wu, Ziwei Huang, and Jing An. "Trends in application of advancing computational approaches in GPCR ligand discovery." Experimental Biology and Medicine 246, no. 9 (2021): 1011–24. http://dx.doi.org/10.1177/1535370221993422.

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G protein-coupled receptors (GPCRs) comprise the most important superfamily of protein targets in current ligand discovery and drug development. GPCRs are integral membrane proteins that play key roles in various cellular signaling processes. Therefore, GPCR signaling pathways are closely associated with numerous diseases, including cancer and several neurological, immunological, and hematological disorders. Computer-aided drug design (CADD) can expedite the process of GPCR drug discovery and potentially reduce the actual cost of research and development. Increasing knowledge of biological str

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Cortat, Youri, Miroslava Nedyalkova, Kevin Schindler, et al. "Computer-Aided Drug Design and Synthesis of Rhenium Clotrimazole Antimicrobial Agents." Antibiotics 12, no. 3 (2023): 619. http://dx.doi.org/10.3390/antibiotics12030619.

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In the context of the global health issue caused by the growing occurrence of antimicrobial resistance (AMR), the need for novel antimicrobial agents is becoming alarming. Inorganic and organometallic complexes represent a relatively untapped source of antibiotics. Here, we report a computer-aided drug design (CADD) based on a ‘scaffold-hopping’ approach for the synthesis and antibacterial evaluation of fac-Re(I) tricarbonyl complexes bearing clotrimazole (ctz) as a monodentate ligand. The prepared molecules were selected following a pre-screening in silico analysis according to modification o

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Gómez-García, Alejandro, and José L. Medina-Franco. "Progress and Impact of Latin American Natural Product Databases." Biomolecules 12, no. 9 (2022): 1202. http://dx.doi.org/10.3390/biom12091202.

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Natural products (NPs) are a rich source of structurally novel molecules, and the chemical space they encompass is far from being fully explored. Over history, NPs have represented a significant source of bioactive molecules and have served as a source of inspiration for developing many drugs on the market. On the other hand, computer-aided drug design (CADD) has contributed to drug discovery research, mitigating costs and time. In this sense, compound databases represent a fundamental element of CADD. This work reviews the progress toward developing compound databases of natural origin, and i

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Hsieh, Chia-Ju, Sam Giannakoulias, E. James Petersson, and Robert H. Mach. "Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development." Pharmaceuticals 16, no. 2 (2023): 317. http://dx.doi.org/10.3390/ph16020317.

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The use of computer-aided drug design (CADD) for the identification of lead compounds in radiotracer development is steadily increasing. Traditional CADD methods, such as structure-based and ligand-based virtual screening and optimization, have been successfully utilized in many drug discovery programs and are highlighted throughout this review. First, we discuss the use of virtual screening for hit identification at the beginning of drug discovery programs. This is followed by an analysis of how the hits derived from virtual screening can be filtered and culled to highly probable candidates t

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Chua, Hui Ming, Said Moshawih, Hui Poh Goh, Long Chiau Ming, and Nurolaini Kifli. "Insights into the computer-aided drug design and discovery based on anthraquinone scaffold for cancer treatment: A protocol for systematic review." PLOS ONE 18, no. 9 (2023): e0290948. http://dx.doi.org/10.1371/journal.pone.0290948.

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There is still unmet medical need in cancer treatment mainly due to drug resistance and adverse drug events. Therefore, the search for better drugs is essential. Computer-aided drug design (CADD) and discovery tools are useful to streamline the lengthy and costly drug development process. Anthraquinones are a group of naturally occurring compounds with unique scaffold that exert various biological properties including anticancer activities. This protocol describes a systematic review that provide insights into the computer-aided drug design and discovery based on anthraquinone scaffold for can

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