scholarly journals COMPUTER AIDED DRUG DESIGN: A MINI-REVIEW

2020 ◽  
Vol 9 (5) ◽  
pp. 2584-2591
Author(s):  
Aateka Y Barrawaz
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Development Process ◽  
De Novo ◽  
Computer Aided Drug Design ◽  
Drug Discovery And Development ◽  
Research Activities ◽  
Complex Process ◽  
Computer Aided ◽  
New Chemical Entities

New drug discovery and development process is considered much complex process which is time consuming and resources accommodating too. So computer aided drug design are being broadly used to enhance the effectiveness of the drug discovery and development process which ultimately saves time and resources. Various approaches to Computer aided drug design are evaluated to shows potential techniques in accordance with their needs. Two approaches are considered to designing of drug first one is structure-based and second one is Ligand based drug designs. In this review, we are discussing about highly effective and powerful techniques for drug discovery and development as well as various methods of Computer aided drug design like molecular docking at virtual screening for lead identification, QSAR, molecular homology, de-novo design, molecular modeling and optimization. It also elaborate about different software used in Computer aided drug design, different application of Computer aided drug design etc. Major objectives of Computer aided drug design are to commence collaborative foundation of research activities and to discover new chemical entities for novel therapeutics drugs

scholarly journals COMPUTER AIDED DRUG DESIGN: AN OVERVIEW

2018 ◽  
Vol 8 (5) ◽  
pp. 504-509 ◽  
Author(s):  
Surabhi Surabhi ◽  
BK Singh
Keyword(s):  
Molecular Docking ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Drug Design ◽  
Computer Aided Drug Design ◽  
Structure Based Drug Design ◽  
Drug Discovery And Development ◽  
Research Areas ◽  
Computer Aided ◽  
Pharmaceutical Industries

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 virtual screening for lead identification and optimization. In the recent times computational tools are widely used in pharmaceutical industries and research areas to improve effectiveness and efficacy of drug discovery and development pipeline. In this article we give an overview of computational approaches, which is inventive process of finding novel leads and aid in the process of drug discovery and development research. Keywords: computer aided drug discovery, structure-based drug design, ligand-based drug design, virtual screening and molecular docking

scholarly journals VIRTUAL SCREENING STATEGIES IN DRUG DISCOVERY – A BRIEF OVERVIEW

2021 ◽  
Vol 59 (4) ◽  
pp. 415
Author(s):  
Quan Minh PHAM ◽  
Long Quoc PHAM
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Development Process ◽  
Biological Activities ◽  
Computer Aided Drug Design ◽  
Computational Approaches ◽  
Drug Discovery And Development ◽  
Drug Lead ◽  
Lead Identification ◽  
Computer Aided

Computer-aided drug design has now become a compulsory tool in the drug discovery and development process which uses computational approaches to discover potential compounds with expected biological activities. Firstly, this review provides a comprehensive introduction of the virtual screening technique, knowledge and advances in both SBVS and LBVS strategies also presented. Secondly, recent database of compounds provided worldwide and drug-like parameters which are helpful in supporting the VS process will be discussed. These information will provides a good platform to estimate the advance of applying these techniques in the new drug-lead identification and optimization.

scholarly journals Current computer-aided drug design methodologies in discovery of novel drug candidates for neuropsychiatric and inflammatory diseases

2021 ◽  
Vol 71 (4) ◽  
pp. 225-256
Author(s):  
Milica Radan ◽  
Jelena Bošković ◽  
Vladimir Dobričić ◽  
Olivera Čudina ◽  
Katarina Nikolić
Keyword(s):  
Drug Discovery ◽  
Side Effects ◽  
Drug Design ◽  
Inflammatory Diseases ◽  
Rational Drug Design ◽  
Computer Aided Drug Design ◽  
Drug Discovery And Development ◽  
Rational Drug ◽  
Computer Aided ◽  
Anti Inflammatory

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, different aspects of design of multitarget ligands for neuropsychiatric and anti-inflammatory diseases were summarized. Apparently, designing multi-target directed ligands for treatment of various complex diseases may offer better efficacy, and fewer side effects. Antipsychotics that act through aminergic G protein-coupled receptors (GPCRs), especially Dopamine D2 and serotonin 5-HT2A receptors, are the best option for treatment of various symptoms associated with neuropsychiatric disorders. Furthermore, multi-target directed cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) inhibitors are also a successful approach to aid the discovery of new anti-inflammatory drugs with fewer side effects. Overall, employing CADD approaches in the process of rational drug design provides a great opportunity for future development, allowing rapid identification of compounds with the optimal polypharmacological profile.

scholarly journals COMPUTER AIDED DRUG DESIGN: A PARADIGM SHIFT TO RATIONAL DRUG DESIGN (A CASE STUDY OF ALZHEIMER’S DRUG INTERPIRDINE FAILURE)

2020 ◽  
Vol 4 (12) ◽  
pp. 13-18
Author(s):  
Dr. Kalpana Virendra Singh ◽  
Dr. Shobha Shouche ◽  
Dr. Ramchander Merugu ◽  
Dr. Jeeven Singh Solanki
Keyword(s):  
Clinical Trials ◽  
Drug Discovery ◽  
Drug Design ◽  
Final Stage ◽  
Financial Burden ◽  
Rational Drug Design ◽  
Financial Loss ◽  
Computer Aided Drug Design ◽  
Computer Aided

Drug discovery and design is a tedious and lengthy process which takes enormous time, andwhen this process reaches it’s final stage that is the final stage of clinical trials 90% of thepromising drug candidates fail levying a huge financial burden of around $2-3bn on thedeveloper company. The drug failure not only incurs a financial loss to the company, but alsosmashes the hopes of the patients and families waiting for the successful approval of the drug.The scenario is even complicated when it comes to the drug approval for diseases likeAlzheimer’s. Computer aided drug design may help in the drug discovery process by slashingthe time required for searching the potential drug target through computer aided software andprograms. However the key to the success of the drug still lies in the understanding of themechanism of the cause of disease and prognosis. Computer aided drug design help in theselection and modification of leads out of number of hits available. The present study dealswith a case study of Intepridine an ambitious Axovant drug molecule which failed in the finalphase of clinical trials and was withdrawn from the market by Axovant the developer pharmacompany.

From the Explored to the Unexplored: Computer-Tailored Drug Design Attempts in the Discovery of Selective Caspase Inhibitors

2019 ◽  
Vol 22 (7) ◽  
pp. 432-444
Author(s):  
Ransford O. Kumi ◽  
Abdul R. Issahaku ◽  
Opeyemi S. Soremekun ◽  
Clement Agoni ◽  
Fisayo A. Olotu ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Therapeutic Effects ◽  
Computer Aided Drug Design ◽  
Neurologic Diseases ◽  
Caspase Inhibitors ◽  
Caspase Inhibition ◽  
Selective Targeting ◽  
Computer Aided ◽  
The Brain

The pathophysiological roles of caspases have made them attractive targets in the treatment and amelioration of neurologic diseases. In normal conditions, the expression of caspases is regulated in the brain, while at the onset of neurodegeneration, such as in Alzheimer’s disease, they are typically overexpressed. Till date, several therapeutic efforts that include the use of small endogenous binders have been put forward to curtail dysfunctionalities that drive aberrant death in neuronal cells. Caspases are highly homologous, both in structure and in sequence, which leaves us with the question: is it possible to specifically and individually target caspases, while multiple therapeutic attempts to achieve selective targeting have failed! Based on antecedent events, the use of Computer-Aided Drug Design (CADD) methods has significantly contributed to the design of small molecule inhibitors, especially with selective target ability and reduced off-target therapeutic effects. Interestingly, we found out that there still exists an enormous room for the integration of structure/ligand-based drug design techniques towards the development of highly specific reversible and irreversible caspase inhibitors. Therefore, in this review, we highlight drug discovery approaches that have been directed towards caspase inhibition in addition to an insightful focus on applicable CADD techniques for achieving selective targeting in caspase research.

scholarly journals GenUI: interactive and extensible open source software platform for de novo molecular generation and cheminformatics

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
M. Sicho ◽  
X. Liu ◽  
D. Svozil ◽  
G. J. P. van Westen
Keyword(s):  
User Interface ◽  
Drug Discovery ◽  
Drug Design ◽  
Open Source ◽  
De Novo ◽  
Design Methods ◽  
Software Platform ◽  
De Novo Drug Design ◽  
Computer Aided ◽  
Generative Algorithms

AbstractMany contemporary cheminformatics methods, including computer-aided de novo drug design, hold promise to significantly accelerate and reduce the cost of drug discovery. Thanks to this attractive outlook, the field has thrived and in the past few years has seen an especially significant growth, mainly due to the emergence of novel methods based on deep neural networks. This growth is also apparent in the development of novel de novo drug design methods with many new generative algorithms now available. However, widespread adoption of new generative techniques in the fields like medicinal chemistry or chemical biology is still lagging behind the most recent developments. Upon taking a closer look, this fact is not surprising since in order to successfully integrate the most recent de novo drug design methods in existing processes and pipelines, a close collaboration between diverse groups of experimental and theoretical scientists needs to be established. Therefore, to accelerate the adoption of both modern and traditional de novo molecular generators, we developed Generator User Interface (GenUI), a software platform that makes it possible to integrate molecular generators within a feature-rich graphical user interface that is easy to use by experts of diverse backgrounds. GenUI is implemented as a web service and its interfaces offer access to cheminformatics tools for data preprocessing, model building, molecule generation, and interactive chemical space visualization. Moreover, the platform is easy to extend with customizable frontend React.js components and backend Python extensions. GenUI is open source and a recently developed de novo molecular generator, DrugEx, was integrated as a proof of principle. In this work, we present the architecture and implementation details of GenUI and discuss how it can facilitate collaboration in the disparate communities interested in de novo molecular generation and computer-aided drug discovery.

Developing Novel Anticancer Drugs for Targeted Populations: An Update

2020 ◽  
Vol 26 ◽  
Author(s):  
Tadesse Bekele Tafesse ◽  
Mohammed Hussen Bule ◽  
Fazlullah Khan ◽  
Mohammad Abdollahi ◽  
Mohsen Amini
Keyword(s):  
Drug Discovery ◽  
Drug Development ◽  
Anticancer Drugs ◽  
Anticancer Drug ◽  
Development Process ◽  
De Novo ◽  
Drug Repurposing ◽  
Drug Discovery And Development ◽  
Probability Of Success ◽  
Selection Of

Background: Due to higher failure rates, lengthy time and high cost of the traditional de novo drug discovery and development process; the rate of opportunity to get new, safe and efficacious drugs for the targeted population including pediatric patients with cancer becomes sluggish. Objectives: This paper discusses the development of novel anticancer drugs focusing on the identification and selection of target anticancer drug development for the targeted population. Methods: Information presented in this review was obtained from different databases including PUBMED, SCOPUS, Web of Science, and EMBASE. Various keywords were used as search terms. Results: The pharmaceutical companies currently are executing drug repurposing as an alternative means to accelerate the drug development process that reduces the risk of failure, time and cost, which takes 3-12 years with almost 25% overall probability of success as compared to de novo drug discovery and development process (10-17 years) which has less than 10% probability of success. An alternative strategy to the traditional de novo drug discovery and development process, called drug repurposing, is also presented. Conclusion: Therefore, to continue with the progress of developing novel anticancer drugs towards the targeted population, identification and selection of the target to the specific disease type is important considering the aspects of the age of the patient and the disease stages such as each cancer types are different when we consider the disease at a molecular level. Drug repurposing technique becomes an influential alternative strategy to discover and develop novel anticancer drug candidates.

An overview of computer-aided drug design tools and recent applications in designing of antidiabetic agents

2020 ◽  
Vol 21 ◽  
Author(s):  
Paranjeet Kaur ◽  
Gopal Khatik
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Structure Prediction ◽  
Material Design ◽  
Computer Assisted ◽  
Antidiabetic Agents ◽  
Computer Aided Drug Design ◽  
In Silico Studies ◽  
Computer Aided

Background: In this fast-growing era, high throughput data is now being so easily accessed by getting transformed into datasets which store the information. Such information is valuable to optimize the hypothesis and drug design via computer-aided drug design (CADD). Nowadays, we can explore the role of CADD in various disciplines like Nanotechnology, Biochemistry, Medical Sciences, Molecular Biology, etc. Methods: We searched the valuable literature using a pertinent database with given keywords like computer-aided drug design, antidiabetic, drug design, etc. We retrieved all valuable articles which are recent and discussing the role of computation in the designing of antidiabetic agents. Results: To facilitate the drug discovery process, the computational approach has set landmarks in the whole pipeline for drug discovery from target identification and mechanism of action to the identification of leads and drug candidates. Along with this, there is a determined endeavor to describe the significance of in-silico studies in predicting the absorption, distribution, metabolism, excretion, and toxicity profile. Thus, globally CADD is accepted with a variety of tools for studying QSAR, virtual screening, protein structure prediction, quantum chemistry, material design, physical and biological property prediction. Conclusion: Computer-assisted tools are used as the drug discovery tool in the area of different diseases, and here we reviewed the collaborative aspects of information technologies and chemoinformatics tools in the discovery of antidiabetic agents keeping in-view of the growing importance for treating diabetes.

Recent Advances in Computer-Aided Drug Design as Applied to Anti-Influenza Drug Discovery

2014 ◽  
Vol 14 (16) ◽  
pp. 1875-1889 ◽  
Author(s):  
Prema Mallipeddi ◽  
Gyanendra Kumar ◽  
Stephen White ◽  
Thomas Webb
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Computer Aided Drug Design ◽  
Recent Advances ◽  
Computer Aided
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