• 제목/요약/키워드: drug design

검색결과 598건 처리시간 0.026초

의약품개발공정에서의 Augmented weighted Tchebycheff 모델링 및 강건설계최적화 (Augmented Weighted Tchebycheff Modeling and Robust Design Optimization on a Drug Development Process)

  • ;신상문
    • 대한산업공학회지
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    • 제39권5호
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    • pp.403-411
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    • 2013
  • The quality of the products/processes has been improved remarkably since robust design (RD) methodology is applied into the practice manufacturing processes. A model building method based on the dual responses methods for multiple and time oriented responses on a drug development process is employed in this paper instead of the previous methods that handle the static nature of data and single response. Subsequently, the optimal solutions of a multiple and time series RD problem are obtained by using the proposed augmented weighted Tchebycheff method that has a significant flexibility on assigning weights. Finally, a pharmaceutical case study associated with a generic drug development process is conducted in order to illustrate the efficient optimal solutions from the proposed model.

Exploration of the Binding Mode of Indole Derivatives as Potent HIV-1 Inhibitors Using Molecular Docking Simulations

  • Balupuri, Anand;Cho, Seung Joo
    • 통합자연과학논문집
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    • 제6권3호
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    • pp.138-142
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    • 2013
  • The HIV-1 envelope glycoprotein gp120 plays a vital role in the entry of the virus into the host cells. The crucial role of the glycoprotein suggests gp120 as potential drug target for the future antiviral therapies. Identification of the binding mode of small drug like compounds has been an important goal in drug design. In the current study we attempt to propose binding mode of indole derivatives in the binding pocket of gp120. These derivatives are reported to inhibit HIV-1 by acting as attachment inhibitors that bind to gp120 and prevent the gp120-CD4 interaction and thus inhibit the infectivity of HIV-1. To elucidate the molecular basis of the small molecules interactions to inhibit the glycoprotein function we employed the molecular docking simulation approach. This study provides insights to elucidate the binding pattern of indole-based gp120 inhibitors and may help in the rational design of novel HIV-1 inhibitors with improved potency.

A Bayesian Meta Analysis for Assessing Bioequivalence among Two Generic Copies of the Same Brand-Name Drug

  • Oh, Hyun-Sook
    • Communications for Statistical Applications and Methods
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    • 제13권2호
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    • pp.285-295
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    • 2006
  • As more generic drugs become available, the quality, safety, and efficacy of generic drugs have become a public concern. Specifically, drug interchangeability among generic copies of the same brand-name drug is a safety concern. This research proposes a Bayesian method for assessing bioequivalence between two generic copies of the same brand-name drug from two independent $2{\times}2$ crossover design experiments. Uninformative priors are considered for general use and the posterior distribution of the difference of two generic drug effects is derived from which the highest probability density interval can be evaluated. Examples are presented for illustration.

신규 약물 설계를 위한 인공지능 기술 동향 (Technical Trends in Artificial Intelligence for De Novo Drug Design)

  • 한영웅;정호열;박수준
    • 전자통신동향분석
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    • 제38권3호
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    • pp.38-46
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    • 2023
  • The value of living a long and healthy life without suffering has increased owing to aging populations, transition to welfare societies, and global interest in health deriving from the novel coronavirus disease pandemic. New drug development has gained attention as both a tool to improve the quality of life and high-value market, with blockbuster drugs potentially generating over 10 billion dollars in annual revenue. However, for newly discovered substances to be used as drugs, various properties must be verified over a long period in a time-consuming and costly process. Recently, the development of artificial intelligence technologies, such as deep and reinforcement learning, has led to significant changes in drug development by enabling the effective identification of drug candidates that satisfy desired properties. We explore and discuss trends in artificial intelligence for de novo drug design.

Antimicrobial resistance in Klebsiella pneumoniae: identification of bacterial DNA adenine methyltransferase as a novel drug target from hypothetical proteins using subtractive genomics

  • Umairah Natasya Mohd Omeershffudin;Suresh Kumar
    • Genomics & Informatics
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    • 제20권4호
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    • pp.47.1-47.13
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    • 2022
  • Klebsiella pneumoniae is a gram-negative bacterium that is known for causing infection in nosocomial settings. As reported by the World Health Organization, carbapenem-resistant Enterobacteriaceae, a category that includes K. pneumoniae, are classified as an urgent threat, and the greatest concern is that these bacterial pathogens may acquire genetic traits that make them resistant towards antibiotics. The last class of antibiotics, carbapenems, are not able to combat these bacterial pathogens, allowing them to clonally expand antibiotic-resistant strains. Most antibiotics target essential pathways of bacterial cells; however, these targets are no longer susceptible to antibiotics. Hence, in our study, we focused on a hypothetical protein in K. pneumoniae that contains a DNA methylation protein domain, suggesting a new potential site as a drug target. DNA methylation regulates the attenuation of bacterial virulence. We integrated computational-aided drug design by using a bioinformatics approach to perform subtractive genomics, virtual screening, and fingerprint similarity search. We identified a new potential drug, koenimbine, which could be a novel antibiotic.

암 환자 통증 조절을 위한 이식형 약물 주입 펌프 개발 (Development of an Implantable Drug Infusion Pump for Pain Control in Cancer Patients)

  • 백두진;박준우;홍소영;이철한;김광기;조영호;김대현
    • 한국유체기계학회 논문집
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    • 제12권3호
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    • pp.31-37
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    • 2009
  • This paper presents a implantable intrathecal drug infusion pump for pain control in cancer patients. This device consists of micropump module, drug reservoir module and control module. The micropump module using cam-follower mechanism composed of small-sized four cams and four followers. Each followers is driven by a cam and liquid is discharged by a sequential reciprocal motion of the followers. The advantage of this structure is that it allows the pump to be clean and valveless. The drug reservoir module composed of drug chamber, gas chamber and diaphragm. The control module composed of battery, wireless communication unit and controller. To design a small-sized, low power pump some analysis were performed to determine the design parameters. To verify the feasibility of the experiment, a prototype was manufactured and its operating characteristics were investigated. Experimental results were in accordance with the expected results obtained from analysis.

탄성체 약물주입기 개선을 위한 이론적·실험적 고찰 (Theoretical and Experimental Considerations for Improving Elastomer Drug Infusers)

  • 김동훈;강태원
    • 한국생산제조학회지
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    • 제26권3호
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    • pp.320-327
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    • 2017
  • The main function of an infuser is to ensure constant dosage of a drug. Elastomer drug infusers have been used widely owing to their economic advantages. The mechanism of the device is primarily based on the pressure created from the elastic material that contains the drugs. However, as the drug is infused and the internal pressure is reduced, the drug is not linearly infused at all times. This study involves investigating factors to improve the design of the infuser. The first factor is the range of proper deformation, which does not affect a significant amount of stress variation during infusion. The second is concerned with the flow restrictor and the associated design variables are recommended by employing finite element analysis and the factorial experiment technique. The last factor is related to the spring device connected to balloon. The results showed that the drug reservoir can compensate for unexpected pressure gradient drops.

Computer-Aided Drug Discovery in Plant Pathology

  • Shanmugam, Gnanendra;Jeon, Junhyun
    • The Plant Pathology Journal
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    • 제33권6호
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    • pp.529-542
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    • 2017
  • Control of plant diseases is largely dependent on use of agrochemicals. However, there are widening gaps between our knowledge on plant diseases gained from genetic/mechanistic studies and rapid translation of the knowledge into target-oriented development of effective agrochemicals. Here we propose that the time is ripe for computer-aided drug discovery/design (CADD) in molecular plant pathology. CADD has played a pivotal role in development of medically important molecules over the last three decades. Now, explosive increase in information on genome sequences and three dimensional structures of biological molecules, in combination with advances in computational and informational technologies, opens up exciting possibilities for application of CADD in discovery and development of agrochemicals. In this review, we outline two categories of the drug discovery strategies: structure- and ligand-based CADD, and relevant computational approaches that are being employed in modern drug discovery. In order to help readers to dive into CADD, we explain concepts of homology modelling, molecular docking, virtual screening, and de novo ligand design in structure-based CADD, and pharmacophore modelling, ligand-based virtual screening, quantitative structure activity relationship modelling and de novo ligand design for ligand-based CADD. We also provide the important resources available to carry out CADD. Finally, we present a case study showing how CADD approach can be implemented in reality for identification of potent chemical compounds against the important plant pathogens, Pseudomonas syringae and Colletotrichum gloeosporioides.

In-silico Modeling of Chemokine Receptor CCR2 And CCR5 to Assist the Design of Effective and Selective Antagonists

  • Kothandan, Gugan;Cho, Seung Joo
    • 통합자연과학논문집
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    • 제5권1호
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    • pp.32-37
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    • 2012
  • Chemokine receptor antagonists have potential applications in field of drug discovery. Although the chemokine receptors are G-protein-coupled receptors, their cognate ligands are small proteins (8 to 12 kDa), and so inhibiting the ligand/receptor interaction has been challenging. The application of structure-based in-silico methods to drug discovery is still considered a major challenge, especially when the x-ray structure of the target protein is unknown. Such is the case with human CCR2 and CCR5, the most important members of the chemokine receptor family and also a potential drug target. Herein, we review the success stories of combined receptor modeling/mutagenesis approach to probe the allosteric nature of chemokine receptor binding by small molecule antagonists for CCR2 and CCR5 using Rhodopsin as template. We also urged the importance of recently available ${\beta}2$-andrenergic receptor as an alternate template to guide mutagenesis. The results demonstrate the usefulness and robustness of in-silico 3D models. These models could also be useful for the design of novel and potent CCR2 and CCR5 antagonists using structure based drug design.