標(biāo)題: Titlebook: Computational Drug Discovery and Design; Mohini Gore,Umesh B. Jagtap Book 2024Latest edition The Editor(s) (if applicable) and The Author( [打印本頁] 作者: 可入到 時(shí)間: 2025-3-21 16:27
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書目名稱Computational Drug Discovery and Design讀者反饋
書目名稱Computational Drug Discovery and Design讀者反饋學(xué)科排名
作者: 厭倦嗎你 時(shí)間: 2025-3-21 23:05
https://doi.org/10.1007/978-3-8349-8138-7rucial component of drug discovery and development. VS is a computational method used in drug design to identify potential drugs from enormous libraries of chemicals. This approach makes use of molecular modeling and docking simulations to assess the small molecule’s ability to bind to the desired p作者: mosque 時(shí)間: 2025-3-22 02:11
,Unentgeltlicher Unternehmensübergang,, high-throughput virtual ligand screening campaigns aim at discovering computationally new binding molecules or fragments to modulate particular biomolecular interactions or biological activities, related to a disease process. The structure-based virtual ligand screening process primarily relies on作者: 積習(xí)已深 時(shí)間: 2025-3-22 05:01
https://doi.org/10.1007/978-3-8349-8138-7ructure for a potential viral protein target can be obtained and then highlight some of the main considerations in preparing for the application of receptor-based molecular docking techniques. Thereafter, we discuss the resources to search for potential drug candidates (ligands) against this target 作者: 葡萄糖 時(shí)間: 2025-3-22 09:00
Steueroptimierter Unternehmenskaufein–protein interactions can be used to refine docking predictions and to detect macro-characteristics, such as the binding funnel. A new GRAMM web server for protein docking predicts a spectrum of docking poses that characterize the intermolecular energy landscape in protein interaction. A user-fri作者: 匍匐前進(jìn) 時(shí)間: 2025-3-22 15:35
Fremdfinanzierung des Unternehmenskaufs,l research. Recently, our new blind docking server named CB-Dock2 has been released and is currently being utilized by researchers worldwide. CB-Dock2 outperforms state-of-the-art methods due to its accuracy in binding site identification and binding pose prediction, which are enabled by its knowled作者: 匍匐前進(jìn) 時(shí)間: 2025-3-22 17:21 作者: 你正派 時(shí)間: 2025-3-23 00:21
,Zusammenführung der Aktionsparameter,odeling, regulation of cell proliferation, cell migration, cell differentiation, participation in bacterial/viral infections, and immune response. They can interact with many important biomolecular partners in the extracellular matrix of the cell including small drug molecules. Recently, several GAG作者: 加劇 時(shí)間: 2025-3-23 01:30
Problemstellung und Gang der Untersuchung,ational prediction of drug–target interactions can facilitate in reducing the search space of experimental wet lab-based verifications steps, thus considerably reducing time and other resources dedicated to the drug discovery pipeline. While machine learning-based methods are more widespread for dru作者: FRET 時(shí)間: 2025-3-23 07:54
https://doi.org/10.1007/978-3-658-11526-5r, most of these resources are built with data from experiments that detect highly hydrophobic stretches located within transiently exposed protein segments. We recently demonstrated that cryptic amyloidogenic regions (CARs) of polar nature have the potential to form amyloid fibrils in vitro. Given 作者: SLING 時(shí)間: 2025-3-23 11:38
Steuerplanung beim Management-Buy-Outr dynamics (MD) simulations due to sampling issues. Gaussian accelerated MD (GaMD) is an enhanced sampling method that adds a harmonic boost to overcome energy barriers, which has demonstrated significant benefits in exploring protein-ligand interactions. Especially, the ligand GaMD (LiGaMD) applies作者: 加劇 時(shí)間: 2025-3-23 17:37 作者: 征兵 時(shí)間: 2025-3-23 20:09 作者: sterilization 時(shí)間: 2025-3-23 23:53
Steuerplanung der Verm?gensnachfolgelity of data available for training, the astute choice of features for prediction, and thorough assessment of the robustness of prediction on a variety of new cases. In this chapter, we address these issues while developing and sharing protocols to build a robust dataset and rigorously compare sever作者: Halfhearted 時(shí)間: 2025-3-24 02:38
Steuerpolitik — Von der Theorie zur Praxisns of dollars every year. While all phases remain crucial to ensure pharmaceutical-level safety, quality, and efficacy of the end product, streamlining these efforts toward compounds with success potential is pivotal for a more efficient and cost-effective process. The use of artificial intelligence作者: NEXUS 時(shí)間: 2025-3-24 06:45
https://doi.org/10.1007/978-3-658-10762-8pensive and time-consuming process of drug design is related to biomedical complexity. CADD can be used to apply effective and efficient strategies to overcome obstacles in the field of drug design in order to properly design and develop a new medicine. To prepare the raw data for consistent and rep作者: encomiast 時(shí)間: 2025-3-24 11:13 作者: Arb853 時(shí)間: 2025-3-24 14:58 作者: 強(qiáng)化 時(shí)間: 2025-3-24 21:24
Computational Drug Discovery and Design978-1-0716-3441-7Series ISSN 1064-3745 Series E-ISSN 1940-6029 作者: 弓箭 時(shí)間: 2025-3-25 01:07
Mohini Gore,Umesh B. JagtapIncludes cutting-edge methods and protocols.Provides step-by-step detail essential for reproducible results.Contains key notes and implementation advice from the experts作者: cogent 時(shí)間: 2025-3-25 05:33 作者: ITCH 時(shí)間: 2025-3-25 10:15 作者: Soliloquy 時(shí)間: 2025-3-25 11:39
978-1-0716-3443-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Busines作者: BRACE 時(shí)間: 2025-3-25 17:22 作者: 諷刺滑稽戲劇 時(shí)間: 2025-3-25 20:54
,Unentgeltlicher Unternehmensübergang, discovery, molecular dynamics (MD) allows introducing protein flexibility before or after a docking protocol, refining the structure of protein–drug complexes in the presence of water, ions, and even in membrane-like environments, describing more precisely the temporal evolution of the biological c作者: bizarre 時(shí)間: 2025-3-26 00:11 作者: 尖牙 時(shí)間: 2025-3-26 05:34 作者: GUILT 時(shí)間: 2025-3-26 11:08
Steuerplanung der Verm?gensnachfolgetive method is used to quantify which features are most important for correct prediction..The resulting well-trained classifier, . can robustly predict the small subset of amino acid residues on the surface of a protein that are energetically most important for binding a protein partner: the interac作者: SPER 時(shí)間: 2025-3-26 15:28 作者: HEW 時(shí)間: 2025-3-26 19:25 作者: Mumble 時(shí)間: 2025-3-26 22:02
Computer-Aided Drug Discovery and Design: Recent Advances and Future Prospects,ing active scaffolds and guiding the subsequent optimization process. Recent groundbreaking advances in the field have also analyzed the integration of state-of-the-art machine learning approaches in every step of the drug discovery process (from prediction of target structure to customized molecula作者: 對(duì)手 時(shí)間: 2025-3-27 04:56
Molecular Dynamics as a Tool for Virtual Ligand Screening, discovery, molecular dynamics (MD) allows introducing protein flexibility before or after a docking protocol, refining the structure of protein–drug complexes in the presence of water, ions, and even in membrane-like environments, describing more precisely the temporal evolution of the biological c作者: paleolithic 時(shí)間: 2025-3-27 05:24 作者: myocardium 時(shí)間: 2025-3-27 10:11 作者: 外面 時(shí)間: 2025-3-27 17:31 作者: 奇思怪想 時(shí)間: 2025-3-27 19:11
Applications of Big Data and AI-Driven Technologies in CADD (Computer-Aided Drug Design),esign of prediction models in the area of drug design is made possible by data pre-processing and applications of big data and AI skills. In the biomedical big data era, knowledge on the biological, chemical, or pharmacological structures of biomedical entities relevant to drug design should be anal作者: 逢迎春日 時(shí)間: 2025-3-27 23:00 作者: POLYP 時(shí)間: 2025-3-28 03:43
Steueroptimierter Unternehmenskaufendly interface provides options to choose free or template-based docking, as well as other advanced features, such as clustering of the docking poses, and interactive visualization of the docked models.作者: 方舟 時(shí)間: 2025-3-28 09:26 作者: 圓錐 時(shí)間: 2025-3-28 13:10 作者: Intend 時(shí)間: 2025-3-28 15:02
Book 2024Latest editionps on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols...?.Authoritative and cutting-edge,?.Computational Drug Discovery and Design, Second Edition?.aims?to effectively?utilize computational methodologies in discovery and design of novel drugs..作者: botany 時(shí)間: 2025-3-28 20:14
Steuerpolitik — Von der Theorie zur Praxisges in the biological target to improve therapeutic longevity. Here, we present a series of in silico tools that address these applications in small molecule development and describe how they can be embedded within the current pharmaceutical development pipeline.作者: 藥物 時(shí)間: 2025-3-29 00:42 作者: 幼稚 時(shí)間: 2025-3-29 07:07
Book 2024Latest editiontual screening, lead discovery and optimization, conformational sampling, prediction of pharmacokinetic properties using computer-based methodologies.?Chapters also focus on the application of the latest artificial intelligence technologies for computer aided drug discovery. Written in the format of作者: enfeeble 時(shí)間: 2025-3-29 11:11
Antiviral Drug Target Identification and Ligand Discovery,protein receptor, how to screen them, and preparing their analogue library. We make specific reference to free, online, open-source tools and resources which can be applied for antiviral drug discovery studies.作者: FAR 時(shí)間: 2025-3-29 15:11 作者: anus928 時(shí)間: 2025-3-29 18:22 作者: Certainty 時(shí)間: 2025-3-29 23:47
,Mining Chemogenomic Spaces for Prediction of Drug–Target Interactions,g–target interaction prediction, network-centric methods are also evolving. In this chapter, we focus on the process of the drug–target interaction prediction from the perspective of using machine learning algorithms and the various stages involved for developing an accurate predictor.作者: 窒息 時(shí)間: 2025-3-30 02:13
Fremdfinanzierung des Unternehmenskaufs,r-friendly tool for the bioinformatics and cheminformatics communities. This chapter provides a brief overview of the methods, followed by a detailed guide on using the CB-Dock2 server. Additionally, we present a case study that evaluates the performance of protein–ligand blind docking using this tool.作者: gain631 時(shí)間: 2025-3-30 05:48
https://doi.org/10.1007/978-3-658-11526-5f predicted CARs from intrinsically disordered regions. This protocol chapter describes how to use CARs-DB to search for sequences of interest that might be connected to disease or functional protein–protein interactions. In addition, we provide study cases to illustrate the database’s features to users. The CARs-DB is readily accessible at ..作者: 信任 時(shí)間: 2025-3-30 10:13 作者: 親愛 時(shí)間: 2025-3-30 15:45 作者: Thyroxine 時(shí)間: 2025-3-30 20:30
Erbschaft- und Schenkungsteuerrecht,lications of predictive modeling and generative modeling to discover and design safe and effective antimicrobial peptides. We will also present their current limitations and suggest future research directions, applicable to peptide drug design campaigns.作者: 無瑕疵 時(shí)間: 2025-3-30 23:55 作者: mendacity 時(shí)間: 2025-3-31 02:36
Expanding the Landscape of Amyloid Sequences with CARs-DB: A Database of Polar Amyloidogenic Peptidf predicted CARs from intrinsically disordered regions. This protocol chapter describes how to use CARs-DB to search for sequences of interest that might be connected to disease or functional protein–protein interactions. In addition, we provide study cases to illustrate the database’s features to users. The CARs-DB is readily accessible at ..作者: 在駕駛 時(shí)間: 2025-3-31 07:13 作者: inventory 時(shí)間: 2025-3-31 10:10 作者: 領(lǐng)巾 時(shí)間: 2025-3-31 16:09
Accelerating the Discovery and Design of Antimicrobial Peptides with Artificial Intelligence,lications of predictive modeling and generative modeling to discover and design safe and effective antimicrobial peptides. We will also present their current limitations and suggest future research directions, applicable to peptide drug design campaigns.作者: effrontery 時(shí)間: 2025-3-31 18:50 作者: Acetaminophen 時(shí)間: 2025-3-31 23:38
https://doi.org/10.1007/978-3-8349-8138-7es of chemicals. This approach makes use of molecular modeling and docking simulations to assess the small molecule’s ability to bind to the desired protein. Virtual screening has a bright future, as high computational power and modern techniques are likely to further enhance the accuracy and speed of the process.作者: Inveterate 時(shí)間: 2025-4-1 04:10 作者: BIDE 時(shí)間: 2025-4-1 09:56
