Current Trends in Computational Modeling for Drug Discovery

Bibliographic Details
Title: Current Trends in Computational Modeling for Drug Discovery
Description: This contributed volume offers a comprehensive discussion on how to design and discover pharmaceuticals using computational modeling techniques. The different chapters deal with the classical and most advanced techniques, theories, protocols, databases, and tools employed in computer-aided drug design (CADD) covering diverse therapeutic classes. Multiple components of Structure-Based Drug Discovery (SBDD) along with its workflow and associated challenges are presented while potential leads for Alzheimer's disease (AD), antiviral agents, anti-human immunodeficiency virus (HIV) drugs, and leads for Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) disease are discussed in detail. Computational toxicological aspects in drug design and discovery, screening adverse effects, and existing or future in silico tools are highlighted, while a novel in silico tool, RASAR, which can be a major technique for small to big datasets when not much experimental data are present, is presented. The book also introduces the reader to the major drug databases covering drug molecules, chemicals, therapeutic targets, metabolomics, and peptides, which are great resources for drug discovery employing drug repurposing, high throughput, and virtual screening. This volume is a great tool for graduates, researchers, academics, and industrial scientists working in the fields of cheminformatics, bioinformatics, computational biology, and chemistry.
Authors: Supratik Kar, Jerzy Leszczynski
Resource Type: eBook.
Subjects: Drug development--Data processing, Drug development--Computer simulation
Categories: SCIENCE / Chemistry / Physical & Theoretical, MEDICAL / Pharmacology, SCIENCE / Life Sciences / Biology, SCIENCE / Chemistry / Clinical, SCIENCE / Chemistry / Computational & Molecular Modeling
Database: eBook Index
FullText Text:
  Availability: 0
Header DbId: edsebk
DbLabel: eBook Index
An: 3638060
RelevancyScore: 969
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 968.509704589844
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Current Trends in Computational Modeling for Drug Discovery
– Name: Abstract
  Label: Description
  Group: Ab
  Data: This contributed volume offers a comprehensive discussion on how to design and discover pharmaceuticals using computational modeling techniques. The different chapters deal with the classical and most advanced techniques, theories, protocols, databases, and tools employed in computer-aided drug design (CADD) covering diverse therapeutic classes. Multiple components of Structure-Based Drug Discovery (SBDD) along with its workflow and associated challenges are presented while potential leads for Alzheimer's disease (AD), antiviral agents, anti-human immunodeficiency virus (HIV) drugs, and leads for Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) disease are discussed in detail. Computational toxicological aspects in drug design and discovery, screening adverse effects, and existing or future in silico tools are highlighted, while a novel in silico tool, RASAR, which can be a major technique for small to big datasets when not much experimental data are present, is presented. The book also introduces the reader to the major drug databases covering drug molecules, chemicals, therapeutic targets, metabolomics, and peptides, which are great resources for drug discovery employing drug repurposing, high throughput, and virtual screening. This volume is a great tool for graduates, researchers, academics, and industrial scientists working in the fields of cheminformatics, bioinformatics, computational biology, and chemistry.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Supratik+Kar%22">Supratik Kar</searchLink><br /><searchLink fieldCode="AR" term="%22Jerzy+Leszczynski%22">Jerzy Leszczynski</searchLink>
– Name: TypePub
  Label: Resource Type
  Group: TypPub
  Data: eBook.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Drug+development--Data+processing%22">Drug development--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Drug+development--Computer+simulation%22">Drug development--Computer simulation</searchLink>
– Name: SubjectBISAC
  Label: Categories
  Group: Su
  Data: <searchLink fieldCode="ZK" term="%22SCIENCE+%2F+Chemistry+%2F+Physical+%26+Theoretical%22">SCIENCE / Chemistry / Physical & Theoretical</searchLink><br /><searchLink fieldCode="ZK" term="%22MEDICAL+%2F+Pharmacology%22">MEDICAL / Pharmacology</searchLink><br /><searchLink fieldCode="ZK" term="%22SCIENCE+%2F+Life+Sciences+%2F+Biology%22">SCIENCE / Life Sciences / Biology</searchLink><br /><searchLink fieldCode="ZK" term="%22SCIENCE+%2F+Chemistry+%2F+Clinical%22">SCIENCE / Chemistry / Clinical</searchLink><br /><searchLink fieldCode="ZK" term="%22SCIENCE+%2F+Chemistry+%2F+Computational+%26+Molecular+Modeling%22">SCIENCE / Chemistry / Computational & Molecular Modeling</searchLink>
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=3638060
RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 615.190113
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Drug development--Data processing
        Type: general
      – SubjectFull: Drug development--Computer simulation
        Type: general
    Titles:
      – TitleFull: Current Trends in Computational Modeling for Drug Discovery
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Supratik Kar
      – PersonEntity:
          Name:
            NameFull: Jerzy Leszczynski
      – PersonEntity:
          Name:
            NameFull: Supratik Kar
      – PersonEntity:
          Name:
            NameFull: Jerzy Leszczynski
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2023
            – D: 03
              M: 07
              Type: profile
              Y: 2023
          Identifiers:
            – Type: isbn-print
              Value: 9783031338700
            – Type: isbn-electronic
              Value: 9783031338717
          Numbering:
            – Type: volume
              Value: 00035
          Titles:
            – TitleFull: Current Trends in Computational Modeling for Drug Discovery
              Type: main
ResultId 1