Indexé dans
  • Base de données des revues académiques
  • Ouvrir la porte J
  • Genamics JournalSeek
  • Clés académiques
  • JournalTOCs
  • Infrastructure nationale des connaissances en Chine (CNKI)
  • CiteFactor
  • Scimago
  • Répertoire des périodiques d'Ulrich
  • Bibliothèque des revues électroniques
  • RechercheRef
  • Université Hamdard
  • EBSCO AZ
  • OCLC - WorldCat
  • Catalogue en ligne SWB
  • Bibliothèque virtuelle de biologie (vifabio)
  • Publions
  • MIAR
  • Commission des bourses universitaires
  • Fondation genevoise pour la formation et la recherche médicales
  • Pub européen
  • Google Scholar
Partager cette page
Dépliant de journal
Flyer image

Abstrait

Panoramic Review on Progress and Development of Molecular Docking

Kiran Rameshbhai Dudhat

In structural molecular biology and computer-assisted drug creation, molecular docking is a crucial tool. Predicting the prevailing binding modes of a ligand with a protein having a known three-dimensional structure is the aim of ligand-protein docking. Effective docking methods use a scoring system that correctly ranks candidate dockings and efficiently explore high-dimensional spaces. Lead optimization benefits greatly from the use of docking to do virtual screening on huge libraries of compounds, rate the outcomes, and offer structural ideas for how the ligands inhibit the target. It can be difficult to interpret the findings of stochastic search methods, and setting up the input structures for docking is just as crucial as docking itself.

In recent years, computer-assisted drug design has relied heavily on the molecular docking technique to estimate the binding affinity and assess the interactive mode since it can significantly increase efficiency and lower research costs. The main concepts, techniques, and frequently utilized molecular docking applications are introduced in this work. Additionally, it contrasts the most popular docking applications and suggests relevant study fields. Finally, a brief summary of recent developments in molecular docking, including the integrated technique and deep learning, is provided. Current docking applications are not precise enough to forecast the binding affinity due to the insufficient molecular structure and the inadequacies of the scoring mechanism.