Virtual screening is a computational technique used in drug discovery to identify potential molecules with desired properties from large databases. Through simulations and predictive modeling, virtual screening evaluates the interactions between molecules and target proteins, predicting their binding affinities and potential biological activities. This approach accelerates the identification of promising candidates, streamlining the initial stages of research by narrowing down the pool of compounds that require further investigation. Virtual screening has become an indispensable tool in modern research, aiding in the efficient design of new drugs and materials with applications across various scientific disciplines.

The sophisticated computational tools harness the power of advanced algorithms to rapidly sift through vast repositories of chemical compounds and biomolecules, aiming to identify potential candidates with desired properties. By simulating interactions between molecules and biological targets, virtual screening tools predict their binding affinities and potential therapeutic effects. These tools significantly expedite the early stages of drug development, helping researchers focus their efforts on a narrower set of promising compounds, thereby reducing time and costs. Furthermore, the availability of expansive databases containing chemical structures and bioactivity data enhances the efficiency of virtual screening, enabling researchers to make informed decisions and uncover novel molecules that could lead to breakthroughs in various fields, from pharmaceuticals to materials science.

Further readings

1. Singh N, Chaput L, Villoutreix BO. Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace. Brief Bioinform. 2021 Mar 22;22(2):1790-1818. doi: 10.1093/bib/bbaa034. PMID: 32187356; PMCID: PMC7986591.
2. Banegas-Luna AJ, Cerón-Carrasco JP, Pérez-Sánchez H. A review of ligand-based virtual screening web tools and screening algorithms in large molecular databases in the age of big data. Future Med Chem. 2018 Nov;10(22):2641-2658. doi: 10.4155/fmc-2018-0076. Epub 2018 Nov 30. PMID: 30499744.
3. Maia EHB, Assis LC, de Oliveira TA, da Silva AM, Taranto AG. Structure-Based Virtual Screening: From Classical to Artificial Intelligence. Front Chem. 2020 Apr 28;8:343. doi: 10.3389/fchem.2020.00343. PMID: 32411671; PMCID: PMC7200080.