Computer-aided drug design for virtual-screening and active-predicting of main protease (Mpro) inhibitors against SARS-CoV-2

Abstract

Introduction: SARS-CoV-2 is a novel coronavirus with highly contagious and has posed a significant threat to global public health. The main protease (Mpro) is a promising target for antiviral drugs against SARS-CoV-2.Methods: In this study, we have used pharmacophore-based drug design technology to identify potential compounds from drug databases as Mpro inhibitors.Results: The procedure involves pharmacophore modeling, validation, and pharmacophore-based virtual screening, which identifies 257 compounds with promising inhibitory activity.Discussion: Molecular docking and non-bonding interactions between the targeted protein Mpro and compounds showed that ENA482732 was the best compound. These results provided a theoretical foundation for future studies of Mpro inhibitors against SARS-CoV-2.

Comprehensive machine learning boosts structure-based virtual screening for PARP1 inhibitors

“…Compounds capable of inhibiting PARP1 at a concentration lower than or equal to 1 µM were classified as actives, while those having an active concentration above 1 µM were labeled as inactives. The threshold of 1 µM is a usual choice in the literature [39][40][41][42], consistent with what can be found in bioactivity databases (e.g., in PubChem, nearly 90% of PARP1 inhibitors have a potency value better than 1 µM, whereas all inactive-labeled compounds cannot inhibit this target at a concentration lower than this threshold [43]). Chemical structures of PARP1 inhibitors were processed according to a previously described data curation workflow [44], which starts by the removal of metal ions and salts, the normalization of chemotypes and the standardization of tautomers using the JChem Standardizer.…”

Targeted Screening of Curcumin Derivatives as Pancreatic Lipase Inhibitors Using Computer-Aided Drug Design

“…CADD was a technique that utilizes computer-based virtual analysis to study the activity and physicochemical properties of drugs . It enabled structure-based or ligand-based drug design, encompassing methods such as molecular docking, molecular dynamics simulations, pharmacophore model screening, and molecular property prediction. , Compared with conventional methods of drug development, CADD demonstrated significant advantages in terms of shortened development cycles and cost savings. CADD played an essential role in the design of antimicrobial, antiviral, and anticancer drugs, among others, enhancing its application prospects. ,, The study utilized CADD to conduct molecular docking and property prediction evaluations of curcumin derivatives.…”

“…It enabled structure-based or ligand-based drug design, encompassing methods such as molecular docking, molecular dynamics simulations, pharmacophore model screening, and molecular property prediction. , Compared with conventional methods of drug development, CADD demonstrated significant advantages in terms of shortened development cycles and cost savings. CADD played an essential role in the design of antimicrobial, antiviral, and anticancer drugs, among others, enhancing its application prospects. ,, The study utilized CADD to conduct molecular docking and property prediction evaluations of curcumin derivatives. In addition to assessing the pancreatic lipase activity and drug-likeness of curcumin derivatives, this method also simulated the dissolution, absorption, binding, and potential side effects upon oral administration of the curcumin derivatives, screening curcumin derivatives that met the desired expectations while closely mimicking the physiological conditions within the body.…”

“… 34 It enabled structure-based or ligand-based drug design, encompassing methods such as molecular docking, molecular dynamics simulations, pharmacophore model screening, and molecular property prediction. 15 , 35 Compared with conventional methods of drug development, CADD demonstrated significant advantages in terms of shortened development cycles and cost savings. CADD played an essential role in the design of antimicrobial, antiviral, and anticancer drugs, among others, enhancing its application prospects.…”

Special Issue “Computer-Aided Drug Discovery and Treatment”

“…Reducing the number of compounds that need to be synthesized and experimentally validated expedites the drug discovery timeline. CADDT allows the design of molecules with specific properties that make them effective against a target protein [ 4 , 5 ].…”