Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add filters

Database
Language
Document Type
Year range
1.
Sci Rep ; 13(1): 7055, 2023 04 29.
Article in English | MEDLINE | ID: covidwho-2302825

ABSTRACT

With the rapid rate of SARS-CoV-2 Main protease (Mpro) structures deposition, a computational method that can combine all the useful structural features becomes crucial. This research focuses on the frequently occurring atoms and residues to find a generalized strategy for inhibitor design given a large amount of protein complexes from SARS-CoV in contrast to SARS-CoV-2 Mpro. By superposing large numbers of the ligands onto the protein template and grid box, we can analyse which part of the structure is conserved from position-specific interaction for both data sets for the development of pan-Mpro antiviral design. The difference in conserved recognition sites from the crystal structures can be used to determine specificity determining residues for designing selective drugs. We can display pictures of the imaginary shape of the ligand by unionising all atoms from the ligand. We also pinpoint the most probable atom adjustments to imitate the frequently found densities from the ligand atoms statistics. With molecular docking, Molecular Dynamics simulation, and MM-PBSA methods, a carbonyl replacement at the nitrile warhead (N5) of Paxlovid's Nirmatrelvir (PF-07321332) was suggested. By gaining insights into the selectivity and promiscuity regions for proteins and ligands, crucial residues are highlighted, and the antiviral design strategies are proposed.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/metabolism , Molecular Docking Simulation , Ligands , Protease Inhibitors/chemistry , Antiviral Agents/pharmacology , Antiviral Agents/chemistry , Molecular Dynamics Simulation , Peptide Hydrolases/metabolism
2.
Structure ; 30(1): 181-189.e5, 2022 01 06.
Article in English | MEDLINE | ID: covidwho-1454541

ABSTRACT

The MANORAA platform uses structure-based approaches to provide information on drug design originally derived from mapping tens of thousands of amino acids on a grid. In-depth analyses of the pockets, frequently occurring atoms, influential distances, and active-site boundaries are used for the analysis of active sites. The algorithms derived provide model equations that can predict whether changes in distances, such as contraction or expansion, will result in improved binding affinity. The algorithm is confirmed using kinetic studies of dihydrofolate reductase (DHFR), together with two DHFR-TS crystal structures. Empirical analyses of 881 crystal structures involving 180 ligands are used to interpret protein-ligand binding affinities. MANORAA links to major biological databases for web-based analysis of drug design. The frequency of atoms inside the main protease structures, including those from SARS-CoV-2, shows how the rigid part of the ligand can be used as a probe for molecular design (http://manoraa.org).


Subject(s)
Computational Biology/methods , Databases, Protein , Machine Learning , Protein Domains , Proteins/chemistry , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/virology , Crystallography, X-Ray , Drug Design , Humans , Ligands , Models, Molecular , Pandemics , Protein Binding , Proteins/metabolism , SARS-CoV-2/metabolism , SARS-CoV-2/physiology , Tetrahydrofolate Dehydrogenase/chemistry , Tetrahydrofolate Dehydrogenase/metabolism , Trimethoprim/chemistry , Trimethoprim/metabolism
SELECTION OF CITATIONS
SEARCH DETAIL