Collecting and assessing human lactate dehydrogenase-A conformations for structure-based virtual screening

Area of Science:

• Biochemistry and Molecular Biology
• Pharmacology and Drug Discovery
• Computational Chemistry

Background:

• Human lactate dehydrogenase-A (LDHA) is a key enzyme in cancer metabolism and a promising anticancer target.
• Previous structure-based drug design efforts for LDHA inhibitors have overlooked the enzyme's active site flexibility.
• Understanding LDHA's dynamic nature is crucial for developing effective and specific inhibitors.

Purpose of the Study:

• To identify reliable human lactate dehydrogenase-A (LDHA) conformations by accounting for active site flexibility.
• To provide a foundation for structure-based ligand design targeting LDHA.
• To validate the identified conformations using virtual screening methods.

Main Methods:

• Utilized replica exchange molecular dynamics (REMD) simulations to explore LDHA conformational space.
• Applied network and cluster analyses to identify stable and relevant LDHA conformations.
• Performed retrospective virtual screening to challenge and validate the selected conformations.

Main Results:

• Successfully identified reliable LDHA conformations that capture active site flexibility.
• The selected conformations proved effective in retrospective virtual screening, validating their utility.
• This approach offers a more accurate representation of the enzyme for inhibitor design.

Conclusions:

• Accounting for active site flexibility is essential for successful structure-based LDHA inhibitor design.
• The identified LDHA conformations provide a robust basis for developing novel anticancer therapeutics.
• This study enhances the potential of targeting LDHA in cancer treatment.