ReviewMini reviews in medicinal chemistry2024
The Power of Molecular Dynamics Simulations and Their Applications to Discover Cysteine Protease Inhibitors.
Review in Mini reviews in medicinal chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 16 citations in OpenAlex.
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- Computational screening and molecular dynamics reveal curcumin III and taxifolin as potential thyroid receptor modulators for hypothyroidism therapy.Frontiers in endocrinology · 2026Article
- Rational Design, Computational Analysis and Antibacterial Activities of Synthesized Peptide-Based Molecules Targeting Quorum Sensing-Dependent Biofilm Formation inPharmaceuticals (Basel, Switzerland) · 2025Article
- Review
- Exploring Subtilisin Inhibition to Discover Antimalarial Drugs: Insights into Medicinal Chemistry and Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Genome-wide molecular characterization and expression profiling of the cysteine protease gene family in maize.BMC genomics · 2025Article
- Synthesis, Biological Evaluation, Molecular Dynamics, and QM-MM Calculation of Spiro-Acridine Derivatives Against Leishmaniasis.Microorganisms · 2025Article
- Current Trends in Drug Discovery Based on Artificial Intelligence and Computer-aided Drug Design: Part II.Current topics in medicinal chemistry · 2025Article
- Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning.Molecules (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A large family of enzymes with the function of hydrolyzing peptide bonds, called peptidases or cysteine proteases (CPs), are divided into three categories according to the peptide chain involved. CPs catalyze the hydrolysis of amide, ester, thiol ester, and thioester peptide bonds. They can be divided into several groups, such as papain-like (CA), viral chymotrypsin-like CPs (CB), papainlike endopeptidases of RNA viruses (CC), legumain-type caspases (CD), and showing active residues of His, Glu/Asp, Gln, Cys (CE). The catalytic mechanism of CPs is the essential cysteine residue present in the active site. These mechanisms are often studied through computational methods that provide new information about the catalytic mechanism and identify inhibitors. The role of computational methods during drug design and development stages is increasing. Methods in Computer-Aided Drug Design (CADD) accelerate the discovery process, increase the chances of selecting more promising molecules for experimental studies, and can identify critical mechanisms involved in the pathophysiology and molecular pathways of action. Molecular dynamics (MD) simulations are essential in any drug discovery program due to their high capacity for simulating a physiological environment capable of unveiling significant inhibition mechanisms of new compounds against target proteins, especially CPs. Here, a brief approach will be shown on MD simulations and how the studies were applied to identify inhibitors or critical information against cysteine protease from several microorganisms, such as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.