Evidence map›Paper›PMID 41298715›Full record

ArticleScientific reports2025

Computational and experimental design of L-amino acid-based alternatives to ketorolac.

Morteza Hosseini, Alireza Fattahi, Atena Pakzadiyan

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Morteza HosseiniDepartment of Chemistry, Institute for Convergence Science and Technology, Bioinformatics Group, Sharif University of Technology, Tehran, Iran.
Alireza FattahiDepartment of Chemistry, Institute for Convergence Science and Technology, Bioinformatics Group, Sharif University of Technology, Tehran, Iran. fattahi@sharif.edu.
Atena PakzadiyanDepartment of Chemistry, K.N. Toosi University of Technology, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

L-amino acids play a vital role in various biological processes, including hormone production, adipose tissue growth and repair, and protein synthesis. Consequently, the design of novel L-amino acid-based drugs with fewer side effects has recently garnered significant attention. Ketorolac, while effective for pain reduction, presents several adverse side effects, motivating the search for alternatives. An ideal alternative should structurally resemble ketorolac but offer improved chemical and thermal stability, as well as enhanced hydrogen bonding capability. In this project, we designed an L-amino acid-based structure as a potential alternative to ketorolac. Using computer-aided drug discovery methods, we generated a detailed, atomic-level description of the drug ligand and evaluated its selectivity properties, ADMET prediction, and Pre-Tox analysis. Molecular docking calculations were then performed to identify the most favorable active site for the newly designed ligand, mimicking ketorolac's binding pose within the protein. The resulting AVH structure exhibited a close resemblance to ketorolac. After these initial assessments, we performed molecular dynamics simulations. The RMSD and RMSF plots indicate the stability of the dynamic structure of the substituted ligand. Analysis of the rotation and hydrogen bond plots revealed strong interactions between the protein and the ligand. Furthermore, analysis of the protein secondary structure and residue-wise secondary structure using the DSSP algorithm confirmed the suitability of the proposed structure and, in some cases, showed improved stability compared to its interaction with ketorolac. In the DCCM analysis, a stronger correlation pattern was observed in AVH, indicating greater stability in this pattern. Principal component analysis based on a free energy perspective revealed closely spaced data points representing low-energy and relatively stable states that are energetically favorable for the system. The protein binding cavity in the electrostatic potential map shows negative and neutral regions, likely indicating greater stabilization of the ligand in the active site. Finally, the MM-PBSA results suggest that although the binding energy of AVH is slightly higher than that of KTR, it remains a negative value, which is thermodynamically favorable, and the binding affinity of AVH to the protein remains strong. Based on these results, we selected and synthesized the best structure compared to ketorolac. We predict that this new structure, designed using a natural product and showing similar chemical effects, will be a potential alternative to ketorolac.

Indexed as

Amino AcidsDrug DesignKetorolacAnti-Inflammatory Agents, Non-SteroidalHumansHydrogen BondingLigandsMolecular Docking SimulationMolecular Dynamics SimulationAmino AcidsAnti-Inflammatory Agents, Non-SteroidalKetorolacLigandsADMET predictionKetorolacl-amino acidsMM-PBSAMolecular dockingMolecular dynamics simulation

Identifiers

PMID41298715
PMCPMC12658042

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