Evidence map›Paper›PMID 40229743›Full record

ArticleBMC bioinformatics2025

M01 tool: an automated, comprehensive computational tool for generating small molecule-peptide hybrids and docking them into curated protein structures.

Mahsa Sheikholeslami, Mohammad Hasan Nazari, Afshin Fassihi

Abstract read
In one paragraph

Article in BMC bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mahsa SheikholeslamiDepartment of Medicinal Chemistry, School of Pharmacy and Pharmaceutical Science, Isfahan University of Medical Science, Hezar Jerib, Isfahan, 817416 - 73461, Iran. mahsaa.sheikholeslami@gmail.com.
Mohammad Hasan NazariDepartment of Medicinal Chemistry, School of Pharmacy and Pharmaceutical Science, Isfahan University of Medical Science, Hezar Jerib, Isfahan, 817416 - 73461, Iran.
Afshin FassihiDepartment of Medicinal Chemistry, School of Pharmacy and Pharmaceutical Science, Isfahan University of Medical Science, Hezar Jerib, Isfahan, 817416 - 73461, Iran. fassihi@pharm.mui.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe field of computational drug design is undergoing rapid advancements, highlighting the need for innovative methods to enhance the efficiency and accuracy of calculating ligand-receptor interactions. In this context, we introduce the M01 tool, a comprehensive computational package designed to facilitate the generation and docking of small molecule-peptide hybrids. M01 integrates several established tools, such as RDKit and EasyDock, into a user-friendly platform that automates the workflow from hybrid generation to docking simulations. This tool is particularly beneficial for researchers with limited chemistry expertise, helping them leverage advanced computational techniques.

resultsThe M01 tool features an intuitive interface for visualizing molecules and selecting connection points in generating new ligands. It also offers automated receptor preparation using UniProt or PDB IDs and generates default docking configuration files. Furthermore, it includes ligand preparation and docking capabilities through EasyDock and calculates molecular descriptors relevant to drug-likeness properties. Validation studies with peptide-alkoxyamine hybrids demonstrated the tool's effectiveness, generating over 14,000 unique hybrid molecules and showcasing its versatility in drug design applications.

conclusionsThe M01 tool represents a significant advancement in computational drug design, streamlining the process of creating hybrid molecules and conducting docking studies. Its ability to automate complex workflows and provide essential molecular insights can empower researchers and enhance the development of novel therapeutics, ultimately contributing to more efficient drug discovery efforts.

Indexed as

Molecular Docking SimulationPeptidesProteinsSmall Molecule LibrariesSoftwareDrug DesignLigandsProtein ConformationLigandsPeptidesProteinsSmall Molecule LibrariesADMET propertiesComputational drug designDocking simulationsHybrid moleculesLigand-receptor interactionsPeptide–drug conjugates

Identifiers

PMID40229743
PMCPMC11995494

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.