MolOptimizer: A Molecular Optimization Toolkit for Fragment-Based Drug Design.

Adam Soffer, Samuel Joshua Viswas, Shahar Alon, Nofar Rozenberg, Amit Peled, Daniel Piro, Dan Vilenchik, Barak Akabayov

Abstract read

In one paragraph

Article in Molecules (Basel, Switzerland), 2024. 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

8 authors.

Adam SofferDepartment of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.

Samuel Joshua ViswasDepartment of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.

Shahar AlonDepartment of Software Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.

Nofar RozenbergDepartment of Software Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.

Amit PeledDepartment of Software Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.

Daniel PiroDepartment of Software Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.

Dan VilenchikSchool of Computer and Electrical Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.ORCID 0000-0002-3895-688X

Barak AkabayovDepartment of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.ORCID 0000-0002-3882-2742

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MolOptimizer is a user-friendly computational toolkit designed to streamline the hit-to-lead optimization process in drug discovery. MolOptimizer extracts features and trains machine learning models using a user-provided, labeled, and small-molecule dataset to accurately predict the binding values of new small molecules that share similar scaffolds with the target in focus. Hosted on the Azure web-based server, MolOptimizer emerges as a vital resource, accelerating the discovery and development of novel drug candidates with improved binding properties.

Indexed as

Drug DesignDrug DiscoveryMachine Learningcheminformaticsfragment screeninghit-to-lead optimization

Identifiers

PMID38202859

DOI10.3390/molecules29010276

PMCPMC10780997

What OpenQuestion holds

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LicenceCC BY

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Registered trials

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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.