Evidence map›Paper›PMID 35889494›Full record

ReviewMolecules (Basel, Switzerland)2022

Open-Source Browser-Based Tools for Structure-Based Computer-Aided Drug Discovery.

Ann Wang, Jacob D Durrant

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

2 authors.

Ann WangDepartment of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA.
Jacob D DurrantDepartment of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA.ORCID 0000-0002-5808-4097

Funding

Advancing drug-lead and chemical-probe discovery using weighted-ensemble simulations and biophysical validationR01GM132353 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DURRANT, JACOB D · 2019 to 2023
$1.7M
NIGMS NIH HHS R01 GM132353NIGMS NIH HHS R01GM132353
6 · The paper itself

Abstract

We here outline the importance of open-source, accessible tools for computer-aided drug discovery (CADD). We begin with a discussion of drug discovery in general to provide context for a subsequent discussion of structure-based CADD applied to small-molecule ligand discovery. Next, we identify usability challenges common to many open-source CADD tools. To address these challenges, we propose a browser-based approach to CADD tool deployment in which CADD calculations run in modern web browsers on users' local computers. The browser app approach eliminates the need for user-initiated download and installation, ensures broad operating system compatibility, enables easy updates, and provides a user-friendly graphical user interface. Unlike server apps-which run calculations "in the cloud" rather than on users' local computers-browser apps do not require users to upload proprietary information to a third-party (remote) server. They also eliminate the need for the difficult-to-maintain computer infrastructure required to run user-initiated calculations remotely. We conclude by describing some CADD browser apps developed in our lab, which illustrate the utility of this approach. Aside from introducing readers to these specific tools, we are hopeful that this review highlights the need for additional browser-compatible, user-friendly CADD software.

Indexed as

ComputersSoftwareDrug DiscoveryInternetLigandsUser-Computer InterfaceWeb BrowserLigandsbrowser-based toolscomputer-aided drug discoverycomputer dockingopen sourcetool developmentusabilityweb-based tools

Identifiers

PMID35889494
PMCPMC9319651

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.