Evidence map›Paper›PMID 36445582›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Computer-Aided Drug Design: An Update.

Wenbo Yu, David J Weber, Alexander D MacKerell

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. 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

3 authors.

Wenbo YuDepartment of Pharmaceutical Sciences, Computer-Aided Drug Design Center, School of Pharmacy, University of Maryland, Baltimore, MD, USA. wyu@rx.umaryland.edu.
David J WeberInstitute for Bioscience and Biotechnology Research (IBBR), Rockville, MD, USA.
Alexander D MacKerellDepartment of Pharmaceutical Sciences, Computer-Aided Drug Design Center, School of Pharmacy, University of Maryland, Baltimore, MD, USA. amackerell@rx.umaryland.edu.

Funding

Macromolecular Conformational HeterogeneityR35GM131710 · NIGMS · UNIVERSITY OF MARYLAND BALTIMORE · PI ALEXANDER D MACKERELL · 2019 to 2026
$6.2M
Signal Propagation in Protein Allostery: Mechanism and EvolutionR01GM129327 · NIGMS · UNIV OF MARYLAND, COLLEGE PARK · PI WEBER, DAVID JOSEPH · 2019 to 2022
$1.3M
Structure-based targeting of the C. difficile toxin (CDT) from hypervirulent bacterial strainsR56AI152397 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI DES GEORGES, AMEDEE, WEBER, DAVID JOSEPH · 2021 to 2021
$522k
NIAID NIH HHS R56 AI152397NIGMS NIH HHS R01 GM129327NIGMS NIH HHS R35 GM131710
6 · The paper itself

Abstract

Computer-aided drug design (CADD) approaches are playing an increasingly important role in understanding the fundamentals of ligand-receptor interactions and helping medicinal chemists design therapeutics. About 5 years ago, we presented a chapter devoted to an overview of CADD methods and covered typical CADD protocols including structure-based drug design (SBDD) and ligand-based drug design (LBDD) approaches that were frequently used in the antibiotic drug design process. Advances in computational hardware and algorithms and emerging CADD methods are enhancing the accuracy and ability of CADD in drug design and development. In this chapter, an update to our previous chapter is provided with a focus on new CADD approaches from our laboratory and other peers that can be employed to facilitate the development of antibiotic therapeutics.

Indexed as

AlgorithmsDrug DesignAnti-Bacterial AgentsLaboratoriesLigandsAnti-Bacterial AgentsLigandsBinding site predictionBiologicsComputer-aided drug designDrude polarizable force fieldMachine learningMembrane permeationMolecular dynamicsProtein-protein interactionSILCSSite identification by ligand competitive saturation

Identifiers

PMID36445582
PMCPMC9838881

What OpenQuestion holds

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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.