Evidence map›Paper›PMID 37626222›Full record

ReviewJournal of molecular evolution2023

Domain Architecture Based Methods for Comparative Functional Genomics Toward Therapeutic Drug Target Discovery.

Pavan Gollapalli, Sushmitha Rudrappa, Vadlapudi Kumar, Hulikal Shivashankara Santosh Kumar

Open access · greenAbstract readReview
PubMed Publisher
In one paragraph

Review in Journal of molecular evolution, 2023. 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, top 100% of its field
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, 0 citations in OpenAlex.

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

4 authors.

Pavan GollapalliCenter for Bioinformatics and Biostatistics, Nitte (Deemed to be University), Mangalore, Karnataka, 575018, India.ORCID 0000-0002-7252-1564
Sushmitha RudrappaDepartment of Biotechnology and Bioinformatics, Jnana Sahyadri Campus, Kuvempu University, Shankaraghatta, Shivamogga, Karnataka, 577451, India.
Vadlapudi KumarDepartment of Biochemistry, Davangere University, Shivagangothri, Davangere, Karnataka, 577007, India.
Hulikal Shivashankara Santosh KumarDepartment of Biotechnology and Bioinformatics, Jnana Sahyadri Campus, Kuvempu University, Shankaraghatta, Shivamogga, Karnataka, 577451, India. sk.genesan@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genes duplicate, mutate, recombine, fuse or fission to produce new genes, or when genes are formed from de novo, novel functions arise during evolution. Researchers have tried to quantify the causes of these molecular diversification processes to know how these genes increase molecular complexity over a period of time, for instance protein domain organization. In contrast to global sequence similarity, protein domain architectures can capture key structural and functional characteristics, making them better proxies for describing functional equivalence. In Prokaryotes and eukaryotes it has proven that, domain designs are retained over significant evolutionary distances. Protein domain architectures are now being utilized to categorize and distinguish evolutionarily related proteins and find homologs among species that are evolutionarily distant from one another. Additionally, structural information stored in domain structures has accelerated homology identification and sequence search methods. Tools for functional protein annotation have been developed to discover, protein domain content, domain order, domain recurrence, and domain position as all these contribute to the prediction of protein functional accuracy. In this review, an attempt is made to summarise facts and speculations regarding the use of protein domain architecture and modularity to identify possible therapeutic targets among cellular activities based on the understanding their linked biological processes.

Indexed as

Drug DiscoveryGenomicsProtein DomainsAnimalsEvolution, MolecularHumansProteinsProteinsCo-occurrence networksDomain architecture and evolutionDomains’ Versatility indexRegulatory networkTherapeutic targets

Identifiers

PMID37626222
OpenAlexW37626222

What OpenQuestion holds

Textmetadata
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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.