Evidence map›Paper›PMID 42864407›Full record

Reviewnpj drug discovery2026

Computational design and translational development of TCR-mimic scFv antibodies for peptide-HLA neoantigen targeting.

Sarfaraz K Niazi, Matthias Magoola, Zamara Mariam

Abstract readReview
In one paragraph

Review in npj drug discovery, 2026. 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.

Sarfaraz K NiaziWashington State University, Spokane, WA, 99202, USA. s.niazi@wsu.edu.
Matthias MagoolaDEI Biopharma, Kampala, Uganda.
Zamara MariamCentre for Health and Life Sciences, Coventry University, Coventry City, CV1 5FB, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-chain variable fragments (scFvs) penetrate tissue more effectively than full antibodies and are simpler to produce, but the mutant proteins that define a tumor are predominantly intracellular and therefore inaccessible to conventional antibodies. What is accessible is the mutation-derived peptide displayed on cell-surface HLA. This review concerns TCR-mimic scFvs directed at those peptide-HLA complexes. It separates three questions that are frequently conflated: which mutations are predicted to be presented, which presented complexes are genuinely targetable given surface density and cross-reactivity risk, and how immunogenic the resulting therapeutic molecule will itself be. We review computational strategies spanning target identification, AI-driven structure prediction, de novo design, affinity and specificity engineering, half-life extension and deimmunization, and distinguish throughout between the scFv as a recognition module and the effector architecture, such as a CD3 bispecific, a chimeric antigen receptor binding domain or an Fc-containing format, in which it must ultimately be deployed.

Identifiers

PMID42864407
PMCPMC13658221

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.