Structural aspects of molecular recognition in the immune system. Part I: Acquired immunity (IUPAC Technical Report)
Bibliographic record
Abstract
Abstract Humoral immunity allows the body to mount a defense against pathogens and foreign substances, and to respond with memory to subsequent exposures. The molecular participants may also recognize self-structures, leading to attack on the body and autoimmune disease. The main players in humoral immunity are antibody-producing B lymphocytes, and several classes of T lymphocytes. This review deals with the molecular details of recognition of antigens by soluble antibodies, and of substances presented to receptors on the surfaces of T cells (TCRs). The prototype antibody consists of a dimer of dimers, two heavy (H) chains and two light (L) chains, with antigen recognition capacity lying in variable “head” regions of an H-L pair. Most crystallographic studies are done with this substructure, called a Fab fragment, bound in a soluble antigen complex. Homologous to this arrangement, the prototype TCR consists of two chains (α and β) that complex not soluble antigen, but usually a short peptide or other small molecule presented by proteins of the major histocompatibility complex. In each case a general background on the historical development of understanding the molecular recognition interface is given, followed by a number of examples of crystal structures from the recent literature that have allowed us to refine our understanding of the complex recognition process. Variations on the prototypical structures are also considered. The spectrum of recognition strategies involves interplay of lock-and-key with flexibility, varying degrees of entropic and enthalpic contributions, surface shaping by entrapped water molecules, and combinations of stabilizing hydrogen bonding, electrostatic interactions, salt bridging, and van der Waals forces. Preeminent in the recent literature are details of antibody binding to influenza A and human immunodeficiency viral antigens. Both viral antigens and attempts to understand autoimmunity are prominent in the recent TCR literature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".