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λ‑analysis quantifies structural freedom with a sensitivity far beyond conventional metrics. The contrast between two experimentally determined structures—6CM4 and 6VM5—illustrates this power.

6CM4 exhibits λ = 3.6063, indicating a highly flexible but still ordered conformation. This state supports localized rearrangements and induced‑fit behavior, enabling ligands to reshape the pocket within a controlled dynamic range.

In sharp contrast, 6VM5 reaches λ = 9.8384, a level of structural freedom nearly three times higher. At this magnitude, the protein enters a distinct dynamic regime: latent pockets emerge, symmetry breaks, and deep cavities form that are invisible in static structural comparisons.

For drug‑discovery teams, this numerical gap is transformative. It reveals which conformations are merely flexible (λ ≈ 3.6) and which are truly activation‑competent, pocket‑forming, and drug‑responsive (λ ≈ 9.8). λ thus enables the identification of hidden druggable states long before they appear in traditional structural or AI‑predicted models.

In short:

• λ = 3.6063 → flexible but ordered

• λ = 9.8384 → dynamically liberated, pocket‑forming, high‑value drug‑target state

We invite partners seeking to integrate λ into next‑generation target evaluation, pocket discovery, and mechanism‑of‑action prediction.

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We have developed a proprietary computational framework that quantifies the strength of allosteric effects induced by ligand binding, expressed as a single parameter, λ (lambda). λ integrates structural fluctuations, energy redistribution, and network centrality shifts within the protein, enabling direct numerical evaluation of allosteric modulation.

Using CCR5 as a benchmark target, our λ model successfully reproduced the known allosteric behavior reported in the literature. For example, structural comparisons such as 4NBS (λ = 0.0925) and 6AKX (λ = 0.1411) demonstrate the model’s ability to detect subtle yet functionally relevant conformational changes consistent with experimentally validated allosteric mechanisms.

Key Advantages for Drug Discovery

• Quantitative prediction of allosteric modulation before wet‑lab experiments

• Identification of novel allosteric sites and disease‑specific regulatory nodes

• High‑resolution differentiation between binding without functional impact vs. true allosteric signaling

• Accelerated SAR optimization guided by λ values

• Repositioning opportunities through functional reassessment of existing compounds

Our approach bridges dynamic structural biology and computational immunology, providing a unique platform for discovering and optimizing allosteric modulators across GPCRs, kinases, and immune‑related targets.

We welcome discussions on collaborative research, joint development, or technology evaluation. Further details can be shared under confidentiality.

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Unified λ Theory Captures Opposite Activation Mechanisms of GPCRs and Nuclear Receptors**

The Zaitsu λ Model provides a unified quantitative framework that captures fundamentally opposite activation mechanisms across major drug target classes.

For GPCRs such as rhodopsin, activation is driven not by dimerization but by vibration‑driven conformational dynamics. In structures like 3PXO (λ = 12.85), the receptor transitions into an active state purely through pocket opening and dynamic phase shifts, even without large-scale domain rearrangement.

In contrast, nuclear receptors (NRs) activate through the exact opposite mechanism. NRs undergo ligand‑induced dimerization, and the formation of a water-mediated pocket network between the two monomers stabilizes the active conformation, including the AF‑2 helix.

Despite these mechanistic differences, the λ parameter quantifies both processes on a single scale, enabling:

• Unified evaluation of activation strength across GPCRs and NRs

• Detection of dynamics‑driven activation states

• Identification of water‑network–dependent activation in dimeric receptors

• Cross‑target comparison of allosteric modulation

• Mechanism‑aware lead optimization

λ is the first parameter capable of numerically describing activation strength across structurally and mechanistically divergent receptor families. This provides pharmaceutical companies with a powerful new tool for allosteric drug discovery, target validation, and mechanism‑based compound triage.

“In 3PXO (λ = 12.85), the protein does not form a dimer nor undergo a large-scale domain rearrangement. Instead, the activation appears to be driven purely by changes in conformational dynamics and pocket opening, representing a vibration-driven active state.”

日本語なら：

「3PXO（λ = 12.85）では、二量体形成や大規模なドメイン再配置は認められず、 ポケットの開大と構造揺らぎの変化のみで活性化状態に移行していると解釈できる。 すなわち、振動駆動型の活性化状態とみなすことができる。」

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The Zaitsu λ Parameter provides a powerful, quantitative lens for interpreting structural biology. Even closely related structures such as 5VEX (λ = 0.07341) and 5VAI (λ = 0.1272) exhibit clearly separable allosteric states when analyzed through λ. This demonstrates λ’s unique ability to detect subtle conformational shifts, classify activation tiers, and extract dynamic information from static PDB coordinates. By converting structural differences into pharmacologically meaningful values, λ enables mechanism‑based compound triage, allosteric site evaluation, and cross‑target comparison with unprecedented clarity.