You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


1.. Introduction   {#sec1}
==================

Apart from the approved drug Fasudil (HA-1077), H-89 is one of the most prominent representatives of the 'H-series' of kinase inhibitors, a set of ATP-competitive isoquinoline sulfonamides (Chijiwa *et al.*, 1990[@bb6]; Hidaka *et al.*, 1984[@bb13]; Ono-Saito *et al.*, 1999[@bb18]; Fig. 1[▶](#fig1){ref-type="fig"}). H-89 was developed and reported to be selective towards the catalytic subunit of cAMP-dependent protein kinase, also known as protein kinase A (PKA). Despite its misregulation in certain types of cancer, PKA is usually considered to be an 'antitarget' in drug development owing to the ubiquitous and essential nature of the cellular processes that it regulates. Hence, the use of H-89 has largely remained confined to academic research. In contrast, the Rho kinase-targeting inhibitor Fasudil was approved in Japan in 1995 for the prevention of cerebral vasospasm in patients with subarachnoid haemorrhage and was found to potentially be useful to enhance the memory and improve the prognosis of Alzheimers patients (Huentelman *et al.*, 2009[@bb14]). However, H-89 became particularly popular for *in vitro* studies requiring the absence of PKA activity or on the regulatory role of PKA itself. It is still used frequently, but now in the context of recent studies that have shown H-89 to be a rather general AGC kinase inhibitor (Davies *et al.*, 2000[@bb10]; Lochner & Moolman, 2006[@bb16]). While one barrier to the development of H-series compounds as drugs may be the inhibition of PKA, H-89 has also proven to be useful in drug-design projects. The H-­89 scaffold has provided the basis for the design of new compounds with selectivity towards protein kinase B (PKB/Akt; Caldwell *et al.*, 2008[@bb4]; Collins *et al.*, 2006[@bb8]; Reuveni *et al.*, 2002[@bb21]), which is structurally similar to PKA (Gassel *et al.*, 2003[@bb12]) and remains an important drug target (Cheng *et al.*, 2005[@bb5]; Wu & Hu, 2010[@bb27]).

2.. Materials and methods   {#sec2}
===========================

2.1.. Protein production, purification and crystallization   {#sec2.1}
------------------------------------------------------------

The full-length human catalytic subunit α of PKA (GenBank accession No. NP_002721) was expressed in *Escherichia coli* BL21 (DE3)-RIL cells (Stratagene) from a construct based on the vector pT7-7 in auto-induction medium (Studier, 2005[@bb23]) over a period of approximately 20 h at 297 K. The procedures used for the purification of PKA followed previously published protocols (Engh *et al.*, 1996[@bb11]).

Cocrystallization of PKA and H-89 was carried out in hanging drops at 277 K. Drops consisting of 10 mg ml^−1^ protein, 25 m*M* bis-tris/MES pH 6.9, 50 m*M* KCl, 1.5 m*M* octanoyl-*N*-methylglucamide, 1 m*M* 'protein kinase inhibitor' peptide (PKI; ~5~TTYADFIASGR­TGRRNAIHD~24~) and 5 m*M* H-89 (added from a 100 m*M* methanol stock) were equilibrated against 12--22%(*v*/*v*) methanol. For data collection, crystals were transferred into 30% 2-methyl-2,4-pentanediol and flash-cooled.

2.2.. Diffraction data collection and data processing   {#sec2.2}
-------------------------------------------------------

The diffraction of a cooled crystal was measured on beamline ID29 at the European Synchrotron Radiation Facility (ESRF; Grenoble, France). The wavelength of 0.91969 Å was chosen for data collection after a scan for the maximum X-ray absorption of the crystal in proximity to the theoretical *K* absorption edge of bromine, and the data-collection strategy was designed to obtain an overall multiplicity of greater than four. Subsequent processing of the data was carried out with the *XDS* software package (Kabsch, 2010[@bb15]) and the *CCP*4 program suite (Winn *et al.*, 2011[@bb7]). The diffraction frames were integrated with *XDS* and the resulting intensities were scaled with *XSCALE*, in which Friedel pairs were not merged ('FRIEDEL'S_LAW=FALSE' option; Table 1[▶](#table1){ref-type="table"}). The data set was phased by molecular replacement with *MOLREP* (Vagin & Teplyakov, 2010[@bb25]) employing the coordinates of PDB entry [1ydt](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=1ydt) (Engh *et al.*, 1996[@bb11]). The structure was refined with *REFMAC*5 (Murshudov *et al.*, 2011[@bb17]; Table 1[▶](#table1){ref-type="table"}) and the resulting structure factors were merged with the columns 'DANO' and 'SIGDANO' of the unphased original `*.mtz` file using the program *CAD*. The resulting `*.mtz` file containing both the structure factors with phases and the anomalous signal of the bromine of H-89 was used to calculate anomalous difference Fourier maps with the program *FFT* (Ten Eyck, 1973[@bb24]).

*REFMAC*5 (Murshudov *et al.*, 2011[@bb17]) was used to generate weighted electron-density and difference maps (2*mF* ~o~ − *DF* ~c~ and *mF* ~o~ − *DF* ~c~, respectively) for the refined structures (Figs. 2[▶](#fig2){ref-type="fig"} *b* and 2[▶](#fig2){ref-type="fig"} *c*). *F* ~o~ and *F* ~c~ refer to the observed and model structure factors, *m* is the figure of merit and *D* is the model error parameter. The *REFMAC*5 calculation of the weighting factors *D* and *m* (Murshudov *et al.*, 2011[@bb17]) matches that in *SIGMAA* (Read, 1986[@bb20]) except that only the free-*R*-­flagged reflections are used to estimate *m* and *D*. For missing reflections, the map coefficients are replaced with *DF* ~c~ in electron-density maps and zero in difference maps.

2.3.. Inhibitors   {#sec2.3}
------------------

The kinase inhibitor H-89 was purchased from Cayman Chemicals (Ann Arbor, USA). The 'protein kinase inhibitor' peptide (PKI; ~5~TTYADFIASGRTGRRNAIHD~24~) used in the purification and cocrystallization of PKA was purchased from GL Biochem Shanghai Ltd (Shanghai, People's Republic of China).

2.4.. Structure deposition   {#sec2.4}
----------------------------

The coordinates and structure factors of the PKA--H-89 complex crystal structure described here have been deposited in the Protein Data Bank (PDB) with accession code [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh).

3.. Results   {#sec3}
=============

3.1.. Overall structure   {#sec3.1}
-------------------------

In PDB entry [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh) the catalytic subunit α of protein kinase A appears in its usual conformation (Fig. 3[▶](#fig3){ref-type="fig"} *a*), similar to that in reference structures such as [1atp](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=1atp) (Zheng *et al.*, 1993[@bb29]) and [1cdk](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=1cdk) (Bossemeyer *et al.*, 1993[@bb3]) and nearly identical to an earlier structure of a PKA--H-89 complex (PDB entry [1ydt](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=1ydt); Engh *et al.*, 1996[@bb11]). The root-mean-square deviation (r.m.s.d.) between the structures [1ydt](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=1ydt) and [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh) is 0.33 Å. In [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh) the fragment 5--24 of the PKI ('protein kinase inhibitor') peptide, which is routinely used for structural work on PKA as it stabilizes the kinase domain and facilitates crystallization, occupies the peptide-substrate site, which is formed primarily by the surface of the α-helical C-terminal lobe of the protein. The N-terminal lobe, which is mainly comprised of a five-stranded antiparallel β-sheet, is linked covalently to the C-terminal lobe by a single peptide chain (the hinge). Their interface forms a deep cleft which constitutes the binding pocket for the nucleotide substrate ATP. In the structure described here, the ATP-competitive inhibitor H-89 occupies the ATP-binding site (Fig. 3[▶](#fig3){ref-type="fig"} *a*). As shown in Fig. 1[▶](#fig1){ref-type="fig"}, H-89 binds with respect to ATP such that the isoquinoline group of H-89 occupies the adenine-binding pocket, the sulfonamide mimics the ribose group of ATP and the bromobenzene moiety occupies the site of the phosphate groups beneath the glycine-rich loop (formed by β-strands 1 and 2 and the β-turn that links them).

As in PDB entry [1ydt](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=1ydt) (Engh *et al.*, 1996[@bb11]), the electron density for the bromobenzene portion of H-89 is diffuse and its position is not clearly defined (Fig. 2[▶](#fig2){ref-type="fig"}).

3.2.. The anomalous signal describes a bivalent binding mode for H-­89   {#sec3.2}
------------------------------------------------------------------------

The anomalous signal of the bromine of H-89 in the collected data set is rather weak, as is evident from the 'Anomal. corr.' and 'SigAno' parameters in Table 2[▶](#table2){ref-type="table"}, which represent the mean correlation factor between two random subsets of anomalous intensity differences and the mean anomalous difference in units of its estimated standard deviation, respectively. As would be hoped for a diffraction data set containing useful anomalous dispersion information, the anomalous correlation ('Anomal. corr.') exceeds 30% and the anomalous signal is stronger than noise ('SigAno' \> 1), but this applies only for resolutions coarser than ∼5 Å (Table 2[▶](#table2){ref-type="table"}). However, although the strength of the anomalous signal is far below the requirements for a successful SAD phasing experiment (Dauter *et al.*, 2002[@bb9]), it is sufficient to unambiguously localize the position of the bromine moiety of H-89 within the asymmetric unit (Fig. 2[▶](#fig2){ref-type="fig"}).

The anomalous difference Fourier maps in Fig. 2[▶](#fig2){ref-type="fig"}(*a*) display a single strong feature in the asymmetric unit which is dominant in the maps contoured at signal-to-noise ratios of 3σ and 4σ and is unique in the map contoured at 5σ. This peak corresponds to the localization of the bromine group of H-89 in the ATP pocket of PKA (Fig. 2[▶](#fig2){ref-type="fig"} *c*). However, the anomalous density is not localized to one site but appears spread out into two spheres of density, indicating two main positions of the bromine moiety. This result correlates well with the unclear electron density of the bromobenzene group of H-89 in both the structure [1ydt](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=1ydt) (Fig. 2[▶](#fig2){ref-type="fig"} *b*; Engh *et al.*, 1996[@bb11]) and the higher resolution H-89--PKA complex structure determined in this study (Fig. 2[▶](#fig2){ref-type="fig"} *c*). In both cases it seems that the bromobenzene group of H-89 has some freedom to rotate about an axis running perpendicular to its benzene ring. While the electron density alone hints at this, the anomalous density shows distinctly preferred positions of the Br atom.

Consistent with the appearance of two peaks of similar intensity in the anomalous difference Fourier map, the ligand H-89 was modelled in the structure [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh) with two alternative conformations, each with 50% occupancy. Rotation of the C3---N4 bond (Fig. 1[▶](#fig1){ref-type="fig"}) in the flexible linker of H-89 and adjustment of the following dihedrals placed the bromine moieties of the two conformers into the distinct positions indicated by the anomalous difference map. The coordinates of the structure were subsequently refined in *REFMAC*5 without positional restraints for the ligand molecule, resulting in the conformations presented in Fig. 2[▶](#fig2){ref-type="fig"}(*c*). In the refinement the bromobenzene moieties of H-89 retained their distinct positions in good agreement with the density of the anomalous difference map. The linker geometries are correspondingly displaced relative to one another; this is in accord with the partial weak electron density of this portion of H-89 in the structure [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh) (Fig. 2[▶](#fig2){ref-type="fig"} *c*). In contrast, the isoquinoline moiety of H-89 is anchored to the hinge of the kinase domain *via* a hydrogen bond (Fig. 3[▶](#fig3){ref-type="fig"} *c*) and hence features the lowest temperature factors in the ligand molecule (Fig. 3[▶](#fig3){ref-type="fig"} *b*); the adjacent sulfonamide group shows a slight rotation. The torsion angles of the amide groups with respect to the isoquinoline vary by ∼17°. The protein--ligand interactions between PKA and the two conformers differ marginally. This is true for both the polar contacts of the linker of H-89 with PKA and the hydrophobic contacts between the bromobenzene moiety of H-89 and the glycine-rich loop of PKA (Fig. 3[▶](#fig3){ref-type="fig"} *c*). In either case the bromine moiety of H-89 is not involved in polar contacts to the protein and the discrete positions of its two conformers are likely to be a consequence of constraints imposed by the linker dihedrals.

3.3.. Data quality   {#sec3.3}
--------------------

The diffraction data utilized for modelling the structure [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh) originate from a single crystal which was exposed to an X-ray dose of approximately 7 MGy. Because neither the overall diffraction quality nor the anomalous signal decayed during data collection, the disorder of the bromine does not appear to result from radiation damage and both H-89 conformers are clearly observable. Consistently, the bromine moieties of both H-89 conformers appear electron-dense and well observed. The lengths of the bromine--carbon bonds in the bromobenzene moieties were both 1.9 Å, which is in good agreement with literature values.

4.. Discussion   {#sec4}
================

The approach of incorporating bromine into small-molecule ligands in order to quickly screen for binding and to subsequently efficiently determine the binding geometry has been employed as a drug-discovery business model (Antonysamy *et al.*, 2008[@bb1]; Blaney *et al.*, 2006[@bb2]; Wolf *et al.*, 2002[@bb26]). Details of its application and utility are sparse in the scientific literature. However, this would be one approach to address the problem of evaluating ligand flexibility in drug design (Seddon *et al.*, 2012[@bb22]). Here, we show the successful use of this approach for a very specific application, namely the characterization of the apparently heterogeneous binding mode of a kinase inhibitor, which was not possible using electron-density maps (2*mF* ~o~ − *DF* ~c~) alone.

Although the statistics showed the overall anomalous signal to only be significant in lower resolution shells, the effects of the total signal transformed into the real-space anomalous electron-density map were unambiguously localized at the bromine group of H-89 with a resolution sufficient to identify two discrete positions. This demonstrates the utility of the approach for other related applications in characterizing binding-mode heterogeneity and also confirms its usefulness for applications involving weak-binding ligands or low-affinity small-molecule fragments that may bind with only partial occupancies.

Regarding the flexible binding mode of H-89 in the ATP pocket of PKA, the question arises whether this information may be useful for application in inhibitor design. In general, binding flexibility is associated with adaptability to variation in binding sites, consistent with the broad inhibition profile of H-89 for AGC kinases (Davies *et al.*, 2000[@bb10]; Lochner & Moolman, 2006[@bb16]). In order to develop H-89 towards a PKB inhibitor the linker between its aromatic moieties was rigidified, but the selectivity of the resulting compounds was not reported (Caldwell *et al.*, 2008[@bb4]; Collins *et al.*, 2006[@bb8]). An interesting approach could be to modify the linker of H-89 to capture the two respective binding conformations and investigate potential changes in the target-selectivity pattern of the compounds.

Supplementary Material
======================

PDB reference: [PKA--H-89 complex, 3vqh](3vqh)

![Chemical structures of adenosine-5′-triphosphate (ATP), Fasudil and H-89 in similar orientations with respect to the ATP pocket (hinge region at the left). The isoquinoline portion of H-89 is highlighted in blue, the sulfonamide portion in green and the bromobenzene moiety in red. The numbering of the H-89 molecule refers to C3 and N4, consistent with the designation of the atoms in the structure [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh). 'PKA' refers to cAMP-dependent protein kinase catalytic subunit α isoform 1 and 'ROCK2' to Rho kinase α. Affinity values were taken from the literature: \*, Rajagopalan *et al.* (2010[@bb19]); †, Gassel *et al.* (2003[@bb12]); ‡, Yano *et al.* (2008[@bb28]); §, Engh *et al.* (1996[@bb11]).](f-68-00873-fig1){#fig1}

![(*a*) Anomalous difference Fourier maps (1.95 Å) generated to cover all atoms of the asymmetric unit in PDB entry [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh) contoured at levels of 3σ, 4σ and 5σ. (*b*) 2.3 Å resolution electron-density map (grey) and difference density map (green) surrounding the compound H-89 in PDB entry [1ydt](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=1ydt) (cyan; Engh *et al.*, 1996[@bb11]). (*c*) 1.95 Å resolution OMIT electron-density map (grey) and anomalous difference density map (blue) carved around the two conformations of compound H-89 in PDB entry [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh) (yellow).](f-68-00873-fig2){#fig2}

![(*a*) Overall structure of PDB entry [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh): a ternary complex of the catalytic subunit α of protein kinase A (PKA; white), the peptidic pseudosubstrate 'protein kinase inhibitor' (PKI; grey) and the ATP-competitive inhibitor H-89 (yellow). (*b*) *B*/temperature factors of the H-89 conformers in the structure [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh) plotted as spheres on the respective atoms. The values are indicated for selected atoms. (*c*) Binding environment of the H-89 conformers in the ATP pocket of PKA in structure [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh). Residues Val123, Glu127 and Asn171 form hydrogen bonds to the ligands; the bromine moieties pack against hydrophobic atoms from the side chains of Phe54 and Lys174 and some main-chain atoms of the glycine-rich loop. The inner surface of the ATP pocket is represented in red (maximum distance of 2 Å from the inhibitor molecule).](f-68-00873-fig3){#fig3}

###### Refinement and structure statistics of PDB entry [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh)

Values in parentheses are for the last shell.

  ---------------------------------------------------- ---------------------------------------
  Data collection and scaling (*XDS*)                  
  X-ray source                                         ID29, ESRF
  Resolution limits ()                                 35.01.95 (2.201.95)
  Unit-cell parameters ()                              *a* = 72.73, *b* = 75.18, *c* = 80.33
  Space group                                          *P*2~1~2~1~2~1~
  Wavelength ()                                        0.91969
  Total No. of reflections                             283804 (84880)
  No. of unique reflections                            61702 (18509)
  Multiplicity                                         4.6 (4.6)
  *I*/(*I*)                                            19.08 (5.68)
  *R* ~mrgd-*F*~ [†](#tfn1){ref-type="table-fn"} (%)   9.0 (28.8)
  Completeness (%)                                     98.0 (99.3)
  Wilson *B* (^2^)                                     21.57
  Refinement (*REFMAC*5)                               
  *R* ~work~ [‡](#tfn2){ref-type="table-fn"} (%)       19.0
  *R* ~free~ [‡](#tfn2){ref-type="table-fn"} (%)       23.4
  Average *B* factor (^2^)                             21.88
  No. of protein atoms                                 3015
  No. of ligand atoms                                  62
  No. of water molecules                               178
  R.m.s.d. bond lengths ()                             0.010
  R.m.s.d. bond angles ()                              1.38
  Ramachandran plot (*PROCHECK*)                       
  Most favoured (%)                                    91.1
  Additionally allowed (%)                             8.9
  Generously allowed (%)                               0
  Disallowed (%)                                       0
  ---------------------------------------------------- ---------------------------------------

*R* ~mrgd-*F*~ = .

*R* ~work~/*R* ~free~ = .

###### Selected columns from the *XSCALE* scaling statistics of PDB entry [3vqh](http://scripts.iucr.org/cgi-bin/cr.cgi?rm=pdb&pdbId=3vqh)

  Resolution limit ()   Completeness of data (%)   *I*/(*I*)   *R* ~mrgd-*F*~ (%)   Anomal. corr.[†](#tfn3){ref-type="table-fn"} (%)   SigAno[‡](#tfn4){ref-type="table-fn"}
  --------------------- -------------------------- ----------- -------------------- -------------------------------------------------- ---------------------------------------
  35                    0.0                        99          99.9                 0                                                  0
  30                    90.0                       65.84       1.3                  35                                                 1.870
  25                    90.9                       32.47       2.4                  3                                                  1.318
  20                    96.7                       62.23       1.4                  75                                                 1.661
  15                    100.0                      56.57       1.3                  57                                                 1.599
  10                    100.0                      59.68       1.2                  47                                                 1.132
  9                     100.0                      54.80       1.3                  53                                                 1.224
  8                     100.0                      53.60       1.6                  42                                                 1.211
  7                     100.0                      50.58       1.6                  44                                                 1.457
  6                     100.0                      46.30       1.7                  36                                                 1.192
  5                     100.0                      46.07       1.8                  22                                                 1.021
  4                     99.8                       46.41       1.8                  15                                                 0.940
  3.8                   99.9                       43.37       2.1                  13                                                 0.920
  3.55                  99.9                       40.27       2.4                  4                                                  0.847
  3.3                   99.9                       35.20       2.8                  8                                                  0.920
  3.05                  100.0                      30.36       3.7                  10                                                 0.935
  2.8                   99.9                       23.71       5.3                  9                                                  0.906
  2.45                  100.0                      16.07       8.6                  6                                                  0.865
  2.2                   100.0                      10.88       13.7                 3                                                  0.836
  1.95                  98.0                       5.68        28.8                 3                                                  0.791
                                                                                                                                        
  Total                 99.3                       19.08       9.0                  6                                                  0.867

Anomal. Corr. is the mean correlation factor between two random subsets of anomalous intensity differences.

SigAno = \[\|*F* ~(+)~ *F* ~()~\|/\].