File:3iaidock.pdb

2024-06-25T15:35:34Z

Alexander Berchansky:

Journal:IUCrJ:S2052252524004627

2024-06-25T15:28:21Z

Alexander Berchansky:

<StructureSection load='' size='450' side='right' scene='10/1051456/Cv/1' caption=''>
===From X-ray crystallographic structure to intrinsic thermodynamics of protein–ligand binding using carbonic anhydrase isozymes as a model system===
<big>Vaida Paketuryte-Latve, Alexey Smirnov, Elena Manakova, Lina Baranauskiene, Vytautas Petrauskas, Asta Zubriene, Jurgita Matuliene, Virginija Dudutiene, Edita Capkauskaite, Audrius Zaksauskas, Janis Leitans, Saulius Grazulis, Kaspars
Tars and Daumantas Matulis</big> <ref>doi: 10.1107/S2052252524004627</ref>
<hr/>
<b>Molecular Tour</b><br>
Rational design of novel pharmaceutical molecules requires deep understanding of how small molecules recognize and bind to the disease target protein molecule. Unfortunately, the mechanism of recognition is still quite poorly understood. Experimentally, the binding reaction can be described structurally and energetically. The X-ray crystallographic structure of the drug candidate molecule bound to the protein molecule provides detailed information on the structural arrangement and the interface between the compound and the protein. However, the structural information does not yield a clue on the strength and affinity, thus the energy of the interaction. Full energetic description should include the measurement of the thermodynamic binding parameters, including the Gibbs energy, enthalpy, entropy, heat capacity, compressibility, and several others and the kinetic parameters, especially the dissociation rate constant or residence time. When the reaction is fully characterized both structurally and energetically, we can begin studying the principles of structure – thermodynamics correlations.
However, both the structural and energetic characterization may succumb to numerous pitfalls. The structure of the protein – ligand complex may be determined by numerous structural methods, such as X-ray crystallography, NMR, and Cryo-EM. The conditions of these experiments may vary a lot, the temperature may be 100K, much lower than the physiological temperature. Dynamic information may be more accessible in NMR than in other methods. Limited resolution may also be insufficient to determine exact positions of all atoms including hydrogens. There are always limitations of what the structural picture can provide. On the other hand, energetic description is also highly complex. There are numerous techniques to characterize the affinity and other thermodynamic parameters of binding. Each technique has limitations as described in this manuscript. However, here we especially emphasize the intrinsic energetics of binding. Numerous protein – ligand binding reactions are linked to protonation reactions that contribute significant energies and without the dissection of such energies it is impossible to draw proper structure – thermodynamics correlations.
In this manuscript we illustrate how detailed structural and thermodynamic characterization, especially taking into account the intrinsic parameters, helped to design high-affinity and high-specificity chemical compounds that would bind carbonic anhydrase IX (CAIX), a protein that is highly overexpressed in most solid hypoxic tumors. The protein participates in the acidification of the tumor microenvironment, helps promote invasion and metastasis processes in cancer. Thus, a possible anticancer strategy could involve inhibition of the protein by inhibitors that would not bind to any other proteins and thus not cause possible toxic side effects. We synthesized over 1000 molecules and demonstrated chemical structure features of a compound to exhibit high affinity for CAIX and low affinity for remaining 11 catalytically active vital human carbonic anhydrase isozymes. The compounds were arranged into a database ([https://plbd.org/db/ plbd.org]) to help researchers apply AI approaches and study the structure – thermodynamics correlations for rational drug design.

'''Compound Vd11-4-2:'''
*<scene name='10/1051456/Vd11-4-2cai/2'>VD11-4-2 CA I</scene> (PDB ID [[5e2m]]).
*<scene name='10/1051456/Vd11-4-2caii/2'>VD11-4-2 CA II</scene> (PDB ID [[4pyy]]).
*<scene name='10/1051456/Vd11-4-2caix/2'>VD11-4-2 CA IX</scene> (PDB ID [[6fe1]]).
*<scene name='10/1051456/Vd11-4-2caxii/3'>VD11-4-2 CA XII</scene> (PDB ID [[4q0l]]).
*<scene name='10/1051456/Vd11-4-2caxiii/3'>VD11-4-2 CA XIII</scene> (PDB ID [[5e2n]]).

'''Compound VD10-35:'''
*<scene name='10/1051456/Vd10-35caii/3'>VD10-35 CA II</scene> (PDB ID [[4pzh]]).
*<scene name='10/1051456/Vd10-35caixdock/1'>VD10-35 CA IX docked</scene>.
*<scene name='10/1051456/Vd10-35caxii/1'>VD10-35 CA XII</scene> (PDB ID [[5msb]]).
*<scene name='10/1051456/Vd10-35caxiii/1'>VD10-35 CA XIII</scene> (PDB ID [[4hu1]]).

'''Compound VD12-05:'''
*<scene name='10/1051456/Vd12-05cai/1'>VD12-05 CA I</scene> (PDB ID [[4wr7]]).
*<scene name='10/1051456/Vd12-05caii/1'>VD12-05 CA II</scene> (PDB ID [[4ww6]]).
*<scene name='10/1051456/Vd12-05caxii/1'>VD12-05 CA XII</scene> (PDB ID [[5msa]]).
*<scene name='10/1051456/Vd12-05caxiii/2'>VD12-05 CA XIII</scene> (PDB ID [[5lln]]).

<b>References</b><br>
<references/>
</StructureSection>
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2024-06-20T15:49:44Z

Alexander Berchansky:

Alexander Berchansky:

<StructureSection load='' size='450' side='right' scene='underdevelopment' caption=''>
===From X-ray crystallographic structure to intrinsic thermodynamics of protein–ligand binding using carbonic anhydrase isozymes as a model system===
<big>Daumantas Matulis</big> <ref>doi: 10.1107/S2052252524004627</ref>
<hr/>
<b>Molecular Tour</b><br>

<b>References</b><br>
<references/>
</StructureSection>
__NOEDITSECTION__

Journal:Acta Cryst D:S2059798324005229

2024-06-16T07:15:36Z

Alexander Berchansky:

<StructureSection load='' size='450' side='right' scene='10/1050322/Cv/1' caption=''>
===Factors affecting macromolecule orientations in thin films formed in cryo-EM===
<big>Swati Yadav and Vinothkumar Kutti Ragunath</big> <ref>doi: 10.1107/S2059798324005229</ref>
<hr/>
<b>Molecular Tour</b><br>
Single particle cryo-EM has become a routine and indispensable technique in structural biology, where macromolecules are imaged with electrons as single particles and subsequently averaged to obtain a high-resolution 3D reconstruction. Single particle cryo-EM reconstruction utilizes the projection slice theorem to build a 3D map of a 3D object using 2D projections, generated when electrons transmitted through a thin specimen are recorded by a detector. The resolution and quality of the final map depend on many factors including heterogeneity in the specimen, adequate sampling of views and signal-to-noise of the images.
A key step in this process is to obtain a thin film of macromolecules (purified or as a mixture) in ice and the most routinely used method for obtaining such thin films was developed by Dubochet and his colleagues (Dubochet ''et al.,'' 1988<ref name="Dubochet1">PMID:3043536</ref>). Obtaining the optimal conditions for freezing of a given macromolecule requires testing several parameters. At the moment, it is one of the rate-limiting steps in obtaining high-resolution maps by cryo-EM. During the freezing process, the macromolecules can encounter and interact with the air-water interface, sometimes resulting in a tendency to adapt one or more preferential orientations along with denaturation and dissociation in the case of multi-subunit complexes (D’Imprima ''et al.,'' 2019<ref name="D’Imprima">PMID:30932812</ref>; Noble ''et al.,'' 2018<ref name="Noble">PMID: 30250056</ref>; Glaeser and Han, 2017<ref name="Glaeser">PMID: 28781996</ref>). The 3D maps reconstructed from preferentially oriented macromolecules exhibit stretching of densities in one direction (also called anisotropy, where with enough particles the resolution will be high but the maps are not easily interpretable). One such example is the spike protein shown in Figure 1A, which illustrates the effects of orientation bias on the final reconstruction.
[[Image:Figure1RR5238.png|left|thumb|400px]]
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'''Figure 1:''' The models used as reference are PDBs [[8h3d]] and [[6cvm]] for the spike protein and b-galactosidase respectively. A) Spike protein, SARS-COV-2. <scene name='10/1050322/Spike_no_additive/1'>Spike, no additive</scene> ([[8h3d]]). <scene name='10/1050322/Spike_with_ctab/1'>Spike with CTAB</scene> ([[8wzi]]). B) β-galactosidase.

There are multiple ways to address orientation bias including the use of support layers like carbon or graphene, tilting of the stage and more commonly, the use of surfactants or detergents as small molecule additives during grid preparation (Liu and Wang, 2023<ref name="Liu">PMID: 36563741</ref>). There are a number of macromolecules where surfactants have been used to overcome the preferred orientation problem. In this work, we asked if an informed decision regarding the grid freezing conditions can be made based on the properties of the macromolecule.
We studied macromolecules of different sizes and symmetries (125-440 kDa, C1 to D3) and tested a few commonly used surfactants to overcome the orientation bias and observed that many of these surfactants are beneficial. One such example is cationic surfactant CTAB, which causes changes in the orientation distribution of SARS-CoV-2 spike protein as shown in Figure1A. Further, we tested the effect of poly-histidine tag on orientation distribution of macromolecules. Figure 1B shows the impact of the N-terminal poly-his tag on orientation in the case of the E. coli β-galactosidase enzyme. We assessed the improvement in orientation distribution with different measures including the orientation distribution plot after 3D refinement (Scheres 2012<ref name="Scheres">PMID: 23000701</ref>), Efficiency of orientation distribution (Naydenova & Russo, 2017<ref name="Naydenova">PMID: 28931821</ref>), 3D-FSC (Tan ''et al.,'' 2018<ref name="Tan">PMID: 28671674</ref>) and the map vs model FSC curve. We also tested the effect of grid hole size and temperature during grid preparation on orientation bias demonstrated using human erythrocyte catalase as an example (Figure 2).

[[Image:Figure2RR5238.png|left|thumb|400px]]
{{Clear}}
'''Figure 2:''' Human erythrocyte catalase. <scene name='10/1050322/Catalase/1'>Catalase at 20 °C</scene> (PDB ID [[8wzj]]).

In summary, physical and chemical factors affecting macromolecule behaviour on grids have been studied to overcome the preferred orientation problem (Figure 3). These findings lay a platform in achieving optimal freezing conditions for any given macromolecule in the future.

[[Image:Figure3RR5238.png|left|thumb|400px]]
{{Clear}}
'''Figure 3'''

<b>References</b><br>
<references/>
</StructureSection>
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