PLBD: protein-ligand binding database of thermodynamic and kinetic intrinsic parameters

Comprehensive analysis of resorcinyl-imidazole Hsp90 inhibitor design

Human Hsp90 chaperones are implicated in various aspects of cancer. Due to this, Hsp90 has been explored as potential target in cancer treatment. Initial attempts to use Hsp90 inhibitors in drug trials failed due to toxicity and inefficacy. The next generation of drugs were less toxic but still insufficiently effective in a clinical setting. Recently, a lot of effort is being put into understanding the consequences of Hsp90 isoform selective inhibition, expecting that this might hold the key in targeting Hsp90 for disease treatment. Here we investigate a series of compounds containing the aryl-resorcinol scaffold with a 5-membered ring as a promising class of new human Hsp90 inhibitors, reaching nanomolar affinity. We compare how the replacement of 5-membered ring, from thiadiazole to imidazole, as well as a variety of their substituents, influences the potency of these inhibitors for Hsp90 alpha and beta isoforms. To further elucidate the dissimilarity in ligand selectivity between the isoforms, a mutant protein was constructed and tested against the ligand library. In addition, we performed a series of molecular dynamics (MD) and docking simulations to further explain our experimental findings as well as evaluated key compounds in cell assays. Our results deepen the understanding of Hsp90 isoform ligand selectivity and serve as an informative base for further Hsp90 inhibitor optimization.

From X-ray crystallographic structure to intrinsic thermodynamics of protein-ligand binding using carbonic anhydrase isozymes as a model system

Carbonic anhydrase (CA) was among the first proteins whose X-ray crystal structure was solved to atomic resolution. CA proteins have essentially the same fold and similar active centers that differ in only several amino acids. Primary sulfonamides are well defined, strong and specific binders of CA. However, minor variations in chemical structure can significantly alter their binding properties. Over 1000 sulfonamides have been designed, synthesized and evaluated to understand the correlations between the structure and thermodynamics of their binding to the human CA isozyme family. Compound binding was determined by several binding assays: fluorescence-based thermal shift assay, stopped-flow enzyme activity inhibition assay, isothermal titration calorimetry and competition assay for enzyme expressed on cancer cell surfaces. All assays have advantages and limitations but are necessary for deeper characterization of these protein-ligand interactions. Here, the concept and importance of intrinsic binding thermodynamics is emphasized and the role of structure-thermodynamics correlations for the novel inhibitors of CA IX is discussed - an isozyme that is overexpressed in solid hypoxic tumors, and thus these inhibitors may serve as anticancer drugs. The abundant structural and thermodynamic data are assembled into the Protein-Ligand Binding Database to understand general protein-ligand recognition principles that could be used in drug discovery.

Inhibitor binding to metal-substituted metalloenzyme: Sulfonamide affinity for carbonic anhydrase IX

Transition metal ions are structural and catalytic cofactors of many proteins including human carbonic anhydrase (CA), a Zn-dependent hydrolase. Sulfonamide inhibitors of CA recognize and form a coordination bond with the Zn ion located in the active site of the enzyme. The Zn ion may be removed or substituted with other metal ions. Such CA protein retains the structure and could serve as a tool to study metal ion role in the recognition and binding affinity of inhibitor molecules. We measured the affinities of selected divalent transition metal ions, including Mn, Fe, Co, Ni, Cu, Cd, Hg, and Zn to metal-free CA isozymes CA I, CA II, and CAIX by fluorescence-based thermal shift assay, prepared metal-substituted CAs, and determined binding of diverse sulfonamide compounds. Sulfonamide inhibitor binding to metal substituted CA followed a U-shape pH dependence. The binding was dissected to contributing binding-linked reactions and the intrinsic binding reaction affinity was calculated. This value is independent of pH and protonation reactions that occur simultaneously upon binding native CA and as demonstrated here, to metal substituted CA. Sulfonamide inhibitor binding to cancer-associated isozyme CAIX diminished in the order: Zn > Co > Hg > Cu > Cd > Mn > Ni. Energetic contribution of the inhibitor-metal coordination bond was determined for all above metals. The understanding of the principles of metal influence on ligand affinity and selectivity should help design new drugs targeting metalloenzymes.

The interoperability of crystallographic data and databases

Interoperability of crystallographic data with other disciplines is essential for the smooth and rapid progress of structure-based science in the computer age. Within crystallography and closely related subject areas, there is already a high level of conformance to the generally accepted FAIR principles (that data be findable, accessible, interoperable and reusable) through the adoption of common information exchange protocols by databases, publishers, instrument vendors, experimental facilities and software authors. Driven by the success within these domains, the IUCr has worked closely with CODATA (the Committee on Data of the International Science Council) to help develop the latter's commitment to cross-domain integration of discipline-specific data. The IUCr has, in particular, emphasized the need for standards relating to data quality and completeness as an adjunct to the FAIR data landscape. This can ensure definitive reusable data, which in turn can aid interoperability across domains. A microsymposium at the IUCr 2023 Congress provided an up-to-date survey of data interoperability within and outside of crystallography, expounded using a broad range of examples.

Enzyme Databases in the Era of Omics and Artificial Intelligence

Enzyme research is important for the development of various scientific fields such as medicine and biotechnology. Enzyme databases facilitate this research by providing a wide range of information relevant to research planning and data analysis. Over the years, various databases that cover different aspects of enzyme biology (e.g., kinetic parameters, enzyme occurrence, and reaction mechanisms) have been developed. Most of the databases are curated manually, which improves reliability of the information; however, such curation cannot keep pace with the exponential growth in published data. Lack of data standardization is another obstacle for data extraction and analysis. Improving machine readability of databases is especially important in the light of recent advances in deep learning algorithms that require big training datasets. This review provides information regarding the current state of enzyme databases, especially in relation to the ever-increasing amount of generated research data and recent advancements in artificial intelligence algorithms. Furthermore, it describes several enzyme databases, providing the reader with necessary information for their use.