Computational 3D Modeling-Based Identification of Inhibitors Targeting Cysteine Covalent Bond Catalysts for JAK3 and CYP3A4 Enzymes in the Treatment of Rheumatoid Arthritis.

This work aimed to find new inhibitors of the CYP3A4 and JAK3 enzymes, which are significant players in autoimmune diseases such as rheumatoid arthritis. Advanced computer-aided drug design techniques, such as pharmacophore and 3D-QSAR modeling, were used. Two strong 3D-QSAR models were created, and their predictive power was validated by the strong correlation (R2 values > 80%) between the predicted and experimental activity. With an ROC value of 0.9, a pharmacophore model grounded in the DHRRR hypothesis likewise demonstrated strong predictive ability. Eight possible inhibitors were found, and six new inhibitors were designed in silico using these computational models. The pharmacokinetic and safety characteristics of these candidates were thoroughly assessed. The possible interactions between the inhibitors and the target enzymes were made clear via molecular docking. Furthermore, MM/GBSA computations and molecular dynamics simulations offered insightful information about the stability of the binding between inhibitors and CYP3A4 or JAK3. Through the integration of various computational approaches, this study successfully identified potential inhibitor candidates for additional investigation and efficiently screened compounds. The findings contribute to our knowledge of enzyme-inhibitor interactions and may help us create more effective treatments for autoimmune conditions like rheumatoid arthritis.

Elucidating the Interaction between Pyridoxine 5'-Phosphate Oxidase and Dopa Decarboxylase: Activation of B6-Dependent Enzyme.

Pyridoxal 5'-phosphate (PLP), the active form of vitamin B6, serves as a cofactor for scores of B6-dependent (PLP-dependent) enzymes involved in many cellular processes. One such B6 enzyme is dopa decarboxylase (DDC), which is required for the biosynthesis of key neurotransmitters, e.g., dopamine and serotonin. PLP-dependent enzymes are biosynthesized as apo-B6 enzymes and then converted to the catalytically active holo-B6 enzymes by Schiff base formation between the aldehyde of PLP and an active site lysine of the protein. In eukaryotes, PLP is made available to the B6 enzymes through the activity of the B6-salvage enzymes, pyridoxine 5'-phosphate oxidase (PNPO) and pyridoxal kinase (PLK). To minimize toxicity, the cell keeps the content of free PLP (unbound) very low through dephosphorylation and PLP feedback inhibition of PNPO and PLK. This has led to a proposed mechanism of complex formation between the B6-salvage enzymes and apo-B6 enzymes prior to the transfer of PLP, although such complexes are yet to be characterized at the atomic level, presumably due to their transient nature. A computational study, for the first time, was used to predict a likely PNPO and DDC complex, which suggested contact between the allosteric PLP tight-binding site on PNPO and the active site of DDC. Using isothermal calorimetry and/or surface plasmon resonance, we also show that PNPO binds both apoDDC and holoDDC with dissociation constants of 0.93 ± 0.07 µM and 2.59 ± 0.11 µM, respectively. Finally, in the presence of apoDDC, the tightly bound PLP on PNPO is transferred to apoDDC, resulting in the formation of about 35% holoDDC.

3D Interaction Homology: Hydropathic Analyses of the "π-Cation" and "π-π" Interaction Motifs in Phenylalanine, Tyrosine, and Tryptophan Residues.

Three-dimensional (3D) maps of the hydropathic environments of protein amino acid residues are information-rich descriptors of preferred conformations, interaction types and energetics, and solvent accessibility. The interactions made by each residue are the primary factor for rotamer selection and the secondary, tertiary, and even quaternary protein structure. Our evolving basis set of environmental data for each residue type can be used to understand the protein structure. This work focuses on the aromatic residues phenylalanine, tyrosine, and tryptophan and their structural roles. We calculated and analyzed side chain-to-environment 3D maps for over 70,000 residues of these three types that reveal, with respect to hydrophobic and polar interactions, the environment around each. After binning with backbone ϕ/ψ and side chain χ1, we clustered each bin by 3D similarities between map-map pairs. For each of the three residue types, four bins were examined in detail: one in the ß-pleat, two in the right-hand α-helix, and one in the left-hand α-helix regions of the Ramachandran plot. For high degrees of side chain burial, encapsulation of the side chain by hydrophobic interactions is ubiquitous. The more solvent-exposed side chains are more likely to be involved in polar interactions with their environments. Evidence for π-π interactions was observed in about half of the residues surveyed [phenylalanine (PHE): 53.3%, tyrosine (TYR): 34.1%, and tryptophan (TRP): 55.7%], but on an energy basis, this contributed to only ∼4% of the total. Evidence for π-cation interactions was observed in 14.1% of PHE, 8.3% of TYR, and 26.8% of TRP residues, but on an energy basis, this contributed to only ∼1%. This recognition of even these subtle interactions in the 3D hydropathic environment maps is key support for our interaction homology paradigm of protein structure elucidation and possibly prediction.

Computational insights into rational design and virtual screening of pyrazolopyrimidine derivatives targeting Janus kinase 3 (JAK3).

The Janus kinase 3 (JAK3) family, particularly JAK3, is pivotal in initiating autoimmune diseases such as rheumatoid arthritis. Recent advancements have focused on developing antirheumatic drugs targeting JAK3, leading to the discovery of novel pyrazolopyrimidine-based compounds as potential inhibitors. This research employed covalent docking, ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) analysis, molecular dynamics modeling, and MM/GBSA (Molecular Mechanics Generalized Born Surface Area) binding free energy techniques to screen 41 in silico-designed pyrazolopyrimidine derivatives. Initially, 3D structures of the JAK3 enzyme were generated using SWISS-MODEL, followed by virtual screening and covalent docking via AutoDock4 (AD4). The selection process involved the AMES test, binding affinity assessment, and ADMET analysis, narrowing down the candidates to 27 compounds that passed the toxicity test. Further covalent docking identified compounds 21 and 41 as the most promising due to their high affinity and favourable ADMET profiles. Subsequent development led to the creation of nine potent molecules, with derivatives 43 and 46 showing exceptional affinity upon evaluation through molecular dynamics simulation and MM/GBSA calculations over 300 nanoseconds, comparable to tofacitinib, an approved RA drug. However, compounds L21 and L46 demonstrated stable performance, suggesting their effectiveness in treating rheumatoid arthritis and other autoimmune conditions associated with JAK3 inhibition.

3D interaction homology: The hydrophobic residues alanine, isoleucine, leucine, proline and valine play different structural roles in soluble and membrane proteins.

The aliphatic hydrophobic amino acid residues-alanine, isoleucine, leucine, proline and valine-are among the most common found in proteins. Their structural role in proteins is seemingly obvious: engage in hydrophobic interactions to stabilize secondary, and to a lesser extent, tertiary and quaternary structure. However, favorable hydrophobic interactions involving the sidechains of these residue types are generally less significant than the unfavorable set arising from interactions with polar atoms. Importantly, the constellation of interactions between residue sidechains and their environments can be recorded as three-dimensional maps that, in turn, can be clustered. The clustered average map sets compose a library of interaction profiles encoding interaction strengths, interaction types and the optimal 3D position for the interacting partners. This library is backbone angle-dependent and suggests solvent and lipid accessibility for each unique interaction profile. In this work, in addition to analysis of soluble proteins, a large set of membrane proteins that contained optimized artificial lipids were evaluated by parsing the structures into three distinct components: soluble extramembrane domain, lipid facing transmembrane domain, core transmembrane domain. The aliphatic residues were extracted from each of these sets and passed through our calculation protocol. Notable observations include: the roles of aliphatic residues in soluble proteins and in the membrane protein's soluble domains are nearly identical, although the latter are slightly more solvent accessible; by comparing maps calculated with sidechain-lipid interactions to maps ignoring those interactions, the potential extent of residue-lipid and residue-interactions can be assessed and likely exploited in structure prediction and modeling; amongst these residue types, the levels of lipid engagement show isoleucine as the most engaged, while the other residues are largely interacting with neighboring helical residues.

In silico computational drug discovery: a Monte Carlo approach for developing a novel JAK3 inhibitors.

Inhibition of Janus kinase 3 (JAK3), a member of the JAK family of tyrosine kinases, remains an essential area of research for developing treatments for autoimmune diseases, particularly cancer and rheumatoid arthritis. The recent discovery of a new JAK3 protein, PDB ID: 4Z16, offers exciting possibilities for developing inhibitors capable of forming a covalent bond with the Cys909 residue, thereby contributing to JAK3 inhibition. A powerful prediction model was constructed and validated using Monte Carlo methods, employing various internal and external techniques. This approach resulted in the prediction of eleven new molecules, which were subsequently filtered to identify six compounds exhibiting potent pIC50 values. These candidates were then subjected to ADMET analysis, molecular docking (including reversible-reversible docking with tofacitinib, an FDA-approved drug, and reversible-irreversible docking for the newly designed compounds), molecular dynamics (MD) analysis for 300 ns, and calculation of free binding energy. The results suggested that these compounds hold promise as JAK3 inhibitors. In summary, the new compounds have exhibited favorable outcomes compared to other compounds across various modeling approaches. The collective findings from these investigations provide valuable insights into the potential therapeutic applications of covalent JAK3 inhibitors, offering a promising direction for the development of novel treatments for autoimmune disorders.Communicated by Ramaswamy H. Sarma.

Characterization of the Escherichia coli pyridoxal 5'-phosphate homeostasis protein (YggS): Role of lysine residues in PLP binding and protein stability.

The pyridoxal 5'-phosphate (PLP) homeostasis protein (PLPHP) is a ubiquitous member of the COG0325 family with apparently no catalytic activity. Although the actual cellular role of this protein is unknown, it has been observed that mutations of the PLPHP encoding gene affect the activity of PLP-dependent enzymes, B6 vitamers and amino acid levels. Here we report a detailed characterization of the Escherichia coli ortholog of PLPHP (YggS) with respect to its PLP binding and transfer properties, stability, and structure. YggS binds PLP very tightly and is able to slowly transfer it to a model PLP-dependent enzyme, serine hydroxymethyltransferase. PLP binding to YggS elicits a conformational/flexibility change in the protein structure that is detectable in solution but not in crystals. We serendipitously discovered that the K36A variant of YggS, affecting the lysine residue that binds PLP at the active site, is able to bind PLP covalently. This observation led us to recognize that a number of lysine residues, located at the entrance of the active site, can replace Lys36 in its PLP binding role. These lysines form a cluster of charged residues that affect protein stability and conformation, playing an important role in PLP binding and possibly in YggS function.

3D interaction homology: Hydropathic interaction environments of serine and cysteine are strikingly different and their roles adapt in membrane proteins.

Atomic-resolution protein structural models are prerequisites for many downstream activities like structure-function studies or structure-based drug discovery. Unfortunately, this data is often unavailable for some of the most interesting and therapeutically important proteins. Thus, computational tools for building native-like structural models from less-than-ideal experimental data are needed. To this end, interaction homology exploits the character, strength and loci of the sets of interactions that define a structure. Each residue type has its own limited set of backbone angle-dependent interaction motifs, as defined by their environments. In this work, we characterize the interactions of serine, cysteine and S-bridged cysteine in terms of 3D hydropathic environment maps. As a result, we explore several intriguing questions. Are the environments different between the isosteric serine and cysteine residues? Do some environments promote the formation of cystine S-S bonds? With the increasing availability of structural data for water-insoluble membrane proteins, are there environmental differences for these residues between soluble and membrane proteins? The environments surrounding serine and cysteine residues are dramatically different: serine residues are about 50% solvent exposed, while cysteines are only 10% exposed; the latter are more involved in hydrophobic interactions although there are backbone angle-dependent differences. Our analysis suggests that one driving force for -S-S- bond formation is a rather substantial increase in burial and hydrophobic interactions in cystines. Serine and cysteine become less and more, respectively, solvent-exposed in membrane proteins. 3D hydropathic environment maps are an evolving structure analysis tool showing promise as elements in a new protein structure prediction paradigm.

Systematized analysis of secondary structure dependence of key structural features of residues in soluble and membrane-bound proteins.

Knowledge of three-dimensional protein structure is integral to most modern drug discovery efforts. Recent advancements have highlighted new techniques for 3D protein structure determination and, where structural data cannot be collected experimentally, prediction of protein structure. We have undertaken a major effort to use existing protein structures to collect, characterize, and catalogue the inter-atomic interactions that define and compose 3D structure by mapping hydropathic interaction environments as maps in 3D space. This work has been performed on a residue-by-residue basis, where we have seen evidence for relationships between environment character, residue solvent-accessible surface areas and their secondary structures. In this graphical review, we apply principles from our earlier studies and expand the scope to all common amino acid residue types in both soluble and membrane proteins. Key to this analysis is parsing the Ramachandran plot to an 8-by-8 chessboard to define secondary structure bins. Our analysis yielded a number of quantitative discoveries: 1) increased fraction of hydrophobic residues (alanine, isoleucine, leucine, phenylalanine and valine) in membrane proteins compared to their fractions in soluble proteins; 2) less burial coupled with significant increases in favorable hydrophobic interactions for hydrophobic residues in membrane proteins compared to soluble proteins; and 3) higher burial and more favorable polar interactions for polar residues now preferring the interior of membrane proteins. These observations and the supporting data should provide benchmarks for current studies of protein residues in different environments and may be able to guide future protein structure prediction efforts.