Visualization and analysis of non-covalent contacts using the Protein Contacts Atlas

Discovery of a urea-based hit compound as a novel inhibitor of transforming growth factor-β type 1 receptor: in silico and in vitro studies

Transforming growth factor β type 1 receptor (TGFβR1), a crucial serine-threonine kinase, is central to the TGFβ/Smad signaling pathway, governing cellular processes like growth, differentiation, apoptosis, and immune response. This pathway is closely linked to the epithelial-mesenchymal transition (EMT) process, which plays an important role in the metastasis of hepatocellular carcinoma (HCC). To date, only limited inhibitors targeting TGFβR1 have entered clinical trials, yet they encounter challenges, notably high toxicity, in clinical applications. Herein, an efficient virtual screening pipeline was developed. Eighty compounds were screened from a pool of over 17 million molecules based on docking scores and binding free energy. Four compounds were manually selected with the assistance of enhanced sampling method BPMD (binding pose metadynamics). The binding stability of these four compounds complexed with TGFβR1 was subsequently studied through long-timescale conventional molecular dynamics simulations. The three most promising compounds were subjected to in vitro bioactivity assays. Cpd272 demonstrated moderate inhibitory activity against TGFβR1, with an IC50 value of 1.57 ± 0.33 μM. Moreover, it exhibited cytotoxic effects on human hepatocellular carcinoma cell line Bel-7402. By shedding light on the binding mode of the receptor-ligand complexes, Cpd272 was identified as a hit compound featuring a novel urea-based scaffold capable of effectively inhibiting TGFβR1.

Structure-based virtual screening discovers novel PKMYT1 inhibitors

PKMYT1, a member of the WEE family, plays a crucial role in the cell cycle by specifically phosphorylating CDK1-CyclinB at Tyr15 and Thr14. Recent investigations have revealed that the amplification of CCNE1 and the inhibition of PKMYT1 kinase collectively result in synthetic lethality, further indicating that PKMYT1 is promising as an effective target for tumor therapy. Existing PKMYT1 inhibitors are mostly derivatives of RP-6306 or pan-inhibitors, limiting their further development. Herein, we conducted virtual screening of a natural product library, and in vitro enzyme experiments demonstrated that EGCG, GCG, and luteolin exhibited potent inhibitory activities with IC50 values of 0.137 μM, 0.159 μM, and 1.5 μM, respectively. Subsequently, analysis of the hit compounds and RP-6306, using different molecular simulation methods, revealed that stable hydrogen bonds with Asp251 and Glu157 in the DFG region were vital for binding to PKMYT1, more so than hydrogen bonds in the hinge and loop regions.

Design Glutamate Dehydrogenase for Nonaqueous System by Motifs Reassembly and Interaction Network Analysis

Glutamate dehydrogenases (GDH) serve as the key regulated enzyme that links protein and carbohydrate metabolism. Combined with motif reassembly and mutation, novel GDHs were designed. Motif reassembly of thermophilic GDH and malate dehydrogenase aims to overcome stability and activity tradeoff in nonaqueous systems. Structural compatibility and dynamic cooperation of the designed AaDHs were studied by molecular dynamics simulation. Furthermore, multipoint mutations improved its catalytic activity for unnatural substrates. Amino acid interaction network analysis indicated that the high density of hydrogen-bonded salt bridges is beneficial to the stability. Finally, the experimental verification determines the kinetics of AaDHs in a nonaqueous system. The activity of Aa05 was increased by 1.78-fold with ionic liquid [EMIM]BF4. This study presents the strategy of a combination of rigid motif assembly and mutations of active sites for robust dehydrogenases with high activity in the nonaqueous system, which overcomes the activity-stability tradeoff effect.

MDavocado: Analysis and Visualization of Protein Motion by Time-Dependent Angular Diagrams

Extracting meaningful information from atomistic molecular dynamics (MD) simulations of proteins remains a challenging task due to the high-dimensionality and complexity of the data. MD simulations yield trajectories that contain the positions of thousands of atoms in millions of steps. Gaining a comprehensive understanding of local dynamical events across the entire trajectory is often difficult. Here, we present a novel approach to visualize MD trajectories in the form of time-dependent Ramachandran plots. Specialized data aggregation techniques are employed to address the challenge of plotting millions of data points on a single image, thereby ensuring that the analysis is independent of the molecule size and/or length of the MD simulation. This approach facilitates quick identification of flexible and dynamic regions, and its strength is the ability to simultaneously observe the movements of all amino acids over time. The Python program MDavocado is freely available at GitHub (https://github.com/zoranstefanic/MDavocado).

Molecular insights into TP53 mutation (p. Arg267Trp) and its connection to Choroid Plexus Carcinomas and Li-Fraumeni Syndrome

BACKGROUND

Choroid plexus carcinomas (CPCs) are rare malignant tumors primarily affecting pediatric patients and often co-occur with Li-Fraumeni Syndrome (LFS), an inherited predisposition to early-onset malignancies in multiple organ systems. LFS is closely linked to TP53 mutations, with germline TP53 gene mutations present in approximately 75% of Li-Fraumeni syndrome families and 25% of Li-Fraumeni-like syndrome families. Individuals with TP53 mutations also have an elevated probability of carrying mutations in BRCA1 and BRCA2 genes.

OBJECTIVE

To investigate the structural and functional implications of the TP53: 799C > T, p. (Arg267Trp) missense mutation, initially identified in a Saudi family, and understand its impact on TP53 functionality and related intermolecular interactions.

METHODS

Computational analyses were conducted to examine the structural modifications resulting from the TP53: 799C > T, p. (Arg267Trp) mutation. These analyses focused on the mutation's impact on hydrogen bonding, ionic interactions, and the specific interaction with Cell Cycle and Apoptosis Regulator 2 (CCAR2), as annotated in UniProt.

RESULTS

The study revealed that the native Arg267 residue is critical for a salt bridge interaction with glutamic acid at position 258. The mutation-induced charge alteration has the potential to disrupt this ionic bonding. Additionally, the mutation is located within an amino acid region crucial for interaction with CCAR2. The altered properties of the amino acid within this domain may affect its functionality and disrupt this interaction, thereby impacting the regulation of catalytic enzyme activity.

CONCLUSIONS

Our findings highlight the intricate intermolecular interactions governing TP53 functionality. The TP53: 799C > T, p. (Arg267Trp) mutation causes structural modifications that potentially disrupt critical ionic bonds and protein interactions, offering valuable insights for the development of targeted mutants with distinct functional attributes. These insights could inform therapeutic strategies for conditions associated with TP53 mutations.

CoDIAC: A comprehensive approach for interaction analysis reveals novel insights into SH2 domain function and regulation

Protein domains are conserved structural and functional units and are the functional building blocks of proteins. Evolutionary expansion means that domain families are often represented by many members in a species, which are found in various configurations with other domains, which have evolved new specificity for interacting partners. Here, we develop a structure-based interface analysis to comprehensively map domain interfaces from available experimental and predicted structures, including interfaces with other macromolecules and intraprotein interfaces (such as might exist between domains in a protein). We hypothesized that a comprehensive approach to contact mapping of domains could yield new insights. Specifically, we use it to gain information about how domains selectivity interact with ligands, whether domain-domain interfaces of repeated domain partnerships are conserved across diverse proteins, and identify regions of conserved post-translational modifications, using relationship to interaction interfaces as a method to hypothesize the effect of post-translational modifications (and mutations). We applied this approach to the human SH2 domain family, an extensive modular unit that is the foundation of phosphotyrosine-mediated signaling, where we identified a novel approach to understanding the binding selectivity of SH2 domains and evidence that there is coordinated and conserved regulation of multiple SH2 domain binding interfaces by tyrosine and serine/threonine phosphorylation and acetylation, suggesting that multiple signaling systems can regulate protein activity and SH2 domain interactions in a regulated manner. We provide the extensive features of the human SH2 domain family and this modular approach, as an open source Python package for COmprehensive Domain Interface Analysis of Contacts (CoDIAC).

Strand-resolved mutagenicity of DNA damage and repair

DNA base damage is a major source of oncogenic mutations1. Such damage can produce strand-phased mutation patterns and multiallelic variation through the process of lesion segregation2. Here we exploited these properties to reveal how strand-asymmetric processes, such as replication and transcription, shape DNA damage and repair. Despite distinct mechanisms of leading and lagging strand replication3,4, we observe identical fidelity and damage tolerance for both strands. For small alkylation adducts of DNA, our results support a model in which the same translesion polymerase is recruited on-the-fly to both replication strands, starkly contrasting the strand asymmetric tolerance of bulky UV-induced adducts5. The accumulation of multiple distinct mutations at the site of persistent lesions provides the means to quantify the relative efficiency of repair processes genome wide and at single-base resolution. At multiple scales, we show DNA damage-induced mutations are largely shaped by the influence of DNA accessibility on repair efficiency, rather than gradients of DNA damage. Finally, we reveal specific genomic conditions that can actively drive oncogenic mutagenesis by corrupting the fidelity of nucleotide excision repair. These results provide insight into how strand-asymmetric mechanisms underlie the formation, tolerance and repair of DNA damage, thereby shaping cancer genome evolution.

Structural basis for selectivity and antagonism in extracellular GPCR-nanobodies

G protein-coupled receptors (GPCRs) are pivotal therapeutic targets, but their complex structure poses challenges for effective drug design. Nanobodies, or single-domain antibodies, have emerged as a promising therapeutic strategy to target GPCRs, offering advantages over traditional small molecules and antibodies. However, an incomplete understanding of the structural features enabling GPCR-nanobody interactions has limited their development. In this study, we investigate VUN701, a nanobody antagonist targeting the atypical chemokine receptor 3 (ACKR3). We determine that an extended CDR3 loop is required for ACKR3 binding. Uncommon in most nanobodies, an extended CDR3 is prevalent in GPCR-targeting nanobodies. Combining experimental and computational approaches, we map an inhibitory ACKR3-VUN701 interface and define a distinct conformational mechanism for GPCR inactivation. Our results provide insights into class A GPCR-nanobody selectivity and suggest a strategy for the development of these new therapeutic tools.

Uncovering the selectivity mechanism of phosphodiesterase 7A/8A inhibitors through computational studies

The expression of phosphodiesterase 7A (PDE7A) and phosphodiesterase 8A (PDE8) genes is integral to human signaling pathways, and the inhibition of PDE7A has been associated with the onset of various diseases, including effects on the immune system and nervous system. The development of PDE7 selective inhibitors can promote research on immune and nervous system diseases, such as multiple sclerosis, chronic inflammation, and autoimmune responses. PDE8A is expressed alongside PDE8B, and its inhibitory mechanism is still unclear. Studying the mechanisms of selective inhibitors against different PDE subtypes is crucial to prevent potential side effects, such as nausea and cardiac toxicity, and the sequence similarity of the two protein subtypes was 55.9%. Therefore, it is necessary to investigate the differences of both subtypes' ligand binding sites. Selective inhibitors of two proteins were chosen to summarize the reason for their selectivity through molecular docking, molecular dynamics simulation, alanine scanning mutagenesis, and MM-GBSA calculation. We found that Phe384PDE7A, Leu401PDE7A, Gln413PDE7A, Tyr419PDE7A, and Phe416PDE7A in the active site positively contribute to the selectivity towards PDE7A. Additionally, Asn729PDE8A, Phe767PDE8A, Gln778PDE8A, and Phe781PDE8A positively contribute to the selectivity towards PDE8A.

Insights into the selective mechanism of PDE2/9a inhibitors from silico aspects

The selective design of competitive enzyme inhibitors is an extremely difficult task but necessary work for certain types of systems, such as the phosphodiesterase (PDE) system addressed in this article. In the PDE family, PDE2A and PDE9 respectively target the central nervous system and heart failure, and share many conserved amino acids at their binding sites. Therefore, gaining a deep understanding of the selective mechanisms of PDE2A/9A is crucial for designing highly selective drugs. In this study, various computer-aided drug design (CADD) methods, including molecular docking, molecular dynamics simulations (MD), and binding free energy calculations, are employed to explore the selective mechanisms of PDE2A/9A. Overall, our research results indicate a selective design strategy for PDE2A, which involves incorporating hydrophobic or aromatic moieties into the molecular structure to better accommodate the hydrophobic pocket of PDE2A. Additionally, it is recommended to introduce functional groups capable of forming connections with selective residues, such as Phe830 and Gln812 for PDE2A, or Ala452 and Tyr424 for PDE9A, to enhance the selectivity of inhibitors targeting PDE2A/9A. This achievement is anticipated to pave the way for the development of innovative and selective small molecules targeting PDE2A/9A.Communicated by Ramaswamy H. Sarma.

Decoding selectivity: computational insights into AKR1B1 and AKR1B10 inhibition

Understanding selectivity mechanisms of inhibitors towards highly homologous proteins is of paramount importance in the design of selective candidates. Human aldo-keto reductases (AKRs) pertain to a superfamily of monomeric oxidoreductases, which serve as NADPH-dependent cytosolic enzymes to catalyze the reduction of carbonyl groups to primary and secondary alcohols using electrons from NADPH. Among AKRs, AKR1B1 is emerging as a promising target for cancer treatment and diabetes, despite its high structural similarity with AKR1B10, which leads to severe adverse events. Therefore, it is crucial to understand the selectivity mechanisms of AKR1B1 and AKR1B10 to discover safe anticancer candidates with optimal therapeutic efficacy. In this study, multiple computational strategies, including sequence alignment, structural comparison, Protein Contacts Atlas analysis, molecular docking, molecular dynamics simulation, MM-GBSA calculation, alanine scanning mutagenesis and pharmacophore modeling analysis were employed to comprehensively understand the selectivity mechanisms of AKR1B1/10 inhibition based on selective inhibitor lidorestat and HAHE. This study would provide substantial evidence in the design of potent and highly selective AKR1B1/10 inhibitors in future.

Distinct chikungunya virus polymerase palm subdomains contribute to virus replication and virion assembly

Alphaviruses encode an error-prone RNA-dependent RNA polymerase (RdRp), nsP4, required for genome synthesis, yet how the RdRp functions in the complete alphavirus life cycle is not well-defined. Previous work using chikungunya virus (CHIKV) has established the importance of the nsP4 residue cysteine 483 in maintaining viral genetic fidelity. Given the location of residue C483 in the nsP4 palm domain, we hypothesized that other residues within this domain and surrounding subdomains would also contribute to polymerase function. To test this hypothesis, we designed a panel of nsP4 variants via homology modeling based on the Coxsackievirus B3 3 polymerase. We rescued each variant in both mammalian and mosquito cells and discovered that the palm domain and ring finger subdomain contribute to polymerase host-specific replication and genetic stability. Surprisingly, in mosquito cells, these variants in the ring finger and palm domain were replication competent and produced viral structural proteins, but they were unable to produce infectious progeny, indicating a yet uncharacterized role for the polymerase in viral assembly. Finally, we have identified additional residues in the nsP4 palm domain that influence the genetic diversity of the viral progeny, potentially via an alteration in NTP binding and/or discrimination by the polymerase. Taken together, these studies highlight that distinct nsP4 subdomains regulate multiple processes of the alphavirus life cycle, placing nsP4 in a central role during the switch from RNA synthesis to packaging and assembly.

Molecular determinants of ligand efficacy and potency in GPCR signaling

Heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptors (GPCRs) bind to extracellular ligands and drugs and modulate intracellular responses through conformational changes. Despite their importance as drug targets, the molecular origins of pharmacological properties such as efficacy (maximum signaling response) and potency (the ligand concentration at half-maximal response) remain poorly understood for any ligand-receptor-signaling system. We used the prototypical adrenaline-β2 adrenergic receptor-G protein system to reveal how specific receptor residues decode and translate the information encoded in a ligand to mediate a signaling response. We present a data science framework to integrate pharmacological and structural data to uncover structural changes and allosteric networks relevant for ligand pharmacology. These methods can be tailored to study any ligand-receptor-signaling system, and the principles open possibilities for designing orthosteric and allosteric compounds with defined signaling properties.

Illuminating the mechanism and allosteric behavior of NanoLuc luciferase

NanoLuc, a superior β-barrel fold luciferase, was engineered 10 years ago but the nature of its catalysis remains puzzling. Here experimental and computational techniques are combined, revealing that imidazopyrazinone luciferins bind to an intra-barrel catalytic site but also to an allosteric site shaped on the enzyme surface. Structurally, binding to the allosteric site prevents simultaneous binding to the catalytic site, and vice versa, through concerted conformational changes. We demonstrate that restructuration of the allosteric site can boost the luminescent reaction in the remote active site. Mechanistically, an intra-barrel arginine coordinates the imidazopyrazinone component of luciferin, which reacts with O2 via a radical charge-transfer mechanism, and then it also protonates the resulting excited amide product to form a light-emitting neutral species. Concomitantly, an aspartate, supported by two tyrosines, fine-tunes the blue color emitter to secure a high emission intensity. This information is critical to engineering the next-generation of ultrasensitive bioluminescent reporters.

Synthesizing biomaterials in living organisms

Living organisms fabricate biomacromolecules such as DNA, RNA, and proteins by the self-assembly process. The research on the mechanism of biomacromolecule formation also inspires the exploration of in vivo synthesized biomaterials. By elaborate design, artificial building blocks or precursors can self-assemble or polymerize into functional biomaterials within living organisms. In recent decades, these so-called in vivo synthesized biomaterials have achieved extensive applications in cell-fate manipulation, disease theranostics, bioanalysis, cellular surface engineering, and tissue regeneration. In this review, we classify strategies for in vivo synthesis into non-covalent, covalent, and genetic types. The development of these approaches is based on the chemical principles of supramolecular chemistry and synthetic chemistry, biological cues such as enzymes and microenvironments, and the means of synthetic biology. By summarizing the design principles in detail, some insights into the challenges and opportunities in this field are provided to  enlighten further research.

Integrated molecular modeling and dynamics approaches revealed the mechanism of selective inhibition of HDAC6/8

The high structural homology of histone deacetylases 6 and 8 (HDAC6/8) poses a challenge in achieving isoform selectivity and has resulted in adverse side effects due to pan-inhibition in clinical applications. Additionally, the rational design of dual-target inhibitors, centered on HDAC6/8, demands a profound understanding of their selectivity mechanisms. Addressing the urgent need for enhanced specificity in the development of inhibitors targeting specific isoforms, we elucidate the mechanism underpinning the selective inhibition of HDAC6/8 inhibitors through in-silico strategies. The hydrogen bonding interaction with Asp101 and Tyr306 is a key factor that enables compound 12b to selectively inhibit HDAC8. Its favorable spatial orientation places the Cap group of 12b between Tyr306 and Tyr100, resulting in an overall L-shaped conformation. These two factors significantly contribute to the selective inhibitory activity of 12b against HDAC8. The zinc binding group (ZBG) of compound NN-390 forms a hydrogen bond with His610, a key residue of HDAC6, facilitating stable chelation with zinc ions. In addition, the Cap group of NN-390 interacts with Phe620 and Phe680 via van der Waals forces, leading to an overall Y-shaped conformation. The aforementioned factors are the main reasons for the selective inhibition of HDAC6 by NN-390. Furthermore, whether the Cap group is in the para or meta-position will influence the selective inhibition of either HDAC6 or HDAC8. We believe these clues can offer valuable insights for the rational design of selective inhibitors targeting HDAC6/8 and pave the way for rational design of dual-target HDAC6/8-based inhibitors.Communicated by Ramaswamy H. Sarma.

AQcalc: A web server that identifies weak molecular interactions in protein structures

Weak molecular interactions play an important role in protein structure and function. Computational tools that identify weak molecular interactions are, therefore, valuable for the study of proteins. Here, we present AQcalc, a web server (https://aqcalcbiocomputing.com/) that can be used to identify anion-quadrupole (AQ) interactions, which are weak interactions involving aromatic residue (Trp, Tyr, and Phe) ring edges and anions (Asp, Glu, and phosphate ion) both within proteins and at their interfaces (protein-protein, protein-nucleic acids, and protein-lipid bilayer). AQcalc identifies AQ interactions as well as clusters involving AQ, cation-π, and salt bridges, among others. Utilizing AQcalc we analyzed weak interactions in protein models, even in the absence of experimental structures, to understand the contributions of weak interactions to deleterious structural changes, including those associated with oncogenic and germline disease variants. We identified several deleterious variants with disrupted AQ interactions (comparable in frequency to cation-π disruptions). Amyloid fibrils utilize AQ to bury anions at frequencies that far exceed those observed for globular proteins. AQ interactions were detected three and five times more frequently than the hydrogen-bonded AQ (HBAQ) in fibril structures and protein-lipid bilayer interfaces, respectively. By contrast, AQ and HBAQ interactions were detected with similar frequencies in globular proteins. Collectively, these findings suggest AQcalc will be effective in facilitating fine structural analysis. As other web utilities designed to identify protein residue interaction networks do not report AQ interactions, wide use of AQcalc will enrich our understanding of residue interaction networks and facilitate hypothesis testing by identifying and experimentally characterizing these comparably weak but important interactions.

Global analysis of aging-related protein structural changes uncovers enzyme-polymerization-based control of longevity

Aging is associated with progressive phenotypic changes. Virtually all cellular phenotypes are produced by proteins, and their structural alterations can lead to age-related diseases. However, we still lack comprehensive knowledge of proteins undergoing structural-functional changes during cellular aging and their contributions to age-related phenotypes. Here, we conducted proteome-wide analysis of early age-related protein structural changes in budding yeast using limited proteolysis-mass spectrometry (LiP-MS). The results, compiled in online ProtAge catalog, unraveled age-related functional changes in regulators of translation, protein folding, and amino acid metabolism. Mechanistically, we found that folded glutamate synthase Glt1 polymerizes into supramolecular self-assemblies during aging, causing breakdown of cellular amino acid homeostasis. Inhibiting Glt1 polymerization by mutating the polymerization interface restored amino acid levels in aged cells, attenuated mitochondrial dysfunction, and led to lifespan extension. Altogether, this comprehensive map of protein structural changes enables identifying mechanisms of age-related phenotypes and offers opportunities for their reversal.

GPCRana: A web server for quantitative analysis of GPCR structures

G protein-coupled receptors (GPCRs) attract tremendous attention from both industrial and academic researchers with currently over 900 released structures. Structural analysis is widely used to understand receptor functionality and pharmacology, but more user-friendly tools are needed. Residue-residue contact score (RRCS) is an atomic distance-based method that allows a quantitative description of GPCR structures. Here, we present GPCRana, a web server that provides a user-friendly interface to analyze GPCR structures. After uploading selected structures, GPCRana immediately generates a comprehensive report covering four aspects: (i) RRCS for all residue pairs incorporated with real-time 3D visualization; (ii) ligand-receptor interactions; (iii) activation pathway analysis; and (iv) RRCS_TMs that indicates the global movements of transmembrane helices. Moreover, conformational changes between two structures can be analyzed. Applying GPCRana on AlphaFold2-predicted models reveals differentiated inter-helical packing forms in a receptor-dependent manner. Our web server offers a fast and precise way to study GPCR structures and is freely available at http://gpcranalysis.com/#/.

Computational characteristics of the structure-activity relationship of inhibitors targeting Pks13-TE domain

Multiple studies have established the Pks13-TE domain as a promising target for anti-tuberculosis drug development. However, recent findings have revealed that the lead compound currently in the pipeline for Pks13-TE has significant cardiotoxicity issues. Given the pressing need for new chemical structures for Pks13-TE inhibitors, this study aims to provide a detailed understanding of the Pks13-TE domain binding site through the application of computational chemical biology techniques. Our results highlight the size and shape of the Pks13-TE domain binding pocket, key residues including Asp1644, Asn1640, Phe1670, and Tyr1674 within the pocket, and inhibitor pharmacophore characteristics such as aromatic ring sites, positively charged sites, and hydrogen bond donors. To our knowledge, these simulation results are novel and contribute to the discovery of next-generation Pks13-TE inhibitors without similar prior studies.

Exploring Oxidoreductases from Extremophiles for Biosynthesis in a Non-Aqueous System

Organic solvent tolerant oxidoreductases are significant for both scientific research and biomanufacturing. However, it is really challenging to obtain oxidoreductases due to the shortages of natural resources and the difficulty to obtained it via protein modification. This review summarizes the recent advances in gene mining and structure-functional study of oxidoreductases from extremophiles for non-aqueous reaction systems. First, new strategies combining genome mining with bioinformatics provide new insights to the discovery and identification of novel extreme oxidoreductases. Second, analysis from the perspectives of amino acid interaction networks explain the organic solvent tolerant mechanism, which regulate the discrete structure-functional properties of extreme oxidoreductases. Third, further study by conservation and co-evolution analysis of extreme oxidoreductases provides new perspectives and strategies for designing robust enzymes for an organic media reaction system. Furthermore, the challenges and opportunities in designing biocatalysis non-aqueous systems are highlighted.

In Silico Analysis of the Structural Dynamics and Substrate Recognition Determinants of the Human Mitochondrial Carnitine/Acylcarnitine SLC25A20 Transporter

The Carnitine-Acylcarnitine Carrier is a member of the mitochondrial Solute Carrier Family 25 (SLC25), known as SLC25A20, involved in the electroneutral exchange of acylcarnitine and carnitine across the inner mitochondrial membrane. It acts as a master regulator of fatty acids β-oxidation and is known to be involved in neonatal pathologies and cancer. The transport mechanism, also known as "alternating access", involves a conformational transition in which the binding site is accessible from one side of the membrane or the other. In this study, through a combination of state-of-the-art modelling techniques, molecular dynamics, and molecular docking, the structural dynamics of SLC25A20 and the early substrates recognition step have been analyzed. The results obtained demonstrated a significant asymmetry in the conformational changes leading to the transition from the c- to the m-state, confirming previous observations on other homologous transporters. Moreover, analysis of the MD simulations' trajectories of the apo-protein in the two conformational states allowed for a better understanding of the role of SLC25A20 Asp231His and Ala281Val pathogenic mutations, which are at the basis of Carnitine-Acylcarnitine Translocase Deficiency. Finally, molecular docking coupled to molecular dynamics simulations lend support to the multi-step substrates recognition and translocation mechanism already hypothesized for the ADP/ATP carrier.

Structural analysis and ensemble docking revealed the binding modes of selected progesterone receptor modulators

Uterine fibroids (UF) are benign smooth muscle neoplasm of uterus that have a significant impact on a woman's quality of life as they perturb hormonal homeostasis resulting in heavy menstrual bleeding, impaired fertility, pregnancy complications and loss. UF can be surgically removed through invasive procedures, but their recurrence rate is often high. Progesterone receptor (PR) has an imperative role in UF management. Mifepristone, ulipristal acetate (UPA) and asoprisnil (ASO) are some selective progesterone receptor modulators (SPRMs), acts on PR, but due to their side effects in long term use, they were withdrawn from the market. Hence, there is a dire need for novel, highly efficient with least side effects, therapeutics for the treatment of UF. To contribute toward the drug discovery for UF, we made an extensive structural comparison of reported PR crystal structures, also elucidated the binding modes of four existing SPRMs against human PR through ensemble docking approach. Our studies revealed the presence of 5 highly repeating water molecules that has an important role in ligand binding and structural stability. Our ensemble docking and MD simulation revealed that studied ligands have preferential selectivity toward the specific conformation of PR. It is anticipated that our study will be a useful resource to all the drug discovery scientists who are engaged in the identification of lead molecules against UF.

Canonical or noncanonical? Structural plasticity of serine protease-binding loops in Kunitz-STI protease inhibitors

The Kunitz-Soybean Trypsin Inhibitor (Kunitz-STI) family is a large family of proteins with most of its members being protease inhibitors. The versatility of the inhibitory profile and the structural plasticity of these proteins, make this family a promising scaffold for designing new multifunctional proteins. Historically, Kunitz-STI inhibitors have been classified as canonical serine protease inhibitors, but new inhibitors with novel inhibition mechanisms have been described in recent years. Different inhibition mechanisms could be the result of different evolutionary pathways. In the present work, we performed a structural analysis of all the crystallographic structures available for Kunitz-STI inhibitors to characterize serine protease-binding loop structural features and locations. Our study suggests a relationship between the conformation of serine protease-binding loops and the inhibition mechanism, their location in the β-trefoil fold, and the plant source of the inhibitors. The classical canonical inhibitors of this family are restricted to plants from the Fabales order and bind their targets via the β4-β5 loop, whereas serine protease-binding loops in inhibitors from other plants lie mainly in the β5-β6 and β9-β10 loops. In addition, we found that the β5-β6 loop is used to inhibit two different families of serine proteases through a steric blockade inhibition mechanism. This work will help to change the general perception that all Kunitz-STI inhibitors are canonical inhibitors and proteins with protease-binding loops adopting noncanonical conformations are exceptions. Additionally, our results will help in the identification of protease-binding loops in uncharacterized or newly discovered inhibitors, and in the design of multifunctional proteins.

Exploration of the Binding Modes of Toll-Like Receptor 4 Competitive Inhibitors: A Combined Ligand-Based and Target-Based Approach

The interactions of Toll-like receptor 4 (TLR4) with competitive inhibitors were investigated by a combined ligand-based and target-based approach. Firstly, the ligand-based pharmacophore model of the reported TLR4 inhibitors was constructed by utilizing the common feature method, which included three hydrophobic groups and a hydrogen bond receptor. The Schrödinger software suite glide module was used to dock inhibitors with proteins and verify the importance of these four interaction points from the target level. Then, molecular dynamics, alanine scanning mutagenesis, and binding free energy calculation were used to identify the key amino acids in the binding mode. In addition, blind docking proved that the TLR4 inhibitor does not bind to TLR4 itself like other TLR family proteins. Based on this, we also screened a class of sesquiterpene coumarins which possibly have TLR4 inhibitory activity and will conduct a detailed study later. Together, this study revealed the interactions between TLR4 protein and its competitive inhibitors, which shed light on better access for developing its novel inhibitors.

Evaluation of (Anti)androgenic Activities of Environmental Xenobiotics in Milk Using a Human Liver Cell Line and Androgen Receptor-Based Promoter-Reporter Assay

The recent reports on milk consumption and its associated risk with hormone related disorders necessitates the evaluation of dairy products for the presence of endocrine disrupting chemicals (EDCs) and ensure the safety of consumers. In view of this, we investigated the possible presence of (anti)androgenic contaminants in raw and commercialized milk samples. For this purpose, a novel HepARE-Luc cell line that stably expresses human androgen receptor (AR) and the androgen responsive luciferase reporter gene was generated and used in the present study. Treatment of this cell line with androgens and corresponding antiandrogen (flutamide) stimulated or inhibited expression of reporter luciferase, respectively. Real time polymerase chain reaction and immunostaining results exhibited transcription response and translocation of AR from the cytoplasm to the nucleus in response to androgen. Observations implied that a cell-based xenobiotic screening assay via AR response can be conducted for assessing the (anti)androgenic ligands present in food chain including milk. Therefore, the cell line was further used to screen the (anti)androgenic activity of a total of 40 milk fat samples procured as raw or commercial milk. Some of the raw and commercial milk fat samples distinctly showed antiandrogenic activities. Subsequently, some commonly used environmental chemicals were also evaluated for their (anti)androgenic activities. Initial observations with molecular docking studies of experimental compounds were performed to assess their interaction with AR ligand binding domain. Furthermore, (anti)androgenic activities of these compounds were confirmed by performing luciferase assay using the HepARE-Luc cell line. None of the test compounds showed androgenic activities rather some of them like Bisphenol A (BPA) and rifamycin showed antiandrogenic activities. In conclusion, our results provide a valuable information about the assessment of (anti)androgenic activities present in milk samples. Overall, it is proposed that a robust cell-based CALUX assay can be used to assess the (anti)androgenic activities present in milk which can be attributed to different environmental chemicals present therein.

Selectivity mechanism of muscarinic acetylcholine receptor antagonism through in silico investigation

Structures of muscarinic acetylcholine receptors illustrate the strikingly high degree of homology of the residues among isoforms, thus leading to difficulty in achieving subtype selectivity when targeting these receptors and causing undesired side effects when treating the corresponding diseases. Considering the urgent need for more selective and potency therapies, this study is aimed at revealing the selectivity mechanism against M4/5 via in silico strategies, revealing crucial molecular interactions such as hydrogen bonds and pi-cation interaction formed between the key residues TYR416, ASN417, and TRP435 of M4, respectively, hydrophobic pocket formed by the key residues, especially CYS484 of M5. Besides, the water around TYR416^M4 and ASN459^M5, which can be replaced by substituent groups which can form the hydrogen bond interaction network by simulated bridging water and the water around ASP112^M4, whose replacement maybe not contribute to the increase in binding affinity of the compound, may affect the inhibitory selectivity among M4/5 in the aspect of the solvent. Moreover, from the point of inhibitors, compounds with a positively ionizable group could selectively bind to M4 receptors, while hydrophobic molecules may bind preferably to M5. We believe that the current study would provide a basis for the design of subsequent M4/5 selective antagonists.

In-silico investigation of systematic missense mutations of middle east respiratory coronavirus spike protein

Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe pneumonia-like symptoms and is still pose a significant threat to global public health. A key component in the virulence of MERS-CoV is the Spike (S) protein, which binds with the host membrane receptor dipeptidyl peptidase 4 (DPP4). The goal of the present investigation is to examine the effects of missense mutations in the MERS-CoV S protein on protein stability and binding affinity with DPP4 to provide insight that is useful in developing vaccines to prevent coronavirus infection. We utilized a saturation mutagenesis approach to simulate all possible mutations in the MERS-CoV full-length S, S Receptor Binding Domain (RBD) and DPP4. We found the mutations in MERS-CoV S protein residues, G552, C503, C526, N468, G570, S532, S451, S419, S465, and S435, affect protein stability. We identified key residues, G538, E513, V555, S557, L506, L507, R511, M452, D537, and S454 in the S protein RBD region are important in the binding of MERS-CoV S protein to the DPP4 receptor. We investigated the effects of MERS-CoV S protein viral mutations on protein stability and binding affinity. In addition, we studied all DPP4 mutations and found the functional substitution R336T weakens both DPP4 protein stability and S-DPP4 binding affinity. We compared the S protein structures of MERS-CoV, SARS-CoV, and SARS-CoV-2 viruses and identified the residues like C526, C383, and N468 located in equivalent positions of these viruses have effects on S protein structure. These findings provide further information on how mutations in coronavirus S proteins effect protein function.

Enzyme activity engineering based on sequence co-evolution analysis

The utility of engineering enzyme activity is expanding with the development of biotechnology. Conventional methods have limited applicability as they require high-throughput screening or three-dimensional structures to direct target residues of activity control. An alternative method uses sequence evolution of natural selection. A repertoire of mutations was selected for fine-tuning enzyme activities to adapt to varying environments during the evolution. Here, we devised a strategy called sequence co-evolutionary analysis to control the efficiency of enzyme reactions (SCANEER), which scans the evolution of protein sequences and direct mutation strategy to improve enzyme activity. We hypothesized that amino acid pairs for various enzyme activity were encoded in the evolutionary history of protein sequences, whereas loss-of-function mutations were avoided since those are depleted during the evolution. SCANEER successfully predicted the enzyme activities of beta-lactamase and aminoglycoside 3'-phosphotransferase. SCANEER was further experimentally validated to control the activities of three different enzymes of great interest in chemical production: cis-aconitate decarboxylase, α-ketoglutaric semialdehyde dehydrogenase, and inositol oxygenase. Activity-enhancing mutations that improve substrate-binding affinity or turnover rate were found at sites distal from known active sites or ligand-binding pockets. We provide SCANEER to control desired enzyme activity through a user-friendly webserver.

Structural plasticity enables evolution and innovation of RuBisCO assemblies

Oligomerization is a core structural feature that defines the form and function of many proteins. Most proteins form molecular complexes; however, there remains a dearth of diversity-driven structural studies investigating the evolutionary trajectory of these assemblies. Ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO) is one such enzyme that adopts multiple assemblies, although the origins and distribution of its different oligomeric states remain cryptic. Here, we retrace the evolution of ancestral and extant form II RuBisCOs, revealing a complex and diverse history of oligomerization. We structurally characterize a newly discovered tetrameric RuBisCO, elucidating how solvent-exposed surfaces can readily adopt new interactions to interconvert or give rise to new oligomeric states. We further use these principles to engineer and demonstrate how changes in oligomerization can be mediated by relatively few mutations. Our findings yield insight into how structural plasticity may give rise to new oligomeric states.

Conformational selection guides β-arrestin recruitment at a biased G protein-coupled receptor

G protein-coupled receptors (GPCRs) recruit β-arrestins to coordinate diverse cellular processes, but the structural dynamics driving this process are poorly understood. Atypical chemokine receptors (ACKRs) are intrinsically biased GPCRs that engage β-arrestins but not G proteins, making them a model system for investigating the structural basis of β-arrestin recruitment. Here, we performed nuclear magnetic resonance (NMR) experiments on ¹³CH₃-ε-methionine-labeled ACKR3, revealing that β-arrestin recruitment is associated with conformational exchange at key regions of the extracellular ligand-binding pocket and intracellular β-arrestin-coupling region. NMR studies of ACKR3 mutants defective in β-arrestin recruitment identified an allosteric hub in the receptor core that coordinates transitions among heterogeneously populated and selected conformational states. Our data suggest that conformational selection guides β-arrestin recruitment by tuning receptor dynamics at intracellular and extracellular regions.

In Silico Studies of Piperidine Derivatives as Protein Kinase B Inhibitors through 3D-QSAR, Molecular Docking and Molecular Dynamics Simulation

Background:

Protein kinase B (Akt) is a serine/threonine-protein kinase that drives the diverse physiological process. Akt is a promising therapeutic target, which involves cancer cell growth, survival, proliferation and metabolism.

Objective:

The study aims to design highly active Akt inhibitors, and to elucidate the structural requirements for their biological activity, we analyzed the key binding features and summarized the structural determinants for their bioactivities.

Methods:

A series of piperidine derivatives have been investigated employing three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics simulation.

Results:

The statistics of the comparative molecular field analysis (CoMFA) model (Q2=0.631, R2=0.951) and the comparative molecular similarity index analysis (CoMSIA) model (Q2=0.663, R2=0.966) indicated that our 3D-QSAR model was accurate and reliable. Besides, the stability of receptor-ligand interactions under physiological conditions was then evaluated by molecular dynamics simulation, in agreement with the molecular docking results.

Conclusion:

Our study provided valuable insights for the discovery of potent Akt inhibitors.

Determinants of trafficking, conduction, and disease within a K+ channel revealed through multiparametric deep mutational scanning

A long-standing goal in protein science and clinical genetics is to develop quantitative models of sequence, structure, and function relationships to understand how mutations cause disease. Deep mutational scanning (DMS) is a promising strategy to map how amino acids contribute to protein structure and function and to advance clinical variant interpretation. Here, we introduce 7429 single-residue missense mutations into the inward rectifier K+ channel Kir2.1 and determine how this affects folding, assembly, and trafficking, as well as regulation by allosteric ligands and ion conduction. Our data provide high-resolution information on a cotranslationally folded biogenic unit, trafficking and quality control signals, and segregated roles of different structural elements in fold stability and function. We show that Kir2.1 surface trafficking mutants are underrepresented in variant effect databases, which has implications for clinical practice. By comparing fitness scores with expert-reviewed variant effects, we can predict the pathogenicity of 'variants of unknown significance' and disease mechanisms of known pathogenic mutations. Our study in Kir2.1 provides a blueprint for how multiparametric DMS can help us understand the mechanistic basis of genetic disorders and the structure-function relationships of proteins.

RING 3.0: fast generation of probabilistic residue interaction networks from structural ensembles

Residue interaction networks (RINs) are used to represent residue contacts in protein structures. Thanks to the advances in network theory, RINs have been proved effective as an alternative to coordinate data in the analysis of complex systems. The RING server calculates high quality and reliable non-covalent molecular interactions based on geometrical parameters. Here, we present the new RING 3.0 version extending the previous functionality in several ways. The underlying software library has been re-engineered to improve speed by an order of magnitude. RING now also supports the mmCIF format and provides typed interactions for the entire PDB chemical component dictionary, including nucleic acids. Moreover, RING now employs probabilistic graphs, where multiple conformations (e.g. NMR or molecular dynamics ensembles) are mapped as weighted edges, opening up new ways to analyze structural data. The web interface has been expanded to include a simultaneous view of the RIN alongside a structure viewer, with both synchronized and clickable. Contact evolution across models (or time) is displayed as a heatmap and can help in the discovery of correlating interaction patterns. The web server, together with an extensive help and tutorial, is available from URL: https://ring.biocomputingup.it/.

The implication of holocytochrome c synthase mutation in Korean familial hypoplastic amelogenesis imperfecta

Objectives

This study aimed to comprehensively characterise genetic variants of amelogenesis imperfecta in a single Korean family through whole-exome sequencing and bioinformatics analysis.

Material and methods

Thirty-one individuals of a Korean family, 9 of whom were affected and 22 unaffected by amelogenesis imperfecta, were enrolled. Whole-exome sequencing was performed on 12 saliva samples, including samples from 8 affected and 4 unaffected individuals. The possible candidate genes associated with the disease were screened by segregation analysis and variant filtering. In silico mutation impact analysis was then performed on the filtered variants based on sequence conservation and protein structure.

Results

Whole-exome sequencing data revealed an X-linked dominant, heterozygous genomic missense mutation in the mitochondrial gene holocytochrome c synthase (HCCS). We also found that HCCS is potentially related to the role of mitochondria in amelogenesis. The HCCS variant was expected to be deleterious in both evolution-based and large population-based analyses. Further, the variant was predicted to have a negative effect on catalytic function of HCCS by in silico analysis of protein structure. In addition, HCCS had significant association with amelogenesis in literature mining analysis.

Conclusions

These findings suggest new evidence for the relationship between amelogenesis and mitochondria function, which could be implicated in the pathogenesis of amelogenesis imperfecta.

Clinical relevance

The discovery of HCCS mutations and a deeper understanding of the pathogenesis of amelogenesis imperfecta could lead to finding solutions for the fundamental treatment of this disease. Furthermore, it enables dental practitioners to establish predictable prosthetic treatment plans at an early stage by early detection of amelogenesis imperfecta through personalised medicine.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00784-022-04413-0.

Synthetic Peptides That Antagonize the Angiotensin-Converting Enzyme-2 (ACE-2) Interaction with SARS-CoV-2 Receptor Binding Spike Protein

The SARS-CoV-2 viral spike protein S receptor-binding domain (S-RBD) binds ACE2 on host cells to initiate molecular events, resulting in intracellular release of the viral genome. Therefore, antagonists of this interaction could allow a modality for therapeutic intervention. Peptides can inhibit the S-RBD:ACE2 interaction by interacting with the protein-protein interface. In this study, protein contact atlas data and molecular dynamics simulations were used to locate interaction hotspots on the secondary structure elements α1, α2, α3, β3, and β4 of ACE2. We designed a library of discontinuous peptides based upon a combination of the hotspot interactions, which were synthesized and screened in a bioluminescence-based assay. The peptides demonstrated high efficacy in antagonizing the SARS-CoV-2 S-RBD:ACE2 interaction and were validated by microscale thermophoresis which demonstrated strong binding affinity (∼10 nM) of these peptides to S-RBD. We anticipate that such discontinuous peptides may hold the potential for an efficient therapeutic treatment for COVID-19.

OUP accepted manuscript

Correct identification and effective visualization of interactions in biomolecular structures facilitate understanding of their functions and molecular design. In response to the practical needs of structure-based analysis, we have created a Mapiya web server. The Mapiya integrates four main functionalities: (i) generation of contact maps - intramolecular and intermolecular-for proteins, nucleic acids, and their complexes; (ii) characterization of the interactions physicochemical nature, (iii) interactive visualization of biomolecular conformations with automatic zoom on selected contacts using Molstar and (iv) additional sequence- and structure-based analyses performed with third-party software and in-house algorithms combined into an easy-to-use interface. Thus, Mapiya offers a highly customized analysis of the molecular interactions' in various biological systems. The web server is available at: http://mapiya.lcbio.pl/.

Identification of raloxifene as a novel α-glucosidase inhibitor using a systematic drug repurposing approach in combination with cross molecular docking-based virtual screening and experimental verification

α-Glucosidase is a promising target for the treatment of diabetes. Drug repurposing can increase the chances of discovering an active inhibitor. Therefore, this study aimed to identify potential α-glucosidase inhibitor using drug repurposing and in silico strategies. We identified critical amino acid residues of the three α-glucosidase proteins. Based on cross molecular docking studies of three α-glucosidase proteins and drugs in the FDA database, we screened hits with the favorable binding affinities and modes targeting the three proteins. Subsequently, an in vitro activity assay showed that raloxifene was an excellent inhibitor of α-glucosidase. Moreover, molecular dynamics simulations of raloxifene and three proteins were performed to assess the stability of the protein-hit systems in physiological conditions and clarify protein-hit interactions. We also performed the binding free energy calculation, Hirshfeld surface and alanine scanning mutagenesis analyses. These results demonstrated that binding between raloxifene and the three proteins was stable, and the critical amino acid residues of the three proteins formed stable contacts with raloxifene. The molecular mechanisms agree well with its activity, reinforcing that raloxifene is a candidate α-glucosidase inhibitor. Our study smoothes the path for the development of novel a-glucosidase inhibitors with high efficacy and low toxicity for the treatment of diabetes.

Mechanical couplings of protein backbone and side chains exhibit scale-free network properties and specific hotspots for function

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Statistical learning from protein dynamics unravels rigidities in interaction network.

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Backbone and side-chain mechanical couplings exhibit scale-free network properties.

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Graphical depiction of network rigidities captures sequence co-evolution patterns.

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Functional sites at secondary structure peripheries are mechanical hotspots.

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Our rigidity scores are compelling metrics for residue biological significance.

A backbone-side-chain elastic network model (bsENM) is devised in this contribution to decipher the network of molecular interactions during protein dynamics. The chemical details in 5 μs all-atom molecular dynamics (MD) simulation are mapped onto the bsENM spring constants by self-consistent iterations. The elastic parameters obtained by this structure-mechanics statistical learning are then used to construct inter-residue rigidity graphs for the chemical components in protein amino acids. A key discovery is that the mechanical coupling strengths of both backbone and side chains exhibit heavy-tailed distributions and scale-free network properties. In both rat trypsin and PDZ3 proteins, the statistically prominent modes of rigidity graphs uncover the sequence-specific coupling patterns and mechanical hotspots. Based on the contributions to graphical modes, our residue rigidity scores in backbone and side chains are found to be very useful metrics for the biological significance. Most functional sites have high residue rigidity scores in side chains while the biologically important glycines are generally next to mechanical hotspots. Furthermore, prominent modes in the rigidity graphs involving side chains oftentimes coincide with the co-evolution patterns due to evolutionary restraints. The bsENM specifically devised to resolve the protein chemical character thus provides useful means for extracting functional information from all-atom MD.

An online GPCR structure analysis platform

We present an online, interactive platform for comparative analysis of all available G-protein coupled receptor (GPCR) structures while correlating to functional data. The comprehensive platform encompasses structure similarity, secondary structure, protein backbone packing and movement, residue-residue contact networks, amino acid properties and prospective design of experimental mutagenesis studies. This lets any researcher tap the potential of sophisticated structural analyses enabling a plethora of basic and applied receptor research studies.

Rational design of selective HDAC2 inhibitors for liver cancer treatment: computational insights into the selectivity mechanism through molecular dynamics simulations and QM/MM calculations

The rational design of selective histone deacetylase 2 (HDAC2) inhibitors is beneficial for the therapeutic treatment of liver cancer, though HDAC2 is highly homologous to HDAC8, which may lead to undesired side effects due to the pan-inhibition towards HDAC2 and HDAC8. To clarify the structural basis of selective inhibition towards HDAC2 over HDAC8, we utilized multiple in silico strategies, including sequence alignment, structural comparison, molecular docking, molecular dynamics simulations, free energy calculations, alanine scanning mutagenesis, pharmacophore modeling, protein contacts atlas analysis and QM/MM calculations to study the binding patterns of HDAC2/8 selective inhibitors. Through the whole process described above, it is found that although HDAC2 has conserved GLY154 and PHE210 that also exist within HDAC8, namely GLY151 and PHE208, the two isoforms exhibit diverse binding modes towards their inhibitors. Typically, HDAC2 inhibitors interact with the Zn²⁺ ions through the core chelate group, while HDAC8 inhibitors adopt a bent conformation within the HDAC8 pocket that inclines to be in contact with the Zn²⁺ ions through the terminal hydroxamic acid group. In summary, our data comprehensively elucidate the selectivity mechanism towards HDAC2 over HDAC8, which would guide the rational design of selective HDAC2 inhibitors for liver cancer treatment.

Evolutionary and structural constraints influencing apolipoprotein A-I amyloid behavior

Apolipoprotein A-I (apoA-I) has a key function in the reverse cholesterol transport. However, aggregation of apoA-I single point mutants can lead to hereditary amyloid pathology. Although several studies have tackled the biophysical and structural consequences introduced by these mutations, there is little information addressing the relationship between the evolutionary and structural features that contribute to the amyloid behavior of apoA-I. We combined evolutionary studies, in silico mutagenesis and molecular dynamics (MD) simulations to provide a comprehensive analysis of the conservation and pathogenic role of the aggregation-prone regions (APRs) present in apoA-I. Sequence analysis demonstrated that among the four amyloidogenic regions described for human apoA-I, only two (APR1 and APR4) are evolutionary conserved across different species of Sarcopterygii. Moreover, stability analysis carried out with the FoldX engine showed that APR1 contributes to the marginal stability of apoA-I. Structural properties of full-length apoA-I models suggest that aggregation is avoided by placing APRs into highly packed and rigid portions of its native fold. Compared to silent variants extracted from the gnomAD database, the thermodynamic and pathogenic impact of amyloid mutations showed evidence of a higher destabilizing effect. MD simulations of the amyloid variant G26R evidenced the partial unfolding of the alpha-helix bundle with the concomitant exposure of APR1 to the solvent, suggesting an insight into the early steps involved in its aggregation. Our findings highlight APR1 as a relevant component for apoA-I structural integrity and emphasize a destabilizing effect of amyloid variants that leads to the exposure of this region.

Exploration of Novel Xanthine Oxidase Inhibitors Based on 1,6-Dihydropyrimidine-5-Carboxylic Acids by an Integrated in Silico Study

Xanthine oxidase (XO) is an important target for the effective treatment of hyperuricemia-associated diseases. A series of novel 2-substituted 6-oxo-1,6-dihydropyrimidine-5-carboxylic acids (ODCs) as XO inhibitors (XOIs) with remarkable activities have been reported recently. To better understand the key pharmacological characteristics of these XOIs and explore more hit compounds, in the present study, the three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, pharmacophore modeling, and molecular dynamics (MD) studies were performed on 46 ODCs. The constructed 3D-QSAR models exhibited reliable predictability with satisfactory validation parameters, including q2 = 0.897, R2 = 0.983, rpred2 = 0.948 in a CoMFA model, and q2 = 0.922, R2 = 0.990, rpred2 = 0.840 in a CoMSIA model. Docking and MD simulations further gave insights into the binding modes of these ODCs with the XO protein. The results indicated that key residues Glu802, Arg880, Asn768, Thr1010, Phe914, and Phe1009 could interact with ODCs by hydrogen bonds, π-π stackings, or hydrophobic interactions, which might be significant for the activity of these XOIs. Four potential hits were virtually screened out using the constructed pharmacophore model in combination with molecular dockings and ADME predictions. The four hits were also found to be relatively stable in the binding pocket by MD simulations. The results in this study might provide effective information for the design and development of novel XOIs.

Discovery of potential multi-target-directed ligands by targeting host-specific SARS-CoV-2 structurally conserved main protease

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has resulted in the current COVID-19 pandemic. Worldwide this disease has infected over 2.5 million individuals with a mortality rate ranging from 5 to 10%. There are several efforts going on in the drug discovery to control the SARS-CoV-2 viral infection. The main protease (MPro) plays a critical role in viral replication and maturation, thus can serve as the primary drug target. To understand the structural evolution of MPro, we have performed phylogenetic and Sequence Similarity Network analysis, that depicted divergence of Coronaviridae MPro in five clusters specific to viral hosts. This clustering was corroborated with the comparison of MPro structures. Furthermore, it has been observed that backbone and binding site conformations are conserved despite variation in some of the residues. These attributes can be exploited to repurpose available viral protease inhibitors against SARS-CoV-2 MPro. In agreement with this, we performed screening of ∼7100 molecules including active ingredients present in the Ayurvedic anti-tussive medicines, anti-viral phytochemicals and synthetic anti-virals against SARS-CoV-2 MPro as the primary target. We identified several natural molecules like δ-viniferin, myricitrin, taiwanhomoflavone A, lactucopicrin 15-oxalate, nympholide A, afzelin, biorobin, hesperidin and phyllaemblicin B that strongly binds to SARS-CoV-2 MPro. Intrestingly, these molecules also showed strong binding with other potential targets of SARS-CoV-2 infection like viral receptor human angiotensin-converting enzyme 2 (hACE-2) and RNA dependent RNA polymerase (RdRp). We anticipate that our approach for identification of multi-target-directed ligand will provide new avenues for drug discovery against SARS-CoV-2 infection.Communicated by Ramaswamy H. Sarma.

Cryptic β-Lactamase Evolution Is Driven by Low β-Lactam Concentrations

Very low antibiotic concentrations have been shown to drive the evolution of antimicrobial resistance. While substantial progress has been made to understand the driving role of low concentrations during resistance development for different antimicrobial classes, the importance of β-lactams, the most commonly used antibiotics, is still poorly studied.

Our current understanding of how low antibiotic concentrations shape the evolution of contemporary β-lactamases is limited. Using the widespread carbapenemase OXA-48, we tested the long-standing hypothesis that selective compartments with low antibiotic concentrations cause standing genetic diversity that could act as a gateway to developing clinical resistance. Here, we subjected Escherichia coli expressing bla_OXA-48, on a clinical plasmid, to experimental evolution at sub-MICs of ceftazidime. We identified and characterized seven single variants of OXA-48. Susceptibility profiles and dose-response curves showed that they increased resistance only marginally. However, in competition experiments at sub-MICs of ceftazidime, they demonstrated strong selectable fitness benefits. Increased resistance was also reflected in elevated catalytic efficiencies toward ceftazidime. These changes are likely caused by enhanced flexibility of the Ω- and β5-β6 loops and fine-tuning of preexisting active site residues. In conclusion, low-level concentrations of β-lactams can drive the evolution of β-lactamases through cryptic phenotypes which may act as stepping-stones toward clinical resistance.

IMPORTANCE Very low antibiotic concentrations have been shown to drive the evolution of antimicrobial resistance. While substantial progress has been made to understand the driving role of low concentrations during resistance development for different antimicrobial classes, the importance of β-lactams, the most commonly used antibiotics, is still poorly studied. Here, we shed light on the evolutionary impact of low β-lactam concentrations on the widespread β-lactamase OXA-48. Our data indicate that the exposure to β-lactams at very low concentrations enhances β-lactamase diversity and drives the evolution of β-lactamases by significantly influencing their substrate specificity. Thus, in contrast to high concentrations, low levels of these drugs may substantially contribute to the diversification and divergent evolution of these enzymes, providing a standing genetic diversity that can be selected and mobilized when antibiotic pressure increases.

Directed Evolution of a Glutathione Transferase for the Development of a Biosensor for Alachlor Determination

In the present work, DNA recombination of three homologous tau class glutathione transferases (GSTUs) allowed the creation of a library of tau class GmGSTUs. The library was activity screened for the identification of glutathione transferase (GST) variants with enhanced catalytic activity towards the herbicide alachlor (2-chloro-2′,6′-diethyl-N-(methoxymethyl)acetanilide). One enzyme variant (GmGSTsf) with improved catalytic activity and binding affinity for alachlor was identified and explored for the development of an optical biosensor for alachlor determination. Kinetics analysis and molecular modeling studies revealed a key mutation (Ile69Val) at the subunit interface (helix α3) that appeared to be responsible for the altered catalytic properties. The enzyme was immobilized directly on polyvinylidenefluoride membrane by crosslinking with glutaraldehyde and was placed on the inner surface of a plastic cuvette. The rate of pH changes observed as a result of the enzyme reaction was followed optometrically using a pH indicator. A calibration curve indicated that the linear concentration range for alachlor was 30–300 μM. The approach used in the present study can provide tools for the generation of novel enzymes for eco-efficient and environment-friendly analytical technologies. In addition, the outcome of this study gives an example for harnessing protein symmetry for enzyme design.

Probing the Role of the Conserved Arg174 in Formate Dehydrogenase by Chemical Modification and Site-Directed Mutagenesis

The reactive adenosine derivative, adenosine 5′-O-[S-(4-hydroxy-2,3-dioxobutyl)]-thiophosphate (AMPS-HDB), contains a dicarbonyl group linked to the purine nucleotide at a position equivalent to the pyrophosphate region of NAD⁺. AMPS-HDB was used as a chemical label towards Candida boidinii formate dehydrogenase (CbFDH). AMPS-HDB reacts covalently with CbFDH, leading to complete inactivation of the enzyme activity. The inactivation kinetics of CbFDH fit the Kitz and Wilson model for time-dependent, irreversible inhibition (K_D = 0.66 ± 0.15 mM, first order maximum rate constant k₃ = 0.198 ± 0.06 min⁻¹). NAD⁺ and NADH protects CbFDH from inactivation by AMPS-HDB, showing the specificity of the reaction. Molecular modelling studies revealed Arg174 as a candidate residue able to be modified by the dicarbonyl group of AMPS-HDB. Arg174 is a strictly conserved residue among FDHs and is located at the Rossmann fold, the common mononucleotide-binding motif of dehydrogenases. Arg174 was replaced by Asn, using site-directed mutagenesis. The mutant enzyme CbFDHArg174Asn was showed to be resistant to inactivation by AMPS-HDB, confirming that the guanidinium group of Arg174 is the target for AMPS-HDB. The CbFDHArg174Asn mutant enzyme exhibited substantial reduced affinity for NAD⁺ and lower thermostability. The results of the study underline the pivotal and multifunctional role of Arg174 in catalysis, coenzyme binding and structural stability of CbFDH.