Aromatic clusters in protein-protein and protein-drug complexes

WDR5 Binding to Histone Serotonylation Is Driven by an Edge-Face Aromatic Interaction with Unexpected Electrostatic Effects

Histone serotonylation has emerged as a key post-translational modification. WDR5 preferentially binds to serotonylated histone 3 (H3), and this binding event has been associated with tumorigenesis. Herein, we utilize genetic code expansion, structure-activity relationship studies, and computation to study an edge-face aromatic interaction between WDR5 Phe149 and serotonin on H3 that is key to this protein-protein interaction. We find experimentally that this edge-face aromatic interaction is unaffected by modulating the electrostatics of the face component but is weakened by electron-withdrawing substituents on the edge component. Overall, these results elucidate that this interaction is governed by van der Waals forces as well as electrostatics of the edge ring, a result that clarifies discrepancies among previous theoretical models and model system studies of this interaction type. This is the first evaluation of the driving force of an edge-face aromatic interaction at a protein-protein interface and provides a key benchmark for the nature of these understudied interactions that are abundant in the proteome.

Phytochemical constituents analysis in laminaria digitata for Alzheimer's disease: molecular docking and in-silico toxicity approach

Alzheimer's disease (AD) is a common brain disease associated with cognitive impairment and dementia. donepezil, an acetylcholinesterase (AChE) inhibitor drug as a commercial AD drug represents a non-cost-effective treatment with the toxic effects reported. As the prevalence of AD increases, the development of effective therapeutic treatments is urgently required. Laminaria digitata is a brown seaweed claimed to be able to prevent and treat neurodegenerative diseases. Therefore, this study measured and compared the binding affinity and toxicity of seven common phytoconstituents in Laminaria digitata against acetylcholinesterase (AChE) with those of donepezil using a molecular docking approach. The binding free energy values of donepezil, dieckol, eckol, fucodiphlorethol G, 7-Phloroecol, laminaran, alginic acid, and fucoidan with acetylcholinesterase (AChE) were -12.3, -13.5, -10.5, -8,7, -9.7, -8.0, -10.3, and -7.4 kcal/mol. All ligands constantly interacted with the AChE amino acid residues, namely Tyr124. Dieckol, with the strongest and most stable interaction, is classified as class IV toxicity, with an LD50 value of 866 mg/kg. It has aryl hydrocarbon receptor (AhR) and mitochondrial membrane potential (MMP) toxicity at certain doses. Theoretically, based on Lipinski's rule, dieckol is likely to have poor absorption and permeation properties; therefore, several considerations during the drug discovery process are needed.

The Development of CDC25A-Derived Phosphoseryl Peptides That Bind 14-3-3ε with High Affinities

Overexpression of the 14-3-3ε protein is associated with suppression of apoptosis in cutaneous squamous cell carcinoma (cSCC). This antiapoptotic activity of 14-3-3ε is dependent on its binding to CDC25A; thus, inhibiting 14-3-3ε - CDC25A interaction is an attractive therapeutic approach to promote apoptosis in cSCC. In this regard, designing peptide inhibitors of 14-3-3ε - CDC25A interactions is of great interest. This work reports the rational design of peptide analogs of pS, a CDC25A-derived peptide that has been shown to inhibit 14-3-3ε-CDC25A interaction and promote apoptosis in cSCC with micromolar IC50. We designed new peptide analogs in silico by shortening the parent pS peptide from 14 to 9 amino acid residues; then, based on binding motifs of 14-3-3 proteins, we introduced modifications in the pS(174-182) peptide. We studied the binding of the peptides using conventional molecular dynamics (MD) and steered MD simulations, as well as biophysical methods. Our results showed that shortening the pS peptide from 14 to 9 amino acids reduced the affinity of the peptide. However, substituting Gln176 with either Phe or Tyr amino acids rescued the binding of the peptide. The optimized peptides obtained in this work can be candidates for inhibition of 14-3-3ε - CDC25A interactions in cSCC.

Structural insights into the transporting and catalyzing mechanism of DltB in LTA D-alanylation

DltB, a model member of the Membrane-Bound O-AcylTransferase (MBOAT) superfamily, plays a crucial role in D-alanylation of the lipoteichoic acid (LTA), a significant component of the cell wall of gram-positive bacteria. This process stabilizes the cell wall structure, influences bacterial virulence, and modulates the host immune response. Despite its significance, the role of DltB is not well understood. Through biochemical analysis and cryo-EM imaging, we discover that Streptococcus thermophilus DltB forms a homo-tetramer on the cell membrane. We further visualize DltB in an apo form, in complex with DltC, and in complex with its inhibitor amsacrine (m-AMSA). Each tetramer features a central hole. The C-tunnel of each protomer faces the intratetramer interface and provides access to the periphery membrane. Each protomer binds a DltC without changing the tetrameric organization. A phosphatidylglycerol (PG) molecule in the substrate-binding site may serve as an LTA carrier. The inhibitor m-AMSA bound to the L-tunnel of each protomer blocks the active site. The tetrameric organization of DltB provides a scaffold for catalyzing D-alanyl transfer and regulating the channel opening and closing. Our findings unveil DltB's dual function in the D-alanylation pathway, and provide insight for targeting DltB as a anti-virulence antibiotic.

Phytochemical identification and in silico elucidation of interactions of bioactive compounds from Citrullus lanatus with androgen receptor towards prostate cancer treatment

Androgen receptor (AR) is known to play a crucial role in the development and progression of prostate cancer, and compounds that inhibit its activity are regarded as promising for the development of drugs to treat the disease. This study aimed to investigate the AR-inhibiting potential of Citrullus lanatus fruit compounds for prostate cancer drug development. Following HPLC identification, the binding energies, molecular interactions, and pharmacological potentials of the compounds against AR were elucidated using in silico techniques such as, molecular docking, induced-fit docking, molecular dynamics simulation, and ADMET prediction. Some of the compounds found to be present in Citrullus lanatus fruit included flavonoids such as proanthocyanin, naringin, flavan 3 ol, flavonones, naringenin, epicatechin, citrulline, and catechin. Naringenin exhibited the highest docking score in the molecular docking analysis, followed by resveratrol, ribalinidine, and epicatechin. These compounds share a common AR binding site with the standard ligand, dihydrotestosterone (DHT). Some of the compounds showed favorable ADMET profiles, while others showed at least one toxicity potential. The induced-fit docking of naringenin with AR yielded a higher docking score than the initial score obtained from standard docking while preserving stable molecular contacts with the interacting amino acids. Consistent hydrogen bond interactions of naringenin with PHE 764, ASN 705, and THR 877 of AR, including a persistent pi-pi stacking contact with PHE 764, were observed from the molecular dynamic simulation. The Citrullus lanatus compounds, particularly naringenin, may therefore be considered for further research towards the development of drugs for prostate cancer therapy.

Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence

Understanding protein sequence and structure is essential for understanding protein-protein interactions (PPIs), which are essential for many biological processes and diseases. Targeting protein binding hot spots, which regulate signaling and growth, with rational drug design is promising. Rational drug design uses structural data and computational tools to study protein binding sites and protein interfaces to design inhibitors that can change these interactions, thereby potentially leading to therapeutic approaches. Artificial intelligence (AI), such as machine learning (ML) and deep learning (DL), has advanced drug discovery and design by providing computational resources and methods. Quantum chemistry is essential for drug reactivity, toxicology, drug screening, and quantitative structure-activity relationship (QSAR) properties. This review discusses the methodologies and challenges of identifying and characterizing hot spots and binding sites. It also explores the strategies and applications of artificial-intelligence-based rational drug design technologies that target proteins and protein-protein interaction (PPI) binding hot spots. It provides valuable insights for drug design with therapeutic implications. We have also demonstrated the pathological conditions of heat shock protein 27 (HSP27) and matrix metallopoproteinases (MMP2 and MMP9) and designed inhibitors of these proteins using the drug discovery paradigm in a case study on the discovery of drug molecules for cancer treatment. Additionally, the implications of benzothiazole derivatives for anticancer drug design and discovery are deliberated.

Bioactives from medicinal herb against bedaquiline resistant tuberculosis: removing the dark clouds from the horizon

Tuberculosis is a contagious bacterial ailment that primarily affects the lungs and is brought on by the bacterium Mycobacterium tuberculosis (MTB). An antimycobacterial medication called bedaquiline (BQ) is specified to treat multidrug-resistant tuberculosis (MDR-TB). Despite its contemporary use in clinical practice, the mutations (D32 A/G/N/V/P) constrain the potential of BQ by causing transitions in the structural conformation of the atpE subunit-c after binding. In this study, we have taken the benzylisoquinoline alkaloids from thalictrum foliolosum due to its antimicrobial activity reported in prior literature. We used an efficient and optimized structure-based strategy to examine the wild type (WT) and mutated protein upon molecule binding. Our results emphasize the drastic decline in BQ binding affinity of mutant and WT atpE subunit-c complexes compared to thalirugidine (top hit) from thalictrum foliolosum. The decrease in BQ binding free energy is due to electrostatic energy because nearly every atom in a macromolecule harbors a partial charge, and molecules taking part in molecular recognition will interact electrostatically. Similarly, the high potential mean force of thalirugidine than BQ in WT and mutant complexes demonstrated the remarkable ability to eradicate mycobacteria efficiently. Furthermore, the Alamar blue cell viability and ATP determination assay were performed to validate the computational outcomes in search of novel antimycobacterial. Upon closer examination of the ATP determination assay, it became apparent that both BQ and thalirugidine showed similar reductions in ATP levels at their respective MICs, presenting a potential common mechanism of action.

In vitro and in silico inhibitory validation of Tapinanthus cordifolius leaf extract on alpha-glucosidase in the management of type 2 diabetes

The anti-diabetic properties of medicinal plants are becoming more widely recognized. To identify potential anti-diabetic agents for diabetes drug discovery, the current study used in vitro and in silico approaches to assess the alpha glucosidase inhibitory activities of Tapinanthus cordifolius (TC) leaf extracts and its bioactive components respectively. In vitro alpha glucosidase inhibitory assay was carried out on TC extract and fractions at various concentrations (50-1600 µg/mL), and the compounds with alpha glucosidase inhibitory potentials were identified using molecular docking, pharmacophore modelling, and molecular dynamics simulation. The crude extract exhibited the highest activity with an IC50 value of 248 μg/mL. Out of the 42 phytocompounds of the extract, α-Tocopherol-β-d-mannoside gave the lowest binding energy of -6.20 Kcal/mol followed by, 5-Ergosterol (-5.46 kcal/mol), Acetosyringone (-4.76 kcal/mol), and Benzaldehyde, 4-(Ethylthio)-2,5-Dimethoxy-(-4.67 kcal/mol). The selected compounds interacted with critical active site amino acid residues of alpha-glucosidase, just like the reference ligand. Molecular dynamics simulation revealed the formation of a stable complex between α-glucosidase and α-Tocopherol-β-d-mannoside, with ASP 564 sustaining two hydrogen bond connections for 99.9 and 75.0% of the simulation duration, respectively. Therefore, the selected TC compounds, especially α-Tocopherol-β-d-mannoside might be explored for future research and development as diabetic medicines.Communicated by Ramaswamy H. Sarma.

Probing the functional hotspots inside protein hydrophobic pockets by in situ photochemical trifluoromethylation and mass spectrometry

Due to the complex high-order structures and interactions of proteins within an aqueous solution, a majority of chemical functionalizations happen on the hydrophilic sites of protein external surfaces which are naturally exposed to the solution. However, the hydrophobic pockets inside proteins are crucial for ligand binding and function as catalytic centers and transporting tunnels. Herein, we describe a reagent pre-organization and in situ photochemical trifluoromethylation strategy to profile the functional sites inside the hydrophobic pockets of native proteins. Unbiased mass spectrometry profiling was applied for the characterization of trifluoromethylated sites with high sensitivity. Native proteins including myoglobin, trypsin, haloalkane dehalogenase, and human serum albumin have been engaged in this mild photochemical process and substantial hydrophobic site-specific and structure-selective trifluoromethylation substitutes are obtained without significant interference to their bioactivity and structures. Sodium triflinate is the only reagent required to functionalize the unprotected proteins with wide pH-range tolerance and high biocompatibility. This "in-pocket" activation model provides a general strategy to modify the potential binding pockets and gain essential structural insights into the functional hotspots inside protein hydrophobic pockets.

Unveiling the Role of Water on π-π Stacking Through Microwave Spectroscopy of (Thiophene)2-(Water)1-2 Clusters

There has been an ongoing debate about whether water enhances or hinders π-π stacking, a phenomenon crucial in various biological and chemical systems. In this study, the influence of water on π-π stacking is investigated by microwave spectroscopic observation of gas-phase hydrated clusters of thiophene dimers. Two isomers of (C4H4S)2-H2O and two isomers of (C4H4S)2-(H2O)2 have been unambiguously identified. These identifications are supported by quantum chemistry calculations and isotopic measurements. In each of these conformations, water molecules are situated between aromatic pairs, forming distinctive interactions. Water molecules engage with thiophene molecules either as hydrogen bond donors through OH···π interactions or as hydrogen bond acceptors through CH···O interactions. The energy decomposition analysis indicates that the bonding pattern of water molecules significantly affects the π···π interactions between aromatic rings. These findings offer valuable structural insights into the role of water in shaping π-π stacking.

How Modulator Binding at the Amyloidβ-γ-Secretase Interface Enhances Substrate Binding and Attenuates Membrane Distortion

Inhibition of γ-secretase, an intramembrane protease, to reduce secretion of Amyloid-β (Aβ) peptides has been considered for treating Alzheimer's disease. However, γ-secretase inhibitors suffer from severe side effects. As an alternative, γ-secretase modulators (GSM) reduce the generation of toxic peptides by enhancing the cleavage processivity without diminishing the enzyme activity. Starting from a known γ-secretase structure without substrate but in complex with an E2012 GSM, we generated a structural model that included a bound Aβ43 peptide and studied interactions among enzyme, substrate, GSM, and lipids. Our result suggests that E2012 binding at the enzyme-substrate-membrane interface attenuates the membrane distortion by shielding the substrate-membrane interaction. The model predicts that the E2012 modulation is charge-dependent and explains the preserved hydrogen acceptor and the aromatic ring observed in many imidazole-based GSM. Predicted effects of γ-secretase mutations on E2012 modulation were confirmed experimentally. We anticipate that the study will facilitate the future development of effective GSMs.

Late-Stage C-H Activation of Drug (Derivative) Molecules with Pd(ll) Catalysis

This review comprehensively analyses representative examples of Pd(II)-catalyzed late-stage C-H activation reactions and demonstrates their efficacy in converting C-H bonds at multiple positions within drug (derivative) molecules into diverse functional groups. These transformative reactions hold immense potential in medicinal chemistry, enabling the efficient and selective functionalization of specific sites within drug molecules, thereby enhancing their pharmacological activity and expanding the scope of potential drug candidates. Although notable articles have focused on late-stage C-H functionalization reactions of drug-like molecules using transition-metal catalysts, reviews specifically focusing on late-stage C-H functionalization reactions of drug (derivative) molecules using Pd(II) catalysts are required owing to their prominence as the most widely utilized metal catalysts for C-H activation and their ability to introduce a myriad of functional groups at specific C-H bonds. The utilization of Pd-catalyzed C-H activation methodologies demonstrates impressive success in introducing various functional groups, such as cyano (CN), fluorine (F), chlorine (Cl), aromatic rings, olefin, alkyl, alkyne, and hydroxyl groups, to drug (derivative) molecules with high regioselectivity and functional-group tolerance. These breakthroughs in late-stage C-H activation reactions serve as invaluable tools for drug discovery and development, thereby offering strategic options to optimize drug candidates and drive the exploration of innovative therapeutic solutions.

High-throughput virtual screening, pharmacophore modelling and antagonist effects of small molecule inhibitors against cytotoxin-induced cytotoxicity

Cobra venom cytotoxins (CTX) cause dermonecrosis in envenomed patients who suffered from limb amputations due to the limitation of serotherapy-based antivenoms. This study aimed to identify small molecule inhibitors against CTX. A structure-based high-throughput virtual screening (HTVS) was conducted based on a conserved CTX, using the Natural Product Activity and Species Source (NPASS) screening library. The hits were valerenic acid, 1-oxo-2H-isoquinoline-4-carboxylic acid, acenaphthene, and 5-bromopyrrole-2-carboxamide, which interacted with contemporary antivenom binding site A and functional loops I-III of CTX, respectively, in molecular docking studies. Furthermore, molecular dynamic simulations were performed along with analysis of ligand fitness through their pharmacophore and pharmacokinetics properties. The antagonist effects of these hits on CTX-induced cytotoxicity were examined in human keratinocytes (HaCaT). Despite having a low binding affinity (KD = 14.45 × 10-4 M), acenaphthene demonstrated a significant increase of cell viability at 6 h and 24 h in experimental envenomed HaCaT. It also demonstrated the highest neutralization potency against CTX with a median effective concentration (EC50) of 0.05 mL/mg. Acenaphthene interacted with the functional loop II, which is the crucial cytotoxic site of CTX. It has an aromatic ring as its primary pharmacophoric feature, commonly used for rational drug design. In conclusion, acenaphthene could be a promising lead compound as a small molecule inhibitor.Communicated by Ramaswamy H. Sarma.

Statistical Analysis and Tokenization of Epitopes to Construct Artificial Neoepitope Libraries

Epitopes are specific regions on an antigen's surface that the immune system recognizes. Epitopes are usually protein regions on foreign immune-stimulating entities such as viruses and bacteria, and in some cases, endogenous proteins may act as antigens. Identifying epitopes is crucial for accelerating the development of vaccines and immunotherapies. However, mapping epitopes in pathogen proteomes is challenging using conventional methods. Screening artificial neoepitope libraries against antibodies can overcome this issue. Here, we applied conventional sequence analysis and methods inspired in natural language processing to reveal specific sequence patterns in the linear epitopes deposited in the Immune Epitope Database (www.iedb.org) that can serve as building blocks for the design of universal epitope libraries. Our results reveal that amino acid frequency in annotated linear epitopes differs from that in the human proteome. Aromatic residues are overrepresented, while the presence of cysteines is practically null in epitopes. Byte pair encoding tokenization shows high frequencies of tryptophan in tokens of 5, 6, and 7 amino acids, corroborating the findings of the conventional sequence analysis. These results can be applied to reduce the diversity of linear epitope libraries by orders of magnitude.

A quinolin-8-ol sub-millimolar inhibitor of UGGT, the ER glycoprotein folding quality control checkpoint

Misfolded glycoprotein recognition and endoplasmic reticulum (ER) retention are mediated by the ER glycoprotein folding quality control (ERQC) checkpoint enzyme, UDP-glucose glycoprotein glucosyltransferase (UGGT). UGGT modulation is a promising strategy for broad-spectrum antivirals, rescue-of-secretion therapy in rare disease caused by responsive mutations in glycoprotein genes, and many cancers, but to date no selective UGGT inhibitors are known. The small molecule 5-[(morpholin-4-yl)methyl]quinolin-8-ol (5M-8OH-Q) binds a CtUGGTGT24 "WY" conserved surface motif conserved across UGGTs but not present in other GT24 family glycosyltransferases. 5M-8OH-Q has a 47 μM binding affinity for CtUGGTGT24in vitro as measured by ligand-enhanced fluorescence. In cellula, 5M-8OH-Q inhibits both human UGGT isoforms at concentrations higher than 750 μM. 5M-8OH-Q binding to CtUGGTGT24 appears to be mutually exclusive to M5-9 glycan binding in an in vitro competition experiment. A medicinal program based on 5M-8OH-Q will yield the next generation of UGGT inhibitors.

Categorization of hotspots into three types - weak, moderate and strong to distinguish protein-protein versus protein-peptide interactions

Protein-protein and protein-peptide interactions (PPI and PPepI) belong to a similar category of interactions, yet seemingly subtle differences exist among them. To characterize differences between protein-protein (PP) and protein-peptide (PPep) interactions, we have focussed on two important classes of residues-hotspot and anchor residues. Using implicit solvation-based free energy calculations, a very large-scale alanine scanning has been performed on benchmark datasets, consisting of over 5700 interface residues. The differences in the two categories are more pronounced, if the data were divided into three distinct types, namely - weak hotspots (having binding free energy loss upon Ala mutation, ΔΔG, ∼2-10 kcal/mol), moderate hotspots (ΔΔG, ∼10-20 kcal/mol) and strong hotspots (ΔΔG ≥ ∼20 kcal/mol). The analysis suggests that for PPI, weak hotspots are predominantly populated by polar and hydrophobic residues. The distribution shifts towards charged and polar residues for moderate hotspot and charged residues (principally Arg) are overwhelmingly present in the strong hotspot. On the other hand, in the PPepI dataset, the distribution shifts from predominantly hydrophobic and polar (in the weak type) to almost similar preference for polar, hydrophobic and charged residues (in moderate type) and finally the charged residue (Arg) and Trp are mostly occupied in the strong type. The preferred anchor residues in both categories are Arg, Tyr and Leu, possessing bulky side chain and which also strike a delicate balance between side chain flexibility and rigidity. The present knowledge should aid in effective design of biologics, by augmentation or disruption of PPIs with peptides or peptidomimetics.Communicated by Ramaswamy H. Sarma.

A review on structural mechanisms of protein-persistent organic pollutant (POP) interactions

With the advent of the industrial revolution, the accumulation of persistent organic pollutants (POPs) in the environment has become ubiquitous. POPs are halogen-containing organic molecules that accumulate, and remain in the environment for a long time, thus causing toxic effects in living organisms. POPs exhibit a high affinity towards biological macromolecules such as nucleic acids, proteins and lipids, causing genotoxicity and impairment of homeostasis in living organisms. Proteins are essential members of the biological assembly, as they stipulate all necessary processes for the survival of an organism. Owing to their stereochemical features, POPs and their metabolites form energetically favourable complexes with proteins, as supported by biological and dose-dependent toxicological studies. Although individual studies have reported the biological aspects of protein-POP interactions, no comprehensive study summarizing the structural mechanisms, thermodynamics and kinetics of protein-POP complexes is available. The current review identifies and classifies protein-POP interaction according to the structural and functional basis of proteins into five major protein targets, including digestive and other enzymes, serum proteins, transcription factors, transporters, and G-protein coupled receptors. Further, analysis detailing the molecular interactions and structural mechanism evidenced that H-bonds, van der Waals, and hydrophobic interactions essentially mediate the formation of protein-POP complexes. Moreover, interaction of POPs alters the protein conformation through kinetic and thermodynamic processes like competitive inhibition and allostery to modulate the cellular signalling processes, resulting in various pathological conditions such as cancers and inflammations. In summary, the review provides a comprehensive insight into the critical structural/molecular aspects of protein-POP interactions.

Carbon nanotube recognition by human Siglec-14 provokes inflammation

For the design and development of innovative carbon nanotube (CNT)-based tools and applications, an understanding of the molecular interactions between CNTs and biological systems is essential. In this study, a three-dimensional protein-structure-based in silico screen identified the paired immune receptors, sialic acid immunoglobulin-like binding lectin-5 (Siglec-5) and Siglec-14, as CNT-recognizing receptors. Molecular dynamics simulations showed the spatiotemporally stable association of aromatic residues on the extracellular loop of Siglec-5 with CNTs. Siglec-14 mediated spleen tyrosine kinase (Syk)-dependent phagocytosis of multiwalled CNTs and the subsequent secretion of interleukin-1β from human monocytes. Ectopic in vivo expression of human Siglec-14 on mouse alveolar macrophages resulted in enhanced recognition of multiwalled CNTs and exacerbated pulmonary inflammation. Furthermore, fostamatinib, a Syk inhibitor, blocked Siglec-14-mediated proinflammatory responses. These results indicate that Siglec-14 is a human activating receptor recognizing CNTs and that blockade of Siglec-14 and the Syk pathway may overcome CNT-induced inflammation.

Investigating the functional role of a buried interchain aromatic cluster in Escherichia coli GrpE dimer

Aromatic clusters in the core of proteins are often involved in imparting structural stability to proteins. However, their functional importance is not always clear. In this study, we investigate the thermosensing role of a phenylalanine cluster present in the GrpE homodimer. GrpE, which acts as a nucleotide exchange factor for the molecular chaperone DnaK, is well known for its thermosensing activity resulting from temperature-dependent structural changes that allow control of chaperone function. Using mutational analysis, we show that an interchain phenylalanine cluster in a four-helix bundle of the GrpE homodimer assists in the thermosensing ability of the co-chaperone. Substitution of aromatic residues with hydrophobic ones in the core of the four-helix bundle reduces the thermal stability of the bundle and that of a connected coiled-coil domain, which impacts thermosensing. Cell growth assays and SEM images of the mutants show filamentous growth of Escherichia coli cells at 42°C, which corroborates with the defect in thermosensing. Our work suggests that the interchain edge-to-face aromatic cluster is important for the propagation of the structural signal from the coiled-coil domain to the four-helical bundle of GrpE, thus facilitating GrpE-mediated thermosensing in bacteria.

Modified coptisine derivatives as an inhibitor against pathogenic Rhizomucor miehei, Mycolicibacterium smegmatis (Black Fungus), Monkeypox, and Marburg virus by molecular docking and molecular dynamics simulation-based drug design approach

During the second phase of SARS-CoV-2, an unknown fungal infection, identified as black fungus, was transmitted to numerous people among the hospitalized COVID-19 patients and increased the death rate. The black fungus is associated with the Mycolicibacterium smegmatis, Mucor lusitanicus, and Rhizomucor miehei microorganisms. At the same time, other pathogenic diseases, such as the Monkeypox virus and Marburg virus, impacted global health. Policymakers are concerned about these pathogens due to their severe pathogenic capabilities and rapid spread. However, no standard therapies are available to manage and treat those conditions. Since the coptisine has significant antimicrobial, antiviral, and antifungal properties; therefore, the current investigation has been designed by modifying coptisine to identify an effective drug molecule against Black fungus, Monkeypox, and Marburg virus. After designing the derivatives of coptisine, they have been optimized to get a stable molecular structure. These ligands were then subjected to molecular docking study against two vital proteins obtained from black fungal pathogens: Rhizomucor miehei (PDB ID: 4WTP) and Mycolicibacterium smegmatis (PDB ID 7D6X), and proteins found in Monkeypox virus (PDB ID: 4QWO) and Marburg virus (PDB ID 4OR8). Following molecular docking, other computational investigations, such as ADMET, QSAR, drug-likeness, quantum calculation and molecular dynamics, were also performed to determine their potentiality as antifungal and antiviral inhibitors. The docking score reported that they have strong affinities against Black fungus, Monkeypox virus, and Marburg virus. Then, the molecular dynamic simulation was conducted to determine their stability and durability in the physiological system with water at 100 ns, which documented that the mentioned drugs were stable over the simulated time. Thus, our in silico investigation provides a preliminary report that coptisine derivatives are safe and potentially effective against Black fungus, Monkeypox virus, and Marburg virus. Hence, coptisine derivatives may be a prospective candidate for developing drugs against Black fungus, Monkeypox and Marburg viruses.

Aromatic ring flips in differently packed ubiquitin protein crystals from MAS NMR and MD

Probing the dynamics of aromatic side chains provides important insights into the behavior of a protein because flips of aromatic rings in a protein's hydrophobic core report on breathing motion involving a large part of the protein. Inherently invisible to crystallography, aromatic motions have been primarily studied by solution NMR. The question how packing of proteins in crystals affects ring flips has, thus, remained largely unexplored. Here we apply magic-angle spinning NMR, advanced phenylalanine 1H-13C/2H isotope labeling and MD simulation to a protein in three different crystal packing environments to shed light onto possible impact of packing on ring flips. The flips of the two Phe residues in ubiquitin, both surface exposed, appear remarkably conserved in the different crystal forms, even though the intermolecular packing is quite different: Phe4 flips on a ca. 10-20 ns time scale, and Phe45 are broadened in all crystals, presumably due to µs motion. Our findings suggest that intramolecular influences are more important for ring flips than intermolecular (packing) effects.

Phytochemical Characterization, Functional Nutrition, and Anti-Diabetic Potentials of Leptadenia hastata (pers) Decne Leaves: In Silico and In Vitro Studies

The geometrical increase in diabetes mellitus (DM) and the undesirable side effects of synthetic drugs have intensified efforts to search for an effective and safe anti-diabetic therapy. This study aimed to identify the antioxidant and anti-diabetic agents in the ethanol extract of Leptadenia hastata (EELH). The phytochemicals, antioxidant vitamins, and minerals present in EELH were determined using standard procedures to achieve this aim. Gas chromatography coupled with mass spectroscopy and flame ionization detector (GC-MS/GC-FID) was employed to identify bioactive compounds. An e-pharmacophore model was generated from the extra precision, and energy-minimized docked position of standard inhibitor, acarbose onto human pancreatic amylase (HPA, PDB-6OCN). It was used to screen the GC-MS/GC-FID library of compounds. The top-scoring compounds were subjected to glide XP-docking and prime MM-GBSA calculation with the Schrodinger suite-v12.4. The Adsorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) prediction of the best-fit compounds was made using SwissADME and PROTOX-II webservers. Further validation of the docking results was performed with the in vitro analysis of the α-amylase and α-glucosidase inhibitory activities. EELH contains appreciable amounts of antioxidant and anti-diabetic phytoconstituents. The top-4 scoring compounds (rutin, epicatechin, kaempferol, and naringenin) from the EELH phytochemical library interacted with amino acid residues within and around the HPA active site. The ADMET prediction shows that epicatechin, kaempferol, and naringenin had favorable drug-likeness, pharmacokinetic properties, and a good safety profile. EELH demonstrated good inhibitory actions against α-amylase and α-glucosidase with 1C50 values of 14.14 and 4.22 µg/mL, respectively. Thus, L hastata phytoconstituents are promising novel candidates for developing an anti-diabetic drug.

De novo determination of mosquitocidal Cry11Aa and Cry11Ba structures from naturally-occurring nanocrystals

Cry11Aa and Cry11Ba are the two most potent toxins produced by mosquitocidal Bacillus thuringiensis subsp. israelensis and jegathesan, respectively. The toxins naturally crystallize within the host; however, the crystals are too small for structure determination at synchrotron sources. Therefore, we applied serial femtosecond crystallography at X-ray free electron lasers to in vivo-grown nanocrystals of these toxins. The structure of Cry11Aa was determined de novo using the single-wavelength anomalous dispersion method, which in turn enabled the determination of the Cry11Ba structure by molecular replacement. The two structures reveal a new pattern for in vivo crystallization of Cry toxins, whereby each of their three domains packs with a symmetrically identical domain, and a cleavable crystal packing motif is located within the protoxin rather than at the termini. The diversity of in vivo crystallization patterns suggests explanations for their varied levels of toxicity and rational approaches to improve these toxins for mosquito control.

A Computational Approach to Elucidate the Interactions of Chemicals From Artemisia annua Targeted Toward SARS-CoV-2 Main Protease Inhibition for COVID-19 Treatment

The inhibitory potential of Artemisia annua, a well-known antimalarial herb, against several viruses, including the coronavirus, is increasingly gaining recognition. The plant extract has shown significant activity against both the Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and the novel SARS-CoV-2 that is currently ravaging the world. It is therefore necessary to evaluate individual chemicals of the plant for inhibitory potential against SARS-CoV-2 for the purpose of designing drugs for the treatment of COVID-19. In this study, we employed computational techniques comprising molecular docking, binding free energy calculations, pharmacophore modeling, induced-fit docking, molecular dynamics simulation, and ADMET predictions to identify potential inhibitors of the SARS-CoV-2 main protease (M^pro) from 168 bioactive compounds of Artemisia annua. Rhamnocitrin, isokaempferide, kaempferol, quercimeritrin, apigenin, penduletin, isoquercitrin, astragalin, luteolin-7-glucoside, and isorhamnetin were ranked the highest, with docking scores ranging from −7.84 to −7.15 kcal/mol compared with the −6.59 kcal/mol demonstrated by the standard ligand. Rhamnocitrin, Isokaempferide, and kaempferol, like the standard ligand, interacted with important active site amino acid residues like HIS 41, CYS 145, ASN 142, and GLU 166, among others. Rhamnocitrin demonstrated good stability in the active site of the protein as there were no significant conformational changes during the simulation process. These compounds also possess acceptable druglike properties and a good safety profile. Hence, they could be considered for experimental studies and further development of drugs against COVID-19.

Structure of the Yeast Cell Wall Integrity Sensor Wsc1 Reveals an Essential Role of Surface-Exposed Aromatic Clusters

In the yeast Saccharomyces cerevisiae and other ascomycetes, the maintenance of cell wall integrity is governed by a family of plasma-membrane spanning sensors that include the Wsc-type proteins. These cell wall proteins apparently sense stress-induced mechanical forces at the cell surface and target the cell wall integrity (CWI) signaling pathway, but the structural base for their sensor function is yet unknown. Here, we solved a high-resolution crystal structure of the extracellular cysteine-rich domain (CRD) of yeast Wsc1, which shows the characteristic PAN/Apple domain fold with two of the four Wsc1 disulfide bridges being conserved in other PAN domain cores. Given the general function of PAN domains in mediating protein–protein and protein–carbohydrate interactions, this finding underpins the importance of Wsc domains in conferring sensing and localization functions. Our Wsc1 CRD structure reveals an unusually high number of surface-exposed aromatic residues that are conserved in other fungal CRDs, and can be arranged into three solvent-exposed clusters. Mutational analysis demonstrates that two of the aromatic clusters are required for conferring S. cerevisiae Wsc1-dependent resistance to the glucan synthase inhibitor caspofungin, and the chitin-binding agents Congo red and Calcofluor white. These findings suggest an essential role of surface-exposed aromatic clusters in fungal Wsc-type sensors that might include an involvement in stress-induced sensor-clustering required to elicit appropriate cellular responses via the downstream CWI pathway.

Specificity and Reactivity of Mycobacterium tuberculosis Serine/Threonine Kinases PknG and PknB

Mycobacterium tuberculosis (Mtb), the causative agent of Tuberculosis, has 11 eukaryotic-like serine/threonine protein kinases, which play essential roles in cell growth, signal transduction, and pathogenesis. Protein kinase G (PknG) regulates the carbon and nitrogen metabolism by phosphorylation of the glycogen accumulation regulator (GarA) protein at Thr21. Protein kinase B (PknB) is involved in cell wall synthesis and cell shape, as well as phosphorylates GarA but at Thr22. While PknG seems to be constitutively activated and recognition of GarA requires phosphorylation in its unstructured tail, PknB activation is triggered by phosphorylation of its activation loop, which allows binding of the forkhead-associated domain of GarA. In the present work, we used molecular dynamics and quantum-mechanics/molecular mechanics simulations of the catalytically competent complex and kinase activity assays to understand PknG/PknB specificity and reactivity toward GarA. Two hydrophobic residues in GarA, Val24 and Phe25, seem essential for PknG binding and allow specificity for Thr21 phosphorylation. On the other hand, phosphorylated residues in PknB bind Arg26 in GarA and regulate its specificity for Thr22. We also provide a detailed analysis of the free energy profile for the phospho-transfer reaction and show why PknG has a constitutively active conformation not requiring priming phosphorylation in contrast to PknB. Our results provide new insights into these two key enzymes relevant for Mtb and the mechanisms of serine/threonine phosphorylation in bacteria.

Interfacial Peptides as Affinity Modulating Agents of Protein-Protein Interactions

The identification of disease-related protein-protein interactions (PPIs) creates objective conditions for their pharmacological modulation. The contact area (interfaces) of the vast majority of PPIs has some features, such as geometrical and biochemical complementarities, "hot spots", as well as an extremely low mutation rate that give us key knowledge to influence these PPIs. Exogenous regulation of PPIs is aimed at both inhibiting the assembly and/or destabilization of protein complexes. Often, the design of such modulators is associated with some specific problems in targeted delivery, cell penetration and proteolytic stability, as well as selective binding to cellular targets. Recent progress in interfacial peptide design has been achieved in solving all these difficulties and has provided a good efficiency in preclinical models (in vitro and in vivo). The most promising peptide-containing therapeutic formulations are under investigation in clinical trials. In this review, we update the current state-of-the-art in the field of interfacial peptides as potent modulators of a number of disease-related PPIs. Over the past years, the scientific interest has been focused on following clinically significant heterodimeric PPIs MDM2/p53, PD-1/PD-L1, HIF/HIF, NRF2/KEAP1, RbAp48/MTA1, HSP90/CDC37, BIRC5/CRM1, BIRC5/XIAP, YAP/TAZ-TEAD, TWEAK/FN14, Bcl-2/Bax, YY1/AKT, CD40/CD40L and MINT2/APP.

Crystal polymorphism in fragment-based lead discovery of ligands of the catalytic domain of UGGT, the glycoprotein folding quality control checkpoint

None of the current data processing pipelines for X-ray crystallography fragment-based lead discovery (FBLD) consults all the information available when deciding on the lattice and symmetry (i.e., the polymorph) of each soaked crystal. Often, X-ray crystallography FBLD pipelines either choose the polymorph based on cell volume and point-group symmetry of the X-ray diffraction data or leave polymorph attribution to manual intervention on the part of the user. Thus, when the FBLD crystals belong to more than one crystal polymorph, the discovery pipeline can be plagued by space group ambiguity, especially if the polymorphs at hand are variations of the same lattice and, therefore, difficult to tell apart from their morphology and/or their apparent crystal lattices and point groups. In the course of a fragment-based lead discovery effort aimed at finding ligands of the catalytic domain of UDP-glucose glycoprotein glucosyltransferase (UGGT), we encountered a mixture of trigonal crystals and pseudotrigonal triclinic crystals-with the two lattices closely related. In order to resolve that polymorphism ambiguity, we have written and described here a series of Unix shell scripts called CoALLA (crystal polymorph and ligand likelihood-based assignment). The CoALLA scripts are written in Unix shell and use autoPROC for data processing, CCP4-Dimple/REFMAC5 and BUSTER for refinement, and RHOFIT for ligand docking. The choice of the polymorph is effected by carrying out (in each of the known polymorphs) the tasks of diffraction data indexing, integration, scaling, and structural refinement. The most likely polymorph is then chosen as the one with the best structure refinement R_free statistic. The CoALLA scripts further implement a likelihood-based ligand assignment strategy, starting with macromolecular refinement and automated water addition, followed by removal of the water molecules that appear to be fitting ligand density, and a final round of refinement after random perturbation of the refined macromolecular model, in order to obtain unbiased difference density maps for automated ligand placement. We illustrate the use of CoALLA to discriminate between H3 and P1 crystals used for an FBLD effort to find fragments binding to the catalytic domain of Chaetomium thermophilum UGGT.

In Silico Molecular Docking and Molecular Dynamic Simulation Analysis of Phytochemicals From Indian Foods as Potential Inhibitors of SARS-CoV-2 RdRp and 3CLpro

With the current pandemic of the novel coronavirus disease 2019 (COVID-19) in hand, researchers around the globe are dexterously working to find the best suitable drug candidates and overcome vaccination-related challenges, to achieve efficient control over the second surge of COVID-19. The medical consultants time and again have been reiterating the need to abide by the precautionary steps to prevent the spread of the coronavirus by maintaining social distancing when outside, sanitizing hands regularly, and wearing masks and gloves. They also suggest taking a good and hygienic meal so as to boost immunity. Indians have an inborn nature of using natural spices, food, and medicines in their daily lives. Indian researchers have paid heed to deploy compounds from natural sources to explore potential antiviral agents against COVID-19 as the chances of acquiring side effects are perceived as less, and the efficacy of phytochemicals from medicinal plants is sometimes greater when compared to their synthetic counterparts. In the present study, we performed an in silico molecular docking and molecular dynamic simulation analysis of screened phytochemicals from a comprehensive list of Ayurvedic herbs/functional foods that are present in natural food products against key receptor proteins of severe acute respiratory syndrome coronavirus 2. We found that Aegle marmelos, Vetiveria zizanoides, Moringaolifera, and Punica granatum have antiviral potential to prevent coronavirus infection in the populace.

Nanopore Stochastic Sensing Based on Non-covalent Interactions

A variety of species could be detected by using nanopores engineered with various recognition sites based upon non-covalent interactions, including electrostatic, aromatic, and hydrophobic interactions. The existence of these engineered non-covalent bonding sites was supported by the single-channel recording technique. The advantage of the non-covalent interaction-based sensing strategy was that the recognition site of the engineered nanopore was not specific for a particular molecule but instead selective for a class of species (e.g., cationic, anionic, aromatic, and hydrophobic). Since different species produce current modulations with quite different signatures represented by amplitude, residence time, and even characteristic voltage-dependence curve, the non-covalent interaction-based nanopore sensor could not only differentiate individual molecules in the same category but also enable differentiation between species with similar structures or molecular weights. Hence, our developed non-covalent interaction-based nanopore sensing strategy may find useful application in the detection of molecules of medical and/or environmental importance.

AromTool: predicting aromatic stacking energy using an atomic neural network model

Aromatic stacking exists widely and plays important roles in protein-ligand interactions. Computational tools to automatically analyze the geometry and accurately calculate the energy of stacking interactions are desired for structure-based drug design. Herein, we employed a Behler-Parrinello neural network (BPNN) to build predictive models for aromatic stacking interactions and further integrated it into an open-source Python package named AromTool for benzene-containing aromatic stacking analysis. Based on extensive testing, AromTool presents desirable precision in comparison to DFT calculations and excellent efficiency for high-throughput aromatic stacking analysis of protein-ligand complexes.