Vocal repertoire of Microhyla nilphamariensis from Delhi and comparison with closely related M. ornata populations from the western coast of India and Sri Lanka.

Advertisement calls in frogs have evolved to be species-specific signals of recognition and are therefore considered an essential component of integrative taxonomic approaches to identify species and delineate their distribution range. The species rich genus Microhyla is a particularly challenging group for species identification, discovery and conservation management due to the small size, conserved morphology and wide distribution of its members, necessitating the need for a thorough description of their vocalization. In this study, we provide quantitative description of the vocal behaviour of Microhyla nilphamariensis, a widely distributed south Asian species, from Delhi, India, based on call recordings of 18 individuals and assessment of 21 call properties. Based on the properties measured acrossed 360 calls, we find that a typical advertisement call of M. nilphamariensis lasts for 393.5 ±  57.5 ms, has 17 pulses on average and produce pulses at rate of 39 pulses/s. The overall call dominant frequency was found to be 2.8 KHz and the call spectrum consisted of two dominant frequency peaks centered at 1.6 KHz and 3.6 KHz, ranging between 1.5-4.1 KHz. Apart from its typical advertisement call, our study also reveals the presence of three 'rare' call types, previously unreported in this species. We describe variability in call properties and discuss their relation to body size and temperature. We found that overall dominant frequency 1 (spectral property) was found to be correlated with body size, while first pulse period (temporal property) was found to be correlated with temperature. Further, we compare the vocal repertoire of M. nilphamariensis with that of the congener Microhyla ornata from the western coast of India and Sri Lanka and also compare the call properties of these two populations of M. ornata to investigate intra-specific call variation. We find statistically significant differentiation in their acoustic repertoire in both cases. Based on 18 call properties (out of 20), individuals of each locality clearly segregate on PCA factor plane forming separate groups. Discriminant function analysis (DFA) using PCA factors shows 100% classification success with individuals of each locality getting classified to a discrete group. This confirms significant acoustic differentiation between these species as well as between geographically distant conspecifics. The data generated in this study will be useful for comparative bioacoustic analysis of Microhyla species and can be utilized to monitor populations and devise conservation management plan for threatened species in this group.

Organocatalytic enantioselective desymmetrization of enal-tethered cyclohexane-1,3-diones.

Organocatalytic asymmetric desymmetrization of prochiral cyclohexane-1,3-diones has been demonstrated through the merging of iminium and enamine activation. The tandem annulation reaction proceeds through a sequential oxa-Michael addition/intramolecular aldol reaction/[1,3]-amino oxetane rearrangement pathway. Mechanistic study using an 18O-water experiment suggests oxetane rearrangement instead of direct dehydration. The formation of other competing Rauhut-Currier products via alkoxy-elimination was not observed.

GLA Mutations Suppress Autophagy and Stimulate Lysosome Generation in Fabry Disease.

Fabry disease (FD) is an X-linked recessive inheritance lysosomal storage disorder caused by pathogenic mutations in the GLA gene leading to a deficiency of the enzyme alpha-galactosidase A (α-Gal A). Multiple organ systems are implicated in FD, most notably the kidney, heart, and central nervous system. In our previous study, we identified four GLA mutations from four independent Fabry disease families with kidney disease or neuropathic pain: c.119C>A (p.P40H), c.280T>C (C94R), c.680G>C (p.R227P) and c.801+1G>A (p.L268fsX3). To reveal the molecular mechanism underlying the predisposition to Fabry disease caused by GLA mutations, we analyzed the effects of these four GLA mutations on the protein structure of α-galactosidase A using bioinformatics methods. The results showed that these mutations have a significant impact on the internal dynamics and structures of GLA, and all these altered amino acids are close to the enzyme activity center and lead to significantly reduced enzyme activity. Furthermore, these mutations led to the accumulation of autophagosomes and impairment of autophagy in the cells, which may in turn negatively regulate autophagy by slightly increasing the phosphorylation of mTOR. Moreover, the overexpression of these GLA mutants promoted the expression of lysosome-associated membrane protein 2 (LAMP2), resulting in an increased number of lysosomes. Our study reveals the pathogenesis of these four GLA mutations in FD and provides a scientific foundation for accurate diagnosis and precise medical intervention for FD.

Kyasanur Forest disease virus NS3 helicase: Insights into structure, activity, and inhibitors.

Kyasanur Forest disease virus (KFDV), a tick-borne flavivirus prevalent in India, presents a serious threat to human health. KFDV NS3 helicase (NS3hel) is considered a potential drug target due to its involvement in the viral replication complex. Here, we resolved the crystal structures of KFDV NS3hel apo and its complex with three phosphate molecules, which indicates a conformational switch during ATP hydrolysis. Our data revealed that KFDV NS3hel has a higher binding affinity for dsRNA, and its intrinsic ATPase activity was enhanced by dsRNA while being inhibited by DNA. Through mutagenesis analysis, several residues within motifs I, Ia, III, V, and VI were identified to be crucial for NS3hel ATPase activity. Notably, the M419A mutation drastically reduced NS3hel ATPase activity. We propose that the methionine-aromatic interaction between residues M419 and W294, located on the surface of the RNA-binding channel, could be a target for the design of efficient inhibitor probes. Moreover, epigallocatechin gallate (EGCG), a tea-derived polyphenol, strongly inhibited NS3hel ATPase activity with an IC50 value of 0.8 µM. Our computational docking data show that EGCG binds at the predicted druggable hotspots of NS3hel. Overall, these findings contribute to the development and design of more effective and specific inhibitors.

Omicron variant (B.1.1.529) challenge the integrity of blood brain barrier: Evidence from protein structural analysis.

Studies on nonhuman primates, wild-type and transgenic mice have shown the presence of SARS-CoV-2 RNA components in the brains. Despite the Blood-Brain Barrier (BBB) provides protection there are less evidences on how the SARS-CoV-2 crosses the BBB. Given that there is an increase of Omicron reinfection rates, transmissibility rate and involvement to cause neurological dysfunctions, we hypothesized to investigate how the Omicron variant (B.1.1.529) binds structurally to key BBB-maintaining proteins and thus can possibly challenge the integrity and transportation to the brain. By using molecular dynamics simulation approaches we examined the interaction of Omicron variant (B.1.1.529) with different structural and transporter proteins located at the BBB. Our results show that in Zona Ocludin 1-RBD complex, we observe a distinct pattern. Omicron demonstrates a docking score of -88.9 ± 6.8 kcal/mol and six interactions, while the wild type (WT) presents a higher score of -94.0 ± 2.3 kcal/mol, forming eight interactions. Comparing affinities, the WT-RBD displays a stronger preference for Claudin-5, boasting a docking score of -110.2 ± 3.0 and nine interactions, versus Omicron-RBD's slightly reduced engagement, with a docking score of -105.6 ± 0.2 and seven interactions. Interestingly, the Omicron variant exhibits heightened stability in interactions with Glucose Transporter and ABC transporters, registering docking scores of -110.6 ± 1.9 and -112.0 ± 3.6 kcal/mol, respectively. This surpasses the WT's respective scores of -95.2 ± 2.2 and -104.0 ± 6.2 kcal/mol, reflecting a unique interaction profile. Rigorous molecular dynamics simulations validate our findings. Our study emphasizes the Omicron variant's increased affinity towards transporter proteins, illuminating potential implications for BBB integrity and brain transportation. While these insights offer a valuable framework, comprehensive experimental validation is indispensable for a comprehensive understanding.

Antifungal and Antiproliferative Activity of Pistagremic Acid and Flavonoids Extracted from the Galls of Pistacia chinensis subsp. integerrima.

Pistacia chinensis subsp. integerrima (J.L. Stewart) Rech. f. is a plant known for its therapeutic applications in traditional medicine, which are related to its antimicrobial, anticancer, antioxidant, anti-inflammatory, analgesic, antidiarrheal, and muscle relaxant properties. The galls of P. chinensis are rich in triterpenes and flavonoids, and we here report the extraction of pistagremic acid (1), apigenin (2) and sakuranetin (3) from this source. The isolated compounds were tested against Aspergillus flavus, Candida albicans, Candida glabrata, Fusarium solani, Microsporum canis and Trichoderma longibrachiatum. The results highlighted the antimicrobial activity of flavonoids 2 and 3, suggesting that this class of molecules may be responsible for the effect related to the traditional use. On the other hand, when the compounds and the extract were tested for their antiproliferative activity on a panel of 4 human cancer cell lines, the triterpene pistagremic acid (1) showed a higher potential, thus demonstrating a different bioactivity profile. Structure-based docking and molecular dynamics simulations were used to help the interpretation of experimental results. Taken together, the here reported findings pave the way for the rationalization of the use of P. chinensis extracts, highlighting the contributions of the different components of galls to the observed bioactivity.

Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach.

Leishmania tropica is a vector-borne parasitic protozoa that is the leading cause of leishmaniasis throughout the global tropics and subtropics. L. tropica is a multidrug-resistant parasite with a diverse set of serological, biochemical, and genomic features. There are currently no particular vaccines available to combat leishmaniasis. The present study prioritized potential vaccine candidate proteins of L. tropica using subtractive proteomics and vaccinomics approaches. These vaccine candidate proteins were downstream analyzed to predict B- and T-cell epitopes based on high antigenicity, non-allergenic, and non-toxic characteristics. The top-ranked overlapping MHC-I, MHC-II, and linear B-cell epitopes were prioritized for model vaccine designing. The lead epitopes were linked together by suitable linker sequences to design multi-epitope constructs. Immunogenic adjuvant sequences were incorporated at the N-terminus of the model vaccine constructs to enhance their immunological potential. Among different combinations of constructs, four vaccine designs were selected based on their physicochemical and immunological features. The tertiary structure models of the designed vaccine constructs were predicted and verified. The molecular docking and molecular dynamic (MD) simulation analyses indicated that the vaccine design V1 demonstrated robust and stable molecular interactions with toll-like receptor 4 (TLR4). The top-ranked vaccine construct model-IV demonstrated significant expressive capability in the E. coli expression system during in-silico restriction cloning analysis. The results of the present study are intriguing; nevertheless, experimental bioassays are required to validate the efficacy of the predicted model chimeric vaccine.

Designing and Exploration of the Biological Potentials of Novel Centrosymmetric Heteroleptic Copper(II) Carboxylates.

Copper(II) complexes with a general formula [Cu2(3,4-F2C6H3CH2COO)4(L)2], where L = 2-methylpyridine (1) and 3-methylpyridine (2), are reported here. The FTIR spectra of the complexes confirmed the bridging bidentate coordination mode of the carboxylate ligand. The low (475 and 449 cm-1) and strong (727 & 725 cm-1) intensity bands in the FTIR spectra, due to Cu-N stretches and pyridyl ring vibrations, confirmed coordination of the 2-/3-methyl pyridine co-ligands in complexes 1 and 2, respectively. A binuclear paddlewheel structural arrangement with a square pyramidal geometry was confirmed for copper atoms in the complexes via single-crystal X-ray analysis. The DPPH, •OH radical, and α-amylase enzyme inhibition assays showed higher activities for the complexes than for the free ligand acid. The binding constant (Kb = 1.32 × 105 for 1 and 5.33 × 105 for 2) calculated via UV-VIS absorption measurements and docking scores (-6.59 for 1 and -7.43 for 2) calculated via molecular docking showed higher SS-DNA binding potential for 2 compared to 1. Viscosity measurement also reflected higher DNA binding ability for 2 than 1. Both complexes 1 and 2 (docking scores of -7.43 and -6.95, respectively) were found to be more active inhibitors than the free ligand acid (docking score of -5.5159) against the target α-amylase protein. This in silico study has shown that the herein reported compounds follow the rules of drug-likeness and exhibit good potential for bioavailability.

Defects mediated weak ferromagnetism in Zn1-yCyO (0.00 ≤ y ≤ 0.10) nanorods semiconductors for spintronics applications.

A series of carbon-doped ZnO [Zn1-yCyO (0.00 ≤ y ≤ 0.10)] nanorods were synthesized using a cost-effective low-temperature (85 °C) dip coating technique. X-ray diffractometer scans of the samples revealed the hexagonal structure of the C-doped ZnO samples, except for y = 0.10. XRD analysis confirmed a decrease in the unit cell volume after doping C into the ZnO matrix, likely due to the incorporation of carbon at oxygen sites (CO defects) resulting from ionic size differences. The morphological analysis confirmed the presence of hexagonal-shaped nanorods. X-ray photoelectron spectroscopy identified C-Zn-C bonding, i.e., CO defects, Zn-O-C bond formation, O-C-O bonding, oxygen vacancies, and sp2-bonded carbon in the C-doped ZnO structure with different compositions. We analyzed the deconvoluted PL visible broadband emission through fitted Gaussian peaks to estimate various defects for electron transition within the bandgap. Raman spectroscopy confirmed the vibrational modes of each constituent. We observed a stronger room-temperature ferromagnetic nature in the y = 0.02 composition with a magnetization of 0.0018 emu/cc, corresponding to the highest CO defects concentration and the lowest measured bandgap (3.00 eV) compared to other samples. Partial density of states analysis demonstrated that magnetism from carbon is dominant due to its p-orbitals. We anticipate that if carbon substitutes oxygen sites in the ZnO structure, the C-2p orbitals become localized and create two holes at each site, leading to enhanced p-p type interactions and strong spin interactions between carbon atoms and carriers. This phenomenon can stabilize the long-range order of room-temperature ferromagnetism properties for spintronic applications.

Identification of Drug Targets and Their Inhibitors in Yersinia pestis Strain 91001 through Subtractive Genomics, Machine Learning, and MD Simulation Approaches.

Yersinia pestis, the causative agent of plague, is a Gram-negative bacterium. If the plague is not properly treated it can cause rapid death of the host. Bubonic, pneumonic, and septicemic are the three types of plague described. Bubonic plague can progress to septicemic plague, if not diagnosed and treated on time. The mortality rate of pneumonic and septicemic plague is quite high. The symptom-defining disease is the bubo, which is a painful lymph node swelling. Almost 50% of bubonic plague leads to sepsis and death if not treated immediately with antibiotics. The host immune response is slow as compared to other bacterial infections. Clinical isolates of Yersinia pestis revealed resistance to many antibiotics such as tetracycline, spectinomycin, kanamycin, streptomycin, minocycline, chloramphenicol, and sulfonamides. Drug discovery is a time-consuming process. It always takes ten to fifteen years to bring a single drug to the market. In this regard, in silico subtractive proteomics is an accurate, rapid, and cost-effective approach for the discovery of drug targets. An ideal drug target must be essential to the pathogen's survival and must be absent in the host. Machine learning approaches are more accurate as compared to traditional virtual screening. In this study, k-nearest neighbor (kNN) and support vector machine (SVM) were used to predict the active hits against the beta-ketoacyl-ACP synthase III drug target predicted by the subtractive genomics approach. Among the 1012 compounds of the South African Natural Products database, 11 hits were predicted as active. Further, the active hits were docked against the active site of beta-ketoacyl-ACP synthase III. Out of the total 11 active hits, the 3 lowest docking score hits that showed strong interaction with the drug target were shortlisted along with the standard drug and were simulated for 100 ns. The MD simulation revealed that all the shortlisted compounds display stable behavior and the compounds formed stable complexes with the drug target. These compounds may have the potential to inhibit the beta-ketoacyl-ACP synthase III drug target and can help to combat Yersinia pestis-related infections. The dataset and the source codes are freely available on GitHub.

Structural and dynamics insights into the GBA variants associated with Parkinson's disease.

The GBA1 gene encodes for the lysosomal enzyme glucocerebrosidase (GCase), which maintains glycosphingolipid homeostasis and regulates the autophagy process. Genomic variants of GBA1 are associated with Goucher disease; however, several heterozygous variants of GBA (E326K, T369M, N370S, L444P) are frequent high-risk factors for Parkinson's disease (PD). The underlying mechanism of these variants has been revealed through functional and patient-centered research, but the structural and dynamical aspects of these variants have not yet been thoroughly investigated. In the current study, we used a thorough computational method to pinpoint the structural changes that GBA underwent because of genomic variants and drug binding mechanisms. According to our findings, PD-linked nsSNP variants of GBA showed structural variation and abnormal dynamics when compared to wild-typ. The docking analysis demonstrated that the mutants E326K, N370S, and L444P have higher binding affinities for Ambroxol. Root means square deviation (RMSD), Root mean square fluctuation analysis (RMSF), and MM-GBSA analysis confirmed that the Ambroxol are more stable in the binding site of N370S and L444P, and that their binding affinities are stronger as compared to the wild-type and T369M variants of GBA. The evaluation of hydrogen bonds and the calculation of the free binding energy provided additional evidence in favor of this conclusion. When docked with Ambroxol, GBA demonstrated an increase in binding affinity and catalytic activity. Understanding the therapeutic efficacy and potential against the aforementioned changes in the GBA will be beneficial in order to use more efficient methods for developing novel drugs.Communicated by Ramaswamy H. Sarma.

Computational formulation of a multiepitope vaccine unveils an exceptional prophylactic candidate against Merkel cell polyomavirus.

Merkel cell carcinoma (MCC) is a rare neuroendocrine skin malignancy caused by human Merkel cell polyomavirus (MCV), leading to the most aggressive skin cancer in humans. MCV has been identified in approximately 43%-100% of MCC cases, contributing to the highly aggressive nature of primary cutaneous carcinoma and leading to a notable mortality rate. Currently, no existing vaccines or drug candidates have shown efficacy in addressing the ailment caused by this specific pathogen. Therefore, this study aimed to design a novel multiepitope vaccine candidate against the virus using integrated immunoinformatics and vaccinomics approaches. Initially, the highest antigenic, immunogenic, and non-allergenic epitopes of cytotoxic T lymphocytes, helper T lymphocytes, and linear B lymphocytes corresponding to the virus whole protein sequences were identified and retrieved for vaccine construction. Subsequently, the selected epitopes were linked with appropriate linkers and added an adjuvant in front of the construct to enhance the immunogenicity of the vaccine candidates. Additionally, molecular docking and dynamics simulations identified strong and stable binding interactions between vaccine candidates and human Toll-like receptor 4. Furthermore, computer-aided immune simulation found the real-life-like immune response of vaccine candidates upon administration to the human body. Finally, codon optimization was conducted on the vaccine candidates to facilitate the in silico cloning of the vaccine into the pET28+(a) cloning vector. In conclusion, the vaccine candidate developed in this study is anticipated to augment the immune response in humans and effectively combat the virus. Nevertheless, it is imperative to conduct in vitro and in vivo assays to evaluate the efficacy of these vaccine candidates thoroughly. These evaluations will provide critical insights into the vaccine's effectiveness and potential for further development.

A comprehensive protein interaction map and druggability investigation prioritized dengue virus NS1 protein as promising therapeutic candidate.

Dengue Virus (DENV) is a serious threat to human life worldwide and is one of the most dangerous vector-borne diseases, causing thousands of deaths annually. We constructed a comprehensive PPI map of DENV with its host Homo sapiens and performed various bioinformatics analyses. We found 1195 interactions between 858 human and 10 DENV proteins. Pathway enrichment analysis was performed on the two sets of gene products, and the top 5 human proteins with the maximum number of interactions with dengue viral proteins revealed noticeable results. The non-structural protein NS1 in DENV had the maximum number of interactions with the host protein, followed by NS5 and NS3. Among the human proteins, HBA1 and UBE2I were associated with 7 viral proteins, and 3 human proteins (CSNK2A1, RRP12, and HSP90AB1) were found to interact with 6 viral proteins. Pharmacophore-based virtual screening of millions of compounds in the public databases was performed to identify potential DENV-NS1 inhibitors. The lead compounds were selected based on RMSD values, docking scores, and strong binding affinities. The top ten hit compounds were subjected to ADME profiling which identified compounds C2 (MolPort-044-180-163) and C6 (MolPort-001-742-737) as lead inhibitors against DENV-NS1. Molecular dynamics trajectory analysis and intermolecular interactions between NS1 and the ligands displayed the molecular stability of the complexes in the cellular environment. The in-silico approaches used in this study could pave the way for the development of potential specie-specific drugs and help in eliminating deadly viral infections. Therefore, experimental and clinical assays are required to validate the results of this study.

Discovery of Terpenes as Novel HCV NS5B Polymerase Inhibitors via Molecular Docking.

Hepatitis C virus (HCV) is a dangerous virus that is responsible for a large number of infections and deaths worldwide. In the treatment of HCV, it is important that the drugs are effective and do not have additional hepatotoxic effects. The aim of this study was to test the in silico activity of 1893 terpenes against the HCV NS5B polymerase (PDB-ID: 3FQK). Two drugs, sofosbuvir and dasabuvir, were used as controls. The GOLD software (CCDC) and InstaDock were used for docking. By using the results obtained from PLP.Fitness (GOLD), pKi, and binding free energy (InstaDock), nine terpenes were finally selected based on their scores. The drug-likeness properties were calculated using Lipinski's rule of five. The ADMET values were studied using SwissADME and pkCSM servers. Ultimately, it was shown that nine terpenes have better docking results than sofosbuvir and dasabuvir. These were gniditrin, mulberrofuran G, cochlearine A, ingenol dibenzoate, mulberrofuran G, isogemichalcone C, pawhuskin B, 3-cinnamyl-4-oxoretinoic acid, DTXSID501019279, and mezerein. Each docked complex was submitted to 150 ns-long molecular dynamics simulations to ascertain the binding stability. The results show that mulberrofuran G, cochlearine A, and both stereoisomers of pawhuskin B form very stable interactions with the active site region where the reaction product should form and are, therefore, good candidates for use as effective competitive inhibitors. The other compounds identified in the docking screen either afford extremely weak (or even hardly any) binding (such as ingenol dibenzoate, gniditrin, and mezerein) or must first undergo preliminary movements in the active site before attaining their stable binding conformations, in a process which may take from 60 to 80 ns (for DTXSID501019279, 3-cinnamyl-4-oxoretinoic acid or isogemichalcone C).

Structural mechanism of dsDNA recognition by the hMNDA HIN domain: New insights into the DNA-binding model of a PYHIN protein.

The hematopoietic interferon-inducible nuclear (HIN) domain of the PYHIN family of proteins recognizes double-stranded DNA (dsDNA) through different dsDNA-binding modes. These modes apparently confer different roles upon these proteins in the regulation of innate immune responses, gene transcription, and apoptosis. Myeloid cell nuclear differentiation antigen (MNDA), a member of the human PYHIN family, binds DNA and regulates gene transcription in monocytes. However, the mechanism of DNA recognition and DNA-binding modes of human MNDA (hMNDA) remain unclear. Here, we determined the crystal structure of the hMNDA-HIN domain in complex with dsDNA at 2.4 Å resolution, and reveal that hMNDA-HIN binds to dsDNA in a sequence-independent manner. Structure and mutation studies indicated that hMNDA-HIN binds to dsDNA through a unique mode, involving two dsDNA-binding interfaces. Interface I exhibits an AIM2-like dsDNA-binding mode, and interface II has a previously unreported mode of dsDNA-binding. These results provide new insights into the DNA-binding modes of this PYHIN protein.

Comparative binding analysis of WGX50 and Alpha-M with APP family proteins APLP1 and APLP2 using structural-dynamics and free energy calculation approaches.

A.D. is a common disease among other neurodegenerative disorders primarily developing due to amyloid-ß (Aß) neurotoxicity derived from the amyloid-ß protein precursor (AßPP). The amyloid precursor-like proteins 1 and 2 (APP1 and APLP2) biochemically behave similarly in many aspects to AßPP. We, therefore, proposed to test WGX-50 and Alpha-M for their interaction mechanism with APLP1 and APLP2 because both these drug candidate compounds previously showed inhibition of Aß aggregation. We employed a comparative atomic investigation on Alpha-M and WGX-50 in complex with novel targets, i.e., APLP1 and APLP2, using biophysical and molecular simulation methods. The docking score was -6.83 kcal mol-1 for Alpha-M-APLP1, -8.41 kcal mol-1 for WGX-50-APLP1, -7.02 kcal mol-1 for Alpha-M-APLP2 and -8.25 kcal mol-1 for the WGX-50-APLP2 complex. Our results also elaborate that in the case of their interaction with both APLP1 and APLP2, the WGX-50 complex exhibits better stability than the APLP1/2-Alpha-M complexes during simulation. Furthermore, WGX50 in both APLP1 and APLP2 stabilized the internal flexibility upon binding in contrast to the Alpha-M complexes. The data showed that the BFE for Alpha-M-APLP1 was calculated to be -27.38 ± 0.93 kcal mol-1, for WGX-50-APLP1 -39.65 ± 0.95 kcal mol-1, for Alpha-M-APLP2 -24.80 ± 0.63 kcal mol-1 while for WGX-50-APLP2 the BFE was -57.16 ± 1.03 kcal mol-1 respectively. These results highlight that APLP2-WGX50 has greater binding energies in all four systems. PCA and FEL analysis further revealed variations in the dynamic behavior of these complexes. Overall, our findings demonstrate that WGX50 potentially acts as a more potent inhibitor for APLP1 and APLP2 than Alpha-M and thus shows the diverse pharmacological potential of WGX50. Due to its stable binding interaction, WGX50 might be a suitable candidate drug compound for targeting these precursors under pathological conditions.

Identification of novel peptide inhibitors for oncogenic KRAS G12D as therapeutic options using mutagenesis-based remodeling and MD simulations.

The Kirsten rat sarcoma 2 viral oncogene homolog (KRAS) serves as a molecular switch, cycling between guanosine triphosphate (GTP)-bound and inactive guanosine diphosphate (GDP)-bound states. KRAS modulates numerous signal transduction pathways including the conventional RAF-MEK-ERK pathway. Mutations in the RAS genes have been linked to the formation of malignant tumors. Human malignancies typically show mutations in the Ras gene including HRAS, KRAS, and NRAS. Among all the mutations in exon 12 and exon 13 of the KRAS gene, the G12D mutation is more prevalent in pancreatic and lung cancer and accounts for around 41% of all G12 mutations, making them potential anticancer therapeutic targets. The present study is aimed at repurposing the peptide inhibitor KD2 of the KRAS G12D mutant. We employed an in-silico mutagenesis approach to design novel peptide inhibitors from the experimentally reported peptide inhibitor, and it was found that substitutions (N8W, N8I, and N8Y) might enhance the peptide's binding affinity toward the KRAS. Molecular dynamics simulations and binding energy calculations confirmed that the newly designed peptide inhibitors are stable and that their binding affinities are stronger as compared to the wild-type peptide. The detailed analysis revealed that newly designed peptides have the potential to inhibit KRAS/Raf interaction and the oncogenic signal of the KRAS G12D mutant. Our findings strongly suggest that these peptides should be tested and clinically validated to combat the oncogenic activity of KRAS.Communicated by Ramaswamy H. Sarma.

Inhibitor and Activator: Dual Role of Subsurface Sulfide Enables Selective and Efficient Electro-Oxidation of Methanol to Formate on CuS@CuO Core-Shell Nanosheet Arrays.

Selective electro-oxidation of aliphatic alcohols into value-added carboxylates at lower potentials than that of the oxygen evolution reaction (OER) is an environmentally and economically desirable anode reaction for clean energy storage and conversion technologies. However, it is challenging to achieve both high selectivity and high activity of the catalysts for the electro-oxidation of alcohols, such as the methanol oxidation reaction (MOR). Herein, a monolithic CuS@CuO/copper-foam electrode for the MOR with superior catalytic activity and almost 100% selectivity for formate is reported. In the core-shell CuS@CuO nanosheet arrays, the surface CuO directly catalyzes MOR, while the subsurface sulfide not only serves as an inhibitor to attenuate the oxidative power of the surface CuO to achieve selective oxidation of methanol to formate and prevent over-oxidation of formate to CO2 but also serves as an activator to form more surface O defects as active sites and enhances the methanol adsorption and charge transfer to achieve superior catalytic activity. CuS@CuO/copper-foam electrodes can be prepared on a large scale by electro-oxidation of copper-foam at ambient conditions and can be readily utilized in clean energy technologies.

WS2 and WS2-ZnO Chemiresistive Gas Sensors: The Role of Analyte Charge Asymmetry and Molecular Size.

We investigate the interaction of various analytes (toluene, acetone, ethanol, and water) possessing different structures, bonding, and molecular sizes with a laser-exfoliated WS2 sensing material in a chemiresistive sensor. The sensor showed a clear response to all analytes, which was significantly enhanced by modifying the WS2 surface. This was achieved by creating WS2-ZnO heterojunctions via the deposition of ZnO nanoparticles on the WS2 surface with a high-throughput, atmospheric-pressure spatial atomic layer deposition system. Water and ethanol produced a much higher response compared to acetone and toluene for both the WS2 and WS2-ZnO sensing mediums. We resolved that the charge-asymmetry points in analyte molecules play a key role in determining the sensor response. High charge-asymmetry points correspond to highly polar bonds (HPBs) in a neutral molecule that have a high probability of interaction with the sensing medium. Our results indicate that the polarity of the HPBs primarily dictates the interaction between the analyte and sensing medium and consequently controls the response of the sensor. Moreover, the size of the analyte molecule was found to affect the sensing response; if two molecules have the same HPBs and are exposed to the same sensing medium, the smaller molecule is likely to produce a higher and faster response. Our study provides a comprehensive picture of analyte-sensor interactions that can help in advancing semiconductor gas sensors, including those based on two-dimensional materials.

Identification of novel inhibitors for SARS-CoV-2 as therapeutic options using machine learning-based virtual screening, molecular docking and MD simulation.

The new coronavirus SARS-COV-2, which emerged in late 2019 from Wuhan city of China was regarded as causing agent of the COVID-19 pandemic. The primary protease which is also known by various synonymous i.e., main protease, 3-Chymotrypsin-like protease (3CLPRO) has a vital role in the replication of the virus, which can be used as a potential drug target. The current study aimed to identify novel phytochemical therapeutics for 3CLPRO by machine learning-based virtual screening. A total of 4,000 phytochemicals were collected from deep literature surveys and various other sources. The 2D structures of these phytochemicals were retrieved from the PubChem database, and with the use of a molecular operating environment, 2D descriptors were calculated. Machine learning-based virtual screening was performed to predict the active phytochemicals against the SARS-CoV-2 3CLPRO. Random forest achieved 98% accuracy on the train and test set among the different machine learning algorithms. Random forest model was used to screen 4,000 phytochemicals which leads to the identification of 26 inhibitors against the 3CLPRO. These hits were then docked into the active site of 3CLPRO. Based on docking scores and protein-ligand interactions, MD simulations have been performed using 100 ns for the top 5 novel inhibitors, ivermectin, and the APO state of 3CLPRO. The post-dynamic analysis i.e,. Root means square deviation (RMSD), Root mean square fluctuation analysis (RMSF), and MM-GBSA analysis reveal that our newly identified phytochemicals form significant interactions in the binding pocket of 3CLPRO and form stable complexes, indicating that these phytochemicals could be used as potential antagonists for SARS-COV-2.