Curcumin can interact with a variety of molecules implicated in a wide range of disorders. It can also hinder dengue virus’s (DENV’s) ability to infect cells. This work used computational analysis to identify and forecast the most potent curcumin analogs against the DENV NS2B/NS3 protease. In this study, curcumin-like compounds were screened using a rational in-silico study, with the least similarity score, docking analysis, and then additional screening for suitable pharmacokinetic properties. According to the findings, DB11672 has been identified as the primary inhibitor of DENV NS2B/NS3 protease. It is recommended that additional research be done on this antiviral property of the lead compound as a part of the process of finding and developing a new drug against DENV.

The capability and potential of C24, ScC23, TiC23, and NiC23 nanocages as novel candidates for delivery and sensor property of the Prothionamide (PA) drug in a biological system are investigated with density functional theory. The adsorption energy and thermodynamic parameters of [email protected]24, [email protected]23, [email protected]23, and [email protected]23 complexes in the absences and presence of static electrical field (SEF) (SEFz+0.01, SEFz+0.02, SEFz+0.03, and SEFz+0.04 a.u.) are calculated, and results indicated that the Eads, ΔH, and ΔG values for all studied complexes in gas media are negative and exothermic. In the presence of water solvent, the ΔΔG(sol) values of all drug and nanocage complexes are positive. The quantum descriptors, molecular electrostatic potential, the density of state, UV–visible spectrum, and dipole moment of all drug and nanocage complexes are determined and results are analyzed. The topological results of atom in molecule and the noncovalent interaction index display that the interaction of PA drug with C24 is electrostatic- and van der Waals-type. The computational results suggest that the ScC23, TiC23, and NiC23 nanocages can be used as good candidates for the delivery and sensor of the PA drug.

Lysosomal storage diseases (LSDs) consist of about 60 different monogenic disorders. Most of them occur due to protein misfolding. Only a few of those have been treated with molecular chaperones; the remaining either have limited treatment options or only management therapies. About 1860 single amino-acid substitutions (SAS) have been identified under LSDs. Merely, a handful of mutations have been studied experimentally. Availability of computational tools has made researchers turn toward genetic disorders to focus light on unexplored disorders and their mutations. Since all the LSDs are rare genetic disorders, not much research is carried out in this area. However, a mutational effect on protein function could be predicted, through bioinformatics tools. On that note, out of 1860 SAS, 58 predictions were neutral and 778 were predicted to be disease associated by all programs included in this study. The result of the prediction analysis of all mutations in each of the LSDs is curated into a database. This would make researchers know the deleterious nature of a mutation causing LSD. The database is available at http://lsddb.vit.ac.in:3000/.

Metastasis remains the reason for chemoresistance and high cancer mortality. It is hence a valuable predictive factor in cancer prognosis and drug sensitivity. Single-cell RNA sequencing (scRNA-seq) can reveal cellular heterogeneity in metastasis microenvironment and capture high-resolution signatures for improved cancer prediction. As a case study, an integrated analysis framework was designed for metastatic lung adenocarcinoma (LUAD) scRNA-seq profiles and we identified nine key prognostic genes (KPGs) that were trained and validated in 407 internal and external patient cohorts using machine learning and other methods. Correlation analysis revealed the strong association between KPGs signatures and several clinical characteristics such as gender, T-stage and N-stage. We incorporated these risk clinical variables into a KPGs nomogram model with superior accuracy for overall survival (OS) prediction. We also found that high risk group with high nomogram scores had poorer prognosis accompanied by a higher tumor mutation burden (TMB) and was more sensitive to chemotherapy and targeted agents, which was associated with the upregulation of DNA replication, ECM receptor interaction, P53 signaling pathway, spliceosome and proteasome pathway. Collectively, we proposed a simple and feasible strategy to mine single-cell resolution metastasis signatures from scRNA-seq data for improved cancer prognosis and drug sensitivity prediction, which will be a useful tool in risk gene discovery and targeted therapy in metastatic cancers.

Enoyl acyl carrier protein reductase (InhA) is a crucial enzyme for the biosynthesis of mycolic acids which are major compartments of the Mycobacterium tuberculosis (Mtb) cell wall. Direct inhibition of InhA without activation by drug-NADH adduct has clinical utility to overcome drug resistance. We aimed at the in silico identification of triclosan derivatives with the potential inhibitory effect of S94A-InhA as a clinically important mutant form. Caver Web 1.0 server was used to analyze the ligand transport through access tunnels. Two macrocyclic triclosan derivatives ( 4 and 6) could be identified with more energy-favorable transfer routes toward the enzyme active site. Molecular dynamics (MD) simulations (50 ns) of the best-scored compounds revealed the stability of enzyme structure upon binding to 4 and 6. Compound 4 could better retain enzyme stability upon target binding. Results of intermolecular H-bond analysis indicated that both complexes were mediated through hydrophobic contacts. Declined solvent accessible surface area (SASA) for the apo and bound enzyme states indicated non-destabilizing behavior and no structural relaxation. Electrostatic and van der Waals interactions between triclosan derivatives and their surroundings were used to acquire binding free energies through the linear interaction energy (LIE) method based on MD simulations (Average ΔGb, −7.83±0.72 kcal/mol and −8.89±0.64 kcal/mol). Both of the triclosan derivatives showed relatively stable energy variations and their steady accommodation inside enzyme active site could be confirmed during 50 ns. These results may be implicated in further structure-guided approaches against drug-resistant Mtb.

Due to their unique thermal and magnetic characteristics, gold-DNA nanoparticles have a wide spectrum of uses in pharmacology, drug delivery systems, treatment for cancer, and other disciplines. The current problem that analyzes the planar Poiseuille flow consists of gold nanoparticles with a typical fluid based on kerosene. The impact of mixed convection is considered in conjunction with the effects of radiative heat flow and thermo-diffusion (Soret). The numerical technique is utilized to solve the one-dimensional transformed equation for flow phenomena using the built-in MATLAB function bvp5c, with specific fixed values of relevant parameters adjusted. However, for different parameters that are either joint or unique, they are presented in both the surface and two-dimensional plots. It is observed that the particle concentration, as well as the resistive forces, favors greatly influencing the fluid velocity; nevertheless, raising the Peclet number also retards it owing to thermal conductivity retardation. The fluid concentration increases as the Reynolds number increases, but the shear rate decreases. Furthermore, in the conclusion section, the applications for the present research and future scope are discussed.

Hypoxia plays a critical role in melanoma development, but the characteristics of elemental oxygen in proteins and adaptation to hypoxia microenvironments are still unidentified. This study aims to explore oxygen contents (OCs) and differentially expressed proteins (DEP). Protein expression data were retrieved from Human Protein Atlas. The DEP in melanoma samples were compared with normal skin cells. We identified 1,969 DEP, and none of the genes coding these proteins were present on chromosome Y. The average oxygen content (AOC) was 7.24% higher in highly expressed proteins than lowly expressed proteins in melanoma and normal skin cells. The AOC is 2.36% higher in the up regulated proteins (URPs) in melanoma. The essential amino acids in the proteins in melanoma cells contributed to increased OC. Functional dissections of the high OCs in URP displayed that some of these proteins are associated with cytoskeleton, cyclins and cell cycle proteins. The URP interactions were generated using a STRING database. Majority of these URPs are associated in expression, exhibiting sufficient interactions with each other. This study provides useful information regarding protein expression in melanoma cells and the molecular mechanism of melanoma using stoichiogenomics.

During the past decade, deep eutectic solvents (DESs), emerging as green, versatile and adjustable alternatives to traditional solvents, have attracted intensive interests and immense research in various research fields. Especially DESs show quite a remarkable potential dissolving capability, due to their ability to donate as well as accept protons and electrons. A thorough and deep understanding of the microstructure, interactions and dissolving mechanism within DESs plays a key role in acquiring a task-specific DES. Quantum chemistry (QC) calculations provide structure-property-function relationship based on the molecular description and make up for the limitations of the current experimental techniques, showing promises for DESs screening and design. This paper summarizes the current research involving QC calculations and combined experiments, on investigating the structure, physicochemical properties and dissolving capability of DESs from the macroscopic and microcosmic perspective. This paper highlights and discusses the dissolving mechanism of various compounds in DESs, covering the recent successes in applying QC calculations to select the appropriate DESs as dissolving media. Furthermore, a brief analysis of perspectives and challenges for the future research in this field is presented. It is expected that this paper will inspire the future development of DESs from synthesis design to various designated applications.

The Hsp90 family has been extensively studied as a promising target against cancer and neurodegenerative diseases due to its crucial role in protein maturation and transport. However, the toxic and side effects such as cardiotoxicity and ocular toxicity caused by the pan-inhibition of Hsp90 cannot be ignored. The development of highly selective inhibitors toward Hsp90α over Grp94 has been proved to be a feasible approach to avoid these toxic and side effects. Therefore, to explore the different binding modes of inhibitors against Hsp90α and Grp94, hybrid computational methods were used to demonstrate the interaction mechanism between selective inhibitors targeting Hsp90α and Grp94. The results showed that hydrogen bond interaction and hydrophobicity are crucial for the selective inhibition of Hsp90α, while Grp94 specificity mainly relies on a typical hydrophobic cavity. These findings would provide the theoretical basis for the future development of novel selective inhibitors of Hsp90α and Grp94.

Buruli ulcer (BU), a severe skin disease is caused by Mycobacterium ulcerans. There are concerns of therapeutic inefficacy of existing drugs coupled with chemoresistance. Databases have been shown to augment data mining and integrative systems pharmacology approaches towards the search for novel therapeutic moieties. So far, there is no known integrated database solely dedicated to BU drug discovery. In this work, Buruli ulcer database (BuDb) is a “one-stop-shop” knowledgebase for supporting BU drug discovery. It contains both manually verified literature and database-curated data on BU. The BuDb provides comprehensive information on the various drug targets, tested compounds, existing drugs, ethnopharmacological plants and information on the genome of M. ulcerans. It also contains cross-referenced links to databases including PubMed, PubChem, DrugBank, NCBI, Gene Ontology (GO), UniProt, Prota4u, String database, KEGG Pathway and KEGG genome database. The BuDb has been implemented with accessibility features such as keyword and specific searches as well as browsing. BuDb is the first useful online repository of its kind integrated with enriched datasets that can aid in the discovery of new biotherapeutic entities for BU. BuDb can be freely accessed at http://197.255.126.13:3000/.

Chronic Myeloid Leukemia (CML) is known as clonal myeloproliferative disorder resulted by the proliferative and deregulated expression of the BCR-ABL gene. Although targeting the BCR-ABL gene is an effective treatment for CML, the development of drug intolerance and drug resistance is still an issue for BCR-ABL targeted therapy. With an aim to develop novel BCR-ABL inhibitors with fewer side effects, we started with the anti-cancerous natural compound coumestrol as the lead. Chalcone and pyrazole are the well-exploited scaffolds in the anticancer domain; hence, in this work, we designed novel coumestrol derivatives with these structures. In order to quantify the structural changes, we employed in silico methods. The new drug leads were compared with the FDA-approved CML drug bosutinib. The molecular orbital analysis of the selected lead compounds was assessed by Density Functional Theory (DFT) approach. Molecular Dynamic (MD) computations were performed on the most promising leads to find the stability. Following which, the pharmacokinetics parameters of the screened compounds were also analyzed to check the drug-like property.

The electroosmotic force effect on the peristaltic motion of the third-grade fluid is considered in a uniform channel. The governing equations that supplement the flow are designed for long wavelengths and low Reynolds numbers. Solutions are obtained for velocity, temperature, concentration, and trapping by considering the variable liquid properties for analyzing the various parameter effects. These effects are depicted through graphs and the relevance is discussed. The variable fluid properties have a declining impact on the velocity and temperature fields. Increasing the Helmholtz–Smoluchowski velocity values decreases the velocity field. Temperature decreases as the Deborah number increases. The velocity slip characteristics rise, and the trapping bolus’s size shrinks. The results of this paper may be beneficial in understanding the control of microvascular transport in the time of fractionation of blood into plasma and erythrocytes.

Thiophene-based small molecules COMP.1 and COMP.2 are explored for optical, electronic and photophysical properties by using theoretical approach. The density functional theory (DFT) at B3LYP/6-31G** level of theory is used to optimize both molecules COMP.1 and COMP.2 at ground state, while for excited state, the time-dependent DFT (TD-DFT) is utilized at the same level of theory. The optoelectronic and photophysical parameters specify that these materials would be good charge transport materials. Computed global reactivity descriptors indicate that COMP.2 T is more stable exhibiting smaller chemical reactivity. High electron mobility of COMP.1 as 0.78cm2⋅V−1⋅s−1 revealing that COMP.1 might be good n-type material. COMP.1 has been anticipated to be a decent n-type material as compared to COMP.2 and might be good material for solar cell applications.

Malaria is a serious illness transmitted through the bite of an infected mosquito, which is caused by a type of parasite called plasmodium and can be fatal if left untreated. Thus, newer antimalarials with unique mode of actions are encouraged. Fused pyridines have been vastly reported for numerous pharmacological activities including but not limited to analgesics, antitubercular, antifungal, antibacterial and antiapoptotic agents. In a current study, a series of substituted Imidazo[1,2-a]pyridine-3-carboxamides (IMPCs) (SM-IMP-01-13) along with some hydrazides (DA-01-DA-02) were synthesized and characterized by Fourier-transform infrared spectroscopy (FTIR), 1H-/13C-NMR (proton/carbon nuclear magnetic resonance), elemental analyses and mass spectra. These synthesized analogies were subjected for in vitro biological activities such as Brine Shrimp lethality (BSL), and assay of β-hematin formation inhibitions. The BSL assay results suggested that compounds, SM-IMP-09, SM-IMP-05 were found to be less toxic and they also had comparable toxicity as of 5-Flurouracil (control) ((e.g., at 10 μg/ml: 20% deaths of nauplii). Derivatives SM-IMP-02, and DA-05inhibited β-hematin formation: IC50: 1.849 and 0.042 μM, respectively). Our molecular docking analysis on plasmodial cysteine protease falcipain-2 indicated that compound DA-05(–9.993 kcal/mol) had highest docking score and it was comparable to standard Chloroquine (–7.673 kcal/mol). The most active molecule, DA-05 was also retained with lower HOMO–LUMO energy gap as 3.36 eV. Further, we have also analyzed MEP, and other global reactivity indexes for all IMPCs using DFT. Finally, our in-silico pharmacokinetic analysis suggested that all compounds were having good% human oral absorption values (≈100%), good Caco-2 cell permeabilities (>1600 nm/s), and non-carcinogenic profiles.

All-atom molecular dynamics simulations have been performed on mixtures of tetrabutylammonium chloride-based deep eutectic solvent and two cosolvents — methanol and acetonitrile. Water, a highly polar protic solvent, strongly interacts with the DES components. Herein, we have chosen methanol, a protic solvent but less polar than water, and acetonitrile, an aprotic solvent, to investigate the structural modifications in DES and new interactions arising after the addition of cosolvent based on both polarity and the presence or absence of labile hydrogen. Of the two cosolvents, methanol is found to affect the interactions present in DES significantly. Strong hydrogen bond interaction occurs between the chloride anion and methanol, leading to changes in the behavior of the mixture at the microscopic level. The self-diffusivity of components of the DES increases with the addition of methanol and acetonitrile; however, the increase is relatively more significant in the latter due to fewer average numbers of H-bonds. The amplitudes of the peaks of the structure factor decrease with an increase in the cosolvent concentration, thereby confirming that cosolvent affects the long-range correlations.

In this study we analyzed the sequence and structure of the human DISC1-Ndel1 complex using bioinformatics tools and molecular dynamics simulation studies. Multiple sequence alignment between the homologue protein sequences in primates shows that corresponding positions of residues in Ndel1 are highly conserved, while the DISC1 has variable conservation lines demonstrating its tolerability against various mutations during evolutionary time scale. In comparison with the mouse variant, structural analysis has shown that the evolutionary inserted charged residues in the human DISC1 (E837-R838) can establish intra-chain electrostatic interactions with the K819-E820 dipeptide that may result in more stability of the DISC1 chain. According to MD simulation studies, the compactness for the human variant of the DISC1-Ndel1 is considerably lower than that of the mouse variant. Analysis of structural fluctuation shows that a fragment at the N-terminus side of the human DISC1 has more residual fluctuation. However, the Ndel1 chain of the human variant has globally more flexibility compared with the mouse variant. Considering the identical amino acid sequence of the Ndel1 chains of human and mouse, it concluded that there is a competition between the inter-chain and intra-chain electrostatic interaction in the human DISC1 that directs the complex to weaker inter-chain interactions with the expense of strengthening the intra-chain stabilizing interaction in complex.

In this study, geometries, electronic structure and first hyperpolarizability of metals doped 15-crown-5 (C5M) were explored through the density functional theory (DFT) method. Alkali metals (Li, Na, K) and silver (Ag) were placed inside and outside of the crown ether, respectively, to deliver three compounds designated as Li[C5M]Ag, Na[C5M]Ag and K[C5M]Ag. All designed complexes were optimized at singlet, triplet, quintet and septet states, where the singlet state was identified as the stable state. The influence of doping on C5M can be investigated by energy gap fluctuation and it was noted that the smallest energy gap (4.68eV) was exhibited by K[C5M]Ag among all the intentional complexes, in contrast to reference C5M (12.73eV). Moreover, the density of state (DOS), transition density matrix (TDM), noncovalent interaction (NCI), molecular electrostatic potential (MESP) and electron density distribution map (EDDM) analysis were implemented. Static isotropic polarizability values were observed in the range of 17.15×10−24–34.68×10−24 esu which were comparable to dynamic isotropic polarizability values; 17.18×10−24–35.40×10−24. Li[C5M]Ag revealed maximum first hyperpolarizability (β) of 45.96×10−30esu with the minimum transition energy (ΔE) of 2.93eV.

Two separate types of multiphase flow models have been developed theoretically in this paper. Fourth-grade fluid model of non-Newtonian in nature is considered the main carrier. Silver and gold metallic particles of spherical shape suspend to form highly viscous multiphase flows which drift through an inclined channel. Effects of magnetic fields acting across the channel are applied as the body force. An approximate solution for the nonlinear flow dynamics of the two-phase suspensions. A comprehensive parametric study is performed to graphs against the pertinent parameters. Further, the obtained mathematical results and visual evidence are validated through computational data and found to be in completer agreement. It is inferred that gold multiphase suspensions can effectively be used in chemical and coating processes.

The SN2 and proton transfer (PT) pathways for OH−+NH2Cl reaction are represented by employing various electronic structure computations. Both back-side SN2 and PT channels are exothermic and stationary points of PESs are below the reactant asymptote. Overall, the PES is similar to the C-centered SN2 reactions. Conversely, ion-dipole complex was not found for OH−+NH2Cl system. The N–HOH/NH–Cl hydrogen bond characterizes on either side of the reaction barrier of nitrogen complexes. Moreover, a halogen-bonded complex (HO−–ClNH2) and two types of H-bond complexes (HONH2–Cl− and Cl−–HONH2) were described, predicting an important role in dynamics. The PT pathway may be the major channel in the title system, which is contradictory to OH−+CH3Cl and F−+NH2Cl reactions. Here, MP2, B3LYP and CAM-B3LYP methods show overall excellent consistency with CCSD(T)/CBS energies and are recommended to carry out dynamics simulations.

Topological data analysis (TDA) is an emerging field in mathematics and data science. Its central technique, persistent homology, has had tremendous success in many science and engineering disciplines. However, persistent homology has limitations, including its inability to handle heterogeneous information, such as multiple types of geometric objects; being qualitative rather than quantitative, e.g., counting a 5-member ring the same as a 6-member ring, and a failure to describe nontopological changes, such as homotopic changes in protein–protein binding. Persistent topological Laplacians (PTLs), such as persistent Laplacian and persistent sheaf Laplacian, were proposed to overcome the limitations of persistent homology. In this work, we examine the modeling and analysis power of PTLs in the study of the protein structures of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike receptor binding domain (RBD). First, we employ PTLs to study how the RBD mutation-induced structural changes of RBD-angiotensin-converting enzyme 2 (ACE2) binding complexes are captured in the changes of spectra of the PTLs among SARS-CoV-2 variants. Additionally, we use PTLs to analyze the binding of RBD and ACE2-induced structural changes of various SARS-CoV-2 variants. Finally, we explore the impacts of computationally generated RBD structures on a topological deep learning paradigm and predictions of deep mutational scanning datasets for the SARS-CoV-2 Omicron BA.2 variant. Our results indicate that PTLs have advantages over persistent homology in analyzing protein structural changes and provide a powerful new TDA tool for data science.