Semisynthetic Research Articles

Candida antartica lipase-catalyzed esterification for efficient partial acylglycerol synthesis in solvent-free system: Substrate selectivity, molecular modelling and optimization

Partial acylglycerols are valued for their emulsifying and stabilizing properties, yet precise green synthesis remains challenging due to low yield and selectivity. This study aimed to elucidate the “lipase selectivity-substrate structure-product composition” relationship to enhance the yield of targeted partial acylglycerol. The results showed that lipase exhibited a greater selectivity towards fatty acids with shorter chain lengths and higher unsaturation. Hydroxyl donors also affected the esterification process, with the enzyme-acyl complex exhibiting selectivity towards hydroxyl donors as follows: glycerol > monoacylglycerol > diacylglycerol. Substrate ratio significantly influenced enzymatic reactions; a 10:1 ratio favored triacylglycerol formation (>80 %), while a 1:1 ratio produced > 90 % partial acylglycerols. Molecular docking simulations revealed that substrates primarily interacted with lipase through hydrogen bonding and hydrophobic interactions. A comprehensive understanding of lipase selectivity patterns could facilitate the design of more efficient reaction systems, enabling the conversion of basic lipid resources into desired high value-added products.

Synthesis of (-) - 6,6'-dinitrohinokinin from hinokinin natural product and in silico and in vitro trypanocidal activity assessment

Chagas disease is a public health problem affecting approximately seven million people worldwide. Thus, there is a need to discover drugs for the adequate treatment of this disease because currently available drugs have serious side effects. Therefore, this study aimed to evaluate the in vitro trypanocidal activity of (-)-6,6'-dinitrohinokinin, obtained from the partial synthesis of (-)-hinokinin, on the trypomastigotes and amastigotes forms. For the trypomastigote assay, blood was collected from mice infected with Trypanosoma cruzi through cardiac puncture at the parasitemic peak. The results show that (-)-6,6'-dinitrohinokinin was effective against the trypomastigote forms, presenting an IC50 of 19.83 µM and lysis percentage values ​​of 78.4% and 69.4% at concentrations of 200 and 100 µM, respectively. Molecular docking calculations indicate that (-)-6,6'-dinitrohinokinin favorably interacts with the amino acids present in the active site of the protein trypanothione reductase, a typical target for anti-trypanosomal drug development. According to the results, the (-)-6,6'-dinitrohinokinin showed more significant trypanocidal activity with IC50 of 1.83 µM than benzonidazole positive control with IC50 of 53.2 µM, showing to be a prototype molecule promising for the development of a new antiparasitic drug.

Partial carbon encapsulation synthesis of separated Ni-Ag catalyst for efficient selective hydrogenation of acetylene: Synergizing hydrogen spillover and steric hindrance

The selective hydrogenation of acetylene is a vital process to for the purification of crude ethylene in petroleum industry. Achieving high activity and selectivity simultaneously over Ni-based catalysts is still challenging. Herein, a partial encapsulation strategy is proposed by fabricating carbon-encapsulated Ag nanoparticles and un-encapsulated Ni nanoparticles on Al2O3 surface (Ni-Ag@C/Al2O3) toward the enhanced selectivity without loss of activity. In particular, the Ni-Ag@C/Al2O3 exhibits higher ethylene selectivity of 81% at the complete acetylene conversion along with excellent stability for 30-h, in sharp with the Ni/Al2O3 (6%) and Ni-Ag/Al2O3 (54%) catalyst. The enhanced selectivity is attributed to the promotion of hydrogen spillover by the carbon species on Al2O3 surface and the inhibition of oligomer formation by a steric hindrance formed by the carbon layer on the Ag surface. This study provides a new structural design avenue of bifunctional bimetallic catalyst for selective hydrogenation reaction.

Approaches to the Full and Partial Chemical Synthesis of Proteins.

Histones are proteins which help to organize DNA. The way in which they function is complex and is partially controlled by post-translational modifications (PTMs). Histone proteins from numerous organisms can be recombinantly produced in bacteria, but many bacterial strains are incapable of installing the variety of PTMs that histones possess. An alternative method of producing histones, which can be used to introduce PTMs, is native chemical ligation (NCL). This chapter provides a general NCL protocol which can be used to produce synthetic, post-translationally modified, histone proteins. The focus is on the NCL procedure itself and not on producing the modified histone protein fragments as there are many different ways in which these can be synthesized, depending on the modification(s) required. The same NCL protocol is also applicable for expressed protein ligation (EPL) with only small modifications to the purification procedure potentially required.

Synthesis of the monomeric counterpart of Marinomycin A and B.

The synthesis of polyketide natural products has been a captivating pursuit in organic chemistry, with a particular focus on selectively introducing 1,3-polyol units. Among these natural products, Marinomycins A-D have garnered substantial interest due to their exceptional structural features and potent cytotoxicity. In this paper, we present a novel approach for synthesising the monomeric counterparts of Marinomycin A and B. Our method employs a previously established iterative cycle in conjunction with a standardised polyketide building block. Through this strategy, we showcase a promising pathway towards total and partial syntheses of these intriguing natural products.

Legibility of Built Space and the Method for Determining Architecturally Conditioned Spatial Identity – MAPPI

There is no space without people and no people without space. The very theory of genius loci (the spirit of a place) highlights the importance of spatial identity, as it is precisely this prerequisite for the formation of awareness of belonging to a certain community. Urban theory, which deals with the morphological composition of the built space, focuses on recognizing existing morphological patterns and reacts to these patterns depending on the different levels of development of thought doctrines or individual interpretations of the researcher. On the other hand, the gestalt spatial-architectural theory focuses on the meaning of an individual particle and its influence on other building blocks within its spatial context. The question arises of the relationship between the patterns of the built space and their building blocks; of the relationship between urban composition and individual architecture - buildings. To intertwine these two levels of reading space, the Method for determining Architecturally Conditioned Spatial Identity (MAPPI) was developed. Using the MAPPI method, we systematically monitor and check qualitative and quantitative data about the building/settlement. The intertwining of two levels and the diversity of data verification offers a different view of the interdependence between the building/settlement, from which the possibility of determining a spatially conditioned identity arises. This can be achieved by recognizing contemporary trends in architectural identity and key changes in recent decades, as well as based on existing classifications of architectural typology. In this way, it is possible to redefine settlement and architectural typologies, their characteristics, and their spatial distribution. The various tools used in the MAPPI method are designed so that, through partial automation and data synthesis, they facilitate the determination of closed spatial entities. The applicability of the MAPPI tools and method was verified on the example of the Prebold settlement.

An Enhanced Hybrid-Level Interface-Reduction Method Combined with an Interface Discrimination Algorithm

This study proposes an interface localizing scheme to enhance the performance of the previous hybrid-level interface-reduction method. The conventional component mode synthesis (CMS) only focuses on interior reduction, while the interface is fully retained for convenient synthesis. Thus, various interface-reduction methods have been suggested to obtain a satisfactory size for the reduced systems. Although previous hybrid-level interface-reduction approaches have addressed major issues associated with conventional interface-reduction methods—in terms of accuracy and efficiency through considering partial substructure synthesis—this method can be applied to limited modeling conditions where interfaces and substructures are independently defined. To overcome this limitation, an interface localizing algorithm is developed to ensure an enhanced performance in the conventional hybrid-level interface-reduction method. The interfaces are discriminated through considering the Boolean operation of substructures, and the interface reduction basis is computed at the localized interface level, which is constructed by a partially coupled system. As a result, a large amount of computational resources are saved, achieving the possibility of efficient design modifications at the semi-substructural level.

A Combined Electronic Position- and Partial Amplitude-Control Synthesis Technique for Sidelobe Reductions in Linear Array Antennas

A Combined Electronic Position- and Partial Amplitude-Control Synthesis Technique for Sidelobe Reductions in Linear Array Antennas

Partial Thermal Condensation Mediated Synthesis of High-Density Nickel Single Atom Sites on Carbon Nitride for Selective Photooxidation of Methane into Methanol.

Direct selective transformation of greenhouse methane (CH4) to liquid oxygenates (methanol) can substitute energy-intensive two-step (reforming/Fischer-Tropsch) synthesis while creating environmental benefits. The development of inexpensive, selective, and robust catalysts that enable room temperature conversion will decide the future of this technology. Single-atom catalysts (SACs) with isolated active centers embedded in support have displayed significant promises in catalysis to drive challenging reactions. Herein, high-density Ni single atoms are developed and stabilized on carbon nitride (NiCN) via thermal condensation of preorganized Ni-coordinated melem units. The physicochemical characterization of NiCN with various analytical techniques including HAADF-STEM and X-ray absorption fine structure (XAFS) validate the successful formation of Ni single atoms coordinated to the heptazine-constituted CN network. The presence of uniform catalytic sites improved visible absorption and carrier separation in densely populated NiCN SAC resulting in 100% selective photoconversion of (CH4) to methanol using H2O2 as an oxidant. The superior catalytic activity can be attributed to the generation of high oxidation (NiIII═O) sites and selective C─H bond cleavage to generate •CH3 radicals on Ni centers, which can combine with •OH radicals to generate CH3OH.

ABO and Rh Blood Group Antigens and Natural Anti-A and ANTI-B Antibodies in the Neonates

ABO blood group is determined by the presence or absence of A and B antigens on the surface of RBC and of anti-A and anti-B antibodies in the serum. The relatively weak expression of A and B antigens in newborns due to their developing immune systems poses challenges in accurately detecting naturally occurring IgM antibodies against these antigens. This difficulty in immunoserological methods contributes to the potential for errors in determining the blood groups of newborns. Despite this, the Rh antigen expression in newborns remains comparable to that in adults. Nonetheless, various factors contribute to diverse blood typing results in newborns, including the utilization of alternative testing methods. The complexity of blood typing is magnified when using samples from the umbilical vein. Furthermore, compared to adults, the exploration of ABO antigen expression in newborns is limited, and the identification of specific subgroups such as A1 and A2 is even rarer. This underscores the need for standardized testing procedures and further research to enhance our understanding of antigen expression patterns in newborns. Based on the aforementioned details, the primary objective of our study was to delve into specific aspects related to blood group characterization in newborns. This encompassed exploring the expression of A, B, AB, and D antigens on the surface of red blood cells (RBCs) and detecting anti-A and anti-B antibodies in the plasma of newborns. These analyses were conducted using samples obtained from the heels of 208 newborns and were typed by forward and reverse blood typing methods with monoclonal antibodies and srandart erythrocytes. The distribution of phenotypic groups within the ABO system among the newborns was not uniform. The r allele was identified with the highest frequency in the analyzed samples (0.6), while the prevalence of the p allele significantly lags at 0.3. The q allele has the lowest frequency (0.1). In our study, we propose that for the majority of cases (43.94±3.5%) among the studied newborns, there was an absence of naturally occurring anti-A and anti-B antibodies (n=87). In a specific scenario, within the O(I) blood group nwborns, partial synthesis of these antibodies was detected in 14.14±2.4% (n=28). Meanwhile, 41.92±3.5% of the newborns in our study exhibited natural antibodies similar to those found in adults. We didn’t find any difficulties in typing the Rh blood group antigens in the newborns. In conclusion, our study's findings indicate that newborns, in certain instances, exhibit strongly pronounced natural anti-A and anti-B antibodies within the ABO system. However, in the majority of cases, these antibodies are not evident. Majority of cases erythrocyte A and B antigens were weakly expressed and for detecting these images optic microscopes were used.

Partial syntheses of aromatic amides: their anti-urease potential and docking studies

The aromatic amide: N-p-trans-coumaroyltyramine (1) was isolated for the first time from the stem bark of Celtis zenkeri (Ulmaceae). Its four new derivatives (1a–d) and previously reported diacetylated product (1e) have been synthesized and characterized spectroscopically followed by their in vitro screening for anti-urease potential. The diacetylated product (1e) was found to be the most potent inhibitor with an IC50 value of 19.5 ± 0.23 μM compared to thiourea used as standard (21.5 ± 0.47 μM). Furthermore, molecular docking studies were conducted revealing striking interactions of the active compounds with catalytically important residues such as His593, Ala636 and Asp633. Subsequently, the prime MM-GBSA calculations provided the ligand binding and strain energies. The molecular dynamic simulations validated the docked and post-docked complexes where compounds 1b, 1c, 1d and 1e remained stable throughout the simulation. This study provides insight into the N-p-trans-coumaroyltyramine derivatives (1b–e) that can block the substrate entry, thereby inhibiting the urease’s catalytic activity. Hence, these hit compounds can proceed for further pre-clinical studies for drug discovery against urease. Communicated by Ramaswamy H. Sarma

New theobromine derivative as apoptotic anti-triple-negative breast cancer targeting EGFR protein: CADD story

A new EGFR inhibitor has been developed from theobromine (meta methoxy phenyl)acetamide derivative), T-1-MMPA, exhibited the essential pharmacophoric characteristics needed to bind toEGFR's pocket. T-1-MMPA's anticancer potential was first estimated through various structure-based computational studies (DFT, docking, MD simulations over 200 ns, MM-GPSA, PLIP, ED, bi-dimensional and ADMET), which revealed that T-1-MMPA effectively bound to and inhibited the EGFR protein. The ADME and toxicity profiles of T-1-MMPA were also predicted computationally before the semi synthesis, and a high degree of drug-likeness was indicated. Then, T-1-MMPA (2-(3,7-Dimethyl-2,6-dioxo-2,3,6,7-tetrahydro-1H-purin-1-yl)-N-(3-methoxyphenyl)acetamide) was prepared to scrutinize the obtained in silico results. Subsequent in vitro studies showed that T-1-MMPA was effective against MDA-MB-231cell lines (triple-negative breast cancer), with an IC50 value of 1.42 µM, compared to the reference drug (0.92 µM) and exhibited a higher selectivity index of 1.9. Interestingly, T-1-MMPA also inhibited the growth of other three cancer cell lines (A549, CaCO-2, and HepG-2) with IC50 values of 1.57, 1.76, and 2.53 µM, respectively. Additionally, T-1-MMPA effectively prevented the healing and migration abilities of the MDA-MB-231 cell lines, arrested the cell growth at the S phase and induced apoptosis, as confirmed by AO/EB staining assay as well as the flow cytometry. Moreover, T-1-MMPA caused down-regulation of the BCL2 and MMP7 gene expression in the treated MDA-MB-231 cells. Finally, as the computational findings indicated T-1-MMPA’s hepatic safety, it was further corroborated through in vivo investigation.

Partial Oxidation Synthesis of Prussian Blue Analogues for Thermo-Rechargeable Battery

A thermo-rechargeable battery or tertiary battery converts thermal energy into electric energy via an electrochemical Seebeck coefficient. The manufacturing of the tertiary batteries requires a pre-oxidation step to align and optimize the cathode and anode potentials. The pre-oxidation step, which is not part of the secondary battery manufacturing process, makes the manufacturing of tertiary batteries complex and costly. To omit the pre-oxidation step, we used partially oxidized Prussian blue analogs, i.e., NaxCo[Fe(CN)6]yzH2O (Co-PBA) and NaxNi[Fe(CN)6]yzH2O (Ni-PBA), as cathode and anode materials. The modified tertiary battery without the pre-oxidation step shows good thermal cyclability between 10 ∘C and 50 ∘C without detectable deterioration of the thermal voltage (Vcell) and discharge capacity (Qcell).

Synthesis of Nonlinear Nonstationary Stochastic Systems by Wavelet Canonical Expansions

The article is devoted to Bayes optimization problems of nonlinear observable stochastic systems (NLOStSs) based on wavelet canonical expansions (WLCEs). Input stochastic processes (StPs) and output StPs of considered nonlinearly StSs depend on random parameters and additive independent Gaussian noises. For stochastic synthesis we use a Bayes approach with the given loss function and minimum risk condition. WLCEs are formed by covariance function expansion coefficients of two-dimensional orthonormal basis of wavelet with a compact carrier. New results: (i) a common Bayes’ criteria synthesis algorithm for NLOStSs by WLCE is presented; (ii) partial synthesis algorithms for three of Bayes’ criteria (minimum mean square error, damage accumulation and probability of error exit outside the limits) are given; (iii) an approximate algorithm based on statistical linearization; (iv) three test examples. Applications: wavelet optimization and parameter calibration in complex measurement and control systems. Some generalizations are formulated.

Automatic correction of RTL designs using a lightweight partial high level synthesis

Correction of the digital designs have emerged as a major bottleneck at Register Transfer Level (RTL) due to the growing complexity of the digital systems and shortening time-to-market. Existing automated correction methods face problems like large number of error root causes, poor scalability, and multiple design errors. To address these problems, we propose an automatic correction methodology based on a lightweight partial high level synthesis (HLS) flow which takes as inputs a golden C specification and a buggy RTL design and outputs the corrected RTL model. Synthesizing the specification using a HLS tool without considering the buggy RTL to obtain the corrected RTL is not the case because manual RTL optimizations done by the designer should be preserved so that the architecture of the corrected RTL design should be as similar as possible to that of the buggy one. The results on industrial large designs show that the proposed methodology achieves 92.3% less new resources and 81.1% less connections compared to synthesizing the golden specification using a HLS tool without considering the architecture of the buggy RTL design.

Isolation and Characterization of Impurities in Commercially Marketed Δ8-THC Products.

Qualitative analysis of several commercial products containing Δ8-tetrahydrocannabinol (Δ8-THC) as a major component using GC-MS resulted in the identification of several impurities along with Δ8-THC. In an attempt to isolate and identify these impurities, a commercial Δ8-THC distillate was selected for the isolation work. Eleven impurities were isolated using a variety of chromatographic techniques, and their chemical structures were determined. These include Δ4,8-iso-tetrahydrocannabinol (1), Δ4-iso-tetrahydrocannabinol (2), Δ8-cis-iso-tetrahydrocannabinol (3), 4,8-epoxy-iso-tetrahydrocannabinol (4), 8-hydroxy-iso-tetrahydrocannabinol (5), 9β-hydroxyhexahydrocannabinol (6), 9α-hydroxyhexa-hydrocannabinol (7), iso-tetrahydrocannabifuran (8), cannabicitran (CBT, 9), olivetol (10), and Δ9-THC (11). The chemical structures of the purified compounds were determined using several spectroscopic methods, including 1D (1H, 13C, and DEPT-135) and 2D (COSY, HMQC, HMBC, and NOESY) NMR, LC-MS, and GC-MS. Other naturally occurring cannabinoids and impurities were also identified in GC-MS chromatograms but were not isolated. These were cannabidiol (CBD, 12), cannabinol (CBN, 13), hexahydrocannabinol (HHC, 14), and Δ8-tetrahydrocannabivarin (Δ8-THCV, 15). The chemical structure of Δ8-THCV (15), for which a standard was not available, was confirmed by partial synthesis and NMR analysis. This is the first report for many of the above compounds as well as Δ8-THCV as impurities in Δ8-THC products.

Computer-aided design and 3-dimensional artificial/convolutional neural network for digital partial dental crown synthesis and validation

The current multiphase, invitro study developed and validated a 3-dimensional convolutional neural network (3D-CNN) to generate partial dental crowns (PDC) for use in restorative dentistry. The effectiveness of desktop laser and intraoral scanners in generating data for the purpose of 3D-CNN was first evaluated (phase 1). There were no significant differences in surface area [t-stat(df) = − 0.01 (10), mean difference = − 0.058, P > 0.99] and volume [t-stat(df) = 0.357(10)]. However, the intraoral scans were chosen for phase 2 as they produced a greater level of volumetric details (343.83 ± 43.52 mm3) compared to desktop laser scanning (322.70 ± 40.15 mm3). In phase 2, 120 tooth preparations were digitally synthesized from intraoral scans, and two clinicians designed the respective PDCs using computer-aided design (CAD) workflows on a personal computer setup. Statistical comparison by 3-factor ANOVA demonstrated significant differences in surface area (P < 0.001), volume (P < 0.001), and spatial overlap (P < 0.001), and therefore only the most accurate PDCs (n = 30) were picked to train the neural network (Phase 3). The current 3D-CNN produced a validation accuracy of 60%, validation loss of 0.68–0.87, sensitivity of 1.00, precision of 0.50–0.83, and serves as a proof-of-concept that 3D-CNN can predict and generate PDC prostheses in CAD for restorative dentistry.

A versatile non-fouling multi-step flow reactor platform: demonstration for partial oxidation synthesis of iron oxide nanoparticles.

In the last decade flow reactors for material synthesis were firmly established, demonstrating advantageous operating conditions, reproducible and scalable production via continuous operation, as well as high-throughput screening of synthetic conditions. Reactor fouling, however, often restricts flow chemistry and the common fouling prevention via segmented flow comes at the cost of inflexibility. Often, the difficulty of feeding reagents into liquid segments (droplets or slugs) constrains flow syntheses using segmented flow to simple synthetic protocols with a single reagent addition step prior or during segmentation. Hence, the translation of fouling prone syntheses requiring multiple reagent addition steps into flow remains challenging. This work presents a modular flow reactor platform overcoming this bottleneck by fully exploiting the potential of three-phase (gas-liquid-liquid) segmented flow to supply reagents after segmentation, hence facilitating fouling free multi-step flow syntheses. The reactor design and materials selection address the operation challenges inherent to gas-liquid-liquid flow and reagent addition into segments allowing for a wide range of flow rates, flow ratios, temperatures, and use of continuous phases (no perfluorinated solvents needed). This "Lego®-like" reactor platform comprises elements for three-phase segmentation and sequential reagent addition into fluid segments, as well as temperature-controlled residence time modules that offer the flexibility required to translate even complex nanomaterial synthesis protocols to flow. To demonstrate the platform's versatility, we chose a fouling prone multi-step synthesis, i.e., a water-based partial oxidation synthesis of iron oxide nanoparticles. This synthesis required I) the precipitation of ferrous hydroxides, II) the addition of an oxidation agent, III) a temperature treatment to initiate magnetite/maghemite formation, and IV) the addition of citric acid to increase the colloidal stability. The platform facilitated the synthesis of colloidally stable magnetic nanoparticles reproducibly at well-controlled synthetic conditions and prevented fouling using heptane as continuous phase. The biocompatible particles showed excellent heating abilities in alternating magnetic fields (ILP values >3 nH m2 kgFe-1), hence, their potential for magnetic hyperthermia cancer treatment. The platform allowed for long term operation, as well as screening of synthetic conditions to tune particle properties. This was demonstrated via the addition of tetraethylenepentamine, confirming its potential to control particle morphology. Such a versatile reactor platform makes it possible to translate even complex syntheses into flow, opening up new opportunities for material synthesis.

AlignBodyNet: Deep Learning-Based Alignment of Non-Overlapping Partial Body Point Clouds From a Single Depth Camera

This article proposes a novel deep learning framework to generate omnidirectional 3-D point clouds of human bodies by registering the front- and back-facing partial scans captured by a single-depth camera. Our approach does not require calibration-assisting devices, canonical postures, nor does it make assumptions concerning an initial alignment or correspondences between the partial scans. This is achieved by factoring this challenging problem into: 1) building virtual correspondences for partial scans and 2) implicitly predicting the rigid transformation between the two partial scans via the predicted virtual correspondences. In this study, we regress the skinned multi-person linear model (SMPL) vertices from the two partial scans for building virtual correspondences. The main challenges are: 1) estimating the body shape and pose under clothing from single partially dressed body point clouds and 2) the predicted bodies from the front- and back-facing inputs required to be the same. We, thus, propose a novel deep neural network (DNN) dubbed AlignBodyNet that introduces shape-interrelated features and a shape-constraint loss for resolving this problem. We also provide a simple yet efficient method for generating real-world partial scans from complete models, which fills the gap in the lack of quantitative comparisons based on real-world data for various studies including partial registration, shape completion, and view synthesis. Experiments based on synthetic and real-world data show that our method achieves state-of-the-art performance in both objective and subjective terms.

Chemoselective Synthesis of Mannich Adducts from 1,4-Naphthoquinones and Profile as Autophagic Inducers in Oral Squamous Cell Carcinoma.

Oral squamous cell carcinoma (OSCC) is a worldwide public health problem, accounting for approximately 90% of all oral cancers, and is the eighth most common cancer in men. Cisplatin and carboplatin are the main chemotherapy drugs used in the clinic. However, in addition to their serious side effects, such as damage to the nervous system and kidneys, there is also drug resistance. Thus, the development of new drugs becomes of great importance. Naphthoquinones have been described with antitumor activity. Some of them are found in nature, but semi synthesis has been used as strategy to find new chemical entities for the treatment of cancer. In the present study, we promote a multiple component reaction (MCR) among lawsone, arylaldehydes, and benzylamine to produce sixteen chemoselectively derivated Mannich adducts of 1,4-naphthoquinones in good yield (up to 97%). The antitumor activities and molecular mechanisms of action of these compounds were investigated in OSCC models and the compound 6a induced cytotoxicity in three different tumor cell lines (OSCC4, OSCC9, and OSCC25) and was more selective (IS &gt; 2) for tumor cells than the chemotropic drug carboplatin and the controls lapachol and shikonin, which are chemically similar compounds with cytotoxic effects. The 6a selectively and significantly reduced the amount of cell colony growth, was not hemolytic, and tolerable in mice with no serious side effects at a concentration of 100 mg/kg with a LD50 of 150 mg/kg. The new compound is biologically stable with a profile similar to carboplatin. Morphologically, 6a does not induce cell retraction or membrane blebs, but it does induce intense vesicle formation and late emergence of membrane bubbles. Exploring the mechanism of cell death induction, compound 6a does not induce ROS formation, and cell viability was not affected by inhibitors of apoptosis (ZVAD) and necroptosis (necrostatin 1). Autophagy followed by a late apoptosis process appears to be the death-inducing pathway of 6a, as observed by increased viability by the autophagy inhibitor (3-MA) and by the appearance of autophagosomes, later triggering a process of late apoptosis with the presence of caspase 3/7 and DNA fragmentation. Molecular modeling suggests the ability of the compound to bind to topoisomerase I and II and with greater affinity to hPKM2 enzyme than controls, which could explain the mechanism of cell death by autophagy. Finally, the in-silico prediction of drug-relevant properties showed that compound 6a has a good pharmacokinetic profile when compared to carboplatin and doxorubicin. Among the sixteen naphthoquinones tested, compound 6a was the most effective and is highly selective and well tolerated in animals. The induction of cell death in OSCC through autophagy followed by late apoptosis possibly via inhibition of the PKM2 enzyme points to a promising potential of 6a as a new preclinical anticancer candidate.