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Bioinformatics has emerged as a valuable tool for screening drugs and understanding their effects. This systematic review aimed to evaluate whether in silico studies using anti-obesity peptides targeting therapeutic pathways for obesity, when subsequently evaluated in vitro and in vivo, demonstrated effects consistent with those predicted in the computational analysis. The review was framed by the question: "What peptides or proteins have been used to treat obesity in in silico studies?" and structured according to the acronym PECo. The systematic review protocol was developed and registered in PROSPERO (CRD42022355540) in accordance with the PRISMA-P, and all stages of the review adhered to these guidelines. Studies were sourced from the following databases: PubMed, ScienceDirect, Scopus, Web of Science, Virtual Heath Library, and EMBASE. The search strategies resulted in 1015 articles, of which, based on the exclusion and inclusion criteria, 7 were included in this systematic review. The anti-obesity peptides identified originated from various sources including bovine alpha-lactalbumin from cocoa seed (Theobroma cacao L.), chia seed (Salvia hispanica L.), rice bran (Oryza sativa), sesame (Sesamum indicum L.), sea buckthorn seed flour (Hippophae rhamnoides), and adzuki beans (Vigna angularis). All articles underwent in vitro and in vivo reassessment and used molecular docking methodology in their in silico studies. Among the studies included in the review, 46.15% were classified as having an "uncertain risk of bias" in six of the thirteen criteria evaluated. The primary target investigated was pancreatic lipase (n = 5), with all peptides targeting this enzyme demonstrating inhibition, a finding supported both in vitro and in vivo. Additionally, other peptides were identified as PPARγ and PPARα agonists (n = 2). Notably, all peptides exhibited different mechanisms of action in lipid metabolism and adipogenesis. The findings of this systematic review underscore the effectiveness of computational simulation as a screening tool, providing crucial insights and guiding in vitro and in vivo investigations for the discovery of novel anti-obesity peptides.

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Conformational isomerism of organic photovoltaic materials has a profound impact on their molecular packing and therefore performance of polymer solar cells (PSCs). However, the conformations of oligomeric acceptors (OAs) are mostly predicted by simulations rather than experimental determinations. Herein, the stereochemical S-shaped structure of two dimeric-type acceptor molecules, V-DYIC and V-DYIC-4F, is first confirmed with different end groups (IC for V-DYIC and IC-2F for V-DYIC-4F), incorporating vinylene linkage for connecting the distinct state-of-the-art small molecule acceptor Y-segments. Through the synthetic control of fluorination sites adjacent to the vinyl-linker, S-shaped the conformation by NMR experiments is validated. Compared to the O-shaped dimer, S-shaped conformation results in enhanced lamellar order and reduced nonradiative recombination losses. The optimal acceptor, V-DYIC-4F, achieved a champion efficiency of 18.10% with the lowest energy loss of 0.556 eV in its devices paired with PM6 due to their efficient carrier transport, and suppressed recombination compared to other devices, being attributed to the synergistic effect of conformation and end group fluorination. The insights gained in this work contribute valuable knowledge of both synthetic control and structural determination of OAs, providing strategic design guidelines for the future development of dimeric acceptors toward high-efficiency PSCs.

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This study investigated the impact of high-intensity ultrasound (HIU) treatment on the physiochemical, conformational, and immunomodulatory activity of the OVT-CA complex, emphasizing the structure-function relationship. HIU treatment reduced particle size, improved dispersion, and increased electronegativity of the complex. It facilitated binding between OVT and CA, achieving a maximum degree of 45.22 mg/g CA grafting and reducing interaction time from 2 h to 15 min. HIU-induced cavitation and shear promoted the exposure of -SH and unfolding of OVT, leading to increased surface hydrophobicity of the complex and transformation of its structure from ß-sheet to α-helix. Additionally, CA binds to OVT in the C-lobe region, and HIU treatment modulates the intermolecular forces governing the complex formation, particularly by reinforcing hydrogen bonding, hydrophobic interactions, and introducing electrostatic interactions. Furthermore, HIU treatment increased the immunomodulatory activity of the complex, which was attributed to complex structural changes facilitating enhanced cell membrane affinity, antigen recognition, and B-cell epitope availability. Hierarchical cluster and Pearson correlation analysis confirmed that HIU treatment duration had a greater impact than power on both the structure and activity of the complex, and an optimal HIU treatment duration within 30 min was found to be crucial for activity enhancement. Moreover, structural changes, including ζ-potential, particle size/turbidity, and surface hydrophobicity, were closely correlated with immunomodulatory activity. This study highlights the potential application of HIU in developing protein-polyphenol immunomodulatory agents for public health and food nutrition.

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The study elucidates that the pH shifting treatment unfolds the conformation of soybean protein isolate (SPI), enabling it to intertwine with bacterial cellulose (BC) and form SPI/BC co-assemblies. Results from intrinsic fluorescence spectroscopy and surface hydrophobicity indicate that the SPI with pH shifting treatment shows a notable blue shift in maximum emission wavelength and increased surface hydrophobicity. It demonstrates that pH shifting treatment facilitates the unfolding of SPI's molecular conformation, promoting its entanglement with high aspect ratio BC. Particle size distribution and microstructural analysis further demonstrate that the pH shifting treatment facilitates the formation of SPI/BC co-assemblies. Evaluation of processing properties reveals that the SPI/BC co-assemblies exhibited exceptional gel and emulsification properties, with gel strength and emulsifying activity respectively six and two times higher than natural SPI. This enhancement is attributed to the thickening properties of BC with a high aspect ratio and the superior hydrophobicity of SPI in its molten globule state.

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Ewing sarcoma (ES) is a highly malignant and aggressive small round-cell tumor originating from primitive neuroepithelium and mesenchymal stem cells. It is usually seen in children and adolescents with a male predilection and a preponderance to occur in long bones. Although skeletal/soft tissue ES is encountered in clinical practice, primary ES of the genital tract, particularly bilateral primary ovarian ES, is highly uncommon, with only a handful of cases reported worldwide. Ovarian ES is occasionally reported to involve para-aortic and pelvic lymph nodes in advanced stages. Still, cervical lymph node metastasis from ovarian ES is an infrequent clinical occurrence and, when present, indicates a worse prognosis. Here, we present an intriguing case of bilateral peripheral primary ovarian ES in an adult female, recurring as metastasis in the left submandibular lymph node. This case underlines the importance of keeping metastasis from ES as a possible differential while diagnosing metastatic small round cell tumors in peripheral lymph nodes. It also highlights the usefulness of a minimally invasive diagnostic modality of fine needle aspiration cytology and cell block preparation with applied ancillary techniques of immunohistochemistry and confirmatory molecular testing by fluorescence in-situ hybridization (FISH), for an accurate and quick diagnosis of such entities. The cytological diagnosis of our patient helped in the prompt and early initiation of chemotherapy without requiring any invasive procedure.

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High-mobility and color-tunable highly emissive organic semiconductors (OSCs) are highly promising for various optoelectronic device applications and novel structure-property relationship investigations. However, such OSCs have never been reported because of the great trade-off between mobility, emission color, and emission efficiency. Here, we report a novel strategy of molecular conformation-induced unique crystalline polymorphism to realize the high mobility and color-tunable high emission in a novel OSC, 2,7-di(anthracen-2-yl) naphthalene (2,7-DAN). Interestingly, 2,7-DAN has unique crystalline polymorphism, which has an almost identical packing motif but slightly different molecular conformation enabled by the small bond rotation angle variation between anthracene and naphthalene units. More remarkably, the subtle covalent bond rotation angle change leads to a big change in color emission (from blue to green) but does not significantly modify the mobility and emission efficiency. The carrier mobility of 2,7-DAN crystals can reach up to a reliable 17 cm2 V-1 s-1, which is rare for the reported high-mobility OSCs. Based on the unique phenomenon, high-performance light-emitting transistors with blue to green emission are simultaneously demonstrated in an OSC crystal. These results open a new way for designing emerging multifunctional organic semiconductors toward next-generation advanced molecular (atomic)-scale optoelectronics devices.

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The envelope (E) protein of the Japanese encephalitis virus (JEV) is a key protein for virus infection and adsorption of host cells, which determines the virulence of the virus and regulates the intensity of inflammatory response. The mutation of multiple aa residues in the E protein plays a critical role in the attenuated strain of JEV. This study demonstrated that the Asp to Gly, Ser, and His mutation of the E389 site, respectively, the replication ability of the viruses in cells was significantly reduced, and the viral neuroinvasiveness was attenuated to different degrees. Among them, the mutation at E389 site enhanced the E protein flexibility contributed to the attenuation of neuroinvasiveness. In contrast, less flexibility of E protein enhanced the neuroinvasiveness of the strain. Our results indicate that the mechanism of attenuation of E389 aa mutation attenuates neuroinvasiveness is related to increased flexibility of the E protein. In addition, the increased flexibility of E protein enhanced the viral sensitivity to heparin inhibition in vitro, which may lead to a decrease in the viral load entering brain. These results suggest that E389 residue is a potential site affecting JEV virulence, and the flexibility of the E protein of aa at this site plays an important role in the determination of neuroinvasiveness.

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CONTEXT: Conformation generation, also known as molecular unfolding (MU), is a crucial step in structure-based drug design, remaining a challenging combinatorial optimization problem. Quantum annealing (QA) has shown great potential for solving certain combinatorial optimization problems over traditional classical methods such as simulated annealing (SA). However, a recent study showed that a 2000-qubit QA hardware was still unable to outperform SA for the MU problem. Here, we propose the use of quantum-inspired algorithm to solve the MU problem, in order to go beyond traditional SA. We introduce a highly compact phase encoding method which can exponentially reduce the representation space, compared with the previous one-hot encoding method. For benchmarking, we tested this new approach on the public QM9 dataset generated by density functional theory (DFT). The root-mean-square deviation between the conformation determined by our approach and DFT is negligible (less than about 0.5Å), which underpins the validity of our approach. Furthermore, the median time-to-target metric can be reduced by a factor of five compared to SA. Additionally, we demonstrate a simulation experiment by MindQuantum using quantum approximate optimization algorithm (QAOA) to reach optimal results. These results indicate that quantum-inspired algorithms can be applied to solve practical problems even before quantum hardware becomes mature. METHODS: The objective function of MU is defined as the sum of all internal distances between atoms in the molecule, which is a high-order unconstrained binary optimization (HUBO) problem. The degree of freedom of variables is discretized and encoded with binary variables by the phase encoding method. We employ the quantum-inspired simulated bifurcation algorithm for optimization. The public QM9 dataset is generated by DFT. The simulation experiment of quantum computation is implemented by MindQuantum using QAOA.

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The prediction of thermodynamic properties of carbon-based molecules based on their geometrical conformation using fluctuation and density functional theories has achieved great success in the field of energy chemistry, while the excessive computational cost provides both opportunities and challenges for the integration of machine learning. In this work, a deep learning-based quantum chemical prediction model was constructed for efficient prediction of thermodynamic properties of carbon-based molecules. We constructed a novel framework - encoding the 3D information into a large language model (LLM), which in turn generates a 2D SMILES string, while embedding a learnable encoding designed to preserve the integrity of the original 3D information, providing better structural information for the model. Additionally, we have designed an equivariant learning module to encompass representations of conformations and feature learning for conformational sampling. This framework aims to predict thermodynamic properties more accurately than learning from 2D topology alone, while providing faster computational speeds than conventional simulations. By combining machine learning and quantum chemistry, we pioneer efficient practical applications in the field of energy chemistry. Our model advances the integration of data-driven and physics-based modeling to unlock novel insights into carbon-based molecules.

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Chemical oxidizers and redox enzymes have traditionally been used to enhance the quality of baked goods. However, consumers now seek natural and clean-label ingredients, avoiding those with chemical-sounding names. Honey, a natural source of glucose oxidase (GOX), represents a promising alternative to purified enzymes for baking purposes. This study aimed to evaluate the effect of honey on the molecular structure and microstructure of gluten proteins in sourdough fermented by different lactic acid bacteria (LAB) strains. Four wheat-rye (1:1) sourdoughs were prepared, each supplemented with honey and inoculated with a different LAB strain. Additionally, two uninoculated doughs, one with honey (honey dough) and the other without (control dough), were prepared under identical conditions. Electronic paramagnetic resonance spectroscopy revealed the presence of hydrogen peroxide in honey solutions, indicating its role as an active source of GOX. Raman spectroscopy showed that honey addition altered the molecular structure of gluten by increasing the proportion of random coils at the expense of α-helix structures. This change is likely attributed to the competition between honey sugars and gluten proteins for water molecules in this system. Moreover, honey led to a decrease in the free sulfhydryl content of gluten compared to the control dough, suggesting an increase in disulfide crosslinking points. These enhanced protein-protein interactions were observed in scanning electron microscopy micrographs as a coarse gluten network composed of interconnected strands and fibrils. All LAB strains exhibited optimal acidification (pH < 4.3) in honey-supplemented sourdoughs, promoting the hydrolysis of gluten proteins into smaller fragments. Overall, honey-supplemented sourdoughs showed a gradual increase in the ß-sheet content while decreasing the proportion of random coils over time. This trend suggests that the polypeptide fragments interacted through interchain hydrogen bonds, leading to a more ordered structure, which likely contributes to providing dough with good baking aptitude.

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In the age of information technology and the additional computational search tools and software available, this systematic review aimed to identify potential therapeutic targets for obesity, evaluated in silico and subsequently validated in vivo. The systematic review was initially guided by the research question "What therapeutic targets have been used in in silico analysis for the treatment of obesity?" and structured based on the acronym PECo (P, problem; E, exposure; Co, context). The systematic review protocol was formulated and registered in PROSPERO (CRD42022353808) in accordance with the Preferred Reporting Items Checklist for Systematic Review and Meta-Analysis Protocols (PRISMA-P), and the PRISMA was followed for the systematic review. The studies were selected according to the eligibility criteria, aligned with PECo, in the following databases: PubMed, ScienceDirect, Scopus, Web of Science, BVS, and EMBASE. The search strategy yielded 1142 articles, from which, based on the evaluation criteria, 12 were included in the systematic review. Only seven these articles allowed the identification of both in silico and in vivo reassessed therapeutic targets. Among these targets, five were exclusively experimental, one was exclusively theoretical, and one of the targets presented an experimental portion and a portion obtained by modeling. The predominant methodology used was molecular docking and the most studied target was Human Pancreatic Lipase (HPL) (n = 4). The lack of methodological details resulted in more than 50% of the papers being categorized with an "unclear risk of bias" across eight out of the eleven evaluated criteria. From the current systematic review, it seems evident that integrating in silico methodologies into studies of potential drug targets for the exploration of new therapeutic agents provides an important tool, given the ongoing challenges in controlling obesity.

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Resistant starch (RS) is important in controlling diabetes. The primary objective of this study is to examine the impact of molecular conformation on the enzymatic hydrolysis efficiency of starch by α-amylase. And the interactions between starch molecules with different conformations and α-amylase were analysed by using molecule dynamics simulation and molecular docking. It was found, the natural conformational starch molecule was hydrolysed from the middle of the starch chain by α-amylase, producing polysaccharides. The bent PS-conformational starch molecules with multiple O2-O3 intramolecular hydrogen bonds produced by high-pressure was hydrolysed from the head of the starch chain to produce glucose, which is not conducive to RS formation. The stretched H-conformation without intramolecular hydrogen bonds produced by heat treatment was not hydrolysed by α-amylase. However, it occupied the active groove and formed strong interactions with α-amylase, which prevented other starch molecules from binding to α-amylase, thus reducing hydrolysis efficiency. Moreover, the total interaction energies between the three starch molecules and α-amylase were approximately 78 kJ/mol. And several hydrogen bonds were formed between the starch molecules and α-amylase, which provides evidence for the continuous sliding hydrolysis hypothesis of α-amylase. Moreover, these results provide an important reference for elucidating the mechanism of RS formation.

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Many artificial molecular machines have been synthesized, and various functions have been expressed by changing their molecular conformations. However, their structures are still simple compared with those of biomolecular machines, and more energy is required to control them. To design artificial molecular machines with more complex structures and higher functionality, it is necessary to combine molecular machines with simple movements such as components. This means that the motion of individual molecular machines must be precisely controlled and observed in various environments. At the air - water interface, the molecular orientation and conformation can be controlled with little energy as thermal fluctuations. We designed various molecular machines and controlled them using mechanical stimuli at the air - water interface. We also controlled the transfer of forces to the molecular machines in various lipid matrices. In this review, we describe molecular pliers with amphiphilic binaphthyl, molecular paddles with binuclear platinum complexes, and molecular rotors with julolidine and BODIPY that exhibit twisted intramolecular charge transfer.

This review discusses the dependence of the behaviour of molecular machines around their environment through the mechanically control of simple molecular machines at the air ­ water interface.

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The differences in the gelling properties of soy protein isolate (SPI) and soy protein isolate amyloid fibrils (SAFs) as well as the role of cellulose nanocrystals (CNC) in regulating their gel behaviors were investigated in this study. The binding of CNC to ß-conglycinin (7S), glycinin (11S), and SAFs was predominantly driven by non-covalent interactions. CNC addition reduced the particle size, turbidity, subunit segments, and crystallinity of SPI and SAFs, promoted the conversion of α-helix to ß-sheet, improved the thermal stability, exposed more tyrosine and tryptophan residues, and enhanced the intermolecular interactions. A more regular and ordered lamellar network structure was formed in the SAFs-CNC composite gel, which could be conducive to the improvement of gel quality. This study would provide theoretical reference for the understanding of the regulatory mechanism of protein amyloid fibrils gelation as well as the high-value utilization of SAFs-CNC complex as a functional protein-based material or food ingredient in food field.

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The luminescence and electronic structure of 3,3'-Diamino-4,4'-azofurazan (DAAzF) were studied under high pressure conditions through experimental and calculation approaches. The transition of π* â†’ π was primarily responsible for DAAzF's broad light emission. Upon applying pressure to DAAzF, high-pressure-stiffened hydrogen-bond interactions enable the restriction of the stretching vibration of NH2 group. The reduced energy loss through nonradiative rotational relaxation and molecular motions lead to a ∼20 times luminescent enhancement of DAAzF from 1 atm to 8.9 GPa. With the further strengthening of interlayer hydrogen bond interactions at higher pressure, the deviation of hydrogen atoms in amino groups from the molecular plane lessens the radiation transition efficiency. In addition, the bending of the C-C-N=N bond further leads to molecular conformation changes at approximately 20.7 GPa, which induces an abrupt redshift and moderate quenching of the luminescence. Furthermore, the band gap of DAAzF is significantly influenced by pressure. As the color undergoes a transition from yellow to red, and becomes darker as the pressure increases, the absorption edge shifted towards red. At 3.4, 9, and 21 GPa, three conformational variations were identified in conjunction with electronic structural alterations.

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ABSTRACT Ewing sarcoma (ES) is a highly malignant and aggressive small round-cell tumor originating from primitive neuroepithelium and mesenchymal stem cells. It is usually seen in children and adolescents with a male predilection and a preponderance to occur in long bones. Although skeletal/soft tissue ES is encountered in clinical practice, primary ES of the genital tract, particularly bilateral primary ovarian ES, is highly uncommon, with only a handful of cases reported worldwide. Ovarian ES is occasionally reported to involve para-aortic and pelvic lymph nodes in advanced stages. Still, cervical lymph node metastasis from ovarian ES is an infrequent clinical occurrence and, when present, indicates a worse prognosis. Here, we present an intriguing case of bilateral peripheral primary ovarian ES in an adult female, recurring as metastasis in the left submandibular lymph node. This case underlines the importance of keeping metastasis from ES as a possible differential while diagnosing metastatic small round cell tumors in peripheral lymph nodes. It also highlights the usefulness of a minimally invasive diagnostic modality of fine needle aspiration cytology and cell block preparation with applied ancillary techniques of immunohistochemistry and confirmatory molecular testing by fluorescence in-situ hybridization (FISH), for an accurate and quick diagnosis of such entities. The cytological diagnosis of our patient helped in the prompt and early initiation of chemotherapy without requiring any invasive procedure.

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Nanostructures, fabricated by locating molecular building blocks in well-defined positions, for example, on a lattice, are ideal platforms for studying atomic-scale quantum effects. In this context, STM data obtained from self-assembled Bis(phthalocyaninato) Terbium (III) (TbPc2) single-molecule magnets on various substrates have raised questions about the conformation of the TbPc2 molecules within the lattice. In order to address this issue, molecular dynamics simulations were carried out on a 2D assembly of TbPc2 molecules. The calculations are in excellent agreement with the experiment, and thus improve our understanding of the self-assembly process. In particular, the calculated electron density of the molecular assembly compares well with STM contrast of self-assembled TbPc2 on Au(111), simultaneously providing the conformation of the two Pc ligands of the individual double-decker molecule. This approach proves valuable in the identification of the STM contrast of LnPc2 layers and could be used in similar cases where it is difficult to interpret the STM images of an assembly of molecular complexes.

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Scalar (J) couplings constitute one of vital features observed in NMR spectroscopy and show valuable information for molecular structure elucidation and conformation analysis. However, existing J coupling measurement techniques are generally confined by the concerns of resolution, SNR, and experimental efficiency. Herein, we exploit an efficient 2D NMR protocol to deal with the above concerns by enabling rapid, sensitive, and high-resolution J coupling extraction. This protocol delivers full-resolved pure shift 2D absorption-mode spectroscopy to gain great convenience for efficient coupling measurements on overcrowded NMR signals. Resulting from band selective signal evolution, this protocol ensures high signal intensity with full magnetization preservation to meet the demand on probing low-concentration samples. This protocol focuses on accessing coupling information between specific two coupled spin families, and it is not applicable to all possible spin systems. Besides, it adopts echo-train selective refocusing acquisition to accelerate pure shift 2D J-edited implementations into pseudo-2D acquisition, and thus holding the experimental efficiency similar to conventional SERF experiments. Therefore, this study presents a promising tool for efficient extraction of J coupling networks, and takes an important step for coupling measurement techniques with wide applications on molecular conformation elucidation and stereochemical configuration analysis.

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Ligand-based virtual screening (LBVS) is a promising approach for rapid and low-cost screening of potentially bioactive molecules in the early stage of drug discovery. Compared with traditional similarity-based machine learning methods, deep learning frameworks for LBVS can more effectively extract high-order molecule structure representations from molecular fingerprints or structures. However, the 3D conformation of a molecule largely influences its bioactivity and physical properties, and has rarely been considered in previous deep learning-based LBVS methods. Moreover, the relative bioactivity benchmark dataset is still lacking. To address these issues, we introduce a novel end-to-end deep learning architecture trained from molecular conformers for LBVS. We first extracted molecule conformers from multiple public molecular bioactivity data and consolidated them into a large-scale bioactivity benchmark dataset, which totally includes millions of endpoints and molecules corresponding to 954 targets. Then, we devised a deep learning-based LBVS called EquiVS to learn molecule representations from conformers for bioactivity prediction. Specifically, graph convolutional network (GCN) and equivariant graph neural network (EGNN) are sequentially stacked to learn high-order molecule-level and conformer-level representations, followed with attention-based deep multiple-instance learning (MIL) to aggregate these representations and then predict the potential bioactivity for the query molecule on a given target. We conducted various experiments to validate the data quality of our benchmark dataset, and confirmed EquiVS achieved better performance compared with 10 traditional machine learning or deep learning-based LBVS methods. Further ablation studies demonstrate the significant contribution of molecular conformation for bioactivity prediction, as well as the reasonability and non-redundancy of deep learning architecture in EquiVS. Finally, a model interpretation case study on CDK2 shows the potential of EquiVS in optimal conformer discovery. The overall study shows that our proposed benchmark dataset and EquiVS method have promising prospects in virtual screening applications.

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Organic solar cells (OSCs) have attracted wide research attention in the past decades. Very recently, oligomerized fused-ring electron acceptors (OFREAs) have emerged as a promising alternative to small-molecular/polymeric acceptor-based OSCs due to their unique advantages such as well-defined structures, batch reproducibility, good film formation, low diffusion coefficient, and excellent stability. So far, rapid advances have been made in the development of OFREAs consisting of directly/rigidly/flexibly linked oligomers and fused ones. In this Minireview, we systematically summarized the recent research progress of OFREAs, including structural diversity, synthesis approach, molecular conformation and packing, and long-term stability. Finally, we conclude with future perspectives on the challenges to be addressed and potential research directions. We believe that this Minireview will encourage the development of novel OFREAs for OSC applications.