Molecular docking with conformer-dependent charges.

Determination of protein-ligand interactions is crucial for structure-based drug design. But, accurate prediction of the binding structures of protein-ligand is still a major challenge for molecular docking methods. Herein, we developed molecular docking with conformer-dependent charges (MDCC), a docking method to combine conformational search with RESP charges. Compared to the conventional Glide SP method (51.9%) and Glide XP method (52.6%), the MDCC method (60%) exhibited a higher docking success rate based on 285 protein-small molecule ligand complexes from the PDBbind core set. And when the ligand met one of the conditions (the total hydrophobic surface area > 438, the number of hydrophobic atoms > 10, and molecular weight > 235), the docking success rate of the MDCC method (>90%) was higher than that of the Glide SP method (∼72%). Furthermore, we also applied the MDCC method to predict the protein-ligand interactions in GPCR Dock 2021 competition, with our prediction models ranking 2nd out of all 202 participating models for APJ and 5th out of all 193 participating models for GPR139, demonstrating the relatively high docking accuracy of the MDCC method. In addition, we also found that the MDCC method combined with molecular dynamics simulations could facilitate the application of AlphaFold 2 in drug discovery. The above results all set the stage for the application of the MDCC method in future practical drug design.

The mechanism of phonetic information in voice identity discrimination: a comparative study based on sighted and blind people.

Purpose: The purpose of this study is to examine whether phonetic information functions and how phonetic information affects voice identity processing in blind people. Method: To address the first inquiry, 25 normal sighted participants and 30 blind participants discriminated voice identity, when listening forward speech and backward speech from their own native language and another unfamiliar language. To address the second inquiry, combining articulatory suppression paradigm, 26 normal sighted participants and 26 blind participants discriminated voice identity, when listening forward speech from their own native language and another unfamiliar language. Results: In Experiment 1, not only in the voice identity discrimination task with forward speech, but also in the discrimination task with backward speech, both the sighted and blind groups showed the superiority of the native language. This finding supports the view that backward speech still retains some phonetic information, and indicates that phonetic information can affect voice identity processing in sighted and blind people. In addition, only the superiority of the native language of sighted people was regulated by the speech manner, which is related to articulatory rehearsal. In Experiment 2, only the superiority of the native language of sighted people was regulated by articulatory suppression. This indicates that phonetic information may act in different ways on voice identity processing in sighted and blind people. Conclusion: The heightened dependence on voice source information in blind people appears not to undermine the function of phonetic information, but it appears to change the functional mechanism of phonetic information. These findings suggest that the present phonetic familiarity model needs to be improved with respect to the mechanism of phonetic information.

A smartphone-enabled visual platform for detecting aflatoxins in peanut oil using colorimetric analysis coupled with magnetic imprinted solid-phase extraction.

The study aimed to develop a rapid and sensitive colorimetric platform based on the Emerson reaction to visualize and determine total aflatoxins (AFs) in peanut oil. This method offers the advantage of fast screening for AFs (AFB1, AFB2, AFG1, and AFG2), eliminating the need for specific antibodies. The proposed approach combined colorimetric detection with magnetic dummy imprinted solid-phase extraction and purification, enhancing sensitivity and selectivity. The oxidizer aided the colorless AFs in reacting with 4-aminoantipyrine, producing green condensates. Thus, a dual-mode approach was developed for AFs detection, employing both UV-vis colorimetric and smartphone-based colorimetry. Both methods showed a good linear relationship with the concentration of AFs. Notably, the smartphone-based method demonstrated a detection range of 0.5-57 µg/kg, with a detection limit as low as 0.21 µg/kg. The suggested colorimetric methods present a promising potential for onsite detection and fast screening of AFs in actual samples.

Discovery of Novel Azaindoles as Potent and Selective PI3Kδ Inhibitors for Treatment of Multiple Sclerosis.

Multiple sclerosis (MS) is a chronic autoimmune disorder of the central nervous system and the unmet need for MS treatment demands new therapeutic development. Particularly, PI3Kδ is a high-value target for autoimmune disease, while the investigation of PI3Kδ inhibitors for MS therapy is relatively scarce. Herein, we report a novel class of azaindoles as PI3Kδ inhibitors for MS treatment. Compound 31, designed via nitrogen bioisosterism, displayed excellent PI3Kδ inhibitory activity and selectivity. In vitro assay showed that 31 exhibited superior activity on T lymphocytes to inhibit the proliferation of CD4+, CD8+, and CD3+ T cells. In the experimental autoimmune encephalomyelitis (EAE) model, 31 showed a comparable therapeutical efficacy with Dexamethasone to significantly ameliorate EAE symptoms. Mechanistic studies showed that compound 31 could significantly inhibit the PI3K/AKT/mTOR signaling pathway and inhibited T-cell proliferation and differentiation. Overall, this work provides a new structural PI3Kδ inhibitor and a new vision for MS therapy.

Discovery of Potent and Selective PI3Kδ Inhibitors for the Treatment of Acute Myeloid Leukemia.

PI3Kδ is an essential target correlated to the occurrence and development of acute myeloid leukemia (AML). Herein, we investigated the pyrazolo[3,4-d]pyrimidine derivatives as potent and selective PI3Kδ inhibitors with high therapeutic efficacy toward AML. There were 44 compounds designed and prepared in a four-round optimization, and the biological evaluation showed that (S)-36 exhibited potent PI3Kδ inhibitory activity, high selectivity, and high antiproliferative activities against MV-4-11 and MOLM-13 cells, coupled with high oral bioavailability (F = 59.6%). In the MOLM-13 subcutaneous xenograft model, (S)-36 could significantly suppress the tumor progression with a TGI of 67.81% at an oral administration dosage of 10 mg/kg without exhibiting obvious toxicity. Mechanistically, (S)-36 could robustly inhibit the PI3K/AKT pathway for significant suppression of cell proliferation and remarkable induction of apoptosis both in vitro and in vivo. Thus, compound (S)-36 represents a promising PI3Kδ inhibitor for the treatment of acute myeloid leukemia with high efficacy.

Task-general or specific: The alertness modulates post-error adjustment.

Previous studies have shown that alertness is closely related to executive control function, but its impact on components of post-error adjustment is unknown. This study applied the Attentional Networks Test and the Four-choice Flanker task with three response stimulus intervals (RSIs) to explore the correlation between alertness and post-error adjustment. The linear mixed-effects model of alertness and RSI on the post-error processing indicators showed a significant negative correlation between the alertness and post-error slowing (PES) under 200 ms RSI , as well as between alertness and post-error improvement in accuracy (PIA) under both 700 ms RSI and 1200 ms RSI. Participants with lower alertness showed larger post-error slowing in the early stages, while those with higher alertness had smaller PIA in later stages. This study revealed the effects of alertness on different processing components of post-error adjustment. The control strategies utilized by individuals with high and low levels of alertness differed in preparation for performance monitoring. Alertness improved post-error response speed in a task-unspecific manner, but not post-error adaptation.

Dynasore Alleviates LPS-Induced Acute Lung Injury by Inhibiting NLRP3 Inflammasome-Mediated Pyroptosis.

Background: Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are clinically severe respiratory disorders without available pharmacological therapies. Dynasore is a cell-permeable molecule that inhibits GTPase activity and exerts protective effects in several disease models. However, whether dynasore can alleviate lipopolysaccharide (LPS)-induced ALI is unknown. This study investigated the effect of dynasore on macrophage activation and explored its potential mechanisms in LPS-induced ALI in vitro and in vivo. Methods: Bone marrow-derived macrophages (BMDMs) were activated classically with LPS or subjected to NLRP3 inflammasome activation with LPS+ATP. A mouse ALI model was established by the intratracheal instillation (i.t.) of LPS. The expression of PYD domains-containing protein 3 (NLRP3), caspase-1, and gasdermin D (GSDMD) protein was detected by Western blots. Inflammatory mediators were analyzed in the cell supernatant, in serum and bronchoalveolar lavage fluid (BALF) by enzyme-linked immunosorbent assays. Morphological changes in lung tissues were evaluated by hematoxylin and eosin staining. F4/80, Caspase-1 and GSDMD distribution in lung tissue was detected by immunofluorescence. Results: Dynasore downregulated nuclear factor (NF)-κB signaling and reduced proinflammatory cytokine production in vitro and inhibited the production and release of interleukin (IL)-1ß, NLRP3 inflammasome activation, and macrophage pyroptosis through the Drp1/ROS/NLRP3 axis. Dynasore significantly reduced lung injury scores and proinflammatory cytokine levels in both BALF and serum in vivo, including IL-1ß and IL-6. Dynasore also downregulated the co-expression of F4/80, caspase-1 and GSDMD in lung tissue. Conclusion: Collectively, these findings demonstrated that dynasore could alleviate LPS-induced ALI by regulating macrophage pyroptosis, which might provide a new therapeutic strategy for ALI/ARDS.

Recent advances in the development of DprE1 inhibitors using AI/CADD approaches.

Tuberculosis (TB) is a global lethal disease caused by Mycobacterium tuberculosis (Mtb). The flavoenzyme decaprenylphosphoryl-ß-d-ribose 2'-oxidase (DprE1) plays a crucial part in the biosynthesis of lipoarabinomannan and arabinogalactan for the cell wall of Mtb and represents a promising target for anti-TB drug development. Therefore, there is an urgent need to discover DprE1 inhibitors with novel scaffolds, improved bioactivity and high drug-likeness. Recent studies have shown that artificial intelligence/computer-aided drug design (AI/CADD) techniques are powerful tools in the discovery of novel DprE1 inhibitors. This review provides an overview of the discovery of DprE1 inhibitors and their underlying mechanism of action and highlights recent advances in the discovery and optimization of DprE1 inhibitors using AI/CADD approaches.

Cognitive and neural mechanisms of voluntary versus forced language switching in Chinese-English bilinguals: an fMRI study.

The ecological validity of bilingual code-switching has garnered increasing attention in recent years. Contrary to traditional studies that have focused on forced language switching, emerging theories posit that voluntary switching may not incur such a cost. To test these claims and understand differences between forced and voluntary switching, the present study conducted a systematic comparison through both behavioral and neural perspectives. Utilizing fMRI alongside picture-naming tasks, our findings diverge from prior work. Voluntary language switching not only demonstrated switching costs at the behavioral level but also significantly activated brain regions associated with inhibitory control. Direct comparisons of voluntary and forced language switching revealed no significant behavioral differences in switching costs, and both shared several common brain regions that were activated. On the other hand, a nuanced difference between the two types of language switching was revealed by whole-brain analysis: voluntary switching engaged fewer language control regions than forced switching. These findings offer a comprehensive view of the neural and behavioral dynamics involved in bilingual language switching, challenging prior claims that voluntary switching imposes no behavioral or neural costs, and thus providing behavioral and neuroimaging evidence for the involvement of inhibitory control in voluntary language switching.

Target-based drug design strategies to overcome resistance to antiviral agents: opportunities and challenges.

Viral infections have a major impact in human health. Ongoing viral transmission and escalating selective pressure have the potential to favor the emergence of vaccine- and antiviral drug-resistant viruses. Target-based approaches for the design of antiviral drugs can play a pivotal role in combating drug-resistant challenges. Drug design computational tools facilitate the discovery of novel drugs. This review provides a comprehensive overview of current drug design strategies employed in the field of antiviral drug resistance, illustrated through the description of a series of successful applications. These strategies include technologies that enhance compound-target affinity while minimizing interactions with mutated binding pockets. Furthermore, emerging approaches such as virtual screening, targeted protein/RNA degradation, and resistance analysis during drug design have been harnessed to curtail the emergence of drug resistance. Additionally, host targeting antiviral drugs offer a promising avenue for circumventing viral mutation. The widespread adoption of these refined drug design strategies will effectively address the prevailing challenge posed by antiviral drug resistance.

Revolutionizing viral disease treatment: Phase separation and lysosome/exosome targeting as new areas and new paradigms for antiviral drug research.

With the advancement of globalization, our world is becoming increasingly interconnected. However, this interconnection means that once an infectious disease emerges, it can rapidly spread worldwide. Specifically, viral diseases pose a growing threat to human health. The COVID-19 pandemic has underscored the pressing need for expedited drug development to combat emerging viral diseases. Traditional drug discovery methods primarily rely on random screening and structure-based optimization, and new approaches are required to address more complex scenarios in drug discovery. Emerging antiviral strategies include phase separation and lysosome/exosome targeting. The widespread implementation of these innovative drug design strategies will contribute towards tackling existing viral infections and future outbreaks.

Discovery of N-(1-(6-Oxo-1,6-dihydropyrimidine)-pyrazole) Acetamide Derivatives as Novel Noncovalent DprE1 Inhibitors against Mycobacterium tuberculosis.

Decaprenylphosphoryl-ß-d-ribose oxidase (DprE1) is a promising target for treating tuberculosis (TB). Currently, most novel DprE1 inhibitors are discovered through high-throughput screening, while computer-aided drug design (CADD) strategies are expected to promote the discovery process. In this study, with the aid of structure-based virtual screening and computationally guided design, a series of novel scaffold N-(1-(6-oxo-1,6-dihydropyrimidine)-pyrazole) acetamide derivatives with significant antimycobacterial activities were identified. Among them, compounds LK-60 and LK-75 are capable of effectively suppressing the proliferation of Mtb with MICMtb values of 0.78-1.56 µM, comparable with isoniazid and much superior to the phase II candidate TBA-7371 (MICMtb = 12.5 µM). LK-60 is also the most active DprE1 inhibitor derived from CADD so far. Further studies confirmed their high affinity to DprE1, good safety profiles to gut microbiota and human cells, and synergy effects with either rifampicin or ethambutol, indicating their broad potential for clinical applications.

The D-SPECT SH reconstruction protocol: improved quantification of small left ventricle volumes.

BACKGROUND: Due to spatial resolution limitations, conventional NaI-SPECT typically overestimates the left ventricular (LV) ejection fraction (EF) in patients with small LV volumes. The purpose of this study was to explore the clinical application value of the small heart (SH) reconstruction protocol embedded in the postprocessing procedure of D-SPECT. METHODS: We retrospectively analyzed patients who undergo both D-SPECT and echocardiography (Echo) within one week. Patients with small LV volume were defined as those with a rest end-systolic volume (rESV) ≤ 25 mL and underwent reconstruction using the standard (SD) reconstruction protocol. The SH protocol was deemed successful in correcting the LVEF value if it decreased by 5% or more compared to the SD protocol. The ROC curve was used to calculate the optimal cutoff value of the SH protocol. LVEF, ESV and EDV were computed with SD and SH, respectively. Echo was performed as a reference, and Echo-LVEF, ESV, and EDV were calculated using the Teichholz formula. One-way ANOVA was used to compare these parameters among the three groups. RESULTS: The final study included 209 patients (73.21% female, age 67.34 ± 7.85 years). Compared with the SD protocol, the SH protocol significantly decreased LVEF (67.43 ± 7.38% vs. 71.30 ± 7.61%, p < 0.001). The optimal cutoff value for using the SH protocol was rESV > 17 mL (AUC = 0.651, sensitivity = 78.43%, specificity = 45.57%, p = 0.001). In the subgroup of rESV > 17 mL, there was no significant difference in LVEF (61.84 ± 4.67% vs. 62.83 ± 2.85%, p = 0.481) between the SH protocol and Echo, and no significant difference was observed in rESV (26.92 ± 3.25 mL vs. 27.94 ± 7.96 mL, p = 0.60) between the SH protocol and Echo. CONCLUSION: This pilot study demonstrated that the SH reconstruction protocol was able to effectively correct the overestimation of LVEF in patients with small LV volumes. Particularly, in the rESV > 17 mL subgroup, the time and computing power waste could be reduced while still ensuring the accuracy of the LVEF value and image quality.

Chemical Evolution and Biological Evaluation of Natural Products for Efficient Therapy of Acute Lung Injury.

Acute lung injury (ALI) is one of the most common complications in COVID-19 and also a syndrome of acute respiratory failure with high mortality rates, but lacks effective therapeutic drugs. Natural products provide inspiration and have proven to be the most valuable source for bioactive molecule discovery. In this study, the chemical evolution of the natural product Tanshinone IIA (Tan-IIA) to achieve a piperidine-fused scaffold through a synthetic route of pre-activation, multi-component reaction, and post-modification is presented. Through biological evaluation, it is pinpointed that compound 8b is a standout candidate with remarkable anti-inflammation and anti-oxidative stress properties, coupled with low toxicity. The mechanistic study unveils a multifaceted biological profile of 8b and shows that 8b is highly efficient in vivo for the treatment of ALI. Therefore, this work not only provides an effective strategy for the treatment of ALI, but also offers a distinctive natural product-inspired drug discovery.