Polypharmacology, which focuses on designing therapeutics to target multiple receptors, has emerged as a new paradigm in drug discovery. Polypharmacological effects are an attribute of most, if not ...all, drug molecules. The efficacy and toxicity of drugs, whether designed as single- or multitarget therapeutics, result from complex interactions between pharmacodynamic, pharmacokinetic, genetic, epigenetic, and environmental factors. Ultimately, to predict a drug response phenotype, it is necessary to understand the change in information flow through cellular networks resulting from dynamic drug-target interactions and the impact that this has on the complete biological system. Although such is a future objective, we review recent progress and challenges in computational techniques that enable the prediction and analysis of in vitro and in vivo drug-response phenotypes.
Microbes are associated with many human diseases and influence drug efficacy. Small-molecule drugs may revolutionize biomedicine by fine-tuning the microbiota on the basis of individual patient ...microbiome signatures. However, emerging endeavors in small-molecule microbiome drug discovery continue to follow a conventional "one-drug-one-target-one-disease" process. A systematic pharmacology approach that would suppress multiple interacting pathogenic species in the microbiome, could offer an attractive alternative solution. We construct a disease-centric signed microbe-microbe interaction network using curated microbe metabolite information and their effects on host. We develop a Signed Random Walk with Restart algorithm for the accurate prediction of effect of microbes on human health and diseases. With a survey on the druggable and evolutionary space of microbe proteins, we find that 8-10% of them can be targeted by existing drugs or drug-like chemicals and that 25% of them have homologs to human proteins. We demonstrate that drugs for diabetes can be the lead compounds for development of microbiota-targeted therapeutics. We further show that the potential drug targets that specifically exist in pathogenic microbes are periplasmic and cellular outer membrane proteins. The systematic studies of the polypharmacological landscape of the microbiome network may open a new avenue for the small-molecule drug discovery of the microbiome. We believe that the application of systematic method on the polypharmacological investigation could lead to the discovery of novel drug therapies.
Phenotype-based compound screening has advantages over target-based drug discovery, but is unscalable and lacks understanding of mechanism. Chemical-induced gene expression profile provides a ...mechanistic signature of phenotypic response. However, the use of such data is limited by their sparseness, unreliability, and relatively low throughput. Few methods can perform phenotype-based
chemical compound screening. Here, we propose a mechanism-driven neural network-based method DeepCE, which utilizes graph neural network and multi-head attention mechanism to model chemical substructure-gene and gene-gene associations, for predicting the differential gene expression profile perturbed by
chemicals. Moreover, we propose a novel data augmentation method which extracts useful information from unreliable experiments in L1000 dataset. The experimental results show that DeepCE achieves superior performances to state-of-the-art methods. The effectiveness of gene expression profiles generated from DeepCE is further supported by comparing them with observed data for downstream classification tasks. To demonstrate the value of DeepCE, we apply it to drug repurposing of COVID-19, and generate novel lead compounds consistent with clinical evidence. Thus, DeepCE provides a potentially powerful framework for robust predictive modeling by utilizing noisy omics data and screening novel chemicals for the modulation of a systemic response to disease.
Here, a scalable, accurate, reliable, and robust protein functional site comparison algorithm is presented. The key components of the algorithm consist of a reduced representation of the protein ...structure and a sequence order-independent profile-profile alignment (SOIPPA). We show that SOIPPA is able to detect distant evolutionary relationships in cases where both a global sequence and structure relationship remains obscure. Results suggest evolutionary relationships across several previously evolutionary distinct protein structure superfamilies. SOIPPA, along with an increased coverage of protein fold space afforded by the structural genomics initiative, can be used to further test the notion that fold space is continuous rather than discrete.
The 2021 Maduo earthquake caused ∼160 km-long complex coseismic surface rupture and postseismic deformation. However, the afterslip pattern and primary reason for the overlapped coseismic slip and ...afterslip in shallow portion in Maduo earthquake are still unclear. Here, we used ∼0.85 yr Sentinel-1 data to obtain the time-dependent postseismic deformation of the 2021 Mw 7.3 Maduo earthquake and inverted afterslip distribution. We calculated the frictional parameter of the seismogenic fault based on the time series afterslip and depicted the rupture surface based on three-dimensional coseismic displacement. Our findings indicated that the more considerable postseismic deformation in the near-field was concentrated on the bending region near the epicenter. The maximum afterslip was ∼0.35 m in the shallow upper crust. The shallow afterslip overlapped with the coseismic rupture, mainly caused by the low frictional parameter (a – b = 0.002) and shear heating in the shallow region. The fault geometry was gentle in the supershear rupture area, while changed substantially in the west of the epicenter. This highlights that the fault bending could have controlled both coseismic and postseismic deformation pattern in near-field. It also indicates that fault bending controls the stress propagation for large strike-slip fault, which provides a new perspective for seismic risk assessment of other strike-slip faults in the Bayan Har block.
•InSAR time series reveal a far-field relaxation time of 20 days and a near-field relaxation time of 6 days.•The dynamic weakening causes overlap between the coseismic and postseismic slip in the shallow crust.•The complex fault geometry controls the near-field deformation pattern of the 2021 Maduo earthquake.
Spatiotemporal distribution of early afterslip is essential for seismic hazard evaluation and determination of fault friction properties. In this study, we used early post-seismic COSMO-SkyMed (19 ...February 2014–08 April 2014) and long-term Sentinel-1 (16 October 2014–17 June 2020) observations from multiple platforms over different periods to create a rate decay model driven by post-seismic afterslip. The combined observations provide full coverage of the post-seismic deformation following the 2014 Yutian Mw 6.9 earthquake that occurred at the southwestern end of the Altyn Tagh Fault. The observation and modeling results showed that post-seismic deformation was characterized by left-lateral strike-slip movement with minor normal slip, which was consistent with that of co-seismic rupture. The maximum early afterslip (7–55 days) was as large as approximately 0.09 m with a depth of 7 km in the west of co-seismic rupture, and the maximum long-term afterslip was about 0.24 m. The simulated post-seismic deformation caused by poroelastic rebound and viscoelastic relaxation suggests that the afterslip mechanism controls the post-seismic deformation. The coupling pattern of the aftershock and afterslip indicates that the aftershock was mainly caused by the afterslip. The post-seismic spatiotemporal features of the 2014 Yutian earthquake have significant implications for analyzing seismic hazards at the southwestern end of the Altyn Tagh Fault.
Multimodal combinatorial therapy merges different modes of therapies in one platform, which can overcome several clinical challenges such as premature drug loss during blood circulation and ...significantly improve treatment efficiency. Here we report a combinatorial therapy nanoplatform that enables dual photothermal therapy and pH-stimulus-responsive chemotherapy. By super-assembly of mesoporous silica nanoparticles (MSN) with metal-phenolic networks (MPN), anti-cancer drugs can be loaded in the MSN matrix, while the outer MPN coating allows dual photothermal and pH-responsive properties. Upon near-infrared light irradiation, the MSN@MPN nanoplatform exhibits excellent photothermal effect, and demonstrates outstanding pH-triggered drug release property.
In vitro
cell experiments suggest the MSN@MPN system exhibits superior biocompatibility and can effectively kill tumor cells after loading anti-cancer drugs. Consequently, the MSN@MPN system shows promising prospects in clinical application for tumor therapy.
The life cycle of mining results in various patterns of surface deformation as it progresses through development, production, and reclamation. Therefore, the spatial–temporal patterns of ground ...deformation provide a crucial indicator to understand the mining activities, related geohazards, and environmental restoration. This study investigates the decadal deformation (2012–2022) of three coal mines during different stages of mines’ life cycles in Henan, China, using radar interferometry with Radarsat-2 and Sentinel-1 data. The results reveal multiple deformation patterns across different areas: the Changcun mine area changed from ground subsidence to uplift following the termination of exploitation in 2016; the Xiadian mine area has been continuously developing over the past decade, resulting in a cumulative subsidence of 55.6 mm; and the Liyuan mine area exhibits surface rebound at a rate of 7.9 mm/year since its closure in 2007. We also probe the mining geometry of the production process by using a rectangular model. This study highlights the significance of long-term InSAR observations and deformation modeling in elucidating the mining operation dynamics of small mining zones in their production, transition, and post-closure periods, thereby facilitating the management of small-scale mining.
Acute myelitis (AM) mainly presents with paralysis, and sensory and autonomic dysfunction, which affects the daily life and quality of life (QoL) of patients. Reasonable selection of treatment and ...nursing can promote the recovery of patients. It was to explore the effect of oral nanoliposomes combined with home care on the rehabilitation of patients. A total of 100 AM patients who received surgical treatment were enrolled. According to the treatment and nursing methods, they were grouped into a control (oral administration of nanoliposomes plus routine nursing, n=50) and an observation group (oral administration of nanoliposomes plus home care, n=50). Differences between patients' neurological recovery, lower limb muscle strength, activities of daily living, QoL, and satisfaction with quality of care were assessed. As against control, the time of muscle strength to level 2, urination recovery time, walking time, and sensory recovery time was shorter, and the degree of lower limb muscle strength recovery was higher, the Barthel and Newcastle Satisfaction with Nursing Scale (NSNS) scores of daily living ability increased, and the QoL EuroQol-5 dimensions (EQ-5D) score decreased in the observation group (P<0.05). Oral administration of nanoliposome plus home care can promote the recovery of lower limb muscle strength, improve daily living ability and QoL, and improve nursing satisfaction in patients with AM surgery.
The Manta ray foraging optimization (MRFO) is a novel swarm-based metaheuristic optimizer. It is mainly modeled by simulating three foraging behaviors of the Manta rays, which has a good performance. ...However, several drawbacks of MRFO have been noticed by analyzing its mathematical model. Random selection of reference points in the early iterations weakens the exploitation capability of MRFO. Chain foraging tends to lead the algorithm into local optimum. In addition, the algorithm suffers from the deficiency of decreasing population diversity in the late iteration. To address these shortcomings, a modified MRFO using three strategies, called m-MRFO, is proposed in this paper. An elite search pool (ESP) is established in this paper to enhance exploitation capability. By using adaptive control parameter strategies (ACP), we expand the range of MRFO's exploration in the early iterations and enhance the accuracy of exploitation in the later iterations, balancing exploiting and exploring capabilities. Furthermore, we use a distribution estimation strategy (DES) to adjust the evolutionary direction using the dominant population information to promote convergence. The m-MRFO performance was verified by selecting 23 classical test functions and CEC2017 test suite. The significance of the results was also verified by Friedman test, Wilcoxon test and Iman-Davenport test. Moreover, we have confirmed the potential of m-MRFO to solve real-world problems by solving three engineering design problems. The simulation results show that the improvement strategy proposed in this paper can effectively improve the performance of MRFO. m-MRFO is highly competitive.
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