Food emergency dispatching method based on optimized fireworks algorithm

In order to solve the problem of food emergency dispatching under emergencies, a food emergency dispatching method based on the optimal fireworks algorithm was proposed. The fitness function was used to measure the individual merits of fireworks, the tabu table was set to avoid the fireworks algorithm falling into the local optimal, and the tournament strategy was adopted as the iterative strategy of fireworks population. The goal of the fitness function is to maximize the satisfaction of demand points and minimize the vehicle travel time.In order to accurately predict the amount of food required at the point of demand, an infectious disease model (SEIR) was used.By comparing with the basic fireworks algorithm and genetic algorithm, the simulation results show that the proposed algorithm has higher computational efficiency and can be used in food emergency dispatching

Structure-Based Target-Specific Screening Leads to Small-Molecule CaMKII Inhibitors

Target-specific scoring methods are more commonly used to identify small-molecule inhibitors among compounds docked to a target of interest. Top candidates that emerge from these methods have rarely been tested for activity and specificity across a family of proteins. In this study we docked a chemical library into CaMKIIδ, a member of the Ca2+ /calmodulin (CaM)-dependent protein kinase (CaMK) family, and re-scored the resulting protein-compound structures using Support Vector Machine SPecific (SVMSP), a target-specific method that we developed previously. Among the 35 selected candidates, three hits were identified, such as quinazoline compound 1 (KIN-1; N4-[7-chloro-2-[(E)-styryl]quinazolin-4-yl]-N1,N1-diethylpentane-1,4-diamine), which was found to inhibit CaMKIIδ kinase activity at single-digit micromolar IC50 . Activity across the kinome was assessed by profiling analogues of 1, namely 6 (KIN-236; N4-[7-chloro-2-[(E)-2-(2-chloro-4,5-dimethoxyphenyl)vinyl]quinazolin-4-yl]-N1,N1-diethylpentane-1,4-diamine), and an analogue of hit compound 2 (KIN-15; 2-[4-[(E)-[(5-bromobenzofuran-2-carbonyl)hydrazono]methyl]-2-chloro-6-methoxyphenoxy]acetic acid), namely 14 (KIN-332; N-[(E)-[4-(2-anilino-2-oxoethoxy)-3-chlorophenyl]methyleneamino]benzofuran-2-carboxamide), against 337 kinases. Interestingly, for compound 6, CaMKIIδ and homologue CaMKIIγ were among the top ten targets. Among the top 25 targets of 6, IC50 values ranged from 5 to 22 μm. Compound 14 was found to be not specific toward CaMKII kinases, but it does inhibit two kinases with sub-micromolar IC50 values among the top 25. Derivatives of 1 were tested against several kinases including several members of the CaMK family. These data afforded a limited structure-activity relationship study. Molecular dynamics simulations with explicit solvent followed by end-point MM-GBSA free-energy calculations revealed strong engagement of specific residues within the ATP binding pocket, and also changes in the dynamics as a result of binding. This work suggests that target-specific scoring approaches such as SVMSP may hold promise for the identification of small-molecule kinase inhibitors that exhibit some level of specificity toward the target of interest across a large number of proteins

A Computational Investigation of Small-Molecule Engagement of Hot Spots at Protein–Protein Interaction Interfaces

The binding affinity of a protein–protein interaction is concentrated at amino acids known as hot spots. It has been suggested that small molecules disrupt protein–protein interactions by either (i) engaging receptor protein hot spots or (ii) mimicking hot spots of the protein ligand. Yet, no systematic studies have been done to explore how effectively existing small-molecule protein–protein interaction inhibitors mimic or engage hot spots at protein interfaces. Here, we employ explicit-solvent molecular dynamics simulations and end-point MM-GBSA free energy calculations to explore this question. We select 36 compounds for which high-quality binding affinity and cocrystal structures are available. Five complexes that belong to three classes of protein–protein interactions (primary, secondary, and tertiary) were considered, namely, BRD4•H4, XIAP•Smac, MDM2•p53, Bcl-xL•Bak, and IL-2•IL-2Rα. Computational alanine scanning using MM-GBSA identified hot-spot residues at the interface of these protein interactions. Decomposition energies compared the interaction of small molecules with individual receptor hot spots to those of the native protein ligand. Pharmacophore analysis was used to investigate how effectively small molecules mimic the position of hot spots of the protein ligand. Finally, we study whether small molecules mimic the effects of the native protein ligand on the receptor dynamics. Our results show that, in general, existing small-molecule inhibitors of protein–protein interactions do not optimally mimic protein–ligand hot spots, nor do they effectively engage protein receptor hot spots. The more effective use of hot spots in future drug design efforts may result in smaller compounds with higher ligand efficiencies that may lead to greater success in clinical trials

Small-molecule CaVα1⋅CaVβ antagonist suppresses neuronal voltage-gated calcium-channel trafficking

Extracellular calcium flow through neuronal voltage-gated CaV2.2 calcium channels converts action potential-encoded information to the release of pronociceptive neurotransmitters in the dorsal horn of the spinal cord, culminating in excitation of the postsynaptic central nociceptive neurons. The CaV2.2 channel is composed of a pore-forming α1 subunit (CaVα1) that is engaged in protein-protein interactions with auxiliary α2/δ and β subunits. The high-affinity CaV2.2α1⋅CaVβ3 protein-protein interaction is essential for proper trafficking of CaV2.2 channels to the plasma membrane. Here, structure-based computational screening led to small molecules that disrupt the CaV2.2α1⋅CaVβ3 protein-protein interaction. The binding mode of these compounds reveals that three substituents closely mimic the side chains of hot-spot residues located on the α-helix of CaV2.2α1 Site-directed mutagenesis confirmed the critical nature of a salt-bridge interaction between the compounds and CaVβ3 Arg-307. In cells, compounds decreased trafficking of CaV2.2 channels to the plasma membrane and modulated the functions of the channel. In a rodent neuropathic pain model, the compounds suppressed pain responses. Small-molecule α-helical mimetics targeting ion channel protein-protein interactions may represent a strategy for developing nonopioid analgesia and for treatment of other neurological disorders associated with calcium-channel trafficking

Small molecules inhibit STAT3 activation, autophagy, and cancer cell anchorage-independent growth

Triple-negative breast cancers (TNBCs) lack the signature targets of other breast tumors, such as HER2, estrogen receptor, and progesterone receptor. These aggressive basal-like tumors are driven by a complex array of signaling pathways that are activated by multiple driver mutations. Here we report the discovery of 6 (KIN-281), a small molecule that inhibits multiple kinases including maternal leucine zipper kinase (MELK) and the non-receptor tyrosine kinase bone marrow X-linked (BMX) with single-digit micromolar IC50s. Several derivatives of 6 were synthesized to gain insight into the binding mode of the compound to the ATP binding pocket. Compound 6 was tested for its effect on anchorage-dependent and independent growth of MDA-MB-231 and MDA-MB-468 breast cancer cells. The effect of 6 on BMX prompted us to evaluate its effect on STAT3 phosphorylation and DNA binding. The compound’s inhibition of cell growth led to measurements of survivin, Bcl-XL, p21WAF1/CIP1, and cyclin A2 levels. Finally, LC3B-II levels were quantified following treatment of cells with 6 to determine whether the compound affected autophagy, a process that is known to be activated by STAT3. Compound 6 provides a starting point for the development of small molecules with polypharmacology that can suppress TNBC growth and metastasis

Small Molecules Engage Hot Spots through Cooperative Binding To Inhibit a Tight Protein–Protein Interaction

Protein–protein interactions drive every aspect of cell signaling, yet only a few small-molecule inhibitors of these interactions exist. Despite our ability to identify critical residues known as hot spots, little is known about how to effectively engage them to disrupt protein–protein interactions. Here, we take advantage of the ease of preparation and stability of pyrrolinone 1, a small-molecule inhibitor of the tight interaction between the urokinase receptor (uPAR) and its binding partner, the urokinase-type plasminogen activator uPA, to synthesize more than 40 derivatives and explore their effect on the protein–protein interaction. We report the crystal structure of uPAR bound to previously discovered pyrazole 3 and to pyrrolinone 12. While both 3 and 12 bind to uPAR and compete with a fluorescently labeled peptide probe, only 12 and its derivatives inhibit the full uPAR·uPA interaction. Compounds 3 and 12 mimic and engage different hot-spot residues on uPA and uPAR, respectively. Interestingly, 12 is involved in a π–cation interaction with Arg-53, which is not considered a hot spot. Explicit-solvent molecular dynamics simulations reveal that 3 and 12 exhibit dramatically different correlations of motion with residues on uPAR. Free energy calculations for the wild-type and mutant uPAR bound to uPA or 12 show that Arg-53 interacts with uPA or with 12 in a highly cooperative manner, thereby altering the contributions of hot spots to uPAR binding. The direct engagement of peripheral residues not considered hot spots through π–cation or salt-bridge interactions could provide new opportunities for enhanced small-molecule engagement of hot spots to disrupt challenging protein–protein interactions

Small molecules inhibit ex vivo tumor growth in bone

Bone is a common site of metastasis for breast, prostate, lung, kidney and other cancers. Bone metastases are incurable, and substantially reduce patient quality of life. To date, there exists no small-molecule therapeutic agent that can reduce tumor burden in bone. This is partly attributed to the lack of suitable in vitro assays that are good models of tumor growth in bone. Here, we take advantage of a novel ex vivo model of bone colonization to report a series of pyrrolopyrazolone small molecules that inhibit cancer cell invasion and ex vivo tumor growth in bone at single-digit micromolar concentration. We find that the compounds modulated the expression levels of genes associated with bone-forming osteoblasts, bone-destroying osteoclasts, cancer cell viability and metastasis. Our compounds provide chemical tools to uncover novel targets and pathways associated with bone metastasis, as well as for the development of compounds to prevent and reverse bone tumor growth in vivo

Hemodynamic Characteristics Associated With Paraclinoid Aneurysm Recurrence in Patients After Embolization

Objective: To investigate the hemodynamic features before and after embolization of paraclinoidal aneurysms using hemodynamic numerical simulation and the influence of embolization on recurrence after embolization.Methods: From January 2016 to December 2017, we enrolled a total of 113 paraclinoidal aneurysms treated with embolization. They were divided into recurrent group and stable group depending on follow-up results. An aneurysm model was generated based on 3D-DSA before and after embolization. The hemodynamic characteristics were analyzed between two groups using Computational fluid dynamic (CFD).Results: In the recurrent group, the peak systolic WSS, OSI and velocity around the aneurysm neck areas prior to embolization were 20.47 ± 3.04 Pa, 0.06 ± 0.02 and 0.07 ± 0.03 m/s, respectively. These values were 23.50 ± 4.11 Pa, 0.06 ± 0.01 and 0.11 ± 0.02 m/s, respectively in the stable group (P > 0.05). The WSS, OSI, velocity around the same areas in the recurrent group after embolization were 35.59 ± 8.75 Pa, 0.07 ± 0.02 and 0.12 ± 0.03 m/s, respectively (P < 0.01). In the stable group, the WSS, OSI and velocity were 13.08 ± 2.89 Pa, 0.04 ± 0.01 and 0.07 ± 0.02 m/s, respectively (P < 0.01). After embolization, the WSS, OSI and velocity around the aneurysm neck areas in the recurrent group were significantly higher than those in the stable group.Conclusions: High peak systolic WSS, OSI and velocity around aneurysm neck areas after embolization of paraclinoidal aneurysms may be important factors leading to recurrence