Management of Combined Atlas Fracture with Type II Odontoid Fracture: A Review of 21 Cases.

PURPOSE: To evaluate the therapeutic effects of combined atlas fracture with type II (C1-type II) odontoid fractures and to outline a management strategy for it. PATIENTS AND METHODS: Twenty three patients with C1-type II odontoid fractures were treated according to our management strategy. Nonoperative external immobilization in the form of cervical collar and halo vest was used in 13 patients with stable atlantoaxial joint. Surgical treatment was early performed in 10 patients whose fractures with traumatic transverse atlantal ligament disruption or atlantoaxial instability. The visual analog scale (VAS), neck disability index (NDI) scale, and American Spinal Injury Association (ASIA) scale at each stage of followup were then collected and compared. RESULTS: Compared to pretreatment, the VAS score, NDI score, and ASIA scale were improved among both groups at followup evaluation after treatment. However, in the nonsurgical group, one patient (1/11) developed nonunion which required surgical treatment in later stage and one patient (1/13) with halo vest immobilization had happened pin site infection. Two patients of the surgical group (2/11) had appeared minor complications: occipital cervical pain in one case and cerebrospinal fluid leakage in one case. Two patients (2/23) were excluded from nonsurgical treatment group because their followup period was less than 12 months. Twenty one patients were followed up regularly with an average of 23.9 months (range 15-45 months). CONCLUSIONS: We outlined our concluding management principle for the treatment of C1-type II odontoid fractures based on the nature of C1 fracture and atlantoaxial stability. The treatment principle can obtain satisfactory results for the management of C1-type II odontoid fractures.

Interactions of Bovine Serum Albumin with Anti-Cancer Compounds Using a ProteOn XPR36 Array Biosensor and Molecular Docking.

The aim of the work was to determine the interactions of a set of anti-cancer compounds with bovine serum albumin (BSA) using a ProteOn XPR36 array biosensor and molecular docking studies. The results revealed that a total of six anti-cancer compounds: gallic acid, doxorubicin, acteoside, salvianolic acid B, echinacoside, and vincristine were able to reversibly bind to the immobilized BSA. The sensorgrams of these six compounds were globally fit to a Langmuir 1:1 interaction model for binding kinetics analysis. There were significant differences in their affinity for BSA, with doxorubicin, the weakest binding compound having 1000-fold less affinity than salvianolic acid B, the strongest binding compound. However, compounds with a similar KD often exhibited markedly different kinetics due to the differences in ka and kd. Molecular docking experiments demonstrated that acteoside was partially located within sub-domain IIA of BSA, whereas gallic acid bound to BSA deep within its sub-domain IIIA. In addition, the interactions between these compounds and BSA were dominated by hydrophobic forces and hydrogen bonds. Understanding the detailed information of these anti-cancer compounds can provide important insights into optimizing the interactions and activity of potential compounds during drug development.

Deciphering the underlying mechanisms of Diesun Miaofang in traumatic injury from a systems pharmacology perspective.

Diesun Miaofang (DSMF) is a traditional herbal formula, which has been reported to activate blood, remove stasis, promote qi circulation and relieve pain. DSMF holds a great promise for the treatment of traumatic injury in an integrative and holistic manner. However, its underlying mechanisms remain to be elucidated. In the present study, a systems pharmacology model, which integrated cluster ligands, human intestinal absorption and aqueous solution prediction, chemical space mapping, molecular docking and network pharmacology techniques were used. The compounds from DSMF were diverse in the clusters and chemical space. The majority of the compounds exhibited drug-like properties. A total of 59 compounds were identified to interact with 16 potential targets. In the herb-compound-target network, the majority of compounds acted on only one target; however, a small number of compounds acted on a large number of targets, up to a maximum of 12. The comparison of key topological properties in compound-target networks associated with the above efficacy intuitively demonstrated that potential active compounds possessed diverse functions. These results successfully explained the polypharmacological mechanism underlying the efficiency of DSMF for the treatment of traumatic injury as well as provided insight into potential novel therapeutic strategies for traumatic injury from herbal medicine.

Understanding the polypharmacological anticancer effects of Xiao Chai Hu Tang via a computational pharmacological model.

Xiao Chai Hu Tang (XCHT), a traditional herbal formula, is widely administered as a cancer treatment. However, the underlying molecular mechanisms of its anticancer effects are not fully understood. In the present study, a computational pharmacological model that combined chemical space mapping, molecular docking and network analysis was employed to predict which chemical compounds in XCHT are potential inhibitors of cancer-associated targets, and to establish a compound-target (C-T) network and compound-compound (C-C) association network. The identified compounds from XCHT demonstrated diversity in chemical space. Furthermore, they occupied regions of chemical space that were the same, or close to, those occupied by drug or drug-like compounds that are associated with cancer, according to the Therapeutic Targets Database. The analysis of the molecular docking and the C-T network demonstrated that the potential inhibitors possessed the properties of promiscuous drugs and combination therapies. The C-C network was classified into four clusters and the different clusters contained various multi-compound combinations that acted on different targets. The study indicated that XCHT has a polypharmacological role in treating cancer and the potential inhibitory components of XCHT require further investigation as potential therapeutic strategies for cancer patients.

[Comparative research on computer simulation of two different therapeutic principles and formulae for osteoarthritis].

OBJECTIVE: To compare the effect of reinforcing Shen method (RSM) and activating blood method (ABM) in treating osteoarthritis (OA) at the molecular level. METHODS: The physical and chemical characteristics of components from respective recipes of RSM and ABM, and network features of component-target interaction network were analyzed by computer simulation methods including chemical space, molecular docking, and biological network, etc. RESULTS: The chemical components of RSM and ABM were scarcely scattered with larger overlapping. Among established networks, the distribution of network features was partially similar in RSM and ABM. The average target number correlated with each component was 1.86 in RSM and 2.11 in ABM respectively. Each average target number was respectively correlated with 4.46 compounds and 3.93 compounds, reflecting multi-component and multi-target actions. CONCLUSION: Computer simulation could intuitively trace out similarities and differences of two different methods and their interaction with targets, which revealed that the compatibility of RSM and ABM could have broader protein targets and potential synergism at the molecular level.

In silico search for multi-target therapies for osteoarthritis based on 10 common Huoxue Huayu herbs and potential applications to other diseases.

Huoxue Huayu (HXHY) has been widely used in traditional Chinese medicine (TCM) as a key therapeutic principle for osteoarthritis (OA), and related herbs have been widely prescribed to treat OA in the clinic. The aims of the present study were to explore a multi-target therapy for OA using 10 common HXHY herbs and to investigate their potential applications for treatment of other diseases. A novel computational simulation approach that integrates chemical structure, ligand clusters, chemical space and drug­likeness evaluations, as well as docking and network analysis, was used to investigate the properties and effects of the herbs. The compounds contained in the studied HXHY herbs were divided into 10 clusters. Comparison of the chemical properties of these compounds to those of other compounds described in the DrugBank database indicated that the properties of the former are more diverse than those of the latter and that most of the HXHY-derived compounds do not violate the 'Lipinski's rule of five'. Docking analysis allowed for the identification of 39 potential bioactive compounds from HXHY herbs and 11 potential targets for these compounds. The identified targets were closely associated with 49 diseases, including neoplasms, musculoskeletal, nervous system and cardiovascular diseases. Ligand­target (L­T) and ligand­target­disease (L­T­D) networks were constructed in order to further elucidate the pharmacological effects of the herbs. Our findings suggest that a number of compounds from HXHY herbs are promising candidates for mult­target therapeutic application in OA and may exert diverse pharmacological effects, affecting additional diseases besides OA.

Computational pharmacological comparison of Salvia miltiorrhiza and Panax notoginseng used in the therapy of cardiovascular diseases.

The herb pair comprising Salvia miltiorrhiza (SM) and Panax notoginseng (PN) has been used as a classical formula for cardiovascular diseases (CVDs) in China and in western countries. However, the pharmacology of SM and PN in this herb pair has not been fully elucidated. The aim of this study was to compare the mechanisms of SM and PN at the molecular level for the treatment of CVDs. We used a systems pharmacology approach, integrating ligand clustering, chemical space, docking simulation and network analysis, to investigate these two herbal medicines. The compounds in SM were attached to clusters 2, 3, 5, 6, 8 and 9, while the compounds in PN were attached to clusters 1, 2, 4, 5, 6, 7, 8 and 10. The distributions of chemical space between the compounds from SM and PN were discrete, with the existence of small portions of overlap, and the majority of the compounds did not violate 'Lipinski's rule of five'. Docking indicated that the average number of targets correlated with each compound in SM and PN were 5.0 and 3.6, respectively. The minority nodes in the SM and PN drug-target networks possessed common values of betweenness centrality, closeness centrality, topological coefficients and shortest path length. Furthermore, network analyses revealed that SM and PN exerted different modes of action between compounds and targets. These results suggest that the method of computational pharmacology is able to intuitively trace out the similarities and differences of two herbs and their interaction with targets from the molecular level, and that the combination of two herbs may extend their activities in different potential multidrug combination therapies for CVDs.

Network pharmacology-based prediction of the multi-target capabilities of the compounds in Taohong Siwu decoction, and their application in osteoarthritis.

Taohong Siwu decoction (THSWD), a formulation prescribed in traditional Chinese medicine (TCM), has been widely used in the treatment of osteoarthritis (OA). TCM has the potential to prevent diseases, such as OA, in an integrative and holistic manner. However, the system-level characterization of the drug-target interactions of THSWD has not been elucidated. In the present study, we constructed a novel modeling system, by integrating chemical space, virtual screening and network pharmacology, to investigate the molecular mechanism of action of THSWD. The chemical distribution of the ligand database and the potential compound prediction demonstrated that THSWD, as a natural combinatorial chemical library, comprises abundant drug-like and lead-like compounds that may act as potential inhibitors for a number of important target proteins associated with OA. Moreover, the results of the 'compound-target network' analysis demonstrated that 19 compounds within THSWD were correlated with more than one target, whilst the maximum degree of correlation for the compounds was seven. Furthermore, the 'target-disease network' indicated that THSWD may potentially be effective against 69 diseases. These results may aid in the understanding of the use of THSWD as a multi-target therapy in OA. Moreover, they may be useful in establishing other pharmacological effects that may be brought about by THSWD. The in silico method used in this study has the potential to advance the understanding of the molecular mechanisms of TCM.

Computational approaches for exploring the potential synergy and polypharmacology of Duhuo Jisheng Decoction in the therapy of osteoarthritis.

The Duhuo Jisheng Decoction (DHJSD), a traditional Chinese medicine (TCM), has been widely used to treat osteoarthritis (OA). However, the mechanisms of action of the DHJSD have not been clearly elucidated. In the present study, the compounds in the DHJSD were characterized by three computational methods; the ligand clustering, chemical space distribution and network construction and analysis methods. The compounds that formed the medical composition of the DHJSD were divided into 10 clusters and possessed a broad diversity in chemical space distribution. The compounds also had the same coverage of chemical space as the OA drug/drug­like compounds from DrugBank. In addition, multiple active compounds were identified as able to target multiple proteins in the drug­target association networks (D­T networks). A certain number of key compounds in the D­T networks have been previously reported in the literature. The present study also constructed drug­drug association networks (D­D networks) and classified the DHJSD compounds into five clusters. The clusters represented multiple diverse combinations binding to the OA targets. These results suggested that the DHJSD had drug­ and lead­like compounds with potential synergy and polypharmacology against OA.

[Computational simulation of multi-target research on the material basis of Caulis sinomenii in treating osteoarthritis].

OBJECTIVE: To explore the material basis of Caulis sinomenii (CS) in treating osteoarthritis (OA), and to give a pharmacodynamic illustration for the multi-targeting therapeutics of CS. METHODS: The computational methods, consisting of molecular docking and biological network were carried out to search the database targeting twelve important OA related enzymes: ASAMTS4, ASAMTS5, MMP-1, MMP-3, MMP-13, MMP-8, MMP-2, COX-2, COX-1, IL-1beta, TNF-alpha, iNOS, and map the ligand-target interaction networks about molecules from CS and DrugBank. After that, an aggregate analysis was performed to analyze the mechanisms of compositions in CS. RESULTS: Totally 14 had good interaction in all molecules in database with two or more than two of the OA correlated enzymes, and 6 molecules had interaction with four or more enzymes. Moreover, both herb ligand-target interaction network and drug ligand-target interaction network were similar in the interaction profiles and network features, which revealed multi-drugs effects in CS. CONCLUSIONS: There were a lot of multi-target molecules in CS, providing pharmacodynamic illustrations for the multi-target therapeutics of Chinese medicine. Meanwhile, they supplied certain reference and inspiration for finding out new drugs for OA therapy.

Potential synergistic and multitarget effect of herbal pair Chuanxiong Rhizome-Paeonia Albifora Pall on osteoarthritis disease: a computational pharmacology approach.

OBJECTIVE: To study the polypharmacological mechanism of herbal pair Chuanxiong Rhizome-Paeonia Albifora Pall (HP CXR-PAP) on the treatment for osteoarthritis (OA). METHODS: Chemical space was used to discuss the similarities and differences between the molecule sets of HP CXR-PAP and drugs. Docking protocol was used to study the interaction between HP CXR-PAP and OA target enzymes. The similarities and differences of HP CXR-PAP and drugs in target spaces were elucidated by network features. RESULTS: The plots between the molecule sets of HP CXR-PAP and drugs in chemical space had the majority in the same region, and compounds from HP CXR-PAP covered a much larger additional region of space than drug molecules, which denoted the diverse structural properties in the molecule set of HP CXR-PAP. The molecules in HP CXR-PAP had the properties of promiscuous drugs and combination drug, and both HP CXR-PAP ligand-target interaction network and drug ligand-target interaction network were similar in the interaction profiles and network features, which revealed the effects of multicomponent and multitarget. CONCLUSION: The clue of potential synergism was obtained in curing OA disease by Chinese medicine, which revealed the advantages of Chinese medicine for targeting osteoarthritis disease.

Computational pharmacology study of tougu xiaotong granule in preventing and treating knee osteoarthritis.

OBJECTIVE: To study the pharmacological properties of Tougu Xiaotong Granule (TGXTG) in preventing and treating knee osteoarthritis (KOA) at the molecular level. METHODS: The computational methods, including principal component analysis, molecular docking, target-ligand space distribution, and the predictions of absorption, distribution, metabolism, excretion and toxicity (ADMET), were introduced to characterize the molecules in TGXTG. RESULTS: The structural properties of molecules in TGXTG were more: diverse than those of the drug/drug-like molecules, and TGXTG could interact with significant target enzymes related to KOA. In addition, the cluster of effective components was preliminarily identified by the target-ligand space distributions. As to the results of ADMET properties, some of them were unsatisfactory, and were merely regarded as references here. CONCLUSION: Based on this computational pharmacology study, TGXTG is a broad-spectrum recipe inhibiting many important target enzymes, which could effectively postpone the degeneration of spectrum cartilage by coordinately inhibiting the biological effects of cytokines, matrix metallopeptidase 3, and oxygen free radicals. radicals.