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Yi Bi

Bio: Yi Bi is an academic researcher from Yantai University. The author has contributed to research in topics: Antibacterial activity & Fusidic acid. The author has an hindex of 11, co-authored 34 publications receiving 410 citations.

Papers
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Patent
16 Jan 2013
TL;DR: In this article, the (20S,24S)-ocotillol ginsenoside derivatives were disclosed as general formula (I) and a preparation method of the ( 20S, 24S) ginsenoide derivatives was described.
Abstract: The invention relates to the fields of organic synthesis and pharmacochemistry, particularly (20S,24S)-ocotillol ginsenoside derivatives, of which the structure is disclosed as general formula (I). The invention also discloses a preparation method of the (20S,24S)-ocotillol ginsenoside derivatives, a pharmaceutical composition containing the (20S,24S)-ocotillol ginsenoside derivatives, and application of the (20S,24S)-ocotillol ginsenoside derivatives in bacterial infection disease inhibition. General formula (I).

8 citations

Journal ArticleDOI
TL;DR: Fusidic acid is a narrow-spectrum bacteriostatic antibiotic and a FA derivative modified by an amino-terminal group at the 3-OH position, namely 2, inhibited the growth of Cryptococcus neoformans.
Abstract: Aim: Fusidic acid (FA) is a narrow-spectrum bacteriostatic antibiotic. We inadvertently discovered that a FA derivative modified by an amino-terminal group at the 3-OH position, namely 2, inhibited the growth of Cryptococcus neoformans. Methods & results: Multiscale molecular modeling approaches were used to analyze the binding modes of 2 with eEF2. FA derivatives modified at the 3-OH position were designed based on in silico models; seven derivatives possessing different amino-terminal groups were synthesized and tested in vitro for antifungal activity against C. neoformans. Conclusion: Compound 7 had the strongest minimum inhibitory concentration. Two protonated nitrogen atoms of 7 interacted with a negative electrostatic pocket of eEF2 likely explain the superiority of 7-2.

8 citations

Journal ArticleDOI
Long Junjun1, Ji Wentao1, Doudou Zhang1, Yifei Zhu1, Yi Bi1 
TL;DR: Fusidic acid (FA) is a natural tetracyclic triterpene isolated from fungi, which is clinically used for systemic and local staphylococcal infections, including methicillin-resistant Staphylitis aureus and coagulase-negative staphlyococci infections as discussed by the authors.
Abstract: Fusidic acid (FA) is a natural tetracyclic triterpene isolated from fungi, which is clinically used for systemic and local staphylococcal infections, including methicillin-resistant Staphylococcus aureus and coagulase-negative staphylococci infections. FA and its derivatives have been shown to possess a wide range of pharmacological activities, including antibacterial, antimalarial, antituberculosis, anticancer, tumor multidrug resistance reversal, anti-inflammation, antifungal, and antiviral activity in vivo and in vitro. The semisynthesis, structural modification and biological activities of FA derivatives have been extensively studied in recent years. This review summarized the biological activities and structure-activity relationship (SAR) of FA in the last two decades. This summary can prove useful information for drug exploration of FA derivatives.

7 citations

Journal ArticleDOI
TL;DR: 28-hydroxyl of 17 was built successfully as a derivatized site of molecular probe’s functional and report groups and provided a valuable basis for probe research of PPD.

7 citations

Journal ArticleDOI
TL;DR: The accurate prediction model and the chemical toxicophores can provide some guidance for designing drugs with low toxicity.
Abstract: Background Chemical toxicity is an important reason for late-stage failure in drug RD (II) Mutagenicity; (III) Tumorigenicity; (IV) Skin and Eye Irritation; (V) Reproductive Effects; (VI) Multiple Dose Effects, using local lazy learning (LLL) method for multi-label learning. 17,120 compounds were split into the training set and the test set as a ratio of 4:1 by using the Kennard-Stone algorithm. Four types of properties, including molecular fingerprints (ECFP_4 and FCFP_4), descriptors, and chemical-chemical-interactions, were adopted for model building. Results The model 'ECFP_4+LLL' yielded the best performance for the test set, while balanced accuracy (BACC) reached 0.692, 0.691, 0.666, 0.680, 0.631, 0.599 for six types of toxicities, respectively. Furthermore, some essential toxicophores for six types of toxicities were identified by using the Laplacian-modified Bayesian model. Conclusion The accurate prediction model and the chemical toxicophores can provide some guidance for designing drugs with low toxicity.

6 citations


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Journal ArticleDOI
TL;DR: This review highlights the trends in the use of nitrogen-based moieties in drug design and the development of different potent and competent candidates against various diseases.
Abstract: The analogs of nitrogen-based heterocycles occupy an exclusive position as a valuable source of therapeutic agents in medicinal chemistry. More than 75% of drugs approved by the FDA and currently available in the market are nitrogen-containing heterocyclic moieties. In the forthcoming decade, a much greater share of new nitrogen-based pharmaceuticals is anticipated. Many new nitrogen-based heterocycles have been designed. The number of novel N-heterocyclic moieties with significant physiological properties and promising applications in medicinal chemistry is ever-growing. In this review, we consolidate the recent advances on novel nitrogen-containing heterocycles and their distinct biological activities, reported over the past one year (2019 to early 2020). This review highlights the trends in the use of nitrogen-based moieties in drug design and the development of different potent and competent candidates against various diseases.

587 citations

Journal ArticleDOI
TL;DR: Computational approaches are reviewed and highlighted their characteristics to provide references for researchers to develop more powerful approaches and to summarized 76 important resources about drug repositioning.
Abstract: Drug discovery is a time-consuming, high-investment, and high-risk process in traditional drug development. Drug repositioning has become a popular strategy in recent years. Different from traditional drug development strategies, the strategy is efficient, economical and riskless. There are usually three kinds of approaches: computational approaches, biological experimental approaches, and mixed approaches, all of which are widely used in drug repositioning. In this paper, we reviewed computational approaches and highlighted their characteristics to provide references for researchers to develop more powerful approaches. At the same time, the important findings obtained using these approaches are listed. Furthermore, we summarized 76 important resources about drug repositioning. Finally, challenges and opportunities in drug repositioning are discussed from multiple perspectives, including technology, commercial models, patents and investment.

407 citations

Journal ArticleDOI
TL;DR: The development of in silico models for some physicochemical parameters, ADME properties and toxicity evaluation, with an emphasis on the modelling approaches thereof, their application in drug discovery, and the potential merits or deficiencies of these models are introduced.
Abstract: In recent decades, in silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) modelling as a tool for rational drug design has received considerable attention from pharmaceutical scientists, and various ADME/T-related prediction models have been reported. The high-throughput and low-cost nature of these models permits a more streamlined drug development process in which the identification of hits or their structural optimization can be guided based on a parallel investigation of bioavailability and safety, along with activity. However, the effectiveness of these tools is highly dependent on their capacity to cope with needs at different stages, e.g. their use in candidate selection has been limited due to their lack of the required predictability. For some events or endpoints involving more complex mechanisms, the current in silico approaches still need further improvement. In this review, we will briefly introduce the development of in silico models for some physicochemical parameters, ADME properties and toxicity evaluation, with an emphasis on the modelling approaches thereof, their application in drug discovery, and the potential merits or deficiencies of these models. Finally, the outlook for future ADME/T modelling based on big data analysis and systems sciences will be discussed.

198 citations

Journal ArticleDOI
TL;DR: Gas‐generating nanoplplatforms (GGNs) have emerged very recently as unique theranostic nanoplatforms for broad gas therapies by either exogenous physical triggers or endogenous disease‐environment responsiveness, and have been successfully developed for versatile biomedical applications, including diagnostic imaging and therapeutic use.
Abstract: The fast advances of theranostic nanomedicine enable the rational design and construction of diverse functional nanoplatforms for versatile biomedical applications, among which gas-generating nanoplatforms (GGNs) have emerged very recently as unique theranostic nanoplatforms for broad gas therapies. Here, the recent developments of the rational design and chemical construction of versatile GGNs for efficient gas therapies by either exogenous physical triggers or endogenous disease-environment responsiveness are reviewed. These gases involve some therapeutic gases that can directly change disease status, such as oxygen (O2 ), nitric oxide (NO), carbon monoxide (CO), hydrogen (H2 ), hydrogen sulfide (H2 S) and sulfur dioxide (SO2 ), and other gases such as carbon dioxide (CO2 ), dl-menthol (DLM), and gaseous perfluorocarbon (PFC) for supplementary assistance of the theranostic process. Abundant nanocarriers have been adopted for gas delivery into lesions, including poly(d,l-lactic-co-glycolic acid), micelles, silica/mesoporous silica, organosilica, MnO2 , graphene, Bi2 Se3 , upconversion nanoparticles, CaCO3 , etc. Especially, these GGNs have been successfully developed for versatile biomedical applications, including diagnostic imaging and therapeutic use. The biosafety issue, challenges faced, and future developments on the rational construction of GGNs are also discussed for further promotion of their clinical translation to benefit patients.

193 citations