Application of Computer-Aided Drug Design to Traditional Chinese Medicine

Computer-aided drug design (CADD) is an interdisciplinary subject, playing a pivotal role during new drug research and development, especially the discovery and optimization of lead compounds. Traditional Chinese Medicine (TCM) modernization is the only way of TCM development and also an effective approach to the development of new drugs and the discovery of potential drug targets (PDTs). Discovery and validation of PTDs has become the “bottle-neck” restricted new drug research and development and is urgently solved. Innovative drug research is of great significance and bright prospects. This paper mainly discusses the “druggability” and specificity of PTDs, the “druglikeness” of drug candidates, the methods and technologies of the discovery and validation of PTDs and their application. It is very important to achieve the invention and innovation strategy “from gene to drug”. In virtue of modern high-new technology, especially CADD, combined with TCM theory, research and develop TCM and initiate an innovating way fitting our country progress. This paper mainly discusses CADD and their application to drug research, especially TCM modernization.

Application of computer-aided engineering optimum design method in aluminum profile extrusion mould

The finite element analysis and the optimum design of aluminum profile extrusion mould were investigated using the ANSYS software and its parameterized modeling method. The optimum dimensions of the mould were obtained. It is found that the stress distribution is very uneven, and the stress convergence is rather severe in the bridge of the aluminum profile extrusion mould. The optimum height of the mould is 70.527 mm, and the optimum radius of dividing holes are 70.182 mm and 80.663 mm. Increasing the height of the mould in the range of 61.282 mm to 70.422 mm can prolong its longevity, but when the height is over 70.422 mm, its longevity reduces.

Integrated computer-aided formulation design:A case study of andrographolide/cyclodextrin ternary formulation

Current formulation development strongly relies on trial-and-error experiments in the laboratory by pharmaceutical scientists,which is time-consuming,high cost and waste materials.This research aims to integrate various computational tools,including machine learning,molecular dynamic simulation and physiologically based absorption modeling(PBAM),to enhance andrographolide(AG)/cyclodextrins(CDs)formulation design.The light GBM prediction model we built before was utilized to predict AG/CDs inclusion's binding free energy.AG/γ-CD inclusion complexes showed the strongest binding affinity,which was experimentally validated by the phase solubility study.The molecular dynamic simulation was used to investigate the inclusion mechanism between AG andγ-CD,which was experimentally characterized by DSC,FTIR and NMR techniques.PBAM was applied to simulate the in vivo behavior of the formulations,which were validated by cell and animal experiments.Cell experiments revealed that the presence of D-α-Tocopherol polyethylene glycol succinate(TPGS)significantly increased the intracellular uptake of AG in MDCKMDR1 cells and the absorptive transport of AG in MDCK-MDR1 monolayers.The relative bioavailability of the AG-CD-TPGS ternary system in rats was increased to 2.6-fold and 1.59-fold compared with crude AG and commercial dropping pills,respectively.In conclusion,this is the first time to integrate various computational tools to develop a new AG-CD-TPGS ternary formulation with significant improvement of aqueous solubility,dissolution rate and bioavailability.The integrated computational tool is a novel and robust methodology to facilitate pharmaceutical formulation design.

Computer-Aided Design of Some Advanced Steels and Cemented Carbides

Thermodynamic and kinetic study on TRIP （transformation induced plasticity） steels, cemented carbides and mold steel for plastics were carried out in order to design modern advanced materials. With the sublattice model, equilibrium compositions of ferrite and austenite phases in TRIP steels, as well as volume fraction of austenite at inter-critical temperatures for different time were calculated. Concentration profiles of carbon, manganese, aluminum and silicon in the steels were also estimated in the lattice fixed frame of reference. The effect of Si and Mn on TRIP was discussed according to thermodynamic and kinetic analyses. In order to understand and produce the graded nanophase structure of cemented carbides, miscellaneous phases in the M-Co-C （M= Ti, Ta, Nh） systems and Co-V-C system were modeled. Solution parameters and thermodynamic： properties were listed in detail. The improvement of machining behavior of prehardened mould steel for plastics was obtained by computer-aided composition design. The results showed that the matrix composition of large-section prehardened mould steel for plastic markedly influences the precipitation of non-metallic inclusion and the composition control by the aid of Thermo-Calc software package minimizes the amount of detrimental oxide inclusion. In addition, the modification of calcium was optimized in composition design.

Computer-aided designing and manufacturing of advanced steels

Suitable optimization and simulation were performed using a powerful software package with a mature database as well as modem measurement facilities, which led to the successful designing and manufacturing of advanced steels. In the course of designing, the composition of a large section of prehardened mold steel for plastics was estimated so as to lower the quantities of oxide inclusions to change the type of carbides and to raise the machinability. The composition and process were adjusted to obtain satisfactory surface quality for the prevailing galvanization in transformation-induced plasticity （TRIP） steel. The refuting process of low-carbon steel was simulated in the light of both Thermo-Calc and Factsage. Thermodynamic and kinetic analyses were always conducted during the test and the procedure.

A Computer-aided Design System for Framed-mould in Autoclave Processing

The general computer-aided design （CAD） software cannot meet the mould design requirement of the autoclave process for composites, because many parameters such as temperature and pressure should be considered in the mould design process, in addition to the material and geometry of the part. A framed-mould computer-aided design system （FMCAD） used in the autoclave moulding process is proposed in this paper. A function model of the software is presented, in which influence factors such as part structure, mould structure, and process parameters are considered; a design model of the software is established using object oriented （O-O） technology to integrate the stiffness calculation, temperature field calculation, and deformation field calculation of mould in the design, and in the design model, a hybrid model of mould based on calculation feature and form feature is presented to support those calculations. A prototype system is developed, in which a mould design process wizard is built to integrate the input information, calculation, analysis, data storage, display, and design results of mould design. Finally, three design examples are used to verify the prototype.

A Novel Human Antibody,HF,against HER2/erb-B2 Obtained by a Computer-Aided Antibody Design Method

Fully human antibodies have minimal immunogenicity and safety profiles.At present,most potential antibody drugs in clinical trials are humanized or fully human.Human antibodies are mostly generated using the phage display method(in vitro)or by transgenic mice(in vivo);other methods include B lymphocyte immortalization,human–human hybridoma,and single-cell polymerase chain reaction.Here,we describe a structure-based computer-aided de novo design technology for human antibody generation.Based on the complex structure of human epidermal growth factor receptor 2(HER2)/Herceptin,we first designed six short peptides targeting the potential epitope of HER2 recognized by Herceptin.Next,these peptides were set as complementarity determining regions in a suitable immunoglobulin frame,giving birth to a novel anti-HER2 antibody named "HF,"which possessed higher affinity and more effective anti-tumor activity than Herceptin.Our work offers a useful tool for the quick design and selection of novel human antibodies for basic mechanical research as well as for imaging and clinical applications in immune-related diseases,such as cancer and infectious diseases.

Computer-Aided Design and Fabrication of Finger Prosthesis

Custom-made esthetic finger prostheses, which are used for rehabilitation of patients with missing or impaired fingers, have been fabricated manually. However, such fabrication is time-consuming and requires manual skill. Here we propose a computer-aided method for fabricating finger pros-theses to save time and allow fabrications that do not require considerable manual skill. In this method, the dimensions of a patient’s healthy finger on the contralateral hand are first measured using a caliper. Using these dimensions, a three-dimensional model is constructed for fabricating a prosthesis for the patient’s impaired finger. Using the 3D model, a mold is designed using 3D modeling tools and a computer-aided design system. The resulting mold is then fabricated using a 3D printer. A finger prosthesis is fabricated by pouring silicone resin into the mold. A finger prosthesis for a volunteer was experimentally fabricated according to the proposed method. To evaluate the size and shape of the finger prosthesis, the difference between the finger prosthesis and the original finger of the volunteer was analyzed. Because the average difference between them was 0.25 mm, it was concluded that the proposed method could be used to fabricate a finger prosthesis of adequate size and shape.

Computer-Aided Design of X-Ray Microtomographic Scanners

The article is to study the development of computer-aided design of X-ray microtomography—the device for investigating the structure and construction of three-dimensional images of organic and inorganic objects on the basis of shadow projections. This article provides basic information regarding CAD of X-ray microtomography and a scheme consisting of three levels. The article also shows basic relations of X-ray computed tomography, the generalized scheme of an X-ray microtomographic scanner. The methods of X-ray imaging of the spatial microstructure and morphometry of materials are described. The main characteristics of an X-ray microtomographic scanner, the X-ray source, X-ray optical elements and mechanical components of the positioning system are shown. The block scheme and software functional scheme for intelligent neural network system of analysis of the internal microstructure of objects are presented. The method of choice of design parameters of CAD of X-ray microtomography aims at improving the quality of design and reducing costs of it. It is supposed to reduce the design time and eliminate the growing number of engineers involved in development and construction of X-ray microtomographic scanners.

Modern drug discovery for inflammatory bowel disease: The role of computational methods

Inflammatory bowel diseases(IBDs)comprising ulcerative colitis,Crohn’s disease and microscopic colitis are characterized by chronic inflammation of the gastrointestinal tract.IBD has spread around the world and is becoming more prevalent at an alarming rate in developing countries whose societies have become more westernized.Cell therapy,intestinal microecology,apheresis therapy,exosome therapy and small molecules are emerging therapeutic options for IBD.Currently,it is thought that low-molecular-mass substances with good oral bio-availability and the ability to permeate the cell membrane to regulate the action of elements of the inflammatory signaling pathway are effective therapeutic options for the treatment of IBD.Several small molecule inhibitors are being developed as a promising alternative for IBD therapy.The use of highly efficient and time-saving techniques,such as computational methods,is still a viable option for the development of these small molecule drugs.The computeraided(in silico)discovery approach is one drug development technique that has mostly proven efficacy.Computational approaches when combined with traditional drug development methodology dramatically boost the likelihood of drug discovery in a sustainable and cost-effective manner.This review focuses on the modern drug discovery approaches for the design of novel IBD drugs with an emphasis on the role of computational methods.Some computational approaches to IBD genomic studies,target identification,and virtual screening for the discovery of new drugs and in the repurposing of existing drugs are discussed.

Computer-aided molecular design and optimization of potent inhibitors disrupting APC-Asef interaction

Colorectal cancer(CRC)is the second leading cause of cancer mortality worldwide.At initial diagnosis,approximately 20%of patients are diagnosed with metastatic CRC(mCRC).Although the APC-Asef interaction is a well-established target for mCRC therapy,the discovery and development of effective and safe drugs for mCRC patients remains an urgent and challenging endeavor.In this study,we identified a novel structural scaffold based on MAI inhibitors,the first-in-class APC-Asef inhibitors we reported previously.ONIOM model-driven optimizations of the N-terminal cap and experimental evaluations of inhibitory activity were performed,and 24-fold greater potency was obtained with the best inhibitor compared to the parental compound.In addition,the cocrystal structure validated that the two-layerπ-πstacking interactions were essential for inhibitor stabilization in the bound state.Furthermore,in vitro and in vivo studies have demonstrated that novel inhibitors suppressed lung metastasis in CRC by disrupting the APC-Asef interaction.These results provide an intrinsic structural basis to further explore drug-like molecules for APC-Asef-mediated CRC therapy.

Formulation of self-nanoemulsifying drug delivery systems containing monoacyl phosphatidylcholine and Kolliphor^(■) RH40 using experimental design

The development of self-nanoemulsifying drug delivery systems(SNEDDS) to enhance the oral bioavailability of lipophilic drugs is usually based on traditional one-factor-at-a-time approaches. These approaches may be inadequate to analyse the effect of each excipient and their potential interactions on the emulsion droplet size formed when dispersing the SNEDDS in an aqueous environment. The current study investigates the emulsion droplet sizes formed from SNEDDS containing different levels of the natural surfactant monoacyl phosphatidylcholine to reduce the concentration of the synthetic surfactant polyoxyl 40 hydrogenated castor oil(Kolliphor ~? RH40). Monoacyl phosphatidylcholine was used in the form of Lipoid S LPC 80(LPC, containing approximately 80% monoacyl phosphatidylcholine, 13% phosphatidylcholine and 4% concomitant components). The investigated SNEDDS comprised of long-chain or medium-chain glycerides(40% to 75%), Kolliphor ~? RH40(5% to 55%), LPC(0 to 40%) and ethanol(0 to 10%). D-optimal design, multiple linear regression, and partial least square regression were used to screen different SNEDDS within the investigated excipient ranges and to analyse the effect of each excipient on the resulting droplet size of the dispersed SNEDDS measured by dynamic light scattering. All investigated formulations formed nano-emulsions with droplet sizes from about 20 to 200 nm. The use of mediumchain glycerides was more likely to result in smaller and more monodisperse droplet sizes compared to the use of long-chain glycerides. Kolliphor~? RH40 exhibited the most significant effect on reducing the emulsion droplet sizes. Increasing LPC concentration increased the emulsion droplet sizes, possibly because of the reduction of Kolliphor~? RH40 concentration. A higher concentration of ethanol resulted in an insignificant reduction of the emulsion droplet size. The study provides different ternary diagrams of SNEDDS containing LPC and Kolliphor ~? RH40 as a reference for formulation developers.

Organs-on-a-Chip: A Future of Rational Drug-Design

Many recent advances in biomedical research are related to the combination of biology and microengineering. Microfluidic devices, such as organ-on-a-chip systems, integrate with living cells to allow for the detailed in vitro study of human physiology and pathophysiology. With the poor translation from animal models to human models, the organ-on-a-chip technology has become a promising substitute for animal testing, and their small scale enables precise control of culture conditions and high-throughput experiments, which would not be an economically sound model on a macroscopic level. These devices are becoming more and more common in research centers, clinics, and hospitals, and are contributing to more accurate studies and therapies, making them a staple technology for future drug design.

Insights into the structural biology of G-protein coupled receptors impacts drug design for central nervous system neurodegenerative processes

In the last few years, there have been important new insights into the structural biology of G-protein coupled receptors. It is now known that allosteric binding sites are involved in the affinity and selec- tivity of ligands for G-protein coupled receptors, and that signaling by these receptors involves both G-protein dependent and independent pathways. The present review outlines the physiological and pharmacological implications of this perspective for the design of new drugs to treat disorders of the central nervous system. Specifically, new possibilities are explored in relation to allosteric and or- thosteric binding sites on dopamine receptors for the treatment of Parkinson＇s disease, and on muscarinic receptors for Alzheimer＇s disease. Future research can seek to identify ligands that can bind to more than one site on the same receptor, or simultaneously bind to two receptors and form a dimer. For example, the design of bivalent drugs that can reach homo/hetero-dimers of D2 dopa- mine receptor holds promise as a relevant therapeutic strategy for Parkinson＇s disease. Regarding the treatment of Alzheimer＇s disease, the design of dualsteric ligands for mono-oligomeric mus- carinic receptors could increase therapeutic effectiveness by generating potent compounds that could activate more than one signaling pathway.

Deep Learning in Medical Imaging and Drug Design

Over the last decade,deep learning(DL)methods have been extremely successful and widely used in almost every domain.Researchers are now focusing on the convergence of medical imaging and drug design using deep learning to revolutionize medical diagnostic and improvement in the monitoring from response to therapy.DL a new machine learning paradigm that focuses on learning with deep hierarchical models of data.Medical imaging has transformed healthcare science,it was thought of as a diagnostic tool for disease,but now it is also used in drug design.Advances in medical imaging technology have enabled scientists to detect events at the cellular level.The role of medical imaging in drug design includes identification of likely responders,detection,diagnosis,evaluation,therapy monitoring,and follow-up.A qualitative medical image is transformed into a quantitative biomarker or surrogate endpoint useful in drug design decision-making.For this,a parameter needs to be identified that characterizes the disease baseline and its subsequent response to treatment.The result is a quantifiable improvement in healthcare quality in most therapeutic areas,resulting in improvements in quality and life duration.This paper provides an overview of recent studies on applying the deep learning method in medical imaging and drug design.We briefly discuss the fields related to the history of deep learning,medical imaging,and drug design.

Applications and prospects of cryo-EM in drug discovery

Drug discovery is a crucial part of human healthcare and has dramatically benefited human lifespan and life quality in recent centuries, however, it is usually time-and effort-consuming. Structural biology has been demonstrated as a powerful tool to accelerate drug development. Among different techniques, cryo-electron microscopy(cryo-EM) is emerging as the mainstream of structure determination of biomacromolecules in the past decade and has received increasing attention from the pharmaceutical industry. Although cryo-EM still has limitations in resolution, speed and throughput, a growing number of innovative drugs are being developed with the help of cryo-EM. Here, we aim to provide an overview of how cryo-EM techniques are applied to facilitate drug discovery. The development and typical workflow of cryo-EM technique will be briefly introduced, followed by its specific applications in structure-based drug design, fragment-based drug discovery, proteolysis targeting chimeras, antibody drug development and drug repurposing. Besides cryo-EM, drug discovery innovation usually involves other state-of-the-art techniques such as artificial intelligence(AI), which is increasingly active in diverse areas. The combination of cryo-EM and AI provides an opportunity to minimize limitations of cryo-EM such as automation, throughput and interpretation of mediumresolution maps, and tends to be the new direction of future development of cryo-EM. The rapid development of cryo-EM will make it as an indispensable part of modern drug discovery.

Exploring unbinding mechanism of drugs from SERT via molecular dynamics simulation and its implication in antidepressants

The human serotonin transporter(SERT)terminates neurotransmission by removing serotonin from the synaptic cleft,which is an essential process that plays an important role in depression.In addition to natural substrate serotonin,SERT is also the target of the abused drug cocaine and,clinically used antidepressants,escitalopram,and paroxetine.To date,few studies have attempted to investigate the unbinding mechanism underlying the orthosteric and allosteric modulation of SERT.In this article,the conserved property of the orthosteric and allosteric sites(S1 and S2)of SERT was revealed by combining the high resolutions of x-ray crystal structures and molecular dynamics(MD)simulations.The residues Tyr95 and Ser438 located within the S1 site,and Arg104 located within the S2 site in SERT illustrate conserved interactions(hydrogen bonds and hydrophobic interactions),as responses to selective serotonin reuptake inhibitors.Van der Waals interactions were keys to designing effective drugs inhibiting SERT and further,electrostatic interactions highlighted escitalopram as a potent antidepressant.We found that cocaine,escitalopram,and paroxetine,whether the S1 site or the S2 site,were more competitive.According to this potential of mean force(PMF)simulations,the new insights reveal the principles of competitive inhibitors that lengths of trails from central SERT to an opening were~18A for serotonin and~22 A for the above-mentioned three drugs.Furthermore,the distance between the natural substrate serotonin and cocaine(or escitalopram)at the allosteric site was~3A.Thus,it can be inferred that the potent antidepressants tended to bind at deeper positions of the S1 or the S2 site of SERT in comparison to the substrate.Continuing exploring the processes of unbinding four ligands against the two target pockets of SERT,this study observed a broad pathway in which serotonin,cocaine,escitalopram(at the S1 site),and paroxetine all were pulled out to an opening between MT1b and MT6a,which may be helpful to understand the dissociation mechanism of antidepressants.

分子对接技术在药物设计学教学中的应用

药物设计学是一门涉及新药研究开发程序、方法手段和要求的新兴学科,涵盖多门学科知识,在新药研发类综合型人才培养的知识体系中具有重要地位。本文采用模拟实操教学法,以人参皂苷抗阿尔茨海默病为例,将计算机辅助药物设计中的分子对接技术应用于实战演练,以提升理论教学的效果,加深学生对课堂理论知识的理解,提升学生的创新思维能力和实践运用能力。