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Accelerating Factor Xa inhibitor discovery with a de novo drug design pipeline

Chinese Journal of Chemical Engineering 2024年第8期72卷 85-94页

作者： Yujing Zhao Qilei Liu Jian Du Qingwei Meng Liang Sun Lei Zhang State Key Laboratory of Fine Chemicals Frontiers Science Center for Smart Materials Oriented Chemical EngineeringInstitute of Chemical Process Systems EngineeringSchool of Chemical EngineeringDalian University of TechnologyDalian 116024China Ningbo Institute of Dalian University of Technology Ningbo 315016China Shenzhen Shuli Tech Co. LtdShenzhen 518126China Department of Physics City University of Hong KongTat Chee AvenueKowloonHong Kong SARChina

Small-molecule drugs are essential for maintaining human health. The objective of this study is to identify a molecule that can inhibit the Factor Xa protein and be easily procured. An optimization-based de novo drug design framework, Drug CAMD, that integrates a deep learning model with a mixed-integer nonlinear programming model is used for designing drug candidates. Within this framework, a virtual chemical library is specifically tailored to inhibit Factor Xa. To further filter and narrow down the lead compounds from the designed compounds, comprehensive approaches involving molecular docking,binding pose metadynamics(BPMD), binding free energy calculations, and enzyme activity inhibition analysis are utilized. To maximize efficiency in terms of time and resources, molecules for in vitro activity testing are initially selected from commercially available portions of customized virtual chemical libraries. In vitro studies assessing inhibitor activities have confirmed that the compound EN300-331859shows potential Factor Xa inhibition, with an IC_(50)value of 34.57 μmol·L^(-1). Through in silico molecular docking and BPMD, the most plausible binding pose for the EN300-331859-Factor Xa complex are identified. The estimated binding free energy values correlate well with the results obtained from biological assays. Consequently, EN300-331859 is identified as a novel and effective sub-micromolar inhibitor of Factor Xa.

关键词： Chemical product design mathematical programming method Deep learning Binding affinity Factor Xa inhibitor

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A new algorithm for numerical solution of 3D elastoplastic contact problems with orthotropic friction law

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COMPUTATIONAL MECHANICS 2004年第1期34卷 1-14页

作者： Zhang, HW He, SY Li, XS Wriggers, P Dalian Univ Technol State Key Lab Struct Anal Ind Equipment Dept Engn Mech Dalian 116024 Peoples R China Univ Hannover Inst Baumech & Numer Mech D-30167 Hannover Germany

3D elastoplastic frictional contact problems with orthotropic friction law belong to the unspecified boundary problems with nonlinearities in both material and geometric forms. One of the difficulties in solving the problem lies in the determination of the tangential slip states at the contact points. A great amount of computational efforts is needed so as to obtain high accuracy numerical results. Based on a combination of the well known mathematical programming method and iterative method, a finite element model is put forward in this paper. The problems are finally reduced to linear complementarity problems. A specially designed smoothing algorithm based on NCP-function is then applied for solving the problems. Numerical results are given to demonstrate the validity of the model and the algorithm proposed.

关键词： 3D contact problem orthotropic friction law elastoplasticity mathematical programming method iterative method linear complementarity problem smoothing algorithm

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QPNet: Lane-changing trajectory planning combining quadratic programming and neural network under the convex optimization framework

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IET INTELLIGENT TRANSPORT SYSTEMS 2022年第11期16卷 1578-1599页

作者： Wang, Ying Wei, Chong Li, Shurong Beijing Jiaotong Univ Sch Traff & Transportat Key Lab Transport Ind Big Data Applicat Technol C Minist Transport Beijing 100044 Peoples R China

Lane-changing is a basic driving behaviour, which largely impacts on traffic safety and efficiency. With the development of technology, the automated lane-changing system has attracted extensive attention. Among it, the trajectory planning part is a challenging problem owing to the complexity and diversity of the driving situations. The planner requires the real-time capability to produce safe and comfortable trajectories for coping with the dynamically changing environment. Based on this, the paper proposes a lane-changing trajectory planning model in dynamic driving environments. The model constructs a neural network to predict the end position of the ego vehicle, and then adopts the mathematical programming method to solve the optimal lane-changing trajectory that guarantees the ride safety and comfort. With the assistance of the neural network, the lane-changing trajectory planning problem is converted into a quadratic programming (QP) model, thereby achieving rapid solution of the model. Moreover, to train the proposed algorithm, a novel approach for generating the scenario data is designed, which can generate rich and diverse traffic scenarios at a low cost. The simulation results show that the proposed model can plan a lane-changing trajectory quickly and effectively, and the ego vehicle can follow the planned trajectory safely and comfortably.

关键词： rich traffic scenarios traffic safety ride safety optimal lane-changing trajectory trajectory planning part road vehicles intelligent transportation systems driving situations trajectory control convex programming optimisation planned trajectory path planning convex optimization framework basic driving behaviour safe trajectories road traffic comfortable trajectories neural network quadratic programming model road safety road traffic control dynamic driving environments lane-changing trajectory planning problem automated lane-changing system quadratic programming dynamically changing environment diverse traffic scenarios lane-changing trajectory planning model ego vehicle mathematical programming method traffic engineering computing

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Topology optimization of truss-like structures with bidirectional non-orthogonal materials based on mathematical programming

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OPTIMIZATION AND ENGINEERING 2024年第2期25卷 605-+页

作者： Shi, Shunyi Zhou, Kemin Huaqiao Univ Coll Civil Engn Xiamen 361021 Peoples R China

Topology optimization of structures composed of truss-like members has been shown to produce results that are very close to the theoretical solution. However, solving complex optimization problems based on the traditional orthogonal truss-like material model remains a challenge. This article proposes a unified framework for solving topology optimization problems based on a non-orthogonal truss-like material model. The framework first establishes a new non-orthogonal truss-like material model that considers the stiffness singularity problem. Several strategies for dynamically changing shear stiffness are studied comparatively. Then, a globally convergent moving asymptote method is employed in three numerical examples, including minimum compliance problems under single and multiple load cases, as well as a stress-constrained problem for an L-shaped design domain. Finally, optimal truss-like structures are obtained with the help of a simple post-processing method. Numerical examples demonstrate that the optimization results for the multiple load cases are better than those obtained using traditional methods for minimum compliance problems. The framework can efficiently solve different types of optimization problems in a unified form, which confirms the effectiveness and advantages of the proposed method.

关键词： Topology optimization Truss-like structure Bidirectional non-orthogonal mathematical programming method Moving asymptote method

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INEQUALITY CONSTRAINED MAXIMUM-LIKELIHOOD ESTIMATION

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ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS 1965年第3期17卷 311-321页

作者： HANSON, MA

The existence of an estimator constrained to lie in a certain type of bounded set is established for a fairly wide class of probability density functions. The necessary and sufficient conditions thus obtained provide a convenient means of finding such an estimator by mathematical programming methods. This result is a generalization of Cramer’s demonstration of the existence of an unconstrained maximum likelihood estimator and of Aitchison and Silvey’s demonstration of the existence of a maximum likelihood estimator constrained to satisfy certain equations.

关键词： Probability Density Function Maximum Likelihood Estimator Convenient Means mathematical programming method Statistical Estimation Problem

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Optimization of 3‐D nonlinear magnetic circuit by using the magnetization integral equation method

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Electrical Engineering in Japan 1992年第6期112卷 1-9页

作者： Takahashi, Norio Nakata, Takayoshi Uchiyama, Noriyuki Okayama University Japan Hitachi Ltd. Japan

To design optimal electrical machines, it is necessary to develop an optimal design method for determining the shapes, sizes, positions of the cores, permanent magnets and windings which produce such specified values as flux distributions and torques. In this paper, a design method for determining the optimal sizes of cores taking into account the nonlinearity of the core has been developed by using the nonlinear programming method and the magnetization integral equation method. The pole shape of an electromagnet which produces the uniform flux distribution is determined by using the design method for determining the optimal sizes of cores. The effectiveness of the method is shown by designing the pole piece of the permanent magnet‐type MRI device. Copyright © 1992 Wiley Periodicals, Inc., A Wiley Company

关键词： 3‐D nonlinear magnetic circuit magnetization integral equation method mathematical programming method Optimal design

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A Hybrid Multi-Objective programming Framework for Modeling and Optimization of Supply Chain Problems

A Hybrid Multi-Objective Programming Framework for Modeling ...

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3rd International Conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Sitek, Pawel Kielce Univ Technol Inst Management Control Syst Al 1000 Lecia PP 7 PL-25314 Kielce Poland

ISBN: (纸本)9788360810668

This paper presents a hybrid programming framework for solving multi-objective optimization problems in supply chain. The proposed approach consists of the integration and hybridization of two modeling and solving environments, i.e., constraint logic programming and mathematical programming, to obtain a programming framework that offers significant advantages over the classical approach derived from operational research. The strongest points of both components are combined in the hybrid framework, which by introducing transformation allows a significant reduction in size of a problem and the optimal solution is found a lot faster. This is particularly important in the multi-objective optimization where problems have to be solved over and over again to find a set of Pareto-optimal solutions. An over two thousand-fold reduction in size was obtained for the illustrative examples together with a few hundred-fold reduction in the speed of finding the solution in relation to the mathematical programming method. In addition, the proposed framework allows the introduction of logical constraints that are difficult or impossible to model in operational research environments.

关键词： Pareto optimisation mathematical programming supply chain management Pareto-optimal solutions constraint logic programming hybrid multiobjective programming framework mathematical programming method operational research environments supply chain problems Linear programming Logic programming mathematical model mathematical programming Supply chains

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Generalized parametric constitutive law for van der Waals force simulation and its applications in computation of nanotubes

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ACTA PHYSICA SINICA 2007年第3期56卷 1422-1428页

作者： Zhang Hong-Wu Wang Jin-Bao Ye Hong-Fei Wang Lei Dalian Univ Technol State Key Lab Struct Anal Ind Equipment Dept Engn Mech Dalian 116023 Peoples R China

In this paper, a parametric variational principle for van der Waals force simulation between any two non-bonded atoms is established together with the corresponding improved quadratic programming method for numerical simulation of mechanical behaviours of carbon nanotubes. Carbon-carbon covalent bond interaction in carbon nanotubes is modeled and computed based on molecular structural mechanics, model. Van der Waals force is simulated by the network of bars with a special nonlinear mechanical constitutive law in the finite element analysis. In comparison with conventional numerical methods, the suggested method does not depend on displacement and stress iteration, but on the base exchanges in the solution of a standard quadratic programming problem. Thus, the model and method developed exhibit very good convergence behavior in computation and provide accurate predictions of the mechanical behaviours and displacement distributions in the nanotubes. Numerical results demonstrate the validity and the efficiency of the proposed method.

关键词： generalized parametric constitutive law mathematical programming method molecular structural mechanics finite element method

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Spectral Reflectance Estimation from Camera Responses Using Local Optimal Dataset

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JOURNAL OF IMAGING 2023年第2期9卷 47-47页

作者： Tominaga, Shoji Sakai, Hideaki Norwegian Univ Sci & Technol Dept Comp Sci N-2815 Gjovik Norway Nagano Univ Dept Business & Informat Ueda 3860032 Japan Kyoto Univ Kyoto 6068501 Japan

A novel method is proposed to estimate surface-spectral reflectance from camera responses using a local optimal reflectance dataset. We adopt a multispectral imaging system that involves an RGB camera capturing multiple images under multiple light sources. A spectral reflectance database is utilized to locally determine the candidates to optimally estimate the spectral reflectance. The proposed estimation method comprises two stages: (1) selecting the local optimal reflectance dataset and (2) determining the best estimate using only the local optimal dataset. In (1), the camera responses are predicted for the respective reflectances in the database, and then the prediction errors are calculated to select the local optimal dataset. In (2), multiple methods are used;in particular, the Wiener and linear minimum mean square error estimators are used to calculate all statistics, based only on the local optimal dataset, and linear and quadratic programming methods are used to solve optimization problems with constraints. Experimental results using different mobile phone cameras show that the estimation accuracy has improved drastically. A much smaller local optimal dataset among spectral reflectance databases is enough to obtain the optimal estimates. The method has potential applications including fields of color science, image science and technology, computer vision, and graphics.

关键词： surface-spectral reflectance reflectance estimation multispectral imaging local optimal dataset statistical estimation method mathematical programming method

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