A Survey on Computational Solutions for Reconstructing Complete Objects by Reassembling Their Fractured Parts

Computer Graphics Forum, Год журнала: 2025, Номер unknown

Опубликована: Апрель 18, 2025

Abstract Reconstructing a complete object from its parts is fundamental problem in many scientific domains. The purpose of this article to provide systematic survey on topic. This reassembly requires understanding the attributes individual pieces and establishing matches between different pieces. Many approaches also model priors underlying object. Existing are tightly connected problems shape segmentation, matching, learning priors. We existing algorithms context emphasize their similarities differences general‐purpose approaches. trends early procedural more recent deep In addition algorithms, will describe datasets, open‐source software packages, applications. To best our knowledge, first comprehensive topic computer graphics.

Язык: Английский

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Protein–Protein Interaction Prediction for Targeted Protein Degradation

International Journal of Molecular Sciences, Год журнала: 2022, Номер 23(13), С. 7033 - 7033

Опубликована: Июнь 24, 2022

Protein–protein interactions (PPIs) play a fundamental role in various biological functions; thus, detecting PPI sites is essential for understanding diseases and developing new drugs. prediction of particular relevance the development drugs employing targeted protein degradation, as their efficacy relies on formation stable ternary complex involving two proteins. However, experimental methods to detect are both costly time-intensive. In recent years, machine learning-based have been developed screening tools. While they computationally more efficient than traditional docking thus allow rapid execution, these tools so far primarily based sequence information, therefore limited ability address spatial requirements. addition, date not applied degradation. Here, we present deep learning architecture concept graph representation that can predict interaction proteins surface representations. We demonstrate our model reaches state-of-the-art performance using AUROC scores established MaSIF dataset. furthermore introduce dataset with diverse show generalizes well this data. These generalization capabilities PPIs relevant which by demonstrating high accuracy available Our results suggest models be valuable tool pairs while

Язык: Английский

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Quantum Chemistry-Based Protein–Protein Docking without Empirical Parameters

Journal of Chemical Theory and Computation, Год журнала: 2024, Номер 20(12), С. 5164 - 5175

Опубликована: Июнь 7, 2024

This study developed a novel protein–protein docking approach based on quantum chemistry. To judge the appropriateness of complex structures, we introduced two criterion values, EV1 and EV2, computed using fragment molecular orbital method without any empirical parameters. These values enable us to search structures in which patterns electrostatic potential proteins are optimally aligned at their interface. The performance our was validated 53 complexes benchmark set provided for docking. When employing bound state success rates reached 64% 76% EV2. On other hand, when unbound 13% 17%

Язык: Английский

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Challenges and Emerging Problems in CADD

Опубликована: Июль 1, 2024

Pharmaceutical synthesis has traditionally been a lengthy, expensive, and labor-intensive process that requires many years of experience considerable personnel. However, with the introduction information technology, it can be done more efficiently. During last few decades, area drug discovery, which leads to discovery novel ligands, evolved into modern science employs both computational experimental methods. Computer-aided design (CADD) emerged as striking feature numerous programming languages in variety contexts research scenarios. To uncover, reinforce, or analyze medications other physiologically active substances, chemistry is employed CADD. It involves creating chemicals, docking them target protein, examining molecular interactions, assessing binding strength along therapeutic properties. advance further stages pipeline market, hit compounds have identified optimized, streamlined by Despite CADD's contributions at several points process, challenges remain. realize promise methodologies, teams must improve communication. Other problems addressed include proper scientific dissemination, data exchange, education minimize false expectations enhance CADD production. This chapter's goal provide thorough review CADD, together an analysis its challenging issues promising future directions.

Язык: Английский

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Structural Bioinformatics

Advances in bioinformatics and biomedical engineering book series, Год журнала: 2024, Номер unknown, С. 169 - 208

Опубликована: Сен. 27, 2024

Within this chapter, the authors offer a concise introduction to concept of structural bioinformatics. In addition proteins, DNA, and RNA, peptides are another type biomolecule covered in chapter. Peptides short chains amino acids (generally, 2-50) connected by peptide bonds. Due their versatility, they play essential roles several biological processes living beings, acting as hormones, enzymes, antibiotics, support, etc. Additionally, chapter will address detail interaction between peptides, protein, application bioinformatics tools for studying these complexes, implications research related interactions, development new drugs, future prospects, challenges topic.

Язык: Английский

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PointDE: Protein Docking Evaluation Using 3D Point Cloud Neural Network

IEEE/ACM Transactions on Computational Biology and Bioinformatics, Год журнала: 2023, Номер 20(5), С. 3128 - 3138

Опубликована: Май 23, 2023

Protein-protein interactions (PPIs) play essential roles in many vital movements and the determination of protein complex structure is helpful to discover mechanism PPI. docking being developed model protein. However, there still a challenge selecting near-native decoys generated by protein-protein docking. Here, we propose evaluation method using 3D point cloud neural network named PointDE. PointDE transforms cloud. Using state-of-the-art architecture novel grouping mechanism, can capture geometries learn interaction information from interface. On public datasets, surpasses deep learning. To further explore ability our different types structures, new dataset high-quality antibody-antigen complexes. The result this shows strong performance PointDE, which will be for understanding PPI mechanisms.

Язык: Английский

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Predictive Modeling and Structure Analysis of Genetic Variants in Familial Hypercholesterolemia: Implications for Diagnosis and Protein Interaction Studies

Current Atherosclerosis Reports, Год журнала: 2023, Номер 25(11), С. 839 - 859

Опубликована: Окт. 17, 2023

Familial hypercholesterolemia (FH) is a hereditary condition characterized by elevated levels of low-density lipoprotein cholesterol (LDL-C), which increases the risk cardiovascular disease if left untreated. This review aims to discuss role bioinformatics tools in evaluating pathogenicity missense variants associated with FH. Specifically, it highlights use predictive models based on protein sequence, structure, evolutionary conservation, and other relevant features identifying genetic within LDLR, APOB, PCSK9 genes that contribute FH.In recent years, various have emerged as valuable resources for analyzing FH-related genes. Tools such REVEL, Varity, CADD diverse computational approaches predict impact function. These consider factors sequence structural alterations, receptor binding aid interpreting identified variants. While these offer insights, accuracy predictions can vary, especially proteins unique characteristics might not be well represented databases used training. emphasizes significance utilizing assessing FH-associated Despite their contributions, definitive diagnosis variant necessitates functional validation through vitro characterization or cascade screening. step ensures precise identification variants, leading more accurate diagnoses. Integrating data reliable enhance our understanding basis FH, enabling improved diagnosis, stratification, personalized treatment affected individuals. The comprehensive approach outlined this promises advance management inherited disorder, potentially better health outcomes those

Язык: Английский

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Studying protein–protein interaction through side-chain modeling method OPUS-Mut

Briefings in Bioinformatics, Год журнала: 2022, Номер 23(5)

Опубликована: Авг. 12, 2022

Abstract Protein side chains are vitally important to many biological processes such as protein–protein interaction. In this study, we evaluate the performance of our previous released side-chain modeling method OPUS-Mut, together with some other methods, on three oligomer datasets, CASP14 (11), CAMEO-Homo (65) and CAMEO-Hetero (21). The results show that OPUS-Mut outperforms methods measured by all residues or interfacial residues. We also demonstrate evaluating docking pose a dataset Oligomer-Dock (75) created using top 10 predictions from ZDOCK 3.0.2. Our scoring function correctly identifies native top-1 in 45 out 75 targets. Different traditional functions, is based overall packing favorableness accordance local environment. It emphasizes significance provides new effective term for studying

Язык: Английский

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Proangiogenic effect and underlying mechanism of holmium oxide nanoparticles: a new biomaterial for tissue engineering

Journal of Nanobiotechnology, Год журнала: 2024, Номер 22(1)

Опубликована: Июнь 21, 2024

Early angiogenesis provides nutrient supply for bone tissue repair, and insufficient will lead engineering failure. Lanthanide metal nanoparticles (LM NPs) are the preferred materials can effectively promote angiogenesis. Holmium oxide (HNPs) LM NPs with function of "tracking" labelling. Preliminary studies have shown that HNPs has potential angiogenesis, but specific role mechanism remain unclear. This limits biological application HNPs.

Язык: Английский

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Docking Foundations: From Rigid to Flexible Docking

Methods in molecular biology, Год журнала: 2024, Номер unknown, С. 3 - 14

Опубликована: Янв. 1, 2024

Язык: Английский

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