arXiv - QuanBio - Biomolecules最新文献_第6页

Barlow Twins Deep Neural Network for Advanced 1D Drug-Target Interaction Prediction 用于高级一维药物-靶点相互作用预测的巴洛双胞胎深度神经网络

arXiv - QuanBio - Biomolecules Pub Date : 2024-07-31 DOI: arxiv-2408.00040

Maximilian G. Schuh, Davide Boldini, Stephan A. Sieber

引用次数: 0

Compact assessment of molecular surface complementarities enhances neural network-aided prediction of key binding residues 分子表面互补性的紧凑评估增强了神经网络辅助预测关键结合残基的能力

arXiv - QuanBio - Biomolecules Pub Date : 2024-07-30 DOI: arxiv-2407.20992

Greta Grassmann, Lorenzo Di Rienzo, Giancarlo Ruocco, Mattia Miotto, Edoardo Milanetti

{"title":"Compact assessment of molecular surface complementarities enhances neural network-aided prediction of key binding residues","authors":"Greta Grassmann, Lorenzo Di Rienzo, Giancarlo Ruocco, Mattia Miotto, Edoardo Milanetti","doi":"arxiv-2407.20992","DOIUrl":"https://doi.org/arxiv-2407.20992","url":null,"abstract":"Predicting interactions between biomolecules, such as protein-protein\u0000complexes, remains a challenging problem. Despite the many advancements done so\u0000far, the performances of docking protocols are deeply dependent on their\u0000capability of identify binding regions. In this context, we present a novel\u0000approach that builds upon our previous works modeling protein surface patches\u0000via sets of orthogonal polynomials to identify regions of high\u0000shape/electrostatic complementarity. By incorporating another key binding\u0000property, such as the balance between hydrophilic and hydrophobic\u0000contributions, we define new binding matrices that serve an effective inputs\u0000for training a neural network. Our approach also allows for the quantitative\u0000definition of a typical binding site area - approximately 10AA~in radius -\u0000where hydrophobic contribution and shape complementarity, which reflects the\u0000Lennard-Jones interaction, are maximized. Using this new architecture, CIRNet\u0000(Core Interacting Residues Network), we achieve an accuracy of approximately\u00000.82 in identifying pairs of core interacting residues on a balanced dataset.\u0000In a blind search for core interacting residues, CIRNet distinguishes these\u0000from decoys with a ROC AUC of 0.72. This protocol can enahnce docking\u0000algorithms by rescaling the proposed poses. When applied to the top ten models\u0000from three popular docking server, CIRNet improves docking outcomes, reducing\u0000the the average RMSD between the refined poses and the native state by up to\u000058%.","PeriodicalId":501022,"journal":{"name":"arXiv - QuanBio - Biomolecules","volume":"74 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141870337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantum Long Short-Term Memory for Drug Discovery 用于药物发现的量子长短期记忆技术

arXiv - QuanBio - Biomolecules Pub Date : 2024-07-29 DOI: arxiv-2407.19852

Liang Zhang, Yin Xu, Mohan Wu, Liang Wang, Hua Xu

引用次数: 0

ToF-SIMS data analysis of Shewanella oneidensis MR-1 biofilms Shewanella oneidensis MR-1 生物膜的 ToF-SIMS 数据分析

arXiv - QuanBio - Biomolecules Pub Date : 2024-07-29 DOI: arxiv-2407.20414

Gabriel D. Parker, Andrew Plymale, Luke Hanley, Xiao-Ying Yu

{"title":"ToF-SIMS data analysis of Shewanella oneidensis MR-1 biofilms","authors":"Gabriel D. Parker, Andrew Plymale, Luke Hanley, Xiao-Ying Yu","doi":"arxiv-2407.20414","DOIUrl":"https://doi.org/arxiv-2407.20414","url":null,"abstract":"Analysis of bacterial biofilms is particularly challenging and important with\u0000diverse applications from systems biology to biotechnology. Among the variety\u0000of techniques that have been applied, time-of-flight secondary ion mass\u0000spectrometry (ToF-SIMS) has many promising features in studying the surface\u0000characteristics of biofilms. ToF-SIMS offers high spatial resolution and high\u0000mass accuracy, which permit surface sensitive analysis of biofilm components.\u0000Thus, ToF-SIMS provides a powerful solution to addressing the challenge of\u0000bacterial biofilm analysis. This dataset covers ToF-SIMS analysis of Shewanella\u0000oneidensis MR-1 isolated from freshwater lake sediment in New York state. The\u0000MR-1 strain is known to have metal and sulfur reducing properties and it can be\u0000used for bioremediation and wastewater treatment. There is a current need to\u0000identify small molecules and fragments produced from bacterial biofilms. Static\u0000ToF-SIMS spectra of MR-1 were obtained using an IONTOF TOF.SIMS V instrument\u0000equipped with a 25 keV Bi3+ metal ion gun. Identified molecules and molecular\u0000fragments are compared against known biological databases and the reported\u0000peaks have at least 65 ppm mass accuracy. These molecules range from lipids and\u0000fatty acids to flavonoids, quinolones, and other naturally occurring organic\u0000compounds. It is anticipated that the spectral identification of key peaks will\u0000assist detection of metabolites, extracellular polymeric substance molecules\u0000like polysaccharides, and biologically relevant small molecules using ToF-SIMS\u0000in future surface and interface research.","PeriodicalId":501022,"journal":{"name":"arXiv - QuanBio - Biomolecules","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141870338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RNACG: A Universal RNA Sequence Conditional Generation model based on Flow-Matching RNACG：基于流匹配的通用 RNA 序列条件生成模型

arXiv - QuanBio - Biomolecules Pub Date : 2024-07-29 DOI: arxiv-2407.19838

Letian Gao, Zhi John Lu

{"title":"RNACG: A Universal RNA Sequence Conditional Generation model based on Flow-Matching","authors":"Letian Gao, Zhi John Lu","doi":"arxiv-2407.19838","DOIUrl":"https://doi.org/arxiv-2407.19838","url":null,"abstract":"RNA plays a crucial role in diverse life processes. In contrast to the rapid\u0000advancement of protein design methods, the work related to RNA is more\u0000demanding. Most current RNA design approaches concentrate on specified target\u0000attributes and rely on extensive experimental searches. However, these methods\u0000remain costly and inefficient due to practical limitations. In this paper, we\u0000characterize all sequence design issues as conditional generation tasks and\u0000offer parameterized representations for multiple problems. For these problems,\u0000we have developed a universal RNA sequence generation model based on flow\u0000matching, namely RNACG. RNACG can accommodate various conditional inputs and is\u0000portable, enabling users to customize the encoding network for conditional\u0000inputs as per their requirements and integrate it into the generation network.\u0000We evaluated RNACG in RNA 3D structure inverse folding, 2D structure inverse\u0000folding, family-specific sequence generation, and 5'UTR translation efficiency\u0000prediction. RNACG attains superior or competitive performance on these tasks\u0000compared with other methods. RNACG exhibits extensive applicability in sequence\u0000generation and property prediction tasks, providing a novel approach to RNA\u0000sequence design and potential methods for simulation experiments with\u0000large-scale RNA sequence data.","PeriodicalId":501022,"journal":{"name":"arXiv - QuanBio - Biomolecules","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141870340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Strategy for Stabilizing Protein Folding Intermediates 稳定蛋白质折叠中间体的最佳策略

arXiv - QuanBio - Biomolecules Pub Date : 2024-07-28 DOI: arxiv-2408.05224

Mengshou Wang, Liangrong Pengb, Baoguo Jia, Liu Hong

{"title":"Optimal Strategy for Stabilizing Protein Folding Intermediates","authors":"Mengshou Wang, Liangrong Pengb, Baoguo Jia, Liu Hong","doi":"arxiv-2408.05224","DOIUrl":"https://doi.org/arxiv-2408.05224","url":null,"abstract":"To manipulate the protein population at certain functional state through\u0000chemical stabilizers is crucial for protein-related studies. It not only plays\u0000a key role in protein structure analysis and protein folding kinetics, but also\u0000affects protein functionality to a large extent and thus has wide applications\u0000in medicine, food industry, etc. However, due to concerns about side effects or\u0000financial costs of stabilizers, identifying optimal strategies for enhancing\u0000protein stability with a minimal amount of stabilizers is of great importance.\u0000Here we prove that either for the fixed terminal time (including both finite\u0000and infinite cases) or the free one, the optimal control strategy for\u0000stabilizing the folding intermediates with a linear strategy for stabilizer\u0000addition belongs to the class of Bang-Bang controls. The corresponding optimal\u0000switching time is derived analytically, whose phase diagram with respect to\u0000several key parameters is explored in detail. The Bang-Bang control will be\u0000broken when nonlinear strategies for stabilizer addition are adopted. Our\u0000current study on optimal strategies for protein stabilizers not only offers\u0000deep insights into the general picture of protein folding kinetics, but also\u0000provides valuable theoretical guidance on treatments for protein-related\u0000diseases in medicine.","PeriodicalId":501022,"journal":{"name":"arXiv - QuanBio - Biomolecules","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Vertex-Edge Weighted Molecular Graphs: A study on topological indices and their relevance to physicochemical properties of drugs in use cancer treatment 顶点-边缘加权分子图：拓扑指数及其与治疗癌症药物理化性质的相关性研究

arXiv - QuanBio - Biomolecules Pub Date : 2024-07-28 DOI: arxiv-2408.06367

Sezer Sorgun, Kahraman Birgin

引用次数: 0

GraphBPE: Molecular Graphs Meet Byte-Pair Encoding GraphBPE：分子图与字节对编码的结合

arXiv - QuanBio - Biomolecules Pub Date : 2024-07-26 DOI: arxiv-2407.19039

Yuchen Shen, Barnabás Póczos

引用次数: 0

Experimental Data Confirm Carrier-Cascade Model for Solid-State Conductance across Proteins 实验数据证实了跨蛋白质固态传导的载流子级联模型

arXiv - QuanBio - Biomolecules Pub Date : 2024-07-25 DOI: arxiv-2407.17982

Eszter Papp, Gabor Vattay, Carlos Romero-Muniz, Linda A. Zotti, Jerry A. Fereiro, Mordechai Sheves, David Cahen

引用次数: 0

Counterions in RNA structure: Structural bioinformatics analysis to identify the role of Mg2+ ions in base pair formation RNA 结构中的反离子：通过结构生物信息学分析确定 Mg2+ 离子在碱基对形成中的作用

arXiv - QuanBio - Biomolecules Pub Date : 2024-07-25 DOI: arxiv-2408.05355

Swati AdhikariThe University of Burdwan, Dhananjay BhattacharyyaSaha Institute of Nuclear PhysicsUniversity of Calcutta, Parthajit RoyThe University of Burdwan

{"title":"Counterions in RNA structure: Structural bioinformatics analysis to identify the role of Mg2+ ions in base pair formation","authors":"Swati AdhikariThe University of Burdwan, Dhananjay BhattacharyyaSaha Institute of Nuclear PhysicsUniversity of Calcutta, Parthajit RoyThe University of Burdwan","doi":"arxiv-2408.05355","DOIUrl":"https://doi.org/arxiv-2408.05355","url":null,"abstract":"Contribution of metal ions on nucleic acids structures and functions is\u0000undeniable. Among the available metal ions like Na+, K+, Ca2+, Mg2+ etc., the\u0000role that play the Mg2+ ion is very significant related to the stability of the\u0000structures of RNA and this is quite well studied. But it is not possible to\u0000grasp the entire functionality of Mg2+ ion in the structure of RNA. So, to have\u0000a better understanding of the Mg-RNA complexes, in the present study, we have\u0000investigated 1541 non-redundant crystal structures of RNA and generated reports\u0000for various statistics related to these Mg-RNA complexes by computing base\u0000pairs and Mg2+ binding statistics. In this study, it has also been reported\u0000whether the presence of Mg2+ ions can alter the stability of base pairs or not\u0000by computing and comparing the base pairs stability. We noted that the Mg2+\u0000ions do not affect the canonical base pair G:C W:WC while majority of the\u0000non-canonical base pair G:G W:HC, which is important also in DNA telomere\u0000structures, has Magnesium ion binding to O6 or N7 atoms of one of the Guanines.","PeriodicalId":501022,"journal":{"name":"arXiv - QuanBio - Biomolecules","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0