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Cover Feature: Diversity Oriented Strategy (DOS) for the Efficient Synthesis of Benzofuro[2,3-b]pyridine Derivatives with Anticancer Activity (ChemMedChem 3/2025)

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ChemMedChem 2025年第3期20卷

作者： Reymark Ereje Jantana Yahuafai Theeranuch Jaroenchuensiri Patcharaporn Supakijjanusorn Sukanya Unson Borwornlak Toopradab Thanyada Rungrotmongkol Somsak Pianwanit Chanat Aonbangkhen Tanatorn Khotavivattana Center of Excellence in Natural Products Department of Chemistry Faculty of Science Chulalongkorn University Pathumwan Bangkok 10330 Thailand Department of Physical Sciences College of Science University of the Philippines Baguio Baguio City 2600 Philippines Clinical Research Section Division of Research and Academic Support National Cancer Institute Bangkok 10400 Thailand Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Pathumwan Bangkok 10330 Thailand Center of Excellence in Computational Chemistry Department of Chemistry Faculty of Science Chulalongkorn University Pathumwan Bangkok 10330 Thailand

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Identify Non-mutational p53 Functional Deficiency in Human Cancers

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Genomics, Proteomics & bioinformatics 2024年第5期22卷 85-98页

作者： Qianpeng Li Yang Zhang Sicheng Luo Zhang Zhang Ann L.Oberg David E.Kozono Hua Lu Jann N.Sarkaria Lina Ma Liguo Wang National Genomics Data Center China National Center for BioinformationBeijing 100101China Beijing Institute of Genomics Chinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China Division of Computational Biology Mayo Clinic College of Medicine and ScienceRochesterMN 55905USA Department of Radiation Oncology Dana-Farber Cancer Institute and Brigham and Women's HospitalBostonMA 02215USA Department of Biochemistry&Molecular Biology and Tulane Cancer Center Tulane University School of MedicineNew OrleansLA 70112USA Department of Radiation Oncology Mayo Clinic College of Medicine and ScienceRochesterMN 55905USA Department of Biochemistry and Molecular Biology Mayo Clinic College of Medicine and ScienceRochesterMN 55905USA Bioinformatics and Computational Biology Graduate Program University of Minnesota RochesterRochesterMN 55904USA

An accurate assessment of p53's functional statuses is critical for cancer genomic ***,there is a significant challenge in identifying tumors with non-mutational p53 inactivation which is not detectable through DNA *** undetected cases are often misclassified as p53-normal,leading to inaccurate prognosis and downstream association *** address this issue,we built the support vector machine(SVM)models to systematically reassess p53's functional statuses in TP53 wild-type(TP53^(WT))tumors from multiple The Cancer Genome Atlas(TCGA)***-validation demonstrated the good performance of the SVM models with a mean area under the receiver operating characteristic curve(AUROC)of 0.9822,precision of 0.9747,and recall of *** study revealed that a significant proportion(87%-99%)of TP53^(WT) tumors actually had compromised p53 *** analyses uncovered that these genetically intact but functionally impaired(termed as predictively reduced function of p53 or TP53^(WT)-pRF)tumors exhibited genomic and pathophysiologic features akin to TP53-mutant tumors:heightened genomic instability and elevated levels of ***,patients with TP53^(WT)-pRF tumors experienced significantly shortened overall survival or progression-free survival compared to those with predictively normal function of p53(TP53^(WT)-pN)tumors,and these patients also displayed increased sensitivity to platinum-based chemotherapy and radiation therapy.

关键词： Cancer Composite expression DNA mutation Machine learning p53 deficiency

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Solution NMR structure of Alr2454 from Nostoc sp. PCC 7120, the first structural representative of Pfam domain family PF11267

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Journal of Structural and Functional Genomics 2012年第3期13卷 171-176页

作者： Aramini, James M. Petrey, Donald Lee, Dong Yup Janjua, Haleema Xiao, Rong Acton, Thomas B. Everett, John K. Montelione, Gaetano T. Department of Molecular Biology and Biochemistry Center for Advanced Biotechnology and Medicine State University of New Jersey Piscataway NJ 08854 United States Department of Biochemistry and Medical Biophysics Center for Computational Biology and Bioinformatics Columbia University New York NY 10032 United States Department of Biochemistry Robert Wood Johnson Medical School University of Medicine and Dentistry of New Jersey Piscataway NJ 08854 United States

Protein domain family PF11267 (DUF3067) is a family of proteins of unknown function found in both bacteria and eukaryotes. Here we present the solution NMR structure of the 102-residue Alr2454 protein from Nostoc sp. PCC 7120, which constitutes the first structural representative from this conserved protein domain family. The structure of Nostoc sp. Alr2454 adopts a novel protein fold. © 2012 Springer Science+Business Media B.V.

关键词： Alr2454 protein DUF3067 PF11267 Protein Structure Initiative Solution NMR structure Structural genomics

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Minimization-Aware Recursive K∗ (MARK∗ ): A Novel, Provable Algorithm that Accelerates Ensemble-Based Protein Design and Provably Approximates the Energy Landscape 1

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23rd International Conference on Research in computational Molecular biology, RECOMB 2019

作者： Jou, Jonathan D. Holt, Graham T. Lowegard, Anna U. Donald, Bruce R. Department of Computer Science Duke University DurhamNC United States Computational Biology and Bioinformatics Program Duke University DurhamNC United States Department of Biochemistry Duke University Medical Center DurhamNC United States Department of Chemistry Duke University DurhamNC United States

ISBN: (数字)9783030170837

ISBN: (纸本)9783030170820

Protein design algorithms that model continuous sidechain flexibility and conformational ensembles better approximate the in vitro and in vivo behavior of proteins. The previous state of the art, iMinDEE- A∗ - K∗, computes provable Ε -approximations to partition functions of protein states (e.g., bound vs. unbound) by computing provable, admissible pairwise-minimized energy lower bounds on protein conformations and using the A∗ enumeration algorithm to return a gap-free list of lowest-energy conformations. iMinDEE-A ∗ - K∗ runs in time sublinear in the number of conformations, but can be trapped in loosely-bounded, low-energy conformational wells containing many conformations with highly similar energies. That is, iMinDEE- A∗ - K∗ is unable to exploit the correlation between protein conformation and energy: similar conformations often have similar energy. We introduce two new concepts that exploit this correlation: Minimization-Aware Enumeration and Recursive K∗. We combine these two insights into a novel algorithm, Minimization-Aware Recursive K∗ (MARK∗ ), that tightens bounds not on single conformations, but instead on distinct regions of the conformation space. We compare the performance of iMinDEE- A∗ - K∗ vs. MARK∗ by running the BBK∗ algorithm, which provably returns sequences in order of decreasing K∗ score, using either iMinDEE- A∗ - K∗ or MARK∗ to approximate partition functions. We show on 200 design problems that MARK∗ not only enumerates and minimizes vastly fewer conformations than the previous state of the art, but also runs upÂ to two orders of magnitude faster. Finally, we show that MARK∗ not only efficiently approximates the partition function, but also provably approximates the energy landscape. To our knowledge, MARK∗ is the first algorithm to do so. We use MARK∗ to analyze the change in energy landscape of the bound and unbound states of the HIV-1 capsid protein C-terminal domain in complex with camelid V H H, and measure the change in conformati

关键词： Proteins

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Higher-Order Generalization Bounds: Learning Deep Probabilistic programs via PAC-Bayes Objectives

arXiv

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arXiv 2022年

作者： Warrell, Jonathan Gerstein, Mark Program in Computational Biology and Bioinformatics Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States

Deep Probabilistic programming (DPP) allows powerful models based on recursive computation to be learned using efficient deep-learning optimization techniques. Additionally, DPP offers a unified perspective, where inference and learning algorithms are treated on a par with models as stochastic programs. Here, we offer a framework for representing and learning flexible PAC-Bayes bounds as stochastic programs using DPP-based methods. In particular, we show that DPP techniques may be leveraged to derive generalization bounds that draw on the compositionality of DPP representations. In turn, the bounds we introduce offer principled training objectives for higher-order probabilistic programs. We offer a definition of a higher-order generalization bound, which naturally encompasses single- and multi-task generalization perspectives (including transfer- and meta-learning) and a novel class of bound based on a learned measure of model complexity. Further, we show how modified forms of all higher-order bounds can be efficiently optimized as objectives for DPP training, using variational techniques. We test our framework using single- and multi-task generalization settings on synthetic and biological data, showing improved performance and generalization prediction using flexible DPP model representations and learned complexity measures. Copyright © 2022, The Authors. All rights reserved.

关键词： Deep learning

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ENERGY-BASED ARCHITECTURE FOR CLASSIFICATION OF PUBLICATION FIGURES

ENERGY-BASED ARCHITECTURE FOR CLASSIFICATION OF PUBLICATION ...

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Annual ORNL Biomedical Sciences and Engineering Conference on Collaborative Biomedical Innovations

作者： P. E. Barbano M. L. Nagy M. Krauthammer Department of Mathematics Yale University Program for Computational Biology and Bioinformatics Yale University

ISBN: (纸本)9781479921195

We present an implementation of the experimental and theoretical results obtained in the analysis of text and image content of biomedical publications. Particularly, we propose a novel optical recognition system using an adaptive algorithm for the classification and analysis of highly heterogeneous images in research papers. When compared with conventional algorithms, our technology substantially increases the probability of detection and classification of images buried in text or obscured by other images. We report successful testing of the new architecture using PubMed publications.

关键词： publications images ARCHITECTURE Classification of algorithms new buildings Taxonomy texts optical identification WWOX gene Image classification

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Leap forward with insect genomics

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Insect Science 2016年第3期23卷 332-334页

作者： Bin Chen Xian-Hui Wang Zhijian Tu Yong-Ping Huang Institute of Entomology and Molecular Biology Chongqing Normal University Chongqing China State Key Laboratory of IntegratedManagement of Pest Insects & Rodents Institute of Zoology Chinese Academy of Sciences Beijing China Department of Biochemistry Fralin Life Science Institute and Program in Genetics Bioinformatics and Computational Biology Virginia Tech Blacksburg Virginia USAand Key Laboratory of Insect Development and Evolutionary Biology Institute of Plant Physiology and Ecology Shanghai Institutes forBiological Sciences Chinese Academy of Sciences Shanghal China

Insects comprise the largest animal group in the world. More than a million insect species have been identified, leaving possibly two to three times more to be discovered. Systematic understanding of the genetic content of an insect species began more than 15 years ago when the genome sequence of the fruit fly, Drosophila melanogaster was reported （Adams et al., 2000）. For the first time, scientists were able to glean unprecedented insights into the genetic blueprint of a model insect, presenting its 13 600 protein coding genes. Such fundamental information opened a floodgate for comparative and functional analysis of these genes and enabled systems approaches to comparative, evolutionary and population genomic studies. In recent years, next-generation and third-generation sequencing platforms brought genome sequencing to more than a hundred insect species, reach- ing far beyond the few well-studied model organisms. The international consortium for insect genomes is work- ing toward an ambitious goal to sequence 5000 species of insects.

关键词： Leap genomics species

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Linguistic Analysis of Genomic Islands Revealed Recent Acquisition of Genetic Materials by Mycobacterium tuberculosis from alpha-Proteobacteria

Linguistic Analysis of Genomic Islands Revealed Recent Acqui...

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International Conference on Information Visualisation (IV)

作者： Oleg N. Reva Oliver Bezuidt Bioinformatics and Computational Biology Unit Biochemistry Department University of Pretoria Pretoria South Africa

Important genes may flux among bacteria by horizontal transfer and trigger substantial evolutionary changes. Novel genome linguistic and visualization approaches helped to identify genomic islands in Mycobacterium tuberculosis and trace their origin down to alpha-Proteobacteria. The identified genomic islands are distinctive from prophage inserts common for Mycobacteria. Donor-recipient relationships were visualized for the analysis on a two-dimensional map. A database of genomic islands found in bacterial chromosomes has been created and it is freely available on-line at http://***/geidb/***.

关键词： bioinformatics Genomics Microorganisms Proteins Biological cells Visualization

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Rank Projection Trees for Multilevel Neural Network Interpretation

arXiv

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arXiv 2018年

作者： Warrell, Jonathan Mohsen, Hussein Gerstein, Mark Program in Computational Biology and Bioinformatics Yale University Molecular Biophysics and Biochemistry Yale University Department of Computer Science Yale University

A variety of methods have been proposed for interpreting nodes in deep neural networks, which typically involve scoring nodes at lower layers with respect to their effects on the output of higher-layer nodes (where lower and higher layers are closer to the input and output layers, respectively). However, we may be interested in picking out a prioritized collection of subsets of the inputs across a range of scales according to their importance for an output node, and not simply a prioritized ranking across the inputs as singletons. Such a situation may arise in biological applications, for instance, where we are interested in epistatic effects between groups of genes in determining a trait of interest. Here, we outline a flexible framework which may be used to generate multiscale network interpretations, using any previously defined scoring function. We demonstrate the ability of our method to pick out biologically important genes and gene sets in the domains of cancer and psychiatric genomics. Copyright © 2018, The Authors. All rights reserved.

关键词： Genes

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Redesign of high-affinity nonspecific nucleases with altered sequence preference

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Journal of the American Chemical Society 2009年第47期131卷 17345-17353页

作者： Wang, Yi-Ting Wright, Jon D. Doudeva, Lyudmila G. Jhang, Hua-Ci Lim, Carmay Yuan, Hanna S. Institute of Molecular Biology Academia Sinica Taipei Taiwan Institute of Biomedical Sciences Academia Sinica Taipei Taiwan Institute of Chemical Biology and Molecular Biophysics Taiwan International Graduate Program Academia Sinica Taipei Taiwan Institute of Bioinformatics and Structural Biology Department of Chemistry National Tsing Hua University HsinChu Taiwan Institute of Biochemistry and Molecular Biology National Taiwan University Taipei Taiwan

It is of crucial importance to elucidate the underlying principles that govern the binding affinity and selectivity between proteins and DNA. Here we use the nuclease domain of Colicin E7 (nColE7) as a model system to generate redesigned nucleases with improved DNA-binding affinities. ColE7 is a bacterial toxin, bearing a nonspecific endonuclease domain with a preference for hydrolyzing DNA phosphodiester bonds at the 3O-side after thymine and adenine;i.e., it prefers Thy and Ade at the -1 site. Using systematic computational screening, six nColE7 mutants were predicted to bind DNA with high affinity. Five of the redesigned single-point mutants were constructed and purified, and four mutants had a 3- to 5-fold higher DNA binding affinity than wild-type nColE7 as measured by fluorescence kinetic assays. Moreover, three of the designed mutants, D493N, D493Q, and D493R, digested DNA with an increased preference for guanine at +3 sites compared to the wild-type enzyme, as shown by DNA footprint assays. X-ray structure determination of the ColE7 mutant D493Q-DNA complex in conjunction with structural and free energy decomposition analyses provides a physical basis for the improved protein-DNA interactions: Replacing D493 at the protein-DNA interface with an amino acid residue that can maintain the native hydrogen bonds removes the unfavorable electrostatic repulsion between the negatively charged carboxylate and DNA phosphate groups. These results show that computational screening combined with biochemical, structural, and free energy analyses provide a useful means for generating redesigned nucleases with a higher DNA-binding affinity and altered sequence preferences in DNA cleavage. © 2009 American Chemical Society.

关键词： DNA

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