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arXiv 2023年

作者： Pashine, Nidhi Wang, Dong Zhang, Jerry Patiballa, Sree Kalyan Witthaus, Sven Shattuck, Mark D. O’Hern, Corey S. Kramer-Bottiglio, Rebecca Department of Mechanical Engineering & Materials Science Yale University New HavenCT06520 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States Graduate Program in Computational Biology & Bioinformatics Yale University New HavenCT06520 United States Benjamin Levich Institute Physics Department The City College of the City University of New York New YorkNY10031 United States

Most granular packings possess shear moduli (G) that increase with the applied external pressure, and bulk moduli (B) that increase or remain constant with pressure. This paper presents "tessellated" granular metamaterials for which both G and the ratio G/B decrease with increasing pressure. The granular metamaterials are made from flexible tessellations forming a ring of closed cells, each containing a small number of solid particles. For under-constrained tessellations, the dominant contributions to G and B are the particle-particle and particle-cell interactions. With specific particle configurations in the cells, we limit the number of possible particle rearrangements to achieve decreasing G as we increase the pressure difference between the inside and outside of the tessellation, leading to G/B 1 at large pressures. We further study tessellated granular metamaterials with cells containing a single particle and many particles to determine the variables that control the mechanical response of particle-filled tessellations as a function of pressure. © 2023, CC BY.

关键词： Metamaterials

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HiC-DC+ enables systematic 3D interaction calls and differential analysis for Hi-C and HiChIP

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Nature Communications 2021年第1期12卷 3366页

作者： Sahin, Merve Wong, Wilfred Zhan, Yingqian Van Deynze, Kinsey Koche, Richard Leslie, Christina S. Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York NY United States Tri-Institutional Training Program in Computational Biology and Medicine New York NY United States Center for Epigenetics Research Memorial Sloan Kettering Cancer Center New York NY United States Bioinformatics Program University of California at San Diego San Diego CA United States

Recent genome-wide chromosome conformation capture assays such as Hi-C and HiChIP have vastly expanded the resolution and throughput with which we can study 3D genomic architecture and function. Here, we present HiC-DC+, a software tool for Hi-C/HiChIP interaction calling and differential analysis using an efficient implementation of the HiC-DC statistical framework. HiC-DC+ integrates with popular preprocessing and visualization tools and includes topologically associating domain (TAD) and A/B compartment callers. We found that HiC-DC+ can more accurately identify enhancer-promoter interactions in H3K27ac HiChIP, as validated by CRISPRi-FlowFISH experiments, compared to existing methods. Differential HiC-DC+ analyses of published HiChIP and Hi-C data sets in settings of cellular differentiation and cohesin perturbation systematically and quantitatively recovers biological findings, including enhancer hubs, TAD aggregation, and the relationship between promoter-enhancer loop dynamics and gene expression changes. HiC-DC+ therefore provides a principled statistical analysis tool to empower genome-wide studies of 3D chromatin architecture and function. © 2021, The Author(s).

关键词： Chromosomes Software Statistical methods

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A zinc finger-dependent, PRDM13-driven mechanism regulates retinal progenitor cell fate from mouse embryonic stem cells via WNT signaling

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Stem Cell Reports 2025年第6期20卷 102508页

作者： Basinski, Brian W. Huang, Yuanhao Li, Qiang Sivakumar, Charukesi D. Carman, Tyler J. Pan, Hana M. Xu, Jing Hannum, D. Ford Liu, Jie Rao, Rajesh C. Department of Ophthalmology and Visual Science W.K. Kellogg Eye Center University of Michigan Ann Arbor 48105 MI United States Molecular and Cellular Pathology Graduate Program Department of Pathology University of Michigan Ann Arbor 48105 MI United States Department of Computational Medicine and Bioinformatics Ann Arbor 48105 MI United States Department of Human Genetics University of Michigan Ann Arbor 48105 MI United States Rogel Cancer Center University of Michigan Ann Arbor 48105 MI United States Center of Computational Medicine and Bioinformatics University of Michigan Ann Arbor 48105 MI United States Center for RNA Biomedicine University of Michigan Ann Arbor 48105 MI United States A. Alfred Taubman Medical Research Institute University of Michigan Ann Arbor 48105 MI United States Section of Ophthalmology Surgical Service Veterans Administration Ann Arbor Healthcare System Ann Arbor 48105 MI United States

The transcriptional regulation underlying eye field (retinal primordium) development requires precise control, yet the mechanisms guiding lineage-specific differentiation within the central nervous system (CNS) remain incompletely understood. Using neuroectoderm (NE) organoids derived from mouse embryonic stem cells, we investigate the role of PRDM13 in eye field specification. We demonstrate that Prdm13 expression inhibits RX⁺ eye field fate but permits non-eye field NE differentiation, an effect that depends on its first and second zinc-finger domains. Prdm13 activates the WNT/β-catenin signaling pathway during differentiation, leading to downregulation of key transcription factors crucial for establishing the eye field. Pharmacological inhibition of WNT signaling abolishes PRDM13-mediated suppression, restoring RX⁺ eye field differentiation. Our work reveals a previously undescribed PRDM13-WNT signaling axis that regulates lineage-specific neural differentiation of embryonic stem cells. © 2025 The Author(s)

关键词： organoids PRDM13 retinal development stem cells WNT

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Assessment of scoring functions for computational models of protein-protein interfaces

arXiv

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arXiv 2024年

作者： Sumner, Jacob Meng, Grace Brandt, Naomi Grigas, Alex T. Córdoba, Andrés Shattuck, Mark D. O’Hern, Corey S. Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Integrated Graduate Program in Physical and Engineering Biology Yale University New HavenCT06520 United States Department of Chemistry Yale University New HavenCT06520 United States Department of Physics Yale University New HavenCT06520 United States Department of Chemistry Duke University DurhamNC27708 United States Department of Physics Duke University DurhamNC27708 United States Benjamin Levich Institute Physics Department City College of New York New YorkNY10031 United States Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States

A goal of computational studies of protein-protein interfaces (PPIs) is to predict the binding site between two monomers that form a heterodimer. The simplest version of this problem is to rigidly re-dock the bound forms of the monomers, which involves generating computational models of the heterodimer and then scoring them to determine the most native-like models. Scoring functions have been assessed previously using rank- and classification-based metrics, however, these methods are sensitive to the number and quality of models in the scoring function training set. We assess the accuracy of seven PPI scoring functions by comparing their scores to a measure of structural similarity to the x-ray crystal structure (i.e. the DockQ score) for a non-redundant set of heterodimers from the Protein Data Bank. For each heterodimer, we generate re-docked models uniformly sampled over DockQ and calculate the Spearman correlation between the PPI scores and DockQ. For some targets, the scores and DockQ are highly correlated;however, for many targets, there are weak correlations. Several physical features can explain the difference between difficult- and easy-to-score targets. For example, strong correlations exist between the score and DockQ for targets with highly intertwined monomers and many interface contacts. We also develop a new score based on only three physical features that matches or exceeds the performance of current PPI scoring functions. These results emphasize that PPI prediction can be improved by focusing on correlations between the PPI score and DockQ and incorporating more discriminating physical features into PPI scoring functions. © 2024, CC BY.

关键词： Monomers

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Dynamic WNT signaling controls differentiation of hematopoietic progenitor cells from human pluripotent stem cells

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Science China Life Sciences 2025年

作者： Mo Li Keiichiro Suzuki Mengge Wang Christopher Benner Manching Ku Li Ma Ladan Kobari Na Young Kim Nuria Montserrat Chan-Jung Chang Guanghui Liu Jing Qu Jinna Xu Yingzi Zhang Emi Aizawa Jun Wu Luc Douay Concepcion Rodriguez Esteban Juan Carlos Izpisua Belmonte Key Laboratory of Organ Regeneration and Reconstruction State Key Laboratory of Membrane Biology Institute of Zoology Chinese Academy of Sciences Institute for Stem Cell and Regeneration Chinese Academy of Sciences EFS Ile de France Unité d’Ingénierie et de Thérapie Cellulaire AP-HP H?pital Saint Antoine/Armand Trousseau Service d’Hématologie et immunologie biologique Altos Labs Bioscience Program Biological and Environmental Science and Engineering Division King Abdullah University of Science and Technology (KAUST) KAUST Center of Excellence for Smart Health (KCSH) Gene Expression Laboratory Salk Institute for Biological Studies Institute for Advanced Co-Creation Studies Osaka University Integrative Genomics and Bioinformatics Core Salk Institute for Biological Studies Next Generation Sequencing Core Salk Institute for Biological Studies UPMC Univ Paris 06 UMRS938 CDR Saint-Antoine Prolifération et Différentiation des Cellules Souches INSERM UMRS938 Prolifération et Différentiation des Cellules Souches Center for Regenerative Medicine in Barcelona

Human pluripotent stem cells (hPSCs) can in theory give rise to any hematopoietic lineages,thereby offering opportunities for disease modeling,drug screening and cell ***,gaps in our knowledge of the signaling requirements for the specification of human hematopoietic stem/progenitor cells (HSPCs),which lie at the apex of all hematopoietic lineages,greatly limit the potential of hPSC in hematological research and *** analysis reveals aberrant regulation of WNT signaling during maturation of h PSC-derived hematopoietic progenitor cells (hPSC-HPCs),which results in higher mitochondria activity,misregulation of HOX genes,loss of selfrenewal and precocious *** defects are partly due to the activation of the WNT target gene ***-stage WNT inhibition improves the yield,self-renewal,multilineage differentiation,and transcriptional and metabolic profiles of *** mapping of transcription factor (TF) accessible chromatin reveals a significant overrepresentation of myeloid TF binding motifs in hPSC-HPCs,which could underlie their myeloid-biased lineage *** our findings uncover a previously unappreciated dynamic requirement of the WNT signaling pathway during the specification of human *** the WNT pathway with small molecules normalizes the molecular differences between hPSC-HPCs and endogenous hematopoietic stem cells (HSCs),thereby representing a promising approach to improve the differentiation and function of hPSC-HPCs.

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Development and Application of a Multi-Level Computational Approach for the Identification of Inhibitors of Mapk3 in Leishmania Martiniquensis and Leishmania Orientalis

SSRN

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SSRN 2024年

作者： Kiriwan, Duangnapa Vieira, Tatiana F. Kumsiri, Nutnaree Sousa, Sergio F. Choowongkomon, Kiattawee Associate Laboratory i4HB—Institute for Health and Bioeconomy Faculdade de Medicina Universidade do Porto Porto Portugal LAQV/REQUIMTE BioSIM - Departamento de Biomedicina Faculdade de Medicina Universidade do Porto Porto Portugal Genetic Engineering and Bioinformatics program Kasetsart University 50 Ngam Wong Wan Road Chatuchak Bangkok10900 Thailand Center for Advanced Studies in Nanotechnology for Chemical Food and Agricultural Industries KU Institute for Advanced Studies Kasetsart University Bangkok10900 Thailand Department of Biochemistry Faculty of Science Kasetsart University 50 Ngam Wong Wan Road Chatuchak Bangkok10900 Thailand

Leishmania martiniquensis and Leishmania orientalis are two major species of parasites, associated to health problems in Thailand. Here, we focused on in silico strategies for the identification of inhibitors of the protein mitogen active protein kinase3 (MAPK3) in these two species. MAPK3 is a Ser/Thr protein kinase that plays an important role in the differentiation of amastigotes to promastigotes. This study describes a multi-level computational method for discovering new MAPK3 inhibitors with high potency. This approach involves creating 3D models of these protein targets through homology modelling, refined with molecular dynamics (MD) simulations, followed by protein-ligand docking validation for protocol validation, virtual screening of large molecular databases, followed by MD simulations on most promising protein-ligand complexes, and binding free energy calculations. This approach was applied to screen an in-house library of 8,000 tripeptides. The structure-based virtual screening results suggested nine tripeptides as promising inhibitors of MAPK3 for all the leishmania species considered. Four tripeptides were validated as very promising binders by the MD simulations and free energy calculations. Subsequent MAP Kinase 3 inhibition assay was performed. Our in vitro kinase assay demonstrated that the peptide WSY exhibited a significantly higher effectiveness in inhibiting MAPK3 compared to WHW at a concentration of 3.33 µM with percentages of 89.97±9.28% and 27.97±14.45%, *** optimized multi-level protocol can now be applied to other types of molecular databases to identify promising candidates targeting proteins LmrMAPK3 and LoMAPK3. © 2024, The Authors. All rights reserved.

关键词： Molecular dynamics

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The Genomic Landscape of Wilms' Tumor 1 (WT1) Mutant Acute Myeloid Leukemia

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BLOOD 2020年 136卷 28-28页

作者： Awada, Hassan Durmaz, Arda Gurnari, Carmelo Zawit, Misam Kongkiatkamon, Sunisa Pagliuca, Simona Kerr, Cassandra M. Carraway, Hetty E. Nazha, Aziz Sekeres, Mikkael A. Maciejewski, Jaroslaw P. Visconte, Valeria Department of Translational Hematology and Oncology Research Taussig Cancer Institute Cleveland Clinic Foundation Cleveland OH Department of Systems biology and Bioinformatics CWRU cleveland Department of Translational Hematology and Oncology Taussig Cancer Institute Cleveland OH Department of Translational Hematology and Oncology Research Taussig Cancer Institute Cleveland Clinic Cleveland OH Department of Hematology and Medical Oncology Leukemia Program Taussig Cancer Institute Cleveland Clinic Foundation Cleveland OH Leukemia Program Department of Hematology and Medical Oncology Taussig Cancer Institute Cleveland Clinic Cleveland OH Leukemia Program Department of Hematology and Medical Oncology Cleveland Clinic Taussig Cancer Institute Cleveland OH

Mutations in tumor suppressor genes and oncogenes are both potentially therapeutically actionable in acute myeloid leukemia (AML). The Wilms' Tumor 1 ( WT1 ) gene is located on 11p13 and encodes a zinc finger transcription factor which has been found to be overexpressed and mutated in AML. In normal development, WT1 is only expressed in a small subset of hematopoietic stem cells. While its overexpression suggests an oncogenic role, the invariable presence of mutations in the cysteine-histidine zinc finger domains indicates a tumor suppressor function, similar to that in WAGR syndrome/11p deletion syndrome in which it was first discovered. Like its unknown function in AML, the clinical significance and genetic associations of WT1 mutations have been also controversial. Although studies of WT1 mutations in AML have been conducted, the lack of solid clinical and molecular characterization of large WT1 -mutant ( WT1 MT ) AML cohort has hampered its definition. In this study, we took advantage of a compendia of genomic results from Cleveland Clinic and publicly available data of 2188 AML patients (primary (p)AML, n= 1636; secondary (s)AML, n= 433; therapy-related (t)AML, n= 119, excluding cases with acute promyelocytic leukemia, MLL- rearrangement, and core-binding factor AML). While several reports only focused on cytogenetic normal AML (CN-AML), which represented 61% of our cohort, we additionally included all other cytogenetic risk groups. In total, WT1 mutations were detected in 5% (114/2188) of patients. WT1 mutations were enriched in pAML (85%) compared to sAML (11%) and tAML (4%). Thirty-nine patients (13%) carried more than 1 WT1 mutation. WT1 MT were younger [59 vs 64 years, P =0.0002] and more often females (55% vs 45%, P =0.03) as compared to WT1 wild type ( WT1 WT ) patients. Univariate analyses of baseline parameters showed that WT1 MT AML had a more proliferative phenotype with a higher WBC [15.1 vs 9.5 x10 9 /L, P =0.03] and bone marrow blast percentages [

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A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation

arXiv

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arXiv 2024年

作者： Tang, Xiangru Dai, Howard Knight, Elizabeth Wu, Fang Li, Yunyang Li, Tianxiao Gerstein, Mark Department of Computer Science Yale University New HavenCT06520 United States School of Medicine Yale University New HavenCT06520 United States Computer Science Department Stanford University CA94305 United States Program in Computational Biology & Bioinformatics Yale University New HavenCT06520 United States Department of Molecular Biophysics & Biochemistry Yale University New HavenCT06520 United States Department of Statistics & Data Science Yale University New HavenCT06520 United States Department of Biomedical Informatics & Data Science Yale University New HavenCT06520 United States

Artificial intelligence (AI)-driven methods can vastly improve the historically costly drug design process, with various generative models already in widespread use. Generative models for de novo drug design, in particular, focus on the creation of novel biological compounds entirely from scratch, representing a promising future direction. Rapid development in the field, combined with the inherent complexity of the drug design process, creates a difficult landscape for new researchers to enter. In this survey, we organize de novo drug design into two overarching themes: small molecule and protein generation. Within each theme, we identify a variety of subtasks and applications, highlighting important datasets, benchmarks, and model architectures and comparing the performance of top models. We take a broad approach to AI-driven drug design, allowing for both micro-level comparisons of various methods within each subtask and macro-level observations across different fields. We discuss parallel challenges and approaches between the two applications and highlight future directions for AI-driven de novo drug design as a whole. An organized repository of all covered sources is available at https://***/gersteinlab/GenAI4Drug. © 2024, CC BY.

关键词： Proteins

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Phosphoproteomic analysis reveals distinctive responses in Mangrovibacter phragmatis under high-salinity condition

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Biochemical and biophysical research communications 2024年 736卷 150514页

作者： Hong Soon Chin Narendrakumar Ravi Varadharajulu Zhi-Han Lin Chuan-Chih Hsu Steve S-F Yu Institute of Chemistry Academia Sinica Taipei Taiwan Chemical Biology and Molecular Biophysics Program Taiwan International Graduate Program Academia Sinica Taipei Taiwan Institute of Bioinformatics and Structural Biology National Tsing Hua University Hsinchu Taiwan. Molecular Science and Technology Program Taiwan International Graduate Program Academia Sinica Taipei Taiwan Department of Chemistry National Tsing Hua University Hsinchu Taiwan. Institute of Biochemical Sciences National Taiwan University Taipei Taiwan. Institute of Plant and Microbial Biology Academia Sinica Taipei Taiwan. Molecular Science and Technology Program Taiwan International Graduate Program Academia Sinica Taipei Taiwan. Electronic address: sfyu@gate.sinica.edu.tw.

We conducted a thorough genome-wide investigation of protein phosphorylation in the halotolerant bacterium Mangrovibacter phragmitis (MPH) ASIOC01, using the Fe-IMAC enrichment method combined with tandem mass spectrometry under low- and high-salinity conditions. The phosphoproteome comprises 86 unique phosphorylated proteins, crucially involving pathways such as glycolysis/gluconeogenesis, the citrate cycle, chaperones, ribosomal proteins, and cell division. This study represents the first and most extensive investigation to-date comparing the bacterial phosphoproteome under different osmotic conditions using a gel-free approach. We identified 45 unique phosphoproteins in MPH cultured in media containing 1 % NaCl, and 33 exclusive phosphoproteins in MPH cultured in media containing 5 % NaCl. Eight phosphoproteins were detected in both growth conditions. Analysis of high-confidence phosphosites reveals that phosphorylation predominantly occurs on serine residues (52.3 %), followed by threonine (35.1 %) and tyrosine (12.6 %) residues. Interestingly, 34 % of the phosphopeptides display multiple phosphosites. Currently, prokaryotic phosphorylation site prediction platforms like MPSite and NetPhosBac 1.0 demonstrate an average prediction accuracy of only 21 % when applied to our dataset. Fourteen phosphoproteins did not yield matches when compared against dbPSP 2.0 (database of Phosphorylation Sites in Prokaryotes), indicating that these proteins may be novel phosphoproteins. These unique proteins undergoing phosphorylation under high salinity growth conditions potentially enhance their adaptive capabilities to environmental challenges.

关键词： Halotolerance LC-MS/MS Mangrovibacter phragmitis Osmotic-stress Phosphoproteomes Ser/thr/tyr phosphorylation

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A perspective on developing foundation models for analyzing spatial transcriptomic data

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Quantitative Biology 2025年第4期13卷

作者： Tianyu Liu Minsheng Hao Xinhao Liu Hongyu Zhao Interdepartmental Program of Computational Biology and Bioinformatics Yale University New Haven Connecticut USA Department of Biostatistics Yale University New Haven Connecticut USA Research and Early Development Genentech South San Francisco California USA Department of Computer Science Princeton University Princeton New Jersey USA

Do we need a foundation model (FM) for spatial transcriptomic analysis? To answer this question, we prepared this perspective as a primer. We first review the current progress of developing FMs for modeling spatial transcriptomic data and then discuss possible tasks that can be addressed by FMs. Finally, we explore future directions of developing such models for understanding spatial transcriptomics by describing both opportunities and challenges. In particular, we expect that a successful FM should boost research productivity, increase novel biological discoveries, and provide user-friendly access.

关键词： artificial intelligence foundation models perspective spatial transcriptomics data

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