25 papers · ranked by Valyu relevance
S. Srivastava, S. B. Lal, D. C. Mishra, U. B. Angadi + 3 more
The proposed algorithm has been implemented in R software. In order to evaluate the performance of the proposed algorithm for protein 3D structure comparison with existing algorithms i.e., (1) CE, (2) jFATCAT and (3) ESA, the benchmark data was collected from the literature . Further, distance matrices based on all…
Carol J Bult, Harold J Drabkin, Alexei Evsikov, Darren Natale + 7 more
'Cecilia Arighi' 'Natalia Roberts' 'Alan Ruttenberg' "Peter D'Eustachio" 'Barry Smith' 'Judith A Blake' 'Cathy Wu'] Background Representing species-specific proteins and protein complexes in ontologies that are both human- and machine-readable facilitates the retrieval, analysis, and interpretation of genome-scale data…
Joeri van Strien, Felix Evers, Madhurya Lutikurti, Stijn L. Berendsen + 8 more
'Stijn L. Berendsen' 'Alejandro Garanto' 'Geert-Jan van Gemert' 'Alfredo Cabrera-Orefice' 'Richard J. Rodenburg' 'Ulrich Brandt' 'Taco W. A. Kooij' 'Martijn A. Huynen' 'Dina Schneidman'] Complexome profiling allows large-scale, untargeted, and comprehensive characterization of protein complexes in a biological sample…
Joeri van Strien, Felix Evers, Madhurya Lutikurti, Stijn L. Berendsen + 7 more
Complexome profiling allows large-scale, untargeted, and comprehensive characterization of protein complexes in a biological sample using a combined approach of separating intact protein complexes e.g., by native gel electrophoresis, followed by mass spectrometric analysis of the proteins in the resulting fractions.…
Federico A Olivieri, Alina Konstantinova, Neža Ribnikar, Nej Bizjak + 4 more
Over the past decade, protein design has evolved from a specialized discipline into a broadly accessible approach for engineering and interrogating biological systems. Despite these advances, protein design continues to be a technically challenging task, often requiring knowledge of programming to be able to use and…
baiqing li, Hongming Chen
Proteolysis targeting chimeras (PROTACs), have emerged as an effective therapeutic modality by harnessing the ubiquitin-proteasome system to selectively induce targeted protein degradation, with the potential to modulate traditional undruggable targets. Due to its hetero-bifunctional characteristics, in which a linker…
Mesih Kilinc, Kejue Jia, Robert L. Jernigan
Title: Significance Homolog detection, finding similar proteins to an unknown protein, is usually the first step in understanding the role and function of that protein. However, if the identity of protein sequences between query and target proteins is low (< 30%), traditional tools struggle to distinguish a correct…
Saahithi Vemuri, Laxmi Priya Bijigiri, Sanjana Gogte, Vani Kondaparthi
PROTACs work by bringing together a protein-of-interest ligand and an E3 ligase recruiter to trigger targeted degradation. However, Diffusion-based generative models frequently produce chemically invalid or disconnected linker structures that satisfy global geometric constraints but violate local bonding requirements.…
Bo Qiang, Wenxian Shi, Yuxuan Song, Menghua Wu
prediction Authors: ['Bo Qiang' 'Wenxian Shi' 'Yuxuan Song' 'Menghua Wu'] Proteolysis targeting chimeras (PROTACs) are small molecules that trigger the breakdown of traditionally "undruggable" proteins by binding simultaneously to their targets and degradation-associated proteins. A key challenge in their rational…
Jürgen Bartel, Philipp T Kaulich, Borja Ferrero-Bordera, Rick Gelhausen + 4 more
In proteome studies, the application of alternative proteases, exclusively or in addition to trypsin, often increases protein sequence or proteome coverage. It has recently been shown that, in particular, the analysis of small proteins benefits from such multi-protease approaches. However, selecting the most optimal…
Zicheng Ma, Chuanliu Fan, Zhicong Wang, Zhenyu Chen + 6 more
'Yanheng Li' 'Shihao Feng' 'Jun Zhang' 'Ziqiang Cao' 'Yi Qin Gao'] Large language models have made remarkable progress in the field of molecular science, particularly in understanding and generating functional small molecules. This success is largely attributed to the effectiveness of molecular tokenization strategies.…
Danial Gharaie Amirabadi, Cody Jackson, Dong Su Kim, Maximilian Sprang + 1 more
Protein engineering often relies on separate models for related developability properties, limiting efficiency and transfer across tasks. We present Prot2Prop, a multitask framework based on a frozen ProstT5 encoder with shared and task-specific adapters for joint prediction of six protein properties: material…
G. Bich, E. Monsellier, G. Travé, Y. Nominé
Here, we present ProFeatMap, an intuitive Python-based website allowing to quickly display protein features such as domains, repeats, post-translational modifications location and so forth, into a highly customizable graphical 2D map. Starting from a user-defined protein list, ProFeatMap automatically extracts the main…
Ali Madani, Bryan McCann, Nikhil Naik, Nitish Shirish Keskar + 4 more
'Namrata Anand' 'Raphael R. Eguchi' 'Po‐Ssu Huang' 'Richard Socher'] Generative modeling for protein engineering is key to solving fundamental problems in synthetic biology, medicine, and material science. We pose protein engineering as an unsupervised sequence generation problem in order to leverage the exponentially…
Victoria Klein, Adam Bond, Conner Craigon, R. Scott Lokey + 1 more
Bifunctional PROTAC degraders belong to "beyond Rule of 5" chemical space, and criteria for predicting their drug-like properties are underdeveloped. PROTAC components are often combined via late-stage amide couplings, due to the reliability and robustness of amide bond formation. Amides, however, can give rise to low…
Jordan C. Rozum, Hunter Ufford, Alexandria K. Im, Tong Zhang + 3 more
Understanding protein function at the molecular level requires connecting residue-level annotations with physical and structural properties. This can be cumbersome and error-prone when functional annotation, computation of physico-chemical properties, and structure visualization are separated. To address this, we…
Dafni Skiadopoulou, Lukas Käll, Harald Barsnes, Veit Schwämmle + 1 more
'Marc Vaudel'] - 1 Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway - 2 Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway - 3Science for Life Laboratory, Department of Gene Technology, KTH - Royal Institute of…
Authors not listed
The key role of monoacylglycerol lipase (MAGL) in signaling pathways involving endocannabinoids and eicosanoids makes it a promising therapeutic target for numerous diseases, such as (neuro)inflammatory and neuropsychiatric disorders, along with acute tissue damage and cancer. From a mechanistic point of view, MAGL…
Eric Deutsch, Luis Mendoza, David Shteynberg, Michael Hoopmann + 3 more
The Trans-Proteomic Pipeline mass spectrometry data analysis suite has been in continual development and refinement since its first tools PeptideProphet and ProteinProphet were published twenty years ago. The current release provides a large complement of tools for spectrum processing, spectrum searching, search…
Bryan Cheng, Austin Jin
Proteolysis-targeting chimeras (PROTACs) can selectively degrade disease-causing proteins, yet predicting which targets are amenable to degradation remains a critical bottleneck: existing computational methods require the complete PROTAC molecular structure, information unavailable before synthesis. We present…
Aadyot Bhatnagar, Sarthak Jain, Joel Beazer, Samuel C. Curran + 6 more
Generative protein language models (PLMs) are powerful tools for designing proteins purpose-built to solve problems in medicine, agriculture, and industrial processes. Recent work has trained ever larger language models, but there has been little systematic study of the optimal training distributions and the influence…
Hongwei Lu, Cai Hong-yu, Yiming Liang, A. Bianchi + 1 more
Knowledge Transfer Authors: ['Hongwei Lu' 'Cai Hong-yu' 'Yiming Liang' 'A. Bianchi' 'Z. Berkay Celik'] Abstract—Language model approaches have recently been integrated into binary analysis tasks, such as function similarity detection and function signature recovery. These models typically employ a two-stage training…
Florbela Pereira, Loay Bedda, Mohamed A. Tammam, Abdul Kader Alabdullah + 2 more
The new coronavirus variant (SARS-CoV-2) and Zika virus are two worldwide health pandemics which outbreak borders and causing significant health difficulties, severe economic problems, and disturbing people’s daily life globally. Although many forms of preventative vaccines have been discovered and approved as…
Rahul Upadhya, Matthew Tamasi, Elena Di Mare, Sanjeeva Murthy + 1 more
The functional structure of proteins is heavily influenced by their folding behavior. AlphaFold, a powerful artificial intelligence (AI) program trained on information from the Protein Data Bank (PDB), was developed to predict the 3D structure of proteins from its amino acid sequence. Inspired by this, we aim to…
Mingze Bai, Jingwen Deng, Chengxin Dai, Julianus Pfeuffer + 1 more
Testing for significant differences in quantities on protein level is a common goal of many LFQ-based mass spectrometry proteomics experiments. Starting from a table of protein and/or peptide quantities from a fixed proteomics quantification software, there exists a multitude of tools and R packages to perform the…