Questions in computational molecular biology generate various discrete optimization problems, such as DNA sequence alignment and RNA secondary structure prediction. However, the optimal solutions are fundamentally dependent on the parameters used in the objective functions. The goal of a parametric analysis is to elucidate such dependencies, especially as they pertain to the accuracy and robustness of the optimal solutions. Techniques from geometric combinatorics, including polytopes and their normal fans, have been used previously to give parametric analyses of simple models for DNA sequence alignment and RNA branching configurations. Here, we present a new computational framework, and proof-of-principle results, which give the first complete parametric analysis of the branching portion of the nearest neighbor thermodynamic model for secondary structure prediction for real RNA sequences.
Computational prediction of RNA structures is an important problem in computational structural biology. Studies of RNA structure formation often assume that the process starts from a fully synthesized sequence. Experimental evidence, however, has shown that RNA folds concurrently with its elongation. We investigate RNA secondary structure formation, including pseudoknots, that takes into account the cotranscriptional effects. We propose a single-nucleotide resolution kinetic model of the folding process of RNA molecules, where the polymerase-driven elongation of an RNA strand by a new nucleoti…
Character-level Tokenizations as Powerful Inductive Biases for RNA Foundational Models
Nostrum Biodiscovery（诺斯特伦生物发现公司）；Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology（巴塞罗那科学技术研究所生物医药研究所（IRB巴塞罗那））；Barcelona Supercomputing Center（巴塞罗那超级计算中心）
Background: RNA exhibits a variety of structural configurations. Here we consider a structure to be tantamount to the noncrossing Watson-Crick and \pairGU -base pairings (secondary structure) and additional cross-serial base pairs. These interactions are called pseudoknots and are observed across the whole spectrum of RNA functionalities. In the context of studying natural RNA structures, searching for new ribozymes and designing artificial RNA, it is of interest to find RNA sequences folding into a specific structure and to analyze their induced neutral networks. Since the established inverse…
The Chinese University of Hong Kong (CUHK)（香港中文大学）；King Abdullah University of Science and Technology (KAUST)（阿卜杜拉国王科技大学）；The CUHK Shenzhen Research Institute（香港中文大学深圳研究院）
Protein-RNA interactions are of vital importance to a variety of cellular activities. Both experimental and computational techniques have been developed to study the interactions. Due to the limitation of the previous database, especially the lack of protein structure data, most of the existing computational methods rely heavily on the sequence data, with only a small portion of the methods utilizing the structural information. Recently, AlphaFold has revolutionized the entire protein and biology field. Foreseeably, the protein-RNA interaction prediction will also be promoted significantly in …
Accurate RNA 3D structure prediction using a language model-based deep learning approach
The Chinese University of Hong Kong（香港中文大学）；Zelixir Biotech（泽利昔生物科技公司）；Shenzhen Institute of Advanced Technology（深圳先进技术研究院）；Fudan University（复旦大学）；Shanghai AI Laboratory（上海人工智能实验室）；Wyss Institute for Biologically Inspired Engineering（威斯生物启发工程研究所）；Harvard University（哈佛大学）；Harvard Medical School（哈佛医学院）；Arizona State University（亚利桑那州立大学）；Massachusetts Institute of Technology（麻省理工学院）；Broad Institute of MIT and Harvard（麻省理工学院与哈佛大学博德研究所）；Synthetic Biology Center（合成生物学中心）；OneAIM Ltd.（OneAIM有限公司）
ZeroFold: Protein-RNA Binding Affinity Predictions from Pre-Structural Embeddings
Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge（错误折叠疾病中心，尤斯夫·哈米埃德化学系，剑桥大学）；Medicinal Chemistry, Research and Early Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca（药物化学，研发与早期开发，呼吸与免疫学，生物制药研发，阿斯利康）
This contribution focuses on the fascinating RNA molecule, its sequence-dependent folding driven by base-pairing interactions, the interplay between these interactions and natural evolution, and its multiple regulatory roles. The four of us have dug into these topics using the tools and the spirit of the statistical physics of disordered systems, and in particular the concept of a disordered (energy/fitness) landscape. After an introduction to RNA molecules and the perspectives they open not only in evolutionary and synthetic biology but also in medicine, we will introduce the important notion…
Biology-Instructions: A Dataset and Benchmark for Multi-Omics Sequence Understanding Capability of Large Language Models
Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；University of Science and Technology of China（中国科学技术大学）；University of Sydney（悉尼大学）；University of Toronto（多伦多大学）；Chinese University of Hong Kong（香港中文大学）；Shanghai Jiao Tong University（上海交通大学）；Fudan University（复旦大学）；Shanghai Innovation Institute（上海创新研究院）
Sequences of nucleotides (for DNA and RNA) or amino acids (for proteins) are central objects in biology. Among the most important computational problems is that of sequence alignment, i.e. arranging sequences from different organisms in such a way to identify similar regions, to detect evolutionary relationships between sequences, and to predict biomolecular structure and function. This is typically addressed through profile models, which capture position-specificities like conservation in sequences, but assume an independent evolution of different positions. Over the last years, it has been w…
Leveraging generative hallucination and biophysics-informed modeling for unified biomolecular sequence-structure co-design
University of Florida（佛罗里达大学）；University of Chicago（芝加哥大学）；Data Science Institute, University of Chicago（芝加哥大学数据科学研究所）；Toyota Technological Institute at Chicago（芝加哥丰田技术研究所）；Mayo Clinic（梅奥诊所）；Argonne National Laboratory（阿贡国家实验室）
