Structural Biology, Biotechnology, Drug Discovery, Cancer Research
10
Scopus Publications
Scopus Publications
Blind Prediction of Complex Water and Ion Ensembles Around RNA in CASP16 Rachael C. Kretsch, Elisa Posani, Eugene F. Baulin, Janusz M. Bujnicki, Giovanni Bussi, Thomas E. Cheatham, Shi‐Jie Chen, Arne Elofsson, Masoud Amiri Farsani, Olivia N. Fisher, M. Michael Gromiha, Ayush Gupta, Michiaki Hamada, K. Harini, Gang Hu, David Huang, Junichi Iwakiri, Anika Jain, Yuki Kagaya, Daisuke Kihara, Sebastian Kmiecik, Sowmya Ramaswamy Krishnan, Ikuo Kurisaki, Olivier Languin‐Cattoën, Jun Li, Shanshan Li, Karim Malekzadeh, Tsukasa Nakamura, Wentao Ni, Chandran Nithin, Michael Z. Palo, Joon Hong Park, Smita P. Pilla, Simón Poblete, Fabrizio Pucci, Pranav Punuru, Anouka Saha, Kengo Sato, Ambuj Srivastava, Genki Terashi, Emilia Tugolukova, Jacob Verburgt, Qiqige Wuyun, Gül H. Zerze, Kaiming Zhang, Sicheng Zhang, Wei Zheng, Yuanzhe Zhou, Wah Chiu, David A. Case, Rhiju Das Proteins Structure Function and Bioinformatics, 2026 Biomolecules rely on water and ions for stable folding, but these interactions are often transient, dynamic, or disordered and thus hidden from experiments and evaluation challenges that represent biomolecules as single, ordered structures. Here, we compare blindly predicted ensembles of water and ion structure to the cryo‐EM densities observed around the Tetrahymena ribozyme at 2.2–2.3 Å resolution, collected through target R1260 in the CASP16 competition. Twenty‐six groups participated in this solvation “cryo‐ensemble” prediction challenge, submitting over 350 million atoms in total, offering the first opportunity to compare blind predictions of dynamic solvent shell ensembles to cryo‐EM density. Predicted atomic ensembles were converted to density through local alignment and these densities were compared to the cryo‐EM densities using Pearson correlation, Spearman correlation, mutual information, and precision‐recall curves. These predictions show that an ensemble representation is able to capture information of transient or dynamic water and ions better than traditional atomic models, but there remains a large accuracy gap to the performance ceiling set by experimental uncertainty. Overall, molecular dynamics approaches best matched the cryo‐EM density, with blind predictions from bussilab_plain_md, SoutheRNA, bussilab_replex, coogs2, and coogs3 outperforming the baseline molecular dynamics prediction. This study indicates that simulations of water and ions can be quantitatively evaluated with cryo‐EM maps. We propose that further community‐wide blind challenges can drive and evaluate progress in modeling water, ions, and other previously hidden components of biomolecular systems.
RNA-Puzzles Round V: blind predictions of 23 RNA structures Fan Bu, Yagoub Adam, Ryszard W. Adamiak, Maciej Antczak, Belisa Rebeca H. de Aquino, Nagendar Goud Badepally, Robert T. Batey, Eugene F. Baulin, Pawel Boinski, Michal J. Boniecki, Janusz M. Bujnicki, Kristy A. Carpenter, Jose Chacon, Shi-Jie Chen, Wah Chiu, Pablo Cordero, Naba Krishna Das, Rhiju Das, Wayne K. Dawson, Frank DiMaio, Feng Ding, Anne-Catherine Dock-Bregeon, Nikolay V. Dokholyan, Ron O. Dror, Stanisław Dunin-Horkawicz, Stephan Eismann, Eric Ennifar, Reza Esmaeeli, Masoud Amiri Farsani, Adrian R. Ferré-D’Amaré, Caleb Geniesse, George E. Ghanim, Horacio V. Guzman, Iris V. Hood, Lin Huang, Dharm Skandh Jain, Farhang Jaryani, Lei Jin, Astha Joshi, Masha Karelina, Jeffrey S. Kieft, Wipapat Kladwang, Sebastian Kmiecik, Deepak Koirala, Markus Kollmann, Rachael C. Kretsch, Mateusz Kurciński, Jun Li, Shuang Li, Marcin Magnus, BenoÎt Masquida, S. Naeim Moafinejad, Arup Mondal, Sunandan Mukherjee, Thi Hoang Duong Nguyen, Grigory Nikolaev, Chandran Nithin, Grace Nye, Iswarya P. N. Pandaranadar Jeyeram, Alberto Perez, Phillip Pham, Joseph A. Piccirilli, Smita Priyadarshini Pilla, Radosław Pluta, Simón Poblete, Almudena Ponce-Salvatierra, Mariusz Popenda, Lukasz Popenda, Fabrizio Pucci, Ramya Rangan, Angana Ray, Aiming Ren, Joanna Sarzynska, Congzhou Mike Sha, Filip Stefaniak, Zhaoming Su, Krishna C. Suddala, Marta Szachniuk, Raphael Townshend, Robert J. Trachman, Jian Wang, Wenkai Wang, Andrew Watkins, Tomasz K. Wirecki, Yi Xiao, Peng Xiong, Yiduo Xiong, Jianyi Yang, Joseph David Yesselman, Jinwei Zhang, Yi Zhang, Zhenzhen Zhang, Yuanzhe Zhou, Tomasz Zok, Dong Zhang, Sicheng Zhang, Adriana Żyła, Eric Westhof, Zhichao Miao Nature Methods, 2025 RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA three-dimensional structure prediction. With agreement from structural biologists, RNA structures are predicted by modeling groups before publication of the experimental structures. We report a large-scale set of predictions by 18 groups for 23 RNA-Puzzles: 4 RNA elements, 2 Aptamers, 4 Viral elements, 5 Ribozymes and 8 Riboswitches. We describe automatic assessment protocols for comparisons between prediction and experiment. Our analyses reveal some critical steps to be overcome to achieve good accuracy in modeling RNA structures: identification of helix-forming pairs and of non-Watson-Crick modules, correct coaxial stacking between helices and avoidance of entanglements. Three of the top four modeling groups in this round also ranked among the top four in the CASP15 contest.
When does molecular dynamics improve RNA models? Insights from CASP15 and practical guidelines Chandran Nithin, Smita P. Pilla, Sebastian Kmiecik Computational and Structural Biotechnology Journal, 2025 force field. Across 61 models representing diverse targets, we find that short simulations (10-50 ns) can provide modest improvements for high-quality starting models, particularly by stabilizing stacking and non-canonical base pairs. In contrast, poorly predicted models rarely benefit and often deteriorate, regardless of their CASP difficulty class. Longer simulations (>50 ns) typically induced structural drift and reduced fidelity. Based on these findings, we provide practical guidelines for selecting suitable input models, defining optimal simulation lengths, and diagnosing early whether refinement is viable. Overall, MD works best for fine-tuning reliable RNA models and for quickly testing their stability, not as a universal corrective method.
Exploring protein functions from structural flexibility using CABS-flex modeling Chandran Nithin, Rocco Peter Fornari, Smita P. Pilla, Karol Wroblewski, Mateusz Zalewski, Rafał Madaj, Andrzej Kolinski, Joanna M. Macnar, Sebastian Kmiecik Protein Science, 2024 Understanding protein function often necessitates characterizing the flexibility of protein structures. However, simulating protein flexibility poses significant challenges due to the complex dynamics of protein systems, requiring extensive computational resources and accurate modeling techniques. In response to these challenges, the CABS‐flex method has been developed as an efficient modeling tool that combines coarse‐grained simulations with all‐atom detail. Available both as a web server and a standalone package, CABS‐flex is dedicated to a wide range of users. The web server version offers an accessible interface for straightforward tasks, while the standalone command‐line program is designed for advanced users, providing additional features, analytical tools, and support for handling large systems. This paper examines the application of CABS‐flex across various structure–function studies, facilitating investigations into the interplay among protein structure, dynamics, and function in diverse research fields. We present an overview of the current status of the CABS‐flex methodology, highlighting its recent advancements, practical applications, and forthcoming challenges.
Are there double knots in proteins? Prediction and in vitro verification based on TrmD-Tm1570 fusion from C. nitroreducens Agata P. Perlinska, Mai Lan Nguyen, Smita P. Pilla, Emilia Staszor, Iwona Lewandowska, Agata Bernat, Elżbieta Purta, Rafal Augustyniak, Janusz M. Bujnicki, Joanna I. Sulkowska Frontiers in Molecular Biosciences, 2023 We have been aware of the existence of knotted proteins for over 30 years—but it is hard to predict what is the most complicated knot that can be formed in proteins. Here, we show new and the most complex knotted topologies recorded to date—double trefoil knots (31#31). We found five domain arrangements (architectures) that result in a doubly knotted structure in almost a thousand proteins. The double knot topology is found in knotted membrane proteins from the CaCA family, that function as ion transporters, in the group of carbonic anhydrases that catalyze the hydration of carbon dioxide, and in the proteins from the SPOUT superfamily that gathers 31 knotted methyltransferases with the active site-forming knot. For each family, we predict the presence of a double knot using AlphaFold and RoseTTaFold structure prediction. In the case of the TrmD-Tm1570 protein, which is a member of SPOUT superfamily, we show that it folds in vitro and is biologically active. Our results show that this protein forms a homodimeric structure and retains the ability to modify tRNA, which is the function of the single-domain TrmD protein. However, how the protein folds and is degraded remains unknown.
Dissecting macromolecular recognition sites in ribosome: implication to its self-assembly Smita P. Pilla, Amal Thomas, Ranjit Prasad Bahadur RNA Biology, 2019 Interactions between macromolecules play a crucial role in ribosome assembly that follows a highly coordinated process involving RNA folding and binding of ribosomal proteins (r-proteins). Although extensive studies have been carried out to understand macromolecular interactions in ribosomes, most of them are confined to either large or small ribosomal-subunit of few species. A comparative analysis of macromolecular interactions across different domains is still missing. We have analyzed the structural and physicochemical properties of protein-protein (PP), protein-RNA (PR) and RNA-RNA (RR) interfaces in small and large subunits of ribosomes, as well as in between the two subunits. Additionally, we have also developed Random Forest (RF) classifier to catalog the r-proteins. We find significant differences as well as similarities in macromolecular recognition sites between ribosomal assemblies of prokaryotes and eukaryotes. PR interfaces are substantially larger and have more ionic interactions than PP and RR interfaces in both prokaryotes and eukaryotes. PP, PR and RR interfaces in eukaryotes are well packed compared to those in prokaryotes. However, the packing density between the large and the small subunit interfaces in the entire assembly is strikingly low in both prokaryotes and eukaryotes, indicating the periodic association and dissociation of the two subunits during the translation. The structural and physicochemical properties of PR interfaces are used to predict the r-proteins in the assembly pathway into early, intermediate and late binders using RF classifier with an accuracy of 80%. The results provide new insights into the classification of r-proteins in the assembly pathway.
Dissecting protein-protein interactions in proteasome assembly: Implication to its self-assembly Smita P. Pilla, Babu R, Ranjit P. Bahadur Journal of Molecular Recognition, 2019 The 26S proteasome is a multi‐catalytic ATP‐dependent protease complex that recognizes and cleaves damaged or misfolded proteins to maintain cellular homeostasis. The 26S subunit consists of 20S core and 19S regulatory particles. 20S core particle consists of a stack of heptameric alpha and beta subunits. To elucidate the structure‐function relationship, we have dissected protein‐protein interfaces of 20S core particle and analyzed structural and physiochemical properties of intra‐alpha, intra‐beta, inter‐beta, and alpha‐beta interfaces. Furthermore, we have studied the evolutionary conservation of 20S core particle. We find the size of intra‐alpha interfaces is significantly larger and is more hydrophobic compared with other interfaces. Inter‐beta interfaces are well packed, more polar, and have higher salt‐bridge density than other interfaces. In proteasome assembly, residues in beta subunits are better conserved than alpha subunits, while multi‐interface residues are the most conserved. Among all the residues at the interfaces of both alpha and beta subunits, Gly is highly conserved. The largest size of intra‐alpha interfaces complies with the hypothesis that large interfaces form first during the 20S assembly. The tight packing of inter‐beta interfaces makes the core particle impenetrable from outer wall of the cylinder. Comparing the three domains, eukaryotes have large and well‐packed interfaces followed by archaea and bacteria. Our findings provide a structural basis of assembly of 20S core particle in all the three domains of life.
Molecular architecture of protein-RNA recognition sites Amita Barik, Nithin C, Smita P. Pilla, Ranjit Prasad Bahadur Journal of Biomolecular Structure and Dynamics, 2015 The molecular architecture of protein-RNA interfaces are analyzed using a non-redundant dataset of 152 protein-RNA complexes. We find that an average protein-RNA interface is smaller than an average protein-DNA interface but larger than an average protein-protein interface. Among the different classes of protein-RNA complexes, interfaces with tRNA are the largest, while the interfaces with the single-stranded RNA are the smallest. Significantly, RNA contributes more to the interface area than its partner protein. Moreover, unlike protein-protein interfaces where the side chain contributes less to the interface area compared to the main chain, the main chain and side chain contributions flipped in protein-RNA interfaces. We find that the protein surface in contact with the RNA in protein-RNA complexes is better packed than that in contact with the DNA in protein-DNA complexes, but loosely packed than that in contact with the protein in protein-protein complexes. Shape complementarity and electrostatic potential are the two major factors that determine the specificity of the protein-RNA interaction. We find that the H-bond density at the protein-RNA interfaces is similar with that of protein-DNA interfaces but higher than the protein-protein interfaces. Unlike protein-DNA interfaces where the deoxyribose has little role in intermolecular H-bonds, due to the presence of an oxygen atom at the 2' position, the ribose in RNA plays significant role in protein-RNA H-bonds. We find that besides H-bonds, salt bridges and stacking interactions also play significant role in stabilizing protein-nucleic acids interfaces; however, their contribution at the protein-protein interfaces is insignificant.
