Allosteric transition, defined as conformational changes induced by ligand binding, is one of the fundamental properties of proteins. Allostery has been observed and characterized in many proteins, ...and has been recently utilized to control protein function via regulation of protein activity. Here, we review the physical and evolutionary origin of protein allostery, as well as its importance to protein regulation, drug discovery, and biological processes in living systems. We describe recently developed approaches to identify allosteric pathways, connected sets of pairwise interactions that are responsible for propagation of conformational change from the ligand-binding site to a distal functional site. We then present experimental and computational protein engineering approaches for control of protein function by modulation of allosteric sites. As an example of application of these approaches, we describe a synergistic computational and experimental approach to rescue the cystic-fibrosis-associated protein cystic fibrosis transmembrane conductance regulator, which upon deletion of a single residue misfolds and causes disease. This example demonstrates the power of allosteric manipulation in proteins to both elucidate mechanisms of molecular function and to develop therapeutic strategies that rescue those functions. Allosteric control of proteins provides a tool to shine a light on the complex cascades of cellular processes and facilitate unprecedented interrogation of biological systems.
Predicting binding affinities between small molecules and the protein target is at the core of computational drug screening and drug target identification. Deep learning-based approaches have ...recently been adapted to predict binding affinities and they claim to achieve high prediction accuracy in their tests; we show that these approaches do not generalize, that is, they fail to predict interactions between unknown proteins and unknown small molecules. To address these shortcomings, we develop a new compound-protein interaction predictor, Yuel, which predicts compound-protein interactions with a higher generalizability than the existing methods. Upon comprehensive tests on various data sets, we find that out of all the deep-learning approaches surveyed, Yuel manifests the best ability to predict interactions between unknown compounds and unknown proteins.
Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization ...of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer,
,
, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.
Accumulation of insoluble amyloid fibrils is widely studied as a critical factor in the pathology of multiple neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), a fatal ...neurodegenerative disease. Misfolded Cu, Zn superoxide dismutase (SOD1) was the first protein linked to ALS, and non-native SOD1 trimeric oligomers were recently linked to cytotoxicity, while larger oligomers were protective to cells. The balance between trimers and larger aggregates in the process of SOD1 aggregation is, thus, a critical determinant of potential therapeutic approaches to treat ALS. However, it is unknown whether these trimeric oligomers are a necessary intermediate for larger aggregate formation or a distinct off-pathway species competing with fibril formation. Depending on the on- or off-pathway scenario of trimer formation, we expect drastically different therapeutic approaches. Here, we show that the toxic SOD1 trimer is an off-pathway intermediate competing with protective fibril formation. We design mutant SOD1 constructs that remain in a trimeric state (super-stable trimers) and show that stabilizing the trimeric SOD1 prevents formation of fibrils in vitro and in a motor neuron-like cell model (NSC-34). Using size exclusion chromatography, we track the aggregation kinetics of purified SOD1 and show direct competition of trimeric SOD1 with larger oligomer and fibril formation. Finally, we show the trimer is structurally independent of both larger soluble oligomers and insoluble fibrils using circular dichroism spectroscopy and limited proteolysis.
Allostery in proteins influences various biological processes such as regulation of gene transcription and activities of enzymes and cell signaling. Computational approaches for analysis of ...allosteric coupling provide inexpensive opportunities to predict mutations and to design small-molecule agents to control protein function and cellular activity. We develop a computationally efficient network-based method, Ohm, to identify and characterize allosteric communication networks within proteins. Unlike previously developed simulation-based approaches, Ohm relies solely on the structure of the protein of interest. We use Ohm to map allosteric networks in a dataset composed of 20 proteins experimentally identified to be allosterically regulated. Further, the Ohm allostery prediction for the protein CheY correlates well with NMR CHESCA studies. Our webserver, Ohm.dokhlab.org, automatically determines allosteric network architecture and identifies critical coupled residues within this network.
mRNA vaccines for cancer immunotherapy Vishweshwaraiah, Yashavantha L; Dokholyan, Nikolay V
Frontiers in immunology,
12/2022, Letnik:
13
Journal Article
Recenzirano
Odprti dostop
Immunotherapy has emerged as a breakthrough strategy in cancer treatment. mRNA vaccines are an attractive and powerful immunotherapeutic platform against cancer because of their high potency, ...specificity, versatility, rapid and large-scale development capability, low-cost manufacturing potential, and safety. Recent technological advances in mRNA vaccine design and delivery have accelerated mRNA cancer vaccines' development and clinical application. In this review, we present various cancer vaccine platforms with a focus on nucleic acid vaccines. We discuss rational design and optimization strategies for mRNA cancer vaccine development. We highlight the platforms available for delivery of the mRNA vaccines with a focus on lipid nanoparticles (LNPs) based delivery systems. Finally, we discuss the limitations of mRNA cancer vaccines and future challenges.
Allostery in proteins plays an important role in regulating protein activities and influencing many biological processes such as gene expression, enzyme catalysis, and cell signaling. The process of ...allostery takes place when a signal detected at a site on a protein is transmitted via a mechanical pathway to a functional site and, thus, influences its activity. The pathway of allosteric communication consists of amino acids that form a network with covalent and non-covalent bonds. By mutating residues in this allosteric network, protein engineers have successfully established novel allosteric pathways to achieve desired properties in the target protein. In this review, we highlight the most recent and state-of-the-art techniques for allosteric communication engineering. We also discuss the challenges that need to be overcome and future directions for engineering protein allostery.
•Experimental and computational methods developed to map allosteric communications.•Engineering hybrid and long-range allosteric pathways.•Directed evolution and rational design of alternative allosteric networks.
iFoldRNA v2: folding RNA with constraints Krokhotin, Andrey; Houlihan, Kevin; Dokholyan, Nikolay V
Bioinformatics,
09/2015, Letnik:
31, Številka:
17
Journal Article
Recenzirano
Odprti dostop
A key to understanding RNA function is to uncover its complex 3D structure. Experimental methods used for determining RNA 3D structures are technologically challenging and laborious, which makes the ...development of computational prediction methods of substantial interest. Previously, we developed the iFoldRNA server that allows accurate prediction of short (<50 nt) tertiary RNA structures starting from primary sequences. Here, we present a new version of the iFoldRNA server that permits the prediction of tertiary structure of RNAs as long as a few hundred nucleotides. This substantial increase in the server capacity is achieved by utilization of experimental information such as base-pairing and hydroxyl-radical probing. We demonstrate a significant benefit provided by integration of experimental data and computational methods.
http://ifoldrna.dokhlab.org
dokh@unc.eu.
Toward rational vaccine engineering Vishweshwaraiah, Yashavantha L.; Dokholyan, Nikolay V.
Advanced drug delivery reviews,
04/2022, Letnik:
183
Journal Article
Recenzirano
Odprti dostop
Display omitted
Technological revolutions in several fields have pushed the boundaries of vaccine design and provided new avenues for vaccine development. Next-generation vaccine platforms have shown ...promise in targeting challenging antigens, for which traditional approaches have been ineffective. With advances in protein engineering, structural biology, computational biology and immunology, the structural vaccinology approach, which uses protein structure information to develop immunogens, holds promise for future vaccine design. In this review, we highlight various vaccine development strategies, along with their advantages and limitations. We discuss the rational vaccine design approach, which focuses on structure-based vaccine design. Finally, we discuss antigen engineering using the epitope-scaffold approach, gaps in structural vaccinology, and remaining challenges in vaccine design.
PDF
