Geometry of compact tubes and protein structures

Proteins form a very important class of polymers. In spite of major advances in the understanding of polymer science, the protein problem has remained largely unsolved. Here, we show that a polymer chain viewed as a tube not only captures the well-known characteristics of polymers and their phases but also provides a natural explanation for many of the key features of protein behavior. There are two natural length scales associated with a tube subject to compaction -- the thickness of the tube and the range of the attractive interactions. For short tubes, when these length scales become comparable, one obtains marginally compact structures, which are relatively few in number compared to those in the generic compact phase of polymers. The motifs associated with the structures in this new phase include helices, hairpins and sheets. We suggest that Nature has selected this phase for the structures of proteins because of its many advantages including the few candidate strucures, the ability to squeeze the water out from the hydrophobic core and the flexibility and versatility associated with being marginally compact. Our results provide a framework for understanding the common features of all proteins.Comment: 15 pages, 3 eps figure

Active learning of the thermodynamics-dynamics tradeoff in protein condensates

Phase-separated biomolecular condensates exhibit a wide range of dynamical properties, which depend on the sequences of the constituent proteins and RNAs. However, it is unclear to what extent condensate dynamics can be tuned without also changing the thermodynamic properties that govern phase separation. Using coarse-grained simulations of intrinsically disordered proteins, we show that the dynamics and thermodynamics of homopolymer condensates are strongly correlated, with increased condensate stability being coincident with low mobilities and high viscosities. We then apply an "active learning" strategy to identify heteropolymer sequences that break this correlation. This data-driven approach and accompanying analysis reveal how heterogeneous amino-acid compositions and non-uniform sequence patterning map to a range of independently tunable dynamical and thermodynamic properties of biomolecular condensates

Molecular modeling to study dendrimers for biomedical applications

© 2014 by the authors; licensee MDPI; Basel; Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). Date of Acceptance: 17/11/2014Molecular modeling techniques provide a powerful tool to study the properties of molecules and their interactions at the molecular level. The use of computational techniques to predict interaction patterns and molecular properties can inform the design of drug delivery systems and therapeutic agents. Dendrimers are hyperbranched macromolecular structures that comprise repetitive building blocks and have defined architecture and functionality. Their unique structural features can be exploited to design novel carriers for both therapeutic and diagnostic agents. Many studies have been performed to iteratively optimise the properties of dendrimers in solution as well as their interaction with drugs, nucleic acids, proteins and lipid membranes. Key features including dendrimer size and surface have been revealed that can be modified to increase their performance as drug carriers. Computational studies have supported experimental work by providing valuable insights about dendrimer structure and possible molecular interactions at the molecular level. The progress in computational simulation techniques and models provides a basis to improve our ability to better predict and understand the biological activities and interactions of dendrimers. This review will focus on the use of molecular modeling tools for the study and design of dendrimers, with particular emphasis on the efforts that have been made to improve the efficacy of this class of molecules in biomedical applications.Peer reviewedFinal Published versio

Phase separation in amino acid mixtures is governed by composition

Macromolecular phase separation has recently come to immense prominence as it is central to the formation of membraneless organelles, leading to a new paradigm of cellular organization. This type of phase transition, often termed liquid-liquid phase separation (LLPS), is mediated by molecular interactions between biomolecules, including nucleic acids and both ordered and disordered proteins. In the latter case, the separation between protein-dense and -dilute phases is often interpreted using models adapted from polymer theory. Specifically, the “stickers and spacers” model proposes that the formation of condensate-spanning networks in protein solutions originates from the interplay between two classes of residues and that the main determinants for phase separation are multivalency and sequence patterning. The duality of roles of stickers (aromatics like Phe and Tyr) and spacers (Gly and polar residues) may apply more broadly in protein-like mixtures, and the presence of these two types of components alone may suffice for LLPS to take place. In order to explore this hypothesis, we use atomistic molecular dynamics simulations of capped amino acid residues as a minimal model system. We study the behavior of pure amino acids in water for three types of residues corresponding to the spacer and sticker categories and of their multicomponent mixtures. In agreement with previous observations, we find that the spacer-type amino acids fail to phase separate on their own, while the sticker is prone to aggregation. However, ternary amino acid mixtures involving both types of amino acids phase separate into two phases that retain intermediate degrees of compaction and greater fluidity than sticker-only condensates. Our results suggest that LLPS is an emergent property of amino acid mixtures determined by composition.Financial support to D.D.S. comes from Eusko Jaurlaritza (Basque Government) through the project IT1254-19 and the Spanish Government through grants RYC-2016-19590 and PID2021-127907NB-I00 (MCIN/AEI/10.13039/501100011033/FEDER, UE). The author thanks Xabier López for useful discussions and Athi N. Naganathan and Robert B. Best for their comments on the manuscript. The author also acknowledges the staff at the DIPC Supercomputing Center for technical support

Targeted modulation of protein liquid-liquid phase separation by evolution of amino-acid sequence.

Rationally and efficiently modifying the amino-acid sequence of proteins to control their ability to undergo liquid-liquid phase separation (LLPS) on demand is not only highly desirable, but can also help to elucidate which protein features are important for LLPS. Here, we propose a computational method that couples a genetic algorithm to a sequence-dependent coarse-grained protein model to evolve the amino-acid sequences of phase-separating intrinsically disordered protein regions (IDRs), and purposely enhance or inhibit their capacity to phase-separate. We validate the predicted critical solution temperatures of the mutated sequences with ABSINTH, a more accurate all-atom model. We apply the algorithm to the phase-separating IDRs of three naturally occurring proteins, namely FUS, hnRNPA1 and LAF1, as prototypes of regions that exist in cells and undergo homotypic LLPS driven by different types of intermolecular interaction, and we find that the evolution of amino-acid sequences towards enhanced LLPS is driven in these three cases, among other factors, by an increase in the average size of the amino acids. However, the direction of change in the molecular driving forces that enhance LLPS (such as hydrophobicity, aromaticity and charge) depends on the initial amino-acid sequence. Finally, we show that the evolution of amino-acid sequences to modulate LLPS is strongly coupled to the make-up of the medium (e.g. the presence or absence of RNA), which may have significant implications for our understanding of phase separation within the many-component mixtures of biological systems