Principles of assembly reveal a periodic table of protein complexes

Structural insights into protein complexes have had a broad impact on our understanding of biological function and evolution. Here we seek a comprehensive understanding of the general principles underlying quaternary structure organisation in protein complexes. To do this, we first examine the fundamental steps by which protein complexes can assemble using experimental and structure-based characterisation of assembly pathways. Most assembly transitions can be classified into three basic types, which can then be used to exhaustively enumerate a large set of possible quaternary structure topologies. These topologies, which include the vast majority of observed protein complex structures, give rise to a natural organisation into a periodic table. Based upon this, we are then able to accurately predict the expected frequencies of quaternary structure topologies, including those not yet observed. Overall, these results have important implications for quaternary structure prediction, modelling and engineering.This work was supported by the Royal Society (S.E.A. and C.V.R.), the Human Frontier Science Program (J.A.M.), the Medical Research Council grant G1000819 (H.H. and C.V.R.) and the Lister Institute for Preventative Medicine (S.A.T.).This is the author accepted manuscript. The final version is available from AAAS via http://dx.doi.org/10.1126/science.aaa224

Principles of assembly reveal a periodic table of protein complexes.

Structural insights into protein complexes have had a broad impact on our understanding of biological function and evolution. In this work, we sought a comprehensive understanding of the general principles underlying quaternary structure organization in protein complexes. We first examined the fundamental steps by which protein complexes can assemble, using experimental and structure-based characterization of assembly pathways. Most assembly transitions can be classified into three basic types, which can then be used to exhaustively enumerate a large set of possible quaternary structure topologies. These topologies, which include the vast majority of observed protein complex structures, enable a natural organization of protein complexes into a periodic table. On the basis of this table, we can accurately predict the expected frequencies of quaternary structure topologies, including those not yet observed. These results have important implications for quaternary structure prediction, modeling, and engineering.This work was supported by the Royal Society (S.E.A. and C.V.R.), the Human Frontier Science Program (J.A.M.), the Medical Research Council grant G1000819 (H.H. and C.V.R.) and the Lister Institute for Preventative Medicine (S.A.T.).This is the author accepted manuscript. The final version is available from AAAS via http://dx.doi.org/10.1126/science.aaa224

Protein design: A perspective from simple tractable models

We review the recent progress in computational approaches to protein design which builds on advances in statistical-mechanical protein folding theory. In particular, we evaluate the degeneracy of the protein code (i.e. how many sequences fold into a given conformation) and outline a simple condition for ''designability`` in a protein model. From this point of view we discuss several popular protein models that were used for sequence design by several authors. We evaluate the strengths and weaknesses of popular approaches based on stochastic optimization in sequence space and discuss possible ways to improve them to bring them closer to experiment. We also discuss how sequence design affects folding and point out to some features of proteins that can be deigned ''in'' or designed ''out''}Comment: 12 pages three figure

Folding Kinetics of Protein Like Heteropolymers

Using a simple three-dimensional lattice copolymer model and Monte Carlo dynamics, we study the collapse and folding of protein-like heteropolymers. The polymers are 27 monomers long and consist of two monomer types. Although these chains are too long for exhaustive enumeration of all conformations, it is possible to enumerate all the maximally compact conformations, which are 3x3x3 cubes. This allows us to select sequences that have a unique global minimum. We then explore the kinetics of collapse and folding and examine what features determine the various rates. The folding time has a plateau over a broad range of temperatures and diverges at both high and low temperatures. The folding time depends on sequence and is related to the amount of energetic frustration in the native state. The collapse times of the chains are sequence independent and are a few orders of magnitude faster than the folding times, indicating a two-phase folding process. Below a certain temperature the chains exhibit glass-like behavior, characterized by a slowing down of time scales and loss of self-averaging behavior. We explicitly define the glass transition temperature (Tg), and by comparing it to the folding temperature (Tf), we find two classes of sequences: good folders with Tf > Tg and non-folders with Tf < Tg.Comment: 23 pages (plus 10 figures included in a seperate file) LaTeX, no local report nu

Inverse Quantum Chemistry: Concepts and Strategies for Rational Compound Design

The rational design of molecules and materials is becoming more and more important. With the advent of powerful computer systems and sophisticated algorithms, quantum chemistry plays an important role in rational design. While traditional quantum chemical approaches predict the properties of a predefined molecular structure, the goal of inverse quantum chemistry is to find a structure featuring one or more desired properties. Herein, we review inverse quantum chemical approaches proposed so far and discuss their advantages as well as their weaknesses.Comment: 43 pages, 5 figure

Enumeration, conformation sampling and population of libraries of peptide macrocycles for the search of chemotherapeutic cardioprotection agents

Peptides are uniquely endowed with features that allow them to perturb previously difficult to drug biomolecular targets. Peptide macrocycles in particular have seen a flurry of recent interest due to their enhanced bioavailability, tunability and specificity. Although these properties make them attractive hit-candidates in early stage drug discovery, knowing which peptides to pursue is non‐trivial due to the magnitude of the peptide sequence space. Computational screening approaches show promise in their ability to address the size of this search space but suffer from their inability to accurately interrogate the conformational landscape of peptide macrocycles. We developed an in‐silico compound enumerator that was tasked with populating a conformationally laden peptide virtual library. This library was then used in the search for cardio‐protective agents (that may be administered, reducing tissue damage during reperfusion after ischemia (heart attacks)). Our enumerator successfully generated a library of 15.2 billion compounds, requiring the use of compression algorithms, conformational sampling protocols and management of aggregated compute resources in the context of a local cluster. In the absence of experimental biophysical data, we performed biased sampling during alchemical molecular dynamics simulations in order to observe cyclophilin‐D perturbation by cyclosporine A and its mitochondrial targeted analogue. Reliable intermediate state averaging through a WHAM analysis of the biased dynamic pulling simulations confirmed that the cardio‐protective activity of cyclosporine A was due to its mitochondrial targeting. Paralleltempered solution molecular dynamics in combination with efficient clustering isolated the essential dynamics of a cyclic peptide scaffold. The rapid enumeration of skeletons from these essential dynamics gave rise to a conformation laden virtual library of all the 15.2 Billion unique cyclic peptides (given the limits on peptide sequence imposed). Analysis of this library showed the exact extent of physicochemical properties covered, relative to the bare scaffold precursor. Molecular docking of a subset of the virtual library against cyclophilin‐D showed significant improvements in affinity to the target (relative to cyclosporine A). The conformation laden virtual library, accessed by our methodology, provided derivatives that were able to make many interactions per peptide with the cyclophilin‐D target. Machine learning methods showed promise in the training of Support Vector Machines for synthetic feasibility prediction for this library. The synergy between enumeration and conformational sampling greatly improves the performance of this library during virtual screening, even when only a subset is used