scholarly journals Toward the computational design of protein crystals with improved resolution

2019 ◽  
Vol 75 (11) ◽  
pp. 1015-1027 ◽  
Author(s):  
Jeliazko R. Jeliazkov ◽  
Aaron C. Robinson ◽  
Bertrand García-Moreno E. ◽  
James M. Berger ◽  
Jeffrey J. Gray

Substantial advances have been made in the computational design of protein interfaces over the last 20 years. However, the interfaces targeted by design have typically been stable and high-affinity. Here, we report the development of a generic computational design method to stabilize the weak interactions at crystallographic interfaces. Initially, we analyzed structures reported in the Protein Data Bank to determine whether crystals with more stable interfaces result in higher resolution structures. We found that for 22 variants of a single protein crystallized by a single individual, the Rosetta-calculated `crystal score' correlates with the reported diffraction resolution. We next developed and tested a computational design protocol, seeking to identify point mutations that would improve resolution in a highly stable variant of staphylococcal nuclease (SNase). Using a protocol based on fixed protein backbones, only one of the 11 initial designs crystallized, indicating modeling inaccuracies and forcing us to re-evaluate our strategy. To compensate for slight changes in the local backbone and side-chain environment, we subsequently designed on an ensemble of minimally perturbed protein backbones. Using this strategy, four of the seven designed proteins crystallized. By collecting diffraction data from multiple crystals per design and solving crystal structures, we found that the designed crystals improved the resolution modestly and in unpredictable ways, including altering the crystal space group. Post hoc, in silico analysis of the three observed space groups for SNase showed that the native space group was the lowest scoring for four of six variants (including the wild type), but that resolution did not correlate with crystal score, as it did in the preliminary results. Collectively, our results show that calculated crystal scores can correlate with reported resolution, but that the correlation is absent when the problem is inverted. This outcome suggests that more comprehensive modeling of the crystallographic state is necessary to design high-resolution protein crystals from poorly diffracting crystals.

2019 ◽  
Author(s):  
Jeliazko R. Jeliazkov ◽  
Aaron C. Robinson ◽  
Bertrand García-Moreno E. ◽  
James M. Berger ◽  
Jeffrey J. Gray

AbstractSubstantial advances have been made in the computational design of protein interfaces over the last 20 years. However, the interfaces targeted by design have typically been stable and high affinity. Here, we report the development of a generic computational design method to stabilize the weak interactions at crystallographic interfaces. Initially, we analyzed structures reported in the Protein Data Bank (PDB) to determine whether crystals with more stable interfaces result in higher resolution structures. We found that, for twenty-two variants of a single protein crystallized by a single individual, Rosetta score correlates with resolution. We next developed and tested a computational design protocol, seeking to identify point mutations that would improve resolution on a highly stable variant of staphylococcal nuclease (SNase Δ+PHS). Only one of eleven initial designs crystallized, forcing us to re-evaluate our strategy and base our designs on an ensemble of protein backbones. Using this strategy, four of the five designed proteins crystallized. Collecting diffraction data for multiple crystals per design and solving crystal structures, we found that designed crystals improved resolution modestly and in unpredictable ways, including altering crystal space group. Post-hoc, in silico analysis showed that crystal space groups could have been predicted for four of six variants (including WT), but that resolution did not correlate with interface stability, as it did in the preliminary results. Our results show that single point mutations can have significant effects on crystal resolution and space group, and that it is possible to computationally identify such mutations, suggesting a potential design strategy to generate high-resolution protein crystals from poorly diffracting ones.


Author(s):  
Rajneesh K. Gaur

The space-group frequency distributions for two types of proteins and their complexes are explored. Based on the incremental availability of data in the Protein Data Bank, an analytical assessment shows a preferential distribution of three space groups, i.e. P212121 > P1211 > C121, in soluble and membrane proteins as well as in their complexes. In membrane proteins, the order of the three space groups is P212121 > C121 > P1211. The distribution of these space groups also shows the same pattern whether a protein crystallizes with a monomer or an oligomer in the asymmetric unit. The results also indicate that the sizes of the two entities in the structures of soluble proteins crystallized as complexes do not influence the frequency distribution of space groups. In general, it can be concluded that the space-group frequency distribution is homogenous across different types of proteins and their complexes.


Author(s):  
Kikuo Fujita ◽  
Shinsuke Akagi

Abstract A Framework of computational design method and model is proposed for layout and geometry design of complicated mechanical systems, which is named “configuration network and its viewing control”. In the method, a design object is represented with a set of declarative relationships among various elements of a system, that is, configurations, which is gradually extended from schematic structure to exact layout and geometry through design process. Since a whole of such configurations forms a too complicated network to compute all together, how to view subparts is controlled based on levels of granularity and width of scope range. Such a configuration network is made to grow and refined through embodying geometry and layout corresponding to a focused subpart with a numerical optimization procedure. The framework has also an ability to flexibly integrate with engineering analysis. Moreover, a design system is implemented with an object-oriented programming technique, and it is applied to a design problem of air conditioner units in order to show the validity and effectiveness of the framework.


Author(s):  
Jun Xu ◽  
Eugeni L. Doubrovski ◽  
Jo Geraedts ◽  
Yu Song

Abstract The geometric shapes and the relative position of coils influence the performance of a three-dimensional (3D) inductive power transfer system. In this paper, we propose a coil design method for specifying the positions and the shapes of a pair of coils to transmit the desired power in 3D. Given region of interests (ROIs) for designing the transmitter and the receiver coils on two surfaces, the transmitter coil is generated around the center of its ROI first. The center of the receiver coil is estimated as a random seed position in the corresponding 3D surface. At this position, we use the heatmap method with electromagnetic constraints to iteratively extend the coil until the desired power can be transferred via the set of coils. In each step, the shape of the extension, i.e. a new turn of the receiver coil, is found as a spiral curve based on the convex hulls of adjacent turns in the 2D projection plane along their normal direction. Then, the optimal position of the receiver coil is found by maximizing the efficiency of the system. In the next step, the position and the shape of the transmitter coil are optimized based on the fixed receiver coil using the same method. This zig-zag optimization process iterates until an optimum is reached. Simulations and experiments with digitally fabricated prototypes were conducted and the effectiveness of the proposed 3D coil design method was verified. Possible future research directions are highlighted well.


1999 ◽  
Vol 32 (2) ◽  
pp. 365-368 ◽  
Author(s):  
Guoguang Lu

In order to facilitate applications of averaging techniques in the MIR/MAD procedure, a program,FINDNCS, which automatically identifies non-crystallographic symmetry (NCS) from heavy-atom sites, has been developed. The program outputs the NCS operations (a rotation matrix and a translation vector), the corresponding root-mean-square (r.m.s.) deviations of heavy-atom sites, polar angles and screw translations, and writes coordinates of matching sites in Protein Data Bank (PDB) format. The program has an interface with the graphics programO[Joneset al. (1991).Acta Cryst.A47, 110–119] so that the NCS operations can be displayed automatically. In the test examples, all the correct NCS operations were identified and were above the noise solutions.


2019 ◽  
Vol 116 (5) ◽  
pp. 1597-1602 ◽  
Author(s):  
Alexander M. Sevy ◽  
Nicholas C. Wu ◽  
Iuliia M. Gilchuk ◽  
Erica H. Parrish ◽  
Sebastian Burger ◽  
...  

Influenza is a yearly threat to global public health. Rapid changes in influenza surface proteins resulting from antigenic drift and shift events make it difficult to readily identify antibodies with broadly neutralizing activity against different influenza subtypes with high frequency, specifically antibodies targeting the receptor binding domain (RBD) on influenza HA protein. We developed an optimized computational design method that is able to optimize an antibody for recognition of large panels of antigens. To demonstrate the utility of this multistate design method, we used it to redesign an antiinfluenza antibody against a large panel of more than 500 seasonal HA antigens of the H1 subtype. As a proof of concept, we tested this method on a variety of known antiinfluenza antibodies and identified those that could be improved computationally. We generated redesigned variants of antibody C05 to the HA RBD and experimentally characterized variants that exhibited improved breadth and affinity against our panel. C05 mutants exhibited improved affinity for three of the subtypes used in design by stabilizing the CDRH3 loop and creating favorable electrostatic interactions with the antigen. These mutants possess increased breadth and affinity of binding while maintaining high-affinity binding to existing targets, surpassing a major limitation up to this point.


Author(s):  
Wei Li ◽  
Daniel A. McAdams

As the advantages of foldable or deployable structures are being discovered, research into origami engineering has attracted more focus from both artists and engineers. With the aid of modern computer techniques, some computational origami design methods have been developed. Most of these methods focus on the problem of origami crease pattern design — the problem of determining a crease pattern to realize a specified origami final shape, but don’t provide computational solutions to actually developing a shape that meets some design performance criteria. This paper presents a design method that includes the computational design of the finished shape as well as the crease pattern. The origami shape will be designed to satisfy geometric, functional, and foldability requirements. This design method is named computational evolutionary embryogeny for optimal origami design (CEEFOOD), which is an extension of the genetic algorithm (GA) and an original computational evolutionary embryogeny (CEE). Unlike existing origami crease pattern design methods that adopt deductive logic, CEEFOOD implements an abductive approach to progressively evolve an optimal design. This paper presents how CEEFOOD — as a member of the GA family — determines the genetic representation (genotype) of candidate solutions, the formulation of the objective function, and the design of evolutionary operators. This paper gives an origami design problem, which has requirements on the folded-state profile, position of center of mass, and number of creases. Several solutions derived by CEEFOOD are listed and compared to highlight the effectiveness of this abductive design method.


2010 ◽  
Vol 4 (2) ◽  
Author(s):  
Francisco Casesnoves

The engineering design of surgical instrumentation to apply mechanical forces and linear moments on the human bones during the operations constitutes a rather difficult task. This is due both to the natural and pathological irregularities of the human bone morphology and surfaces and also to the individual variations from one patient to another. Usually, the forces are applied by the surgeon only on a determined part of the bone surfaces. This paper describes an innovative computational design method to digitalize, simulate, and fit mathematically the anterior vertebral body facet. We used real experimental data from 17 human cadaveric specimens to get and store a large amount of numerical surface digital values. The complete anterior vertebral body side was visualized and analyzed with grid data Subroutine, which was also used first to select the so-called natural regions of interest (ROIs). These ROIs correspond to those parts of the surface in contact with the surgical instrumentation, where the mechanical forces are applied. Subsequently, a numerical mathematical fitting-model was implemented for these ROIs. This was carried out with the development of a 3D geometrical least-squares optimization algorithm and appropriate software designed according to the proper numerical method selected. In doing so, the 3D superficies equations of the anterior vertebral body (L3, L4, L5, and S1) were determined after these fittings were mathematically checked as appropriate. Statistical parameters and determination coefficients that define the error boundaries and the goodness of this optimal fitting-model were calculated and NURBS error data in similar studies were commented. It was proven that the principal source of error was the micro- and macro-irregularities of human bone facets. The final surface equations, and their geodesics, were used to obtain accurate data for the spinal surgery instrumentation manufacturing. The industrial bioengineering result was the application of these equations for the design of a new spinal vertebral surgical distractor. This innovative distractor separates two adjacent vertebrae while keeping them parallel. That is, at their natural inclination, avoiding hammering the vertebrae to make the intervertebral space wider. The device mechanics also minimizes the necessary force to be carried out by the surgeon during the operation.


1998 ◽  
Vol 54 (6) ◽  
pp. 1199-1206 ◽  
Author(s):  
Suhail A. Islam ◽  
David Carvin ◽  
Michael J. E. Sternberg ◽  
Tom L. Blundell

Information on the preparation and characterization of heavy-atom derivatives of protein crystals has been collected, either from the literature or directly from protein crystallographers, and assembled in the form of a heavy-atom data bank (HAD). The data bank contains coordinate data for the heavy-atom positions in a form that is compatible with the crystallographic data in the Brookhaven Protein Data Bank, together with a wealth of information on the crystallization conditions, the nature of the heavy-atom reagent and references to relevant publications. Some statistical information derived from the data bank, such as the most popular heavy-atom derivatives, is also included. The information can be directly accessed and should be useful to protein crystallographers seeking to improve their success in preparing heavy-atom derivatives for the methods of isomorphous replacement and anomalous dispersion. The World Wide Web address of HAD is http://www.icnet.uk/bmm/had.


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