Modeling Rice rgMT as a Plant Metallothionein-Like Protein by the Distance Geometry and Homology Methods

Rice metallothionein-like protein (rgMT) shows characteristics of a three-section pattern composed of two highly conserved cysteine rich (CR) domains in the terminals and a spacer without cysteine (cys) residues in the center of the molecule. In this paper, the two CR domains and the spacer region were modeled by the distance geometry and homology methods separately. For the CR domains, twenty random models were generated for each cys combination based on the constraint conditions of CXC (C represents cys, X represents any amino acid other than cys), and CXXC motifs and a metal-sulfur chelating cluster. Four models for the N-terminal and two for C-terminal CR domain containing metal chelating structures formed by different combinations of cys were selected from 900 possible conformations. The GOR method was used to predict the secondary structure of the spacer region and its model was built by the homology method. After three parts of the protein were modeled, they were connected to form a three-dimensional structure model of rgMT. The whole conformation showed that rgMT could form two independent metal-sulfur chelating structures connected by a spacer peptide, without a structural or energy barrier for them to form two independent metal-chelating clusters just as mammalian metallothionein (MT) proteins. As all plant metallothionein-like (MT-L) proteins have the same primary structural characteristic, two CR domains connected by a spacer region, and many have the same cys arrangement pattern as rgMT, the three-dimensional structure model of rgMT will provide an important reference for the structural study of other plant MT-L proteins.

Modeling the Cysteine Rich Domain of Plant Metallothionein-like Protein

With the progress of plant genome research, more than 50 plant metallothionein_like (MT_L) genes have been found, but only several MT_L proteins have been detected and no experimental structural information for MT_L proteins has been reported so far. Since detailed knowledge of the protein tertiary structure is required to understand its biological function, a method is needed to determine the structure of these proteins. In this study, the structural data of known mammal MT was used to determine the interatomic distance constraints of the CXC and CXXC motifs and the metal_sulfur chelating cluster. Then several possible MT conformations were predicted using a distance geometry algorithm. The statistical analysis was used to select those with much lower target function values and lower conformation energies as the predicted tertiary structural models of the cysteine_rich (CR) domains of these proteins. A suitable prediction method for modeling the CR domain of the plant MT_L protein was constructed. The accurately predicted result for the known structure of an MT protein from blue crab suggests that this method is practicable. The tertiary structures of CR domains of rape MT_L protein LSC54 was then modeled with this method.

Selection and characterization of the novel anti-human PD-1 FV78 antibody from a targeted epitope mammalian cell-displayed antibody library

Currently,display-based methods are well established and widely used in antibody engineering for affinity maturation and structural stability improvement.We obtained a novel anti-human programmed death 1(PD-1)antibody using computer-aided design and a mammalian cell display technology platform.We used computer-aided modeling and distance geometry methods to predict and assign the key residues that contributed to the binding of human PD-L1 to PD-1.Then,we analyzed the sequence of nivolumab(an anti-human PD-1 antibody,referred to as MIL75 in the article)to determine the template for antibody design and library construction.We identified a series of potential substitutions on the obtained template and constructed a virtual epitope-targeted antibody library based on the physicochemical properties and each possible location of the assigned key residues.The virtual antibody libraries were displayed on the surface of mammalian cells as the antigen-binding fragments of full-length immunoglobulin G.Then,we used flow cytometry and sequencing approaches to sort and screen the candidates.Finally,we obtained a novel anti-human PD-1 antibody named FV78.FV78 competitively recognized the PD-1 epitopes that interacted with MIL75 and possessed an affinity comparable to MIL75.Our results implied that FV78 possessed equivalent bioactivity in vitro and in vivo compared with MIL75,which highlighted the probability and prospect of FV78 becoming a new potential antibody therapy.

Phase Retrieval via Sensor Network Localization

The problem of phase retrieval is revisited and studied from a fresh perspective.In particular,we establish a connection between the phase retrieval problem and the sensor network localization problem,which allows us to utilize the vast theoretical and algorithmic literature on the latter to tackle the former.Leveraging this connection,we develop a two-stage algorithm for phase retrieval that can provably recover the desired signal.In both sparse and dense settings,our proposed algorithm improves upon prior approaches simultaneously in the number of required measurements for recovery and the reconstruction time.We present numerical results to corroborate our theory and to demonstrate the efficiency of the proposed algorithm.As a side result,we propose a new form of phase retrieval problem and connect it to the complex rigidity theory proposed by Gortler and Thurston(in:Connelly R,Ivic Weiss A,Whiteley W(eds)Rigidity and symmetry,Springer,New York,pp 131–154,2014).