Synthesis and biological evaluation of two chemically modified peptide epitopes for the class I MHC protein HLA-B*2705

The T-cell receptor of a CD8(+) T-cell recognises peptide epitopes bound by class I major histocompatibility complex (MHC) glycoproteins presented in a groove on their upper surface. Within the groove of the MHC molecule are 6 pockets, two of which mostly display a high degree of specificity for binding amino acids capable of making conserved and energetically favourable contacts with the MHC. One type of MHC molecule, HLA-B*2705, preferentially binds peptides containing an arginine at position 2. In an effort to increase the affinity of peptides for HLA-B*2705, potentially leading to better immune responses to such a peptide, we synthesised two modified epitopes where the amino acid at position 2 involved in anchoring the peptide to the class I molecule was replaced with the alpha-methylated beta,gamma-unsaturated arginine analogue 2-(S)-amino-5-guanidino-2-methyl-pent-3-enoic acid. The latter was prepared via a multi-step synthetic sequence, starting from alpha-methyl serine, and incorporated into dipeptides which were fragment-coupled to resin-bound heptameric peptides yielding the target nonameric sequences. Biological characterisation indicated that the modified peptides were poorer than the native peptides at stabilising empty class I MHC complexes, and cells sensitised with these peptides were not recognised as well by cognate CD8(+) T-cells, where available, compared to those sensitised with the native peptide. We suggest that the modifications made to the peptide have decreased its ability to bind to the peptide binding groove of HLA-B*2705 molecules which may explain the decrease in recognition by cytotoxic T-cells when compared to the native peptide.     

T-cell epitopes of the La/SSB autoantigen: prediction based on the homology modeling of HLA-DQ2/DQ7 with the insulin-B peptide/HLA-DQ8 complex

T-cell epitopes are important components of the inappropriate response of the immune system to self-proteins in autoimmune diseases. In this study, the candidate T-cell epitopes of the La/SSB autoantigen, the main target of the autoimmune response in patients with Sjogren's Syndrome (SS), and Systemic Lupus Erythematosus (SLE) were predicted using as a template the HLA-DQ2 and DQ7 molecules, which are genetically linked to patients with SS and SLE. Modeling of DQ2 and DQ7 was based on the crystal structure of HLA-DQ8, an HLA molecule of high risk factor of type I diabetes, which is also an autoimmune disease. The quality and reliability of the modeled DQ2 and DQ7 was confirmed by the Ramachandran plot and the TINKER molecular modeling software. Common and/or similar candidate T-cell epitopes, obtained by comparing three different approaches the Taylor's sequence pattern, the TEPITOPE quantitative matrices, and the MULTIPRED artificial neural network, were subjected to homology modeling with the crystal structure of the insulin-B peptide complexed with HLA-DQ8, and the best superposed candidate epitopes were placed into the modeled HLA-DQ2 and DQ7 binding grooves to perform energy minimization calculations. Six T-cell epitopes were predicted for HLA-DQ7 and nine for HLA-DQ2 covering parts of the amino-terminal and the central regions of the La/SSB autoantigen. Residues corresponding to the P1, P4, and P9 pockets of the HLA-DQ2 and DQ7 binding grooves experience very low SASA because they are less exposed to the microenvironment of the groove. The proposed T-cell epitopes complexed with HLA-DQ2/DQ7 were further evaluated for their binding efficiency according to their potential interaction energy, binding affinity, and IC50 values. Our approach constitutes the ground work for a rapid and reliable experimentation concerning the T-cell epitope mapping of autoantigens, and could lead to the development of T-cell inhibitors as immunotherapeutics in autoimmune diseases.     

Dynamic characterization of HLA-B*44 Alleles: A comparative molecular dynamics simulation study

Human Leukocyte Antigens (HLA) are highly polymorphic proteins that play a key role in the immune system. HLA molecule is present on the cell membrane of antigen-presenting cells of the immune system and presents short peptides, originating from the proteins of invading pathogens or self-proteins, to the T-cell Receptor (TCR) molecule of the T-cells. In this study, peptide-binding characteristics of HLA-B*44:02, 44:03, 44:05 alleles bound to three nonameric peptides were studied using molecular dynamics simulations. Polymorphisms among these alleles (Asp116Tyr and Asp156Leu) result in major differences in the allele characteristics. While HLA-B*44:02 (Asp116, Asp156) and HLA-B*44:03 (Asp116, Leu156) depend on tapasin for efficient peptide loading, HLA-B*44:05 (Tyr116, Asp156) is tapasin independent. On the other hand, HLA-B*44:02 and HLA-B*44:03 mismatch is closely related to transplant rejection and acute-graft-versus-host disease. In order to understand the dynamic characteristics, the simulation trajectories were analyzed by applying Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) calculations and hydrogen bonding analysis. Binding dynamics of the three HLA-B*44 alleles and peptide sequences are comparatively discussed. In general, peptide binding stability is found to depend on the peptide rather than the allele type for HLA-B*44 alleles.     

Molecular dynamics and thermodynamics of protein-RNA interactions: mutation of a conserved aromatic residue modifies stacking interactions and structural adaptation in the U1A-stem loop 2 RNA complex.

Molecular dynamics (MD) simulations and free energy component analysis have been performed to evaluate the molecular origins of the 5.5 kcal/mol destabilization of the complex formed between the N-terminal RNP domain of U1A and stem loop 2 of U1 snRNA upon mutation of a conserved aromatic residue, Phe56, to Ala. MD simulations, including counterions and water, have been carried out on the wild type and Phe56Ala peptide-stem loop 2 RNA complexes, the free wild type and Phe56Ala peptides, and the free stem loop 2 RNA. The MD structure of the Phe56Ala-stem loop 2 complex is similar to that of the wild type complex except the stacking interaction between Phe56 and A6 of stem loop 2 is absent and loop 3 of the peptide is more dynamic. However, the MD simulations predict large changes in the structure and dynamics of helix C and increased dynamic range of loop 3 for the free Phe56Ala peptide compared to the wild type peptide. Since helix C and loop 3 are highly variable regions of RNP domains, this indicates that a significant contribution to the reduced affinity of the Phe56Ala peptide for RNA results from cooperation between highly conserved and highly variable regions of the RNP domain of U1A. Surprisingly, these structural effects, which are manifested as cooperative free energy changes, occur in the free peptide, rather than in the complex, and are revealed only by study of both the initial and final states of the complexation process. Free energy component analysis correctly accounts for the destabilization of the Phe56Ala-stem loop 2 complex, and indicates that approximately 80% of the destabilization is due to the loss of the stacking interaction and approximately 20% is due to differences in U1A adaptation.     

Fine specificity of antigen binding to two class I major histocompatibility proteins (B*2705 and B*2703) differing in a single amino acid residue

Starting from the X-ray structure of a class I majorhistocompatibility complex (MHC)-encoded protein (HLA-B*2705), a naturallypresented self-nonapeptide and two synthetic analogues were simulated in thebinding groove of two human leukocyte antigen (HLA) alleles (B*2703 andB*2705) differing in a single amino acid residue. After 200 ps moleculardynamics simulations of the solvated HLA–peptide pairs, some molecularproperties of the complexes (distances between ligand and protein center ofmasses, atomic fluctuations, buried versus accessible surface areas,hydrogen-bond frequencies) allow a clear discrimination of potent from weakMHC binders. The binding specificity of the three nonapeptides for the twoHLA alleles could be explained by the disruption of one hydrogen-bondingnetwork in the binding pocket of the HLA-B*2705 protein where the singlemutation occurs. Rearrangements of interactions in the B pocket, which bindsthe side chain of peptidic residue 2, and a weakening of interactionsinvolving the C-terminal end of the peptide also took place. In addition,extension of the peptide backbone using a -Ala analogue did notabolish binding to any of the two HLA-B27 subtypes, but increased theselectivity for B*2703, as expected from the larger peptide binding groovein this subtype. A better understanding of the atomic details involved inpeptide selection by closely related HLA alleles is of crucial importancefor unraveling the molecular features linking particular HLA alleles toautoimmune diseases, and for the identification of antigenic peptidestriggering such pathologies.     

Normal mode analysis of Zika virus

In recent years, Zika virus (ZIKV) caused a new pandemic due to its rapid spread and close relationship with microcephaly. As a result, ZIKV has become an obvious global health concern. Information about the fundamental viral features or the biological process of infection remains limited, despite considerable efforts. Meanwhile, the icosahedral shell structure of the mature ZIKV was recently revealed by cryo-electron microscopy. This structural information enabled us to simulate ZIKV. In this study, we analyzed the dynamic properties of ZIKV through simulation from the mechanical viewpoint. We performed normal mode analysis (NMA) for a dimeric structure of ZIKV consisting of the envelope proteins and the membrane proteins as a unit structure. By analyzing low-frequency normal modes, we captured intrinsic vibrational motions and defined basic vibrational properties of the unit structure. Moreover, we also simulated the entire shell structure of ZIKV at the reduced computational cost, similar to the case of the unit structure, by utilizing its icosahedral symmetry. From the NMA results, we can not only comprehend the putative dynamic fluctuations of ZIKV but also verify previous inference such that highly mobile glycosylation sites would play an important role in ZIKV. Consequently, this theoretical study is expected to give us an insight on the underlying biological functions and infection mechanism of ZIKV.     

Effect of the R119G mutation on human P5CR structure and its interactions with NAD: Insights derived from molecular dynamics simulation and free energy analysis

Pyrroline-5-carboxylate reductase (P5CR), an enzyme with conserved housekeeping roles, is involved in the etiology of cutis laxa. While previous work has shown that the R119G point mutation in the P5CR protein is involved, the structural mechanism behind the pathology remains to be elucidated. In order to probe the role of the R119G mutation in cutis laxa, we performed molecular dynamics (MD) simulations, essential dynamics (ED) analysis, and Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations on wild type (WT) and mutant P5CR-NAD complex. These MD simulations and ED analyses suggest that the R119G mutation decreases the flexibility of P5CR, specifically in the substrate binding pocket, which could decrease the kinetics of the cofactor entrance and egress. Furthermore, the MM-PBSA calculations suggest the R119G mutant has a lower cofactor binding affinity for NAD than WT. Our study provides insight into the possible role of the R119G mutation during interactions between P5CR and NAD, thus bettering our understanding of how the mutation promotes cutis laxa.     

Physical quantity of residue electrostatic energy in flavin mononucleotide binding protein dimer

The electrostatic (ES) energy of each residue was for the first time quantitatively evaluated in a flavin mononucleotide binding protein (FBP). A residue electrostatic energy (RES) was obtained as the sum of the ES energies between atoms in each residue and all other atoms in the FBP dimer using atomic coordinates obtained by a molecular dynamics (MD) simulation. ES is one of the most important energies among the interaction energies in a protein. It is determined from the RES, the residues which mainly contribute to stabilize the structure of each subunit, and the binding energy between two subunits can be estimated. The RES of all residues in subunit A (Sub A) and subunit B (Sub B) were attractive forces, even though the residues contain net negative or positive charges. This reveals that the ES energies of any of the residues can contribute to stabilize the protein structure. The total binding ES energy over all residues among the subunits was distributed between −0.2 to −1.2 eV (mean = −0.67 eV) from the MD simulation time.     

Recovery of known T-cell epitopes by computational scanning of a viral genome

A new computational method (EpiDock) is proposed for predicting peptide binding to class I MHC proteins, from the amino acid sequence of any protein of immunological interest. Starting from the primary structure of the target protein, individual three-dimensional structures of all possible MHC-peptide (8-, 9- and 10-mers) complexes are obtained by homology modelling. A free energy scoring function (Fresno) is then used to predict the absolute binding free energy of all possible peptides to the class I MHC restriction protein. Assuming that immunodominant epitopes are usually found among the top MHC binders, the method can thus be applied to predict the location of immunogenic peptides on the sequence of the protein target. When applied to the prediction of HLA-A^*0201-restricted T-cell epitopes from the Hepatitis B virus, EpiDock was able to recover 92% of known high affinity binders and 80% of known epitopes within a filtered subset of all possible nonapeptides corresponding to about one tenth of the full theoretical list.The proposed method is fully automated and fast enough to scan a viral genome in less than an hour on a parallel computing architecture. As it requires very few starting experimental data, EpiDock can be used: (i) to predict potential T-cell epitopes from viral genomes (ii) to roughly predict still unknown peptide binding motifs for novel class I MHC alleles.     

Immunology of O-glycosylated proteins: approaches to the design of a MUC1 glycopeptide-based tumor vaccine

Until about 1990 there was general consent about the assumption that only protein and peptide antigens have the capacity of CD4(+) or CD8(+) T-cell stimulation. Since about ten years evidence is now accumulating that carbohydrate-peptide epitopes do play a role in classical MHC-mediated immune responses. This holds true for glycopeptides, where the glycan chain is short and not located at an "anchor residue" needed for MHC interaction. T-cell recognition of O-glycosylated peptides is potentially of high biomedical significance, because it can mediate the immune protection against microorganisms, the vaccination in anti-tumor therapies, but also some aspects of autoimmunity. The epithelial type 1 transmembrane mucin MUC1 is established as a marker for monitoring recurrence of breast cancer and is a promising target for immunotherapeutic strategies to treat cancer by active specific immunization. Natural human immune responses to the tumor-associated glycoforms of the mucin indicate that antibody reactivities are more directed to glycopeptide than to non-glycosylated peptide epitopes. To overcome the weak immunogenicity of the natural target, heavily O-glycosylated MUC1, the question was addressed whether O-linked glycans remain intact during processing in the MHC class II pathway and interfere with endosomal processing and peptide presentation. Attempts were made to define on a biochemical level the structural requirements for an efficient endosomal proteolysis catalyzed by cathepsin L in antigen-presenting cells. Evidence based on work with CD4(+) T-hybridomas confirms that O-glycopeptides can be effectively presented to T-cells and that glycans can form integral parts of the TCR defined epitopes. Similar approaches are currently followed in the MHC class I pathway which aim at the identification of immunogenic glycopeptides generated by immunoproteasomes.     

Using random forest to classify T-cell epitopes based on amino acid properties and molecular features

T-lymphocyte (T-cell) is a very important component in human immune system. T-cell epitopes can be used for the accurately monitoring the immune responses which activation by major histocompatibility complex (MHC), and rationally designing vaccines. Therefore, accurate prediction of T-cell epitopes is crucial for vaccine development and clinical immunology. In current study, two types peptide features, i.e., amino acid properties and chemical molecular features were used for the T-cell epitopes peptide representation. Based on these features, random forest (RF) algorithm, a powerful machine learning algorithm, was used to classify T-cell epitopes and non-T-cell epitopes. The classification accuracy, sensitivity, specificity, Matthews correlation coefficient (MCC), and area under the curve (AUC) values for proposed method are 97.54%, 97.22%, 97.60%, 0.9193, and 0.9868, respectively. These results indicate that current method based on the combined features and RF is effective for T-cell epitopes prediction.     

Efficient estimation of binding free energies between peptides and an MHC class II molecule using coarse‐grained molecular dynamics simulations with a weighted histogram analysis method

We estimate the binding free energy between peptides and an MHC class II molecule using molecular dynamics (MD) simulations with the weighted histogram analysis method (WHAM). We show that, owing to its more thorough sampling in the available computational time, the binding free energy obtained by pulling the whole peptide using a coarse‐grained (CG) force field (MARTINI) is less prone to significant error induced by inadequate‐sampling than using an atomistic force field (AMBER). We further demonstrate that using CG MD to pull 3–4 residue peptide segments while leaving the remaining peptide segments in the binding groove and adding up the binding free energies of all peptide segments gives robust binding free energy estimations, which are in good agreement with the experimentally measured binding affinities for the peptide sequences studied. Our approach thus provides a promising and computationally efficient way to rapidly and reliably estimate the binding free energy between an arbitrary peptide and an MHC class II molecule. © 2017 Wiley Periodicals, Inc.     

Discovery of potential Zika virus RNA polymerase inhibitors by docking-based virtual screening

Zika virus (ZIKV) infection has been associated with Guillain-Barre syndrome in adults and microcephaly in infants. The existence of insufficient structural data in most of the protein databases hinders the synthesis of anti-ZIKV pharmaceutics. In this work, we attempted to model the catalytic domain of the ZIKV RNA polymerase (RdRpC) along with a detailed assessment of conserved aspartates in ZIKV RdRpC palm domain as potential drug targets. The conserved and catalytically active aspartate residues present in the predicted RdRpC protein were virtually screened against a ZINC database for inhibitors, and the selected potential drug candidates were further filtered based on their ADMET profiles. One of the pharmacokinetically active compounds (Ligand 6) showed a remarkable docking profile against the strictly conserved aspartate residues of the RdRpC active site. We hypothesize that the Ligand 6 may form a potential drug candidate for RdRpC inhibition in the clinical treatment of ZIKV infection.     

Forcefield evaluation and accelerated molecular dynamics simulation of Zn(II) binding to N-terminus of amyloid-β

We report conventional and accelerated molecular dynamics simulation of Zn(II) bound to the N-terminus of amyloid-β. By comparison against NMR data for the experimentally determined binding mode, we find that certain combinations of forcefield and solvent model perform acceptably in describing the size, shape and secondary structure, and that there is no appreciable difference between implicit and explicit solvent models. We therefore used the combination of ff14SB forcefield and GBSA solvent model to compare the result of different binding modes of Zn(II) to the same peptide, using accelerated MD to enhance sampling and comparing the free peptide simulated in the same way. We show that Zn(II) imparts significant rigidity to the peptide, disrupts the secondary structure and pattern of salt bridges seen in the free peptide, and induces closer contact between residues. Free energy surfaces in 1 or 2 dimensions further highlight the effect of metal coordination on peptide’s spatial extent. We also provide evidence that accelerated MD provides improved sampling over conventional MD by visiting as many or more configurations in much shorter simulation times.     

Studies on peptides. CLXVII. Solid-phase syntheses and immunological properties of fragment peptides related to human malaria circumsporozoite protein

A glycine-linked tetramer of Asn-Ala-Asn-Pro, a tandem repeated sequence of malaria circumsporozoite (CS) protein, was synthesized by the Boc-based solid phase method, followed by deprotection with 1 M trimethylsilyl trifluoromethanesulfonate-thioanisole in trifluoroacetic acid. In addition, three tetramer-related peptides were similarly synthesized, i.e., a 34-residue peptide [linked with TH, a proposed T-cell epitope of CS, at the C-terminus of the tetramer], a 46-residue peptide and a 59-residue peptide [linked with HA or HA', two proposed T-cell epitopes of influenza hemagglutinin protein, at the N-terminus of the above 34-residue peptide]. Their immunological properties were examined by enzyme-linked immunosorbent assay, for which three different congenic strains of mouse were used to raise the specific antibodies. Despite conjugation of T-cell epitopes to the tetramer, the mice of low-responder strains to the tetramer failed to produce any antibody specific to the tetramer. However, with the aid of recombinant interleukin 2 as an adjuvant, the low-responder mice produced antibody with relatively high titers.     

Analysis of a Critical Residue Determining Herbicide Efficiency Sensitivity in Carboxyltransferase Domain of Acetyl-CoA Carboxylase from Poaceae by Homology Modeling and Free Energy Simulation

Carboxyltransferase domain(CT) of acetyl-coenzyme A carboxylase(ACCase, EC 6.4.1.2) from a family of Poaceae is an important target of commercial herbicide APPs for controlling grass weed growth. As the abuse of APPs herbicides, the resistant ACCase due to the mutation of a single residue(Ile→Leu), which is lo-cated in CT active site, is emergent in many populations and species of Poaceae. So it is urgent to understand the re-sistant mecha-nism so as to design new effect herbicides. Herein lies the complex of CT dimmer from Lolium rigi-dum and herbicide haloxyfop successfully constructed for wild type enzyme and Ile/Leu mutant, respectively, pro-viding a basis for explaining the resistance from microscopic structure. Moreover, the binding free energy difference between wild type and mutant enzymes was predicted in good agreement with the known observation, and the various contributions to it were analyzed, by Molecular mechanics-Poisson-Boltzmann surface area(MM-PBSA) method. The results indicate the van der Waals interaction difference between the protein and inhibitor, –22.94 kJ/mol of CT wild type lower than that of mutant, is the major reason for resistance. Structure analysis further suggests that van der Waals interaction difference is originated from the steric hindrance between the side chain of mutated residue Leu and the chiral methyl group of haloxyfop. All these findings enhance the understanding of resistant mechanism of ACCase to herbicide by Ile/Leu mutation and provide an important clue for the rational design of high effective herbicides.     

The importance of dynamics in substrate-assisted catalysis and specificity

The QM/MM MD and free energy simulations show that the dynamics involving a His residue at the P1 site of the substrate may play an important role in substrate-assisted catalysis and specificity for a serine-carboxyl peptidase.     

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity: in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide-MHC binding affinity. The ISC-PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide-MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms--q2, SEP, and NC--ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made freely available online (http://www.jenner.ac.uk/MHCPred).     

Y220C突变体影响p53C蛋白质构象转换的分子动力学模拟

p53是迄今发现突变频率最高的一种肿瘤抑制蛋白质,突变会导致p53抑癌功能丧失并诱导癌症的发生。绝大多数的突变发生在p53的核心DNA结合区域（p53C）,其中Y220C是研究较多的一种突变体。虽然已有研究表明该突变能够降低p53C的结构稳定性,但其影响p53C构象转换的分子机制尚不清晰。本文利用分子动力学（MD）模拟方法研究了p53C突变体Y220C（p53C-Y220C）的结构变化,发现Y220C突变主要影响Y220C cluster区域（包括残基138-164和215-238）,且Y220C突变减少了Y220C cluster的β-折叠含量。进一步分析发现,Y220C突变不仅直接破坏突变氨基酸与周围氨基酸Leu145和Thr155之间的氢键,而且降低了Y220C cluster区域的折叠片S3和S8之间的氢键数量,使Y220C突变所形成的亲水性空腔变大,加速了水分子进入该蛋白质内部,并最终导致了p53C-Y220C变性。MD模拟结果揭示了Y220C突变影响p53C结构转换的分子机制,该研究对p53C-Y220C突变体高效稳定剂的筛选和设计具有重要意义。     

Structure-based design and confirmation of peptide ligands for neuronal polo-like kinase to promote neuroregeneration

Neuronal polo-like kinase (nPLK) is an essential regular of cell cycle and differentiation in nervous system, and targeting nPLK has been established as a promising therapeutic strategy to treat neurological disorders and to promote neuroregeneration. The protein contains an N-terminal kinase domain (KD) and a C-terminal Polo-box domain (PBD) that are mutually inhibited by each other. Here, the intramolecular KD–PBD complex in nPLK was investigated at structural level via bioinformatics analysis, molecular dynamics (MD) simulation and binding affinity scoring. From the complex interface two regions representing separately two continuous peptide fragments in PBD domain were identified as the hot spots of KD–PBD interaction. Structural and energetic analysis suggested that one (PBD peptide 1) of the two peptides can bind tightly to a pocket nearby the active site of KD domain, which is thus potential as self-inhibitory peptide to target and suppress nPLK kinase activity. The knowledge harvesting from computational studies were then used to guide the structural optimization and mutation of PBD peptide 1. Consequently, two of three peptide mutants separately exhibited moderately and considerably increased affinity as compared to the native peptide. The computationally modeled complex structures of KD domain with these self-inhibitory peptides were also examined in detail to unravel the structural basis and energetic property of nPLK-peptide recognition and interaction.