NMR Studies of the Interactions between Sialyllactoses and the Polysialytransferase Domain for Polysialylation Inhibition.

It is known that sialyllactose (SL) in mammalians is a major source of sialic acid (Sia), which can further form cytidine monophosphate sialic acid (CMP-Sia), and the final product is polysialic acid (polySia) using polysialyltransferases (polySTs) on the neural cell adhesion molecule (NCAM). This process is called NCAM polysialylation. The overexpression of polysialylation is strongly related to cancer cell migration, invasion, and metastasis. In order to inhibit the overexpression of polysialylation, in this study, SL was selected as an inhibitor to test whether polysialylation could be inhibited. Our results suggest that the interactions between the polysialyltransferase domain (PSTD) in polyST and CMP-Siaand the PSTD and polySia could be inhibited when the 3'-sialyllactose (3'-SL) or 6'-sialyllactose (6'-SL) concentration is about 0.5 mM or 6'-SL and 3 mM, respectively. The results also show that SLs (particularly for 3'-SL) are the ideal inhibitors compared with another two inhibitors, low-molecular-weight heparin (LMWH) and cytidine monophosphate (CMP), because 3'-SL can not only be used to inhibit NCAM polysialylation, but is also one of the best supplements for infant formula and the gut health system.

The Bifunctional Effects of Lactoferrin (LFcinB11) in Inhibiting Neural Cell Adhesive Molecule (NCAM) Polysialylation and the Release of Neutrophil Extracellular Traps (NETs).

The expression of polysialic acid (polySia) on the neuronal cell adhesion molecule (NCAM) is called NCAM-polysialylation, which is strongly related to the migration and invasion of tumor cells and aggressive clinical status. Thus, it is important to select a proper drug to block tumor cell migration during clinical treatment. In this study, we proposed that lactoferrin (LFcinB11) may be a better candidate for inhibiting NCAM polysialylation when compared with CMP and low-molecular-weight heparin (LMWH), which were determined based on our NMR studies. Furthermore, neutrophil extracellular traps (NETs) represent the most dramatic stage in the cell death process, and the release of NETs is related to the pathogenesis of autoimmune and inflammatory disorders, with proposed involvement in glomerulonephritis, chronic lung disease, sepsis, and vascular disorders. In this study, the molecular mechanisms involved in the inhibition of NET release using LFcinB11 as an inhibitor were also determined. Based on these results, LFcinB11 is proposed as being a bifunctional inhibitor for inhibiting both NCAM polysialylation and the release of NETs.

The NMR studies of CMP inhibition of polysialylation.

The overexpression of polysialic acid (polySia) on neural cell adhesion molecules (NCAM) promotes hypersialylation, and thus benefits cancer cell migration and invasion. It has been proposed that the binding between the polysialyltransferase domain (PSTD) and CMP-Sia needs to be inhibited in order to block the effects of hypersialylation. In this study, CMP was confirmed to be a competitive inhibitor of polysialyltransferases (polySTs) in the presence of CMP-Sia and triSia (oligosialic acid trimer) based on the interactional features between molecules. The further NMR analysis suggested that polysialylation could be partially inhibited when CMP-Sia and polySia co-exist in solution. In addition, an unexpecting finding is that CMP-Sia plays a role in reducing the gathering extent of polySia chains on the PSTD, and may benefit for the inhibition of polysialylation. The findings in this study may provide new insight into the optimal design of the drug and inhibitor for cancer treatment.

Highly efficient bioconversion of icariin to icaritin by whole-cell catalysis.

BACKGROUND: Icaritin is an aglycone of flavonoid glycosides from Herba Epimedii. It has good performance in the treatment of hepatocellular carcinoma in clinical trials. However, the natural icaritin content of Herba Epimedii is very low. At present, the icaritin is mainly prepared from flavonoid glycosides by α-L-rhamnosidases and ß-glucosidases in two-step catalysis process. However, one-pot icaritin production required reported enzymes to be immobilized or bifunctional enzymes to hydrolyze substrate with long reaction time, which caused complicated operations and high costs. To improve the production efficiency and reduce costs, we explored α-L-rhamnosidase SPRHA2 and ß-glucosidase PBGL to directly hydrolyze icariin to icaritin in one-pot, and developed the whole-cell catalytic method for efficient icaritin production. RESULTS: The SPRHA2 and PBGL were expressed in Escherichia coli, respectively. One-pot production of icaritin was achieved by co-catalysis of SPRHA2 and PBGL. Moreover, whole-cell catalysis was developed for icariin hydrolysis. The mixture of SPRHA2 cells and PBGL cells transformed 200 g/L icariin into 103.69 g/L icaritin (yield 95.23%) in 4 h in whole-cell catalysis under the optimized reaction conditions. In order to further increase the production efficiency and simplify operations, we also constructed recombinant E. coli strains that co-expressed SPRHA2 and PBGL. Crude icariin extracts were also efficiently hydrolyzed by the whole-cell catalytic system. CONCLUSIONS: Compared to previous reports on icaritin production, in this study, whole-cell catalysis showed higher production efficiency of icaritin. This study provides promising approach for industrial production of icaritin in the future.

The Graphical Studies of the Major Molecular Interactions for Neural Cell Adhesion Molecule (NCAM) Polysialylation by Incorporating Wenxiang Diagram into NMR Spectroscopy.

Polysialylation is a process of polysialic acid (polySia) addition to neural cell adhesion molecule (NCAM), which is associated with tumor cell migration and progression in many metastatic cancers and neurocognition. Polysialylation can be catalyzed by two highly homologous mammalian polysialyltransferases (polySTs), ST8Sia II (STX) and ST8Sia IV (PST). It has been proposed that two polybasic domains, polybasic region (PBR) and polysialyltransferase domain (PSTD) in polySTs, are possible binding sites for the intermolecular interactions of polyST-NCAM and polyST-polySia, respectively, as well as the intramolecular interaction of PSTD-PBR. In this study, Chou's wenxiang diagrams of the PSTD and PBR are used to determine the key amino acids of these intermolecular and intramolecular interactions, and thus it may be helpful for the identification of the crucial amino acids in the polyST and for the understanding of the molecular mechanism of NCAM polysialylation by incorporating the wenxiang diagram and molecular modeling into NMR spectroscopy.

Molecular Mechanism of Inhibition of Polysialyltransferase Domain (PSTD) by Heparin.

The polysialic acid (polySia) is a unique carbohydrate polymer produced on the surface of Neuronal Cell Adhesion Molecule (NCAM) in a number of cancer cells, and strongly correlates with the migration and invasion of tumor cells and with aggressive, metastatic disease and poor clinical prognosis in the clinic. Its synthesis is catalyzed by two polysialyltransferases (polySTs), ST8SiaIV (PST) and ST8SiaII (STX). Selective inhibition of polySTs, therefore, presents a therapeutic opportunity to inhibit tumor invasion and metastasis due to NCAM polysialylation. It has been proposed that NCAM polysialylation could be inhibited by two types of heparin inhibitors, low molecular heparin (LMWH) and heparin tetrasaccharide (DP4). This review summarizes how the interactions between Polysialyltransferase Domain (PSTD) in ST8SiaIV and CMP-Sia, and between the PSTD and polySia take place, and how these interactions are inhibited by LMWH and DP4. Our NMR studies indicate that LMWH is a more effective inhibitor than DP4 for inhibition of NCAM polysialylation. The NMR identification of heparin-binding sites in the PSTD may provide insight into the design of specific inhibitors of polysialylation.

Molecular Interactions of the Polysialytransferase Domain (PSTD) in ST8Sia IV with CMP-Sialic Acid and Polysialic Acid Required for Polysialylation of the Neural Cell Adhesion Molecule Proteins: An NMR Study.

Polysialic acid (polySia) is an unusual glycan that posttranslational modifies neural cell adhesion molecule (NCAM) proteins in mammalian cells. The up-regulated expression of polySia-NCAM is associated with tumor progression in many metastatic human cancers and in neurocognitive processes. Two members of the ST8Sia family of α2,8-polysialyltransferases (polySTs), ST8Sia II (STX) and ST8Sia IV (PST) both catalyze synthesis of polySia when activated cytidine monophosphate(CMP)-Sialic acid (CMP-Sia) is translocate into the lumen of the Golgi apparatus. Two key polybasic domains in the polySTs, the polybasic region (PBR) and the polysialyltransferase domain (PSTD) areessential forpolysialylation of the NCAM proteins. However, the precise molecular details to describe the interactions required for polysialylation remain unknown. In this study, we hypothesize that PSTD interacts with both CMP-Sia and polySia to catalyze polysialylation of the NCAM proteins. To test this hypothesis, we synthesized a 35-amino acid-PSTD peptide derived from the ST8Sia IV gene sequence and used it to study its interaction with CMP-Sia, and polySia. Our results showed for the PSTD-CMP-Sia interaction,the largest chemical-shift perturbations (CSP) were in amino acid residues V251 to A254 in the short H1 helix, located near the N-terminus of PSTD. However, larger CSP values for the PSTD-polySia interaction were observed in amino acid residues R259 to T270 in the long H2 helix. These differences suggest that CMP-Sia preferentially binds to the domain between the short H1 helix and the longer H2 helix. In contrast, polySia was principally bound to the long H2 helix of PSTD. For the PSTD-polySia interaction, a significant decrease in peak intensity was observed in the 20 amino acid residues located between the N-and C-termini of the long H2 helix in PSTD, suggesting a slower motion in these residues when polySia bound to PSTD. Specific features of the interactions between PSTD-CMP-Sia, and PSTD-polySia were further confirmed by comparing their 800 MHz-derived HSQC spectra with that of PSTD-Sia, PSTD-TriSia (DP 3) and PSTD-polySia. Based on the interactions between PSTD-CMP-Sia, PSTD-polySia, PBR-NCAM and PSTD-PBR, these findingsprovide a greater understanding of the molecular mechanisms underlying polySia-NCAM polysialylation, and thus provides a new perspective for translational pharmacological applications and development by targeting the two polysialyltransferases.

The Cooperative Effect between Polybasic Region (PBR) and Polysialyltransferase Domain (PSTD) within Tumor-Target Polysialyltranseferase ST8Sia II.

ST8Sia II (STX) is a highly homologous mammalian polysialyltransferase (polyST), which is a validated tumor-target in the treatment of cancer metastasis reliant on tumor cell polysialylation. PolyST catalyzes the synthesis of α2,8-polysialic acid (polySia) glycans by carrying out the activated CMP-Neu5Ac (Sia) to N- and O-linked oligosaccharide chains on acceptor glycoproteins. In this review article, we summarized the recent studies about intrinsic correlation of two polybasic domains, Polysialyltransferase domain (PSTD) and Polybasic region (PBR) within ST8Sia II molecule, and suggested that the critical amino acid residues within the PSTD and PBR motifs of ST8Sia II for polysialylation of Neural cell adhesion molecules (NCAM) are related to ST8Sia II activity. In addition, the conformational changes of the PSTD domain due to point mutations in the PBR or PSTD domain verified an intramolecular interaction between the PBR and the PSTD. These findings have been incorporated into Zhou's NCAM polysialylation/cell migration model, which will provide new perspectives on drug research and development related to the tumor-target ST8Sia II.

A Possible Modulation Mechanism of Intramolecular and Intermolecular Interactions for NCAM Polysialylation and Cell Migration.

Polysialic acid (polySia) is a novel glycan that posttranslationally modifies neural cell adhesion molecules (NCAMs) in mammalian cells. Up-regulation of polySia-NCAM expression or NCAM polysialylation is associated with tumor cell migration and progression in many metastatic cancers and neurocognition. It has been known that two highly homologous mammalian polysialyltransferases (polySTs), ST8Sia II (STX) and ST8Sia IV (PST), can catalyze polysialylation of NCAM, and two polybasic domains, polybasic region (PBR) and polysialyltransferase domain (PSTD) in polySTs play key roles in affecting polyST activity or NCAM polysialylation. However, the molecular mechanisms of NCAM polysialylation and cell migration are still not entirely clear. In this minireview, the recent research results about the intermolecular interactions between the PBR and NCAM, the PSTD and cytidine monophosphate-sialic acid (CMP-Sia), the PSTD and polySia, and as well as the intramolecular interaction between the PBR and the PSTD within the polyST, are summarized. Based on these cooperative interactions, we have built a novel model of NCAM polysialylation and cell migration mechanisms, which may be helpful to design and develop new polysialyltransferase inhibitors.

The Inhibition of Polysialyltranseferase ST8SiaIV Through Heparin Binding to Polysialyltransferase Domain (PSTD).

BACKGROUND: The polysialic acid (polySia) is a unique carbohydrate polymer produced on the surface Of Neuronal Cell Adhesion Molecule (NCAM) in a number of cancer cells, and strongly correlates with the migration and invasion of tumor cells and with aggressive, metastatic disease and poor clinical prognosis in the clinic. Its synthesis is catalyzed by two polysialyltransferases (polySTs), ST8SiaIV (PST) and ST8SiaII (STX). Selective inhibition of polySTs, therefore, presents a therapeutic opportunity to inhibit tumor invasion and metastasis due to NCAM polysialylation. Heparin has been found to be effective in inhibiting the ST8Sia IV activity, but no clear molecular rationale. It has been found that polysialyltransferase domain (PSTD) in polyST plays a significant role in influencing polyST activity, and thus it is critical for NCAM polysialylation based on the previous studies. OBJECTIVE: To determine whether the three different types of heparin (unfractionated hepain (UFH), low molecular heparin (LMWH) and heparin tetrasaccharide (DP4)) is bound to the PSTD; and if so, what are the critical residues of the PSTD for these binding complexes? METHODS: Fluorescence quenching analysis, the Circular Dichroism (CD) spectroscopy, and NMR spectroscopy were used to determine and analyze interactions of PSTD-UFH, PSTD-LMWH, and PSTD-DP4. RESULTS: The fluorescence quenching analysis indicates that the PSTD-UFH binding is the strongest and the PSTD-DP4 binding is the weakest among these three types of the binding; the CD spectra showed that mainly the PSTD-heparin interactions caused a reduction in signal intensity but not marked decrease in α-helix content; the NMR data of the PSTD-DP4 and the PSTDLMWH interactions showed that the different types of heparin shared 12 common binding sites at N247, V251, R252, T253, S257, R265, Y267, W268, L269, V273, I275, and K276, which were mainly distributed in the long α-helix of the PSTD and the short 3-residue loop of the C-terminal PSTD. In addition, three residues K246, K250 and A254 were bound to the LMWH, but not to DP4. This suggests that the PSTD-LMWH binding is stronger than the PSTD-DP4 binding, and the LMWH is a more effective inhibitor than DP4. CONCLUSION: The findings in the present study demonstrate that PSTD domain is a potential target of heparin and may provide new insights into the molecular rationale of heparin-inhibiting NCAM polysialylation.

Enhanced production of optical (S)-acetoin by a recombinant Escherichia coli whole-cell biocatalyst with NADH regeneration.

Acetoin is an important platform chemical with a variety of applications in foods, cosmetics, chemical synthesis, and especially in the asymmetric synthesis of optically active pharmaceuticals. It is also a useful breath biomarker for early lung cancer diagnosis. In order to enhance production of optical (S)-acetoin and facilitate this building block for a series of chiral pharmaceuticals derivatives, we have developed a systematic approach using in situ-NADH regeneration systems and promising diacetyl reductase. Under optimal conditions, we have obtained 52.9 g L-1 of (S)-acetoin with an enantiomeric purity of 99.5% and a productivity of 6.2 g (L h)-1. The results reported in this study demonstrated that the production of (S)-acetoin could be effectively improved through the engineering of cofactor regeneration with promising diacetyl reductase. The systematic approach developed in this study could also be applied to synthesize other optically active α-hydroxy ketones, which may provide valuable benefits for the study of drug development.

The Intrinsic Relationship Between Structure and Function of the Sialyltransferase ST8Sia Family Members.

As a subset of glycosyltransferases, the family of sialyltransferases catalyze transfer of sialic acid (Sia) residues to terminal non-reducing positions on oligosaccharide chains of glycoproteins and glycolipids, utilizing CMP-Neu5Ac as the activated sugar nucleotide donor. In the four known sialyltransferase families (ST3Gal, ST6Gal, ST6GalNAc and ST8Sia), the ST8Sia family catalyzes synthesis of α2, 8-linked sialic/polysialic acid (polySia) chains according to their acceptor specificity. We have determined the 3D structural models of the ST8Sia family members, designated ST8Sia I (1), II(2), IV(4), V(5), and VI(6) using the Phyre2 server. Accuracy of these predicted models are based on the ST8Sia III crystal structure as the calculated template. The common structural features of these models are: (1) Their parallel templates and disulfide bonds are buried within the enzymes and are predominately surrounded by helices; (2) The anti-parallel ß-sheets are located at the N-terminal region of the enzymes; (3) The mono-sialytransferases (mono-STs), ST8Sia I and ST8Sia VI, contain only a single pair of disulfide bonds, and there are no anti-parallel ß-sheets in ST8Sia VI; (4) The Nterminal region of all of the mono-STs are located some distant away from their core structure; (5) These conformational features show that the 3D structures of the mono-STs are less compact than the two polySTs, ST8Sia II and ST8Sia IV, and the oligo-ST, ST8Sia III. These structural features relate to the catalytic specificity of the monoSTs; (6) In contrast, the more compact structural features of ST8Sia II, ST8Sia IV and ST8Sia III relate to their ability to catalyze the processive synthesis of oligo- (ST8Sia III) and polySia chains (ST8Sia II & ST8Sia IV); (7) Although ST8Sia II, III and IV have similar conformations in their corresponding polysialyltransferase domain (PSTD) and polybasic region (PBR) motifs, the structure of ST8Sia III is less compact than ST8Sia II and ST8Sia IV, and the amino acid components of the several three-residue-loops in the two motifs of ST8Sia III are different from that in ST8Sia II and ST8Sia IV. This is likely the structural basis for why ST8Sia III is an oligoST and not able to polysialylate and; (8) In contrast, essentially all amino acids within the threeresidue- loops in the PSTD of ST8Sia II and ST8Sia IV are highly conserved, and many amino acids in the loops and the helices of these two motifs are critical for NCAM polysialylation, as determined by mutational analysis and confirmed by our recent NMR results. In summary, these new findings provide further insights into the molecular mechanisms underlying polyST-NCAM recognition, polySTpolySia/ oligoSia interactions, and polysialylation of NCAM.

Recent development of peptide drugs and advance on theory and methodology of peptide inhibitor design.

Due to the low toxicity, easy synthesis, rapid elimination, and less side effect, more and more peptide inhibitors are emerging as the effective drugs that are clinically used in therapies of a number of diseases. At the same time the computer-aided drug design (CADD) methods have remarkably developed. In this mini review the newly developed peptide inhibitors and drugs are introduced, including peptide vaccines for cancers, peptide inhibitors for HIV, Alzheimer's disease and related diseases, and the peptides as the leading compounds of drugs. The recent progress in the theory and methodology of peptide inhibitor design is reviewed. (1) The flexible protein-peptide docking model is introduced, in which the peptide structures are treated as segment-flexible chains using genetic algorithm and special force field parameters. (2) The "Wenxiang diagram" is illustrated for protein-peptide interaction analysis that has been successfully used in the coiled-coil interaction analysis. (3) The "Distorted key" theory is reviewed, which is an effective method to convert the peptide inhibitors to the small chemical drugs. (4) The amino acid property-based peptide prediction method (AABPP) is described that is a twolevel QSAR prediction network for the bioactivity prediction of peptide inhibitors. (5) Finally, several types of molecular interactions between protein and peptide ligands are summarized, including cation-π interactions; polar hydrogen-π interactions; and π-π stocking interactions.

Insight into a molecular interaction force supporting peptide backbones and its implication to protein loops and folding.

Although not being classified as the most fundamental protein structural elements like α-helices and ß-strands, the loop segment may play considerable roles for protein stability, flexibility, and dynamic activity. Meanwhile, the protein loop is also quite elusive; i.e. its interactions with the other parts of protein as well as its own shape-maintaining forces have still remained as a puzzle or at least not quite clear yet. Here, we report a molecular force, the so-called polar hydrogen-π interaction (Hp-π), which may play an important role in supporting the backbones of protein loops. By conducting the potential energy surface scanning calculations on the quasi π-plane of peptide bond unit, we have observed the following intriguing phenomena: (1) when the polar hydrogen atom of a peptide unit is perpendicularly pointing to the π-plane of other peptide bond units, a remarkable Hp-π interaction occurs; (2) the interaction is distance and orientation dependent, acting in a broad space, and belonging to the 'point-to-plane' one. The molecular force reported here may provide useful interaction concepts and insights into better understanding the loop's unique stability and flexibility feature, as well as the driving force of the protein global folding.

Physics and chemistry-driven artificial neural network for predicting bioactivity of peptides and proteins and their design.

Predicting the bioactivity of peptides and proteins is an important challenge in drug development and protein engineering. In this study we introduce a novel approach, the so-called "physics and chemistry-driven artificial neural network (Phys-Chem ANN)", to deal with such a problem. Unlike the existing ANN approaches, which were designed under the inspiration of biological neural system, the Phys-Chem ANN approach is based on the physical and chemical principles, as well as the structural features of proteins. In the Phys-Chem ANN model the "hidden layers" are no longer virtual "neurons", but real structural units of proteins and peptides. It is a hybridization approach, which combines the linear free energy concept of quantitative structure-activity relationship (QSAR) with the advanced mathematical technique of ANN. The Phys-Chem ANN approach has adopted an iterative and feedback procedure, incorporating both machine-learning and artificial intelligence capabilities. In addition to making more accurate predictions for the bioactivities of proteins and peptides than is possible with the traditional QSAR approach, the Phys-Chem ANN approach can also provide more insights about the relationship between bioactivities and the structures involved than the ANN approach does. As an example of the application of the Phys-Chem ANN approach, a predictive model for the conformational stability of human lysozyme is presented.

Recent advances in QSAR and their applications in predicting the activities of chemical molecules, peptides and proteins for drug design.

This review is to summarize three new QSAR (quantitative structure-activity relationship) methods recently developed in our group and their applications for drug design. Based on more solid theoretical models and advanced mathematical techniques, the conventional QSAR technique has been recast in the following three aspects. (1) In the fragment-based two dimensional QSAR, or abbreviated as FB-QSAR, the molecular structures in a family of drug candidates are divided into several fragments according to the substitutes being investigated. The bioactivities of drug candidates are correlated with physicochemical properties of the molecular fragments through two sets of coefficients: one is for the physicochemical properties and the other for the molecular fragments. (2) In the multiple field three dimensional QSAR, or MF-3D-QSAR, more molecular potential fields are integrated into the comparative molecular field analysis (CoMFA) through two sets of coefficients: one is for the potential fields and the other for the Cartesian three dimensional grid points. (3) In the AABPP (amino acid-based peptide prediction), the bioactivities of peptides or proteins are correlated with the physicochemical properties of all or partial residues of the sequence through two sets of coefficients: one is for the physicochemical properties of amino acids and the other for the weight factors of the residues. Meanwhile, an iterative double least square (IDLS) technique is developed for solving the two sets of coefficients in a training dataset alternately and iteratively. Using the two sets of coefficients, one can predict the bioactivity of a query peptide, protein, or drug candidate. Compared with the old methods, the new QSAR approaches as summarized in this review possess machine learning ability, can remarkably enhance the prediction power, and provide more structural information. Meanwhile, the future challenge and possible development in this area have been briefly addressed as well.

Predicting the affinity of epitope-peptides with class I MHC molecule HLA-A*0201: an application of amino acid-based peptide prediction.

A new peptide design strategy, the amino acid-based peptide prediction (AABPP) approach, is applied for predicting the affinity of epitope-peptides with class I MHC molecule HLA-A*0201. The AABPP approach consists of two sets of predictive coefficients. The former is the coefficients for the physicochemical properties of amino acids and the latter is the weight factors for the residue positions in a peptide sequence. An iterative double least square technique is introduced to determine the two sets of coefficients alternately through a benchmark dataset. The coefficients converged through such an iterative process are further used to predict the bioactivities of query peptides. In the AABPP algorithm, the following eight physicochemical properties are used as the descriptors of amino acids: (i) lipophilic indices, (ii) hydrophilic indices, (iii) lipophilic surface area, (iv) hydrophilic surface area, (v) alpha-potency indices, (vi) beta-potency indices, (vii) coil-potency indices and (viii) volume of amino acid side chains. In comparison with the existing methods in this area, a remakable advantage of the current approach is that there is no need to know the exact conformation of a query peptide and its alignment with a template. The two steps are indispensable but cannot always be successfully realized otherwise. It is anticipated that the AABPP approach will become a powerful tool for peptide drug design, or at least play a complemetary role to the existing methods.

Peptide reagent design based on physical and chemical properties of amino acid residues.

It has tremendous values for both drug discovery and basic research to develop a solid bioinformatical tool for guiding peptide reagent design. Based on the physical and chemical properties of amino acids, a new strategy for peptide reagent design, the so-called AABPD (amino acid based-peptide design), is proposed. The peptide samples in a training dataset are described by a series of HMLP (heuristic molecular lipophilicity potential) parameters and other physicochemical properties of amino acid residues that form a three-dimensional data matrix where each component is defined by three indexes: the first index refers to the peptide samples, the second to the amino acid positions, and the third to the amino acid parameters. The binding free energy between a peptide ligand and its protein receptor is calculated by a linear free energy equation through the physicochemical parameters, resulting in a set of simultaneous linear equations between the bioactivity of the peptides and the physicochemical properties of amino acids. An iterative double least square technique is developed for the solution of the three-dimensional simultaneous linear equation set to determine the amino acid position coefficients of peptide sequence and the physicochemical parameter coefficients of amino acid residues alternately. The two sets of coefficients thus obtained are used for predicting the bioactivity of other query peptide reagents. Two calculation examples, the peptide substrate specificity of the SARS coronavirus 3C-like proteinase and the affinity prediction for epitope-peptides with Class I MHC molecules are studied by using the peptide reagent design strategy.