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.     

Two-level QSAR network (2L-QSAR) for peptide inhibitor design based on amino acid properties and sequence positions

In the design of peptide inhibitors the huge possible variety of the peptide sequences is of high concern. In collaboration with the fast accumulation of the peptide experimental data and database, a statistical method is suggested for peptide inhibitor design. In the two-level peptide prediction network (2L-QSAR) one level is the physicochemical properties of amino acids and the other level is the peptide sequence position. The activity contributions of amino acids are the functions of physicochemical properties and the sequence positions. In the prediction equation two weight coefficient sets {a_k} and {b_l} are assigned to the physicochemical properties and to the sequence positions, respectively. After the two coefficient sets are optimized based on the experimental data of known peptide inhibitors using the iterative double least square (IDLS) procedure, the coefficients are used to evaluate the bioactivities of new designed peptide inhibitors. The two-level prediction network can be applied to the peptide inhibitor design that may aim for different target proteins, or different positions of a protein. A notable advantage of the two-level statistical algorithm is that there is no need for host protein structural information. It may also provide useful insight into the amino acid properties and the roles of sequence positions.     

Tea Bags for Fmoc Solid-Phase Peptide Synthesis: An Example of Circular Economy

Peptide synthesis is an area with a wide field of application, from biomedicine to nanotechnology, that offers the option of simultaneously synthesizing a large number of sequences for the purpose of preliminary screening, which is a powerful tool. Nevertheless, standard protocols generate large volumes of solvent waste. Here, we present a protocol for the multiple Fmoc solid-phase peptide synthesis in tea bags, where reagent recycling steps are included. Fifty-two peptides with wide amino acid composition and seven to twenty amino acid residues in length were synthesized in less than three weeks. A clustering analysis was performed, grouping the peptides by physicochemical features. Although a relationship between the overall yield and the physicochemical features of the sequences was not established, the process showed good performance despite sequence diversity. The recycling system allowed to reduce N, N-dimethylformamide usage by 25–30% and reduce the deprotection reagent usage by 50%. This protocol has been optimized for the simultaneous synthesis of a large number of peptide sequences. Additionally, a reagent recycling system was included in the procedure, which turns the process into a framework of circular economy, without affecting the quality of the products obtained.     

QSAR modeling and design of cationic antimicrobial peptides based on structural properties of amino acids

Drug resistance to existing antibiotics poses alarming threats to global public health, which inspires heightened interests in searching for new antibiotics, including antimicrobial peptides (AMPs). Accurate prediction of antibacterial activities of AMPs may expedite novel AMP design and reduce the costs and efforts involved in laboratory screening. In the present study, a novel quantitative prediction method of AMP was established by quantitative structure-activity relationship (QSAR) modeling based on the physicochemical properties of amino acids. The indices of these physicochemical properties were used to define AMP. The structural variables were optimized by stepwise regression (STR). Three series of AMPs from the QSAR model were constructed by multiple linear regressions (MLR). These QSAR models showed good performance in reliability and predictability. The normalized regression coefficients of the QSAR model and the contribution of amino acids at each position of AMP may determine the suitableness of a particular residue at any given position. QSAR models constructed by STR-MLR should prove to be useful tools in peptide design with respect to the calculation, explanation, good and reliable performance, and definition of physiochemical properties.     

3D-Epitope-Explorer (3DEX): localization of conformational epitopes within three-dimensional structures of proteins

Neutralizing antibodies often recognize conformational, discontinuous epitopes. Linear peptides mimicking such conformational epitopes can be selected from phage display peptide libraries by screening with the respective antibodies. However, it is difficult to localize these "mimotopes" within the three-dimensional (3D) structures of the target proteins. Knowledge of conformational epitopes of neutralizing antibodies would help to design antigens able to elicit protective immune responses. Therefore, we provide here a software that allows to localize linear peptide sequences within 3D structures of proteins. The 3D-Epitope-Explorer (3DEX) software allows to map conformational epitopes in 3D protein structures based on an algorithm that takes into account the physicochemical neighborhood of C(alpha)- or C(beta)-atoms of individual amino acids. A given amino acid of a peptide sequence is localized within the protein and the software searches within predefined distances for the amino acids neighboring that amino acid in the peptide. Surface exposure of the amino acids can also be taken into consideration. The procedure is then repeated for the remaining amino acids of the peptide. The introduction of a joker function allows to map peptide mimotopes, which do not necessarily have 100% sequence homology to the protein. Using this software we were able to localize mimotopes selected from phage displayed peptide libraries with polyclonal antibodies from HIV-positive patient plasma within the 3D structure of gp120, the exterior glycoprotein of HIV-1. We also analyzed two recently published peptide sequences corresponding to known conformational epitopes to further confirm the integrity of 3DEX.     

Two-dimensional classification of amphiphilic monomers based on interfacial and partitioning properties. 2. Amino acids and amino acid residues

A new classification for amino acid residues is proposed, based on interfacial and partitioning properties. Amino acid residues are characterized by two parameters: standard free energy of adsorption at the hexane/water interface and standard free energy of the partition between hexane and water. Theoretical approaches are used for the estimation of these parameters. As a result, several groups of amino acid units having close values of the parameters are distinguished. Classification of the amino acid units by such a method is believed to be able to provide promising results in the search of correlations in protein sequences. The comparison of experimental and theoretical studies of free amino acids at the hexane/water interface confirm the predictive power of the theory used, because a very good coincidence between theoretical and experimental data points is observed. The obtained values of standard free energies of adsorption are consistent with literature data.     

Free solution capillary electrophoresis and micellar electrokinetic resolution of amino acid enantiomers and peptide isomers with L- and D-Marfey's reagents

Separation of amino acid enantiomers and peptide isomers has been made possible through the use of Marfey's reagent and high-performance capillary electrophoresis (HPCE). Samples of amino acids and peptides were first derivatized with Marfey's reagent and subsequently analyzed by HPCE. Different modes of separation were investigated including free solution and micellar electrokinetic chromatography. The use of micellar electrokinetic chromatography in combination with L- and D-Marfey's reagent offered unequivocal means to confirm the presence of D-amino acid in an unknown sample. This method is also particularly useful for the analysis of peptide isomers.     

Hydration, charge, size, and shape characteristics of peptides from their CZE analyses

A CZE model is presented for peptide characterization on the basis of well-established physicochemical equations. The effective mobility is used as basic data in the model to estimate relevant peptide properties such as, for instance, hydration, net and total electrical charge numbers, hydrodynamic size and shape, particle average orientation, and pH-microenvironment from the charge regulation phenomenon. Therefore 102 experimental effective mobilities of different peptides are studied and discussed in relation to previous work. An equation for the estimation of peptide hydration as a function of ionizing, polar, and non-polar amino acid residues is included in the model. It is also shown that the shape-orientation factor of peptides may be either lower or higher than one, and its value depends on a complex interplay among total charge number, molar mass, hydration, and amino acid sequence.     

Predicting sequences and structures of MHC-binding peptides: a computational combinatorial approach

Peptides bound to MHC molecules on the surface of cells convey critical information about the cellular milieu to immune system T cells. Predicting which peptides can bind an MHC molecule, and understanding their modes of binding, are important in order to design better diagnostic and therapeutic agents for infectious and autoimmune diseases. Due to the difficulty of obtaining sufficient experimental binding data for each human MHC molecule, computational modeling of MHC peptide-binding properties is necessary. This paper describes a computational combinatorial design approach to the prediction of peptides that bind an MHC molecule of known X-ray crystallographic or NMR-determined structure. The procedure uses chemical fragments as models for amino acid residues and produces a set of sequences for peptides predicted to bind in the MHC peptide-binding groove. The probabilities for specific amino acids occurring at each position of the peptide are calculated based on these sequences, and these probabilities show a good agreement with amino acid distributions derived from a MHC-binding peptide database. The method also enables prediction of the three-dimensional structure of MHC-peptide complexes. Docking, linking, and optimization procedures were performed with the XPLOR program [1].     

我国油料产品品质的近红外光谱快速检测技术研究进展

近红外光谱技术是一种快速无损检测技术,具有操作简单、检测成本低、无需化学试剂、绿色环保,以及可实现多品质参数同步检测等优点。该文综述了我国油料和食用植物油品质的近红外光谱速测技术研究进展,包括油料含油量、粗蛋白含量、脂肪酸含量等品质指标,食用油的理化指标,以及脂肪酸和食用油的真实性鉴别,并对油料产品品质的近红外光谱速测技术的发展前景进行了展望。     

Design of radical-resistant amino acid residues: a combined theoretical and experimental investigation

Ab initio calculations have been used to design radical-resistant amino acid residues. Optimized structures of free and protected amino acids and their corresponding alpha-carbon-centered radicals were determined with B3-LYP/6-31G(d). Single-point RMP2/6-31G(d) calculations on these structures were then used to obtain radical stabilization energies, to examine the effect of steric repulsion between the side chains and amide carbonyl groups on the stability of alpha-carbon-centered peptide radicals. Relative to glycine, the destabilization for alanine and valine residues was found to be approximately 9 and 18 kJ mol(-1), respectively, which correlates with the reactivity of analogous amino acid residues in peptides toward hydrogen atom abstraction in conventional free radical reactions. To design amino acid residues that would resist radical reactions, strategies by which the steric effects could be magnified were considered. This resulted in the identification of tert-leucine and 3,3,3-trifluoroalanine as suitable molecules. With these amino acid residues, the destabilization of the alpha-carbon-centered radicals relative to that of glycine is increased substantially to approximately 36 and 41 kJ mol(-1), respectively. The theoretical predictions have been supported by experimental observations: a tert-leucine derivative was shown to be very slow to react with N-bromosuccinimide, while the corresponding trifluoroalanine derivative was found to be inert.     

Relative importance of secondary structure and solvent accessibility to the stability of protein mutants. A case study with amino acid properties and energetics on T4 and human lysozymes

Understanding the factors influencing the stability of protein mutants is an important task in molecular and computational biology. In this work, we have approached this problem by examining the relative importance of secondary structure and solvent accessibility of the mutant residue for understanding/predicting the stability of protein mutants. We have used hydrophobic, electrostatic and hydrogen bond free energy terms and nine unique physicochemical, energetic and conformational properties of amino acids in the present study and these parameters have been related with changes in thermal stability (DeltaTm) of all the single mutants of lysozymes based on single and multiple correlation coefficients. As expected the properties reflecting hydrophobicity and hydrophobic free energy play a major role to distinguish stabilizing and destabilizing mutants. The hydrophobic free energy due to carbon and nitrogen atoms distinguish the stability of coil and strand mutations to the accuracy of 100 and 90%, respectively. In agreement with previous results, the subgroup classification based on secondary structure and the information about its location in the structure yielded good relationship with the experimental DeltaTm. We revealed that the secondary structure information is equally or more important than solvent accessibility for understanding the stability of protein mutants. The comparison of amino acid properties with free-energy terms indicate that the energetic contribution explains the mutant stability better in coil region whereas the amino acid properties do better in strand region. Further, the combination of free energies with amino acid properties increased the correlation significantly. The present study demonstrates the importance of classifying the mutants based on secondary structure to the stability of proteins upon mutations.     

Requirements for prediction of peptide retention time in reversed-phase high-performance liquid chromatography: hydrophilicity/hydrophobicity of side-chains at the N- and C-termini of peptides are dramatically affected by the end-groups and location

The value of reversed-phase high-performance liquid chromatography (RP-HPLC) and the field of proteomics would be greatly enhanced by accurate prediction of retention times of peptides of known composition. The present study investigates the hydrophilicity/hydrophobicity of amino acid side-chains at the N- and C-termini of peptides while varying the functional end-groups at the termini. We substituted all 20 naturally occurring amino acids at the N- and C-termini of a model peptide sequence, where the functional end-groups were N(alpha)-acetyl-X- and N(alpha)-amino-X- at the N-terminus and -X-C(alpha)-carboxyl and -X-C(alpha)-amide at the C-terminus. Amino acid coefficients were subsequently derived from the RP-HPLC retention behaviour of these peptides and compared to each other as well as to coefficients determined in the centre of the peptide chain (internal coefficients). Coefficients generated from residues substituted at the C-terminus differed most (between the -X-C(alpha)-carboxyl and -X-C(alpha)-amide peptide series) for hydrophobic side-chains. A similar result was seen for the N(alpha)-acetyl-X- and N(alpha)-amino-X- peptide series, where the largest differences in coefficient values were observed for hydrophobic side-chains. Coefficients derived from substitutions at the C-terminus for hydrophobic amino acids were dramatically different compared to internal coefficients for hydrophobic side-chains, ranging from 17.1 min for Trp to 4.8 min for Cys. In contrast, coefficients derived from substitutions at the N-terminus showed relatively small differences from the internal coefficients. Subsequent prediction of peptide retention time, within an error of just 0.4 min, was achieved by a predictive algorithm using a combination of internal coefficients and coefficients for the C-terminal residues. For prediction of peptide retention time, the sum of the coefficients must include internal and terminal coefficients.     

Calculation of amino acid hydrophilicity indices for retention of peptides on amide, diol and silica columns in normal-phase liquid chromatography

Summary A set of hydrophilicity parameters in a normal-phase liquid chromatography of peptides is presented in order to clarify the contribution of individual amino acid residues to peptide retention and to predict retention times. The retention of 100 peptides was studied using normal-phase liquid chromatography on amide, diol and silica columns. An acetonitrile-water mixed solution containing 0.2% trifluoroacetic acid +0.2% triethylamine was used as the mobile phase in a linear gradient elution system. The contribution of each residue upon retention was calculated by linear multiple regression analysis. This paper described the contribution values as “hydrophilicity retention coefficients”. Using these hydrophilicity retention coefficients, retention times could be predicted for peptides of known amino acid content and sequence. A set of hydrophilicity retention coefficients on each column was successfully explained by contributions to the degree of retention.     

Self-assembly of cyclic homo- and hetero-beta-peptides with cis- furanoid sugar amino acid and beta-hGly as building blocks

The design, synthesis and characterization of a new class of peptide nanotubes, self-assembled from cyclic homo- and hetero-beta-peptides based on cis-furanoid sugar amino acid and beta-hGly residues are described; these results represent the expansion of the conformational pool of cis beta-sugar amino acids in the design of peptide nanotubes.     

An automated fluorescence protein sequencer using 7-methylthio-4-(2,1,3-benzoxadiazolyl) isothiocyanate (MTBD-NCS) as an Edman reagent

An automated fluorescence protein sequencer using 7-methylthio-5-(2,1,3-benzoxadiazolyl) isithiocyanate (MTBD-NCS), a fluorescent Edman reagent, is developed by the modification of a commercial protein sequencer. The generated MTBD-thiohydantoin amino acids fluoresced strongly, whereas the by-products such as MTBD-thiocarbamoyl amino acids and MTBD-carbamoly amino acids did not fluoresce. A few interfering peaks were observed in the chromatogram and amino acid sequence was easily determined. The coupling and cyclization/cleavage reaction conditions and extraction conditions of generated MTBD-thiazolinone amino acids were optimized using an autonalyzer. Finally, the sequence of a synthetic peptide (25 pmol), leucine-enkephalin-Thr-amide, was determined and up to six residues were successively analyzed.     

A general method for designing combinatorial peptide libraries decodable by amino acid analysis

Herein we describe an algorithm for designing combinatorial peptide libraries for split-and-mix synthesis on solid support that are decodable by amino acid analysis (AAA) of the beads. AAA is a standard service analysis available in most biochemical laboratories, and it allows one to control the quality of the peptide on each bead, an important feature that is missing from most library decoding protocols. In the algorithm, each AA is assigned to two variable positions in the sequence grouped in a "unique pair". This arrangement limits sequence design because both the number of unique pairs U (setting the maximum number of variable AA) and the maximum number S of different AA per variable position depend on the peptide length N (U=N(N-1)/2), S=N-1). The method is therefore only suitable for focused libraries. An application example is shown for the selection of peptides with N-terminal proline or hydroxyproline catalyzing an aldol reaction from a combinatorial library of 65536 octapeptides. A simple enumeration program is available to help design combinatorial libraries decodable by amino acid analysis. The method applies to linear and cyclic peptides, can be used for nonnatural building blocks, including beta-amino acids, and should help to explore the vast chemistry of linear and cyclic peptide for catalysis and bioactivity.     

Biosynthetic Strategies for Macrocyclic Peptides

Macrocyclic peptides are predominantly peptide structures bearing one or more rings and spanning multiple amino acid residues. Macrocyclization has become a common approach for improving the pharmacological properties and bioactivity of peptides. A variety of ribosomal-derived and non-ribosomal synthesized cyclization approaches have been established. The biosynthesis of backbone macrocyclic peptides using seven new emerging methodologies will be discussed with regard to the features and strengths of each platform rather than medicinal chemistry tools. The mRNA display variant, known as the random nonstandard peptide integrated discovery (RaPID) platform, utilizes flexible in vitro translation (FIT) to access macrocyclic peptides containing nonproteinogenic amino acids (NAAs). As a new discovery approach, the ribosomally synthesized and post-translationally modified peptides (RiPPs) method involves the combination of ribosomal synthesis and the phage screening platform together with macrocyclization chemistries to generate libraries of macrocyclic peptides. Meanwhile, the split-intein circular ligation of peptides and proteins (SICLOPPS) approach relies on the in vivo production of macrocyclic peptides. In vitro and in vivo peptide library screening is discussed as an advanced strategy for cyclic peptide selection. Specifically, biosynthetic bicyclic peptides are highlighted as versatile and attractive modalities. Bicyclic peptides represent another type of promising therapeutics that allow for building blocks with a heterotrimeric conjugate to address intractable challenges and enable multimer complexes via linkers. Additionally, we discuss the cell-free chemoenzymatic synthesis of macrocyclic peptides with a non-ribosomal catalase known as the non-ribosomal synthetase (NRPS) and chemo-enzymatic approach, with recombinant thioesterase (TE) domains. Novel insights into the use of peptide library tools, activity-based two-hybrid screening, structure diversification, inclusion of NAAs, combinatorial libraries, expanding the toolbox for macrocyclic peptides, bicyclic peptides, chemoenzymatic strategies, and future perspectives are presented. This review highlights the broad spectrum of strategy classes, novel platforms, structure diversity, chemical space, and functionalities of macrocyclic peptides enabled by emerging biosynthetic platforms to achieve bioactivity and for therapeutic purposes.     

Heuristic molecular lipophilicity potential (HMLP): lipophilicity and hydrophilicity of amino acid side chains

Heuristic molecular lipophilicity potential (HMLP) is applied in the study of lipophilicity and hydrophilicity of 20 natural amino acids side chains. The HMLP parameters, surface area S(i), lipophilic indices L(i), and hydrophilic indices H(i) of amino acid side chains are derived from lipophilicity potential L(r). The parameters are correlated with the experimental data of phase-transferring free energies of vapor-to-water, vapor-to-cyclohexane, vapor-to-octanol, cyclohexane-to-water, octanol-to-water, and cyclohexane-to-octanol through a linear free energy equation DeltaG(0)(tr,i) = b(0) + b(1)S(i) (+) + b(2)S(i) (-) + b(3)L(i) + b(4)H(i). For all above six phase-transfer free energies, the HMLP parameters of 20 amino acid side chains give good calculation results using linear free energy equation. HMLP is an ab initio quantum chemical approach and a structure-based technique. Except for atomic van der Waals radii, there are no other empirical parameters used. The HMLP has clear physical and chemical meaning and provides useful lipophilic and hydrophilic parameters for the studies of proteins and peptides.     

Global conformations of proteins as predicted from the modeling of their CZE mobility data

Estimations of protein global conformations in well-specified physicochemical microenvironments are obtained through global structural parameters defined from polypeptide-scale analyses. For this purpose protein electrophoretic mobility data must be interpreted through a physicochemical CZE model to obtain estimates of protein equivalent hydrodynamic radius, effective and total charge numbers, hydration, actual ionizing pK and pH-near molecule. The electrical permittivity of protein domain is also required. In this framework, the solvent drag on proteins is obtained via the characteristic friction power coefficient associated with the number of amino acid residues defining the global chain conformation in solution. Also, the packing dimension related to the spatial distribution of amino acid residues within the protein domain is evaluated and discussed. These scaling coefficients together with the effective and total charge number fractions of proteins provide relevant interpretations of protein global conformations mainly from collapsed globule to hybrid chain regimes. Also, protein transport properties may be estimated within this framework. In this regard, the central role played by the friction power coefficient in the evaluation of these properties is highlighted.