Crystal-structure-based design and synthesis of novel C-terminal inhibitors of HIV protease

A rational in silico approach to identify inhibitors of Batroxrhagin from Bothrops atrox

Bothrops atrox venom comprises several types of bioactive molecules, enzymatic and non-enzymatic, among those, Batroxrhagin is the most predominant SVMP P-III enzyme, which are responsible for induction of local and systemic hemorrhage and muscle fibers damage, impairing regeneration. Due to great difficulties in establishing an antibothropic drug, new strategies must be addressed to achieve a more effective and efficient treatment. There are no studies of specific catalytic inhibitors of Batroxrhagin. However, there are in vitro studies that have described similar metalloprotease inhibitors. The inhibitor batimastat was used as a leading compound for the search and selection of similar candidates. This molecule is widely cited as a metalloprotease inhibitor and as an antimetastatic. In addition to batimastat-like molecules, four other reported metalloprotease inhibitors were included to compose the study's positive control group. Hence, 580 molecules were tested. The three-dimensional structure of B. atrox Batroxrhagin was predicted based on homologous structures using Modeller 9.20. Molecular docking calculation was performed using Autodock 4.2 and molecular surfaces and interactions were analyzed using Biovia/Discovery Studio 2017. Among 576 molecules, 42 similar to batismast resulted in a better energy of interaction than all positive controls, including batimastat itself. The batimastat-like molecules with lowest energy and positive controls were subjected to molecular dynamics for 30 ns in Gromacs 2019.4. This batimastat-like molecule produced better stability among all the Batroxrhagin-ligand complexes analyzed. Overall, the proposed compounds present justifiable evidence for future in vitro tests aiming to inhibit Batroxrhagin. Communicated by Ramaswamy H. Sarma.

Physics of biomolecular recognition and conformational dynamics

Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.

Identification of HIV inhibitors guided by free energy perturbation calculations

Free energy perturbation (FEP) theory coupled to molecular dynamics (MD) or Monte Carlo (MC) statistical mechanics offers a theoretically precise method for determining the free energy differences of related biological inhibitors. Traditionally requiring extensive computational resources and expertise, it is only recently that its impact is being felt in drug discovery. A review of computer-aided anti-HIV efforts employing FEP calculations is provided here that describes early and recent successes in the design of human immunodeficiency virus type 1 (HIV-1) protease and non-nucleoside reverse transcriptase inhibitors. In addition, our ongoing work developing and optimizing leads for small molecule inhibitors of cyclophilin A (CypA) is highlighted as an update on the current capabilities of the field. CypA has been shown to aid HIV-1 replication by catalyzing the cis/trans isomerization of a conserved Gly-Pro motif in the Nterminal domain of HIV-1 capsid (CA) protein. In the absence of a functional CypA, e.g., by the addition of an inhibitor such as cyclosporine A (CsA), HIV-1 has reduced infectivity. Our simulations of acylurea-based and 1-indanylketone-based CypA inhibitors have determined that their nanomolar and micromolar binding affinities, respectively, are tied to their ability to stabilize Arg55 and Asn102. A structurally novel 1-(2,6-dichlorobenzamido) indole core was proposed to maximize these interactions. FEP-guided optimization, experimental synthesis, and biological testing of lead compounds for toxicity and inhibition of wild-type HIV-1 and CA mutants have demonstrated a dose-dependent inhibition of HIV-1 infection in two cell lines. While the inhibition is modest compared to CsA, the results are encouraging.

An analysis of hydrophobic interactions of thymidylate synthase with methotrexate: free energy calculations involving mutant and native structures bound to methotrexate

Since the human body for many reasons can adapt and become resistant to drugs, it is important to develop and validate computer aided drug design (CADD) methods that could help predict binding affinity changes that can result from these resistant enzymes. The free energy perturbation (FEP) methodology is the most accurate means of estimating relative binding affinities between inhibitors and protein variants. In this paper, we describe the role played by hydrophobic residues lining the active site region, particularly (79)Ile and (176)Phe, in the binding of methotrexate to the Escherichia coli (E. coli) thymidylate synthase (TS) enzyme, using the thermodynamic cycle perturbation (TCP) approach. The computed binding free energy differences on the binding of methotrexate to the native and some mutant E. coli TS structures have been compared with experimental results. Computationally, four different 'mutations' have been simulated on the TS enzyme with methotrexate (MTX): (79)Ile --> (79)Val; (79)Ile --> (79)Ala; (79)Ile --> (79)Leu; and (176)Phe --> (176)Ile. The calculated results indicate that in each of these cases, the native residues ((79) Ile and (176) Phe) interact more favorably with methotrexate than the mutant residues and these results are corroborated by experimental measurements. Binding preference to wild type residues can be rationalized in terms of their better hydrophobic contacts with the phenyl ring of methotrexate.

Calculation of relative binding affinities of fructose 1,6-bisphosphatase mutants with adenosine monophosphate using free energy perturbation method

The free energy perturbation (FEP) methodology is the most accurate means of estimating relative binding affinities between inhibitors and protein variants. In this article, the importance of hydrophobic and hydrophilic residues to the binding of adenosine monophosphate (AMP) to the fructose 1,6-bisphosphatase (FBPase), a target enzyme for type-II diabetes, was examined by FEP method. Five mutations were made to the FBPase enzyme with AMP inhibitor bound: 113Tyr --> 113Phe, 31Thr --> 31Ala, 31Thr --> 31Ser, 177Met --> 177Ala, and 30Leu --> 30Phe. These mutations test the strength of hydrogen bonds and van der Waals interactions between the ligand and enzyme. The calculated relative free energies indicated that: 113Tyr and 31Thr play an important role, each via two hydrogen bonds affecting the binding affinity of inhibitor AMP to FBPase, and any changes in these hydrogen bonds due to mutations on the protein will have significant effect on the binding affinity of AMP to FBPase, consistent to experimental results. Also, the free energy calculations clearly show that the hydrophilic interactions are more important than the hydrophobic interactions of the binding pocket of FBPase.

HIV-1 protease variants from 100-fold drug resistant clinical isolates: expression, purification, and crystallization

High-resolution X-ray crystallographic structures of HIV-1 protease clinical variants complexed with licensed inhibitors are essential to understanding the fundamental cause of protease drug resistance. There is a need for structures of naturally evolved HIV-1 proteases from patients failing antiretroviral therapy. Here, we report the expression, purification, and crystallization of clinical isolates of HIV-1 protease that have been characterized to be more than 100 times less susceptible to US FDA approved protease inhibitors.

Rational approach to AIDS drug design through structural biology

The discovery and development of more than a dozen drugs in the past 15 years for the treatment of AIDS offer an excellent example of progress in the field of rational drug design. At this time, the principal targets are reverse transcriptase and protease, enzymes encoded by the human immunodeficiency virus. The introduction of protease inhibitors, in particular, has drastically decreased the mortality and morbidity associated with AIDS. This review presents the methods used to develop such drugs and discusses the remaining problems, such as the rapid emergence of drug resistance.

Calculation of relative binding free energy differences for fructose 1,6-bisphosphatase inhibitors using the thermodynamic cycle perturbation approach

An iterative, computer-assisted, drug design strategy that combines molecular design, molecular mechanics, molecular dynamics (MD), and free energy perturbation (FEP) calculations with compound synthesis, biochemical testing of inhibitors, and crystallographic structure determination of protein-inhibitor complexes was successfully used to predict the rank order of a series of nucleoside monophosphate analogues as fructose 1,6-bisphosphatase (FBPase) inhibitors. The X-ray structure of FBPase complexed with 5-aminoimidazole-4-carboxamide-1-beta-D-ribofuranosyl 5'-monophosphate (ZMP) provided structural information used for subsequent analogue design and free energy calculations. The FEP protocol was validated by calculating the free energy differences for the mutation of ZMP (1) to AMP (2). The calculated results showed a net gain of 1.7 kcal/mol, which agreed with the experimental result of 1.3 kcal/mol. FEP calculations were performed for 18 other AMP analogues. Inhibition constants were determined for over half of these analogues, usually after completion of the calculation, and were consistent with the predictions. Solvation free energy differences between AMP and various AMP analogues proved to be an important factor in binding free energies, suggesting that increased desolvation costs associated with the addition of polar groups to an inhibitor must be overcome by stronger ligand-protein interactions if the structural modification is to enhance inhibitor potency. The results indicate that FEP calculations predict relative binding affinities with high accuracy and provide valuable insight into the factors that influence inhibitor binding and therefore should greatly aid efforts to optimize initial lead compounds and reduce the time required for the discovery of new drug candidates.

Structure-based drug design approaches for predicting binding affinities of HIV1 protease inhibitors

Computational assessment of the binding affinity of enzyme inhibitors prior to synthesis is an important component of computer-assisted drug design (CADD) paradigms. The free energy perturbation (FEP) methodology is the most accurate means of estimating relative binding affinities between two inhibitors. However, due to its complexity and computation-intensive nature, practical applications are restricted to analysis of structurally-related inhibitors. Accordingly, there is a need for methods that enable rapid assessment of large number of structurally-unrelated molecules in a suitably accurate manner. In this review, the FEP method is compared with regression-based methods that employ multivariate models to assess the advantages of each in the estimation of relative binding affinities of inhibitors to an enzyme. Semiquantitative predictions of relative binding free energies of human immunodeficiency virus 1 (HIV1) protease inhibitors are also presented and compared with the corresponding FEP results. The results indicate that the regression-based methods and the FEP method are useful in the semi-quantitative and quantitative assessment of relative binding affinities of enzyme inhibitors, respectively, prior to synthesis.

Inhibitors of HIV-1 protease: a major success of structure-assisted drug design

Retroviral protease (PR) from the human immunodeficiency virus type 1 (HIV-1) was identified over a decade ago as a potential target for structure-based drug design. This effort was very successful. Four drugs are already approved, and others are undergoing clinical trials. The techniques utilized in this remarkable example of structure-assisted drug design included crystallography, NMR, computational studies, and advanced chemical synthesis. The development of these drugs is discussed in detail. Other approaches to designing HIV-1 PR inhibitors, based on the concepts of symmetry and on the replacement of a water molecule that had been found tetrahedrally coordinated between the enzyme and the inhibitors, are also discussed. The emergence of drug-induced mutations of HIV-1 PR leads to rapid loss of potency of the existing drugs and to the need to continue the development process. The structural basis of drug resistance and the ways of overcoming this phenomenon are mentioned.

An approach to rapid estimation of relative binding affinities of enzyme inhibitors: application to peptidomimetic inhibitors of the human immunodeficiency virus type 1 protease

This report describes a method for rapid assessment of the binding affinities of a series of analogous ligands to an enzyme. This approach is based on two variables (scores), representing (i) the enthalpy of binding and (ii) the strength of hydrophobic interaction. The method is then used to evaluate the binding of 11 different peptidomimetic inhibitors to the HIV-1 protease. Three-dimensional structures of these enzyme-inhibitor complexes are modeled based on the crystal structures of HIV-1 protease complexes with the known inhibitors. These structures are minimized using the AMBER force field, and the scores of binding enthalpy for each of the ligands are calculated. A second score to represent the hydrophobic interaction between a pair of atoms uses an exponential function of distance between the atoms and the product of their atomic hydrophobicity constants. This exponential function is used to assess the hydrophobic interaction energy between an enzyme and its inhibitor and also to compute and display a 'molecular hydrophobicity map' as a 3D visualization tool. These methods are then applied to obtain trends in relative binding affinities of pairs of analogous inhibitors. Calculated scores agree well with corresponding results from thermodynamic cycle perturbation (TCP) simulations as well as experimental binding data. Since the proposed calculations are computationally cheaper and faster than TCP calculations, it is suggested that these scores can form the basis for rapid, preliminary theoretical screening of proposed derivatives of an inhibitor prior to TCP analysis, synthesis, and testing.

A preference-based free-energy parameterization of enzyme-inhibitor binding. Applications to HIV-1-protease inhibitor design

The interface between protein receptor-ligand complexes has been studied with respect to their binary interatomic interactions. Crystal structure data have been used to catalogue surfaces buried by atoms from each member of a bound complex and determine a statistical preference for pairs of amino-acid atoms. A simple free energy model of the receptor-ligand system is constructed from these atom-atom preferences and used to assess the energetic importance of interfacial interactions. The free energy approximation of binding strength in this model has a reliability of about +/- 1.5 kcal/mol, despite limited knowledge of the unbound states. The main utility of such a scheme lies in the identification of important stabilizing atomic interactions across the receptor-ligand interface. Thus, apart from an overall hydrophobic attraction (Young L, Jernigan RL, Covell DG, 1994, Protein Sci 3:717-729), a rich variety of specific interactions is observed. An analysis of 10 HIV-1 protease inhibitor complexes is presented that reveals a common binding motif comprised of energetically important contacts with a rather limited set of atoms. Design improvements to existing HIV-1 protease inhibitors are explored based on a detailed analysis of this binding motif.