CONFORMATIONAL STUDY OF MOLECULES IN A BIOLOGICAL ENVIRONMENT, DESIGN OF INHIBITORS OF HUMAN AMINOPEPTIDASE M1 IMPLICATED IN CANCER THERAPY

Objective: A novel subnanomolar anticancer hydroxamic acid containing drug candidates, inhibitors of human M1 aminopeptidase (APN) a recent validated target and has reached the predicted subnanomolar range of inhibitory potency. Methods: A quantitative structure activity relationships (QSAR) complexation model has been developed from a compounds of 37 hydroxamic acid derivatives (AHD1-37 as training set, TS) to establish a linear correlation between the calculated relative Gibbs free energies (GFE: ΔΔGcom) of APN-AHDx complex formation and the experimental inhibition potency (Kiexp). The predictive power of the QSAR model was then validated first with 9 other AHDs not included in the TS and thereafter with the generation of a 3D-QSAR-PH4 pharmacophore (PH4) model to screen the AHD chemical subspace built as a virtual combinatorial library of more than 58,644 AHD analogs). Finally the best PH4 hits were evaluated with the initial QSAR model for predicted potency (Kipre) and pharmacokinetic profile. Results: The QSAR model linear correlation equation: pKiexp=-0.1901×∆∆Gcom + 8.2886 , R2=0.94, the subsequent PH4 model linear correlation between experiment and PH4-estimated Ki: pKiexp=1.0006× pKipre + 0.0028, R2=0.79 documents the high predictive power of this approach. Finally the screening of the virtual library of AHD analogs yielded 95 orally bioavailable candidates the best reaching a predicted potency (Kipre) of 50 pM and displaying favorable pharmacokinetic profile. Conclusion: The combined use of molecular modeling (QSAR) and in silico PH4-based screening of the hypothetical combinatorial library has resulted in proposed and predicted potent anticancer candidates with a suitable pharmacokinetic profile.                        Peer Review History: Received: 3 August 2023; Revised: 12 September; Accepted: 25 October, Available online: 15 November 2023 Academic Editor: Dr. Nuray Arı, Ankara University, Turkiye, [email protected] Received file:                             Reviewer's Comments: Average Peer review marks at initial stage: 7.0/10 Average Peer review marks at publication stage: 9.0/10 Reviewers: Prof. Hassan A.H. Al-Shamahy, Sana'a University, Yemen, [email protected] Prof. Dr. A. Hakan AKTAŞ, Süleyman Demirel University, Faculty of Science and Art, Department of Chemistry, Isparta-Turkey, [email protected]

Design of Thymidine Analogues Targeting Thymidilate Kinase of Mycobacterium tuberculosis

We design here new nanomolar antituberculotics, inhibitors of Mycobacterium tuberculosis thymidine monophosphate kinase (TMPKmt), by means of structure-based molecular design. 3D models of TMPKmt-inhibitor complexes have been prepared from the crystal structure of TMPKmt cocrystallized with the natural substrate deoxythymidine monophosphate (dTMP) (1GSI) for a training set of 15 thymidine analogues (TMDs) with known activity to prepare a QSAR model of interaction establishing a correlation between the free energy of complexation and the biological activity. Subsequent validation of the predictability of the model has been performed with a 3D QSAR pharmacophore generation. The structural information derived from the model served to design new subnanomolar thymidine analogues. From molecular modeling investigations, the agreement between free energy of complexation (ΔΔGcom) and Ki values explains 94% of the TMPKmt inhibition (pKi=-0.2924ΔΔGcom+3.234;R2=0.94) by variation of the computed ΔΔGcom and 92% for the pharmacophore (PH4) model (pKi=1.0206×pKipred-0.0832,  R2=0.92). The analysis of contributions from active site residues suggested substitution at the 5-position of pyrimidine ring and various groups at the 5′-position of the ribose. The best inhibitor reached a predicted Ki of 0.155 nM. The computational approach through the combined use of molecular modeling and PH4 pharmacophore is helpful in targeted drug design, providing valuable information for the synthesis and prediction of activity of novel antituberculotic agents

STRUCTURE-BASED DESIGN OF NOVEL PYRIMIDINE CARBONITRILES ANALOGS TARGETING THE CYSTEINE PROTEASE FALCIPAIN 2 OF PLASMODIUM FALCIPARUM (pfFP2) AT THE TROPHOZOÏTE STAGE WITH FAVORABLE ADME SPECIFICITIES

Aim and Objective: Structure-based drug design (SBDD) of new antimalarials at the moment of resistance of the most causative agent, Plasmodium falciparum to the more valuable artemisinin combination therapy (ACT) is even more urgent. Carbonitriles pyrimidine derivatives (CNP) has emerged as potential inhibitors of the cysteine protease falcipain 2 of Plasmodium falciparum (pfFP2), so here we report virtual pharmacophore based screening of the CNP chemical subspace yielding novel CNP analogs with predicted high inhibitory potency against pfFP2. Methods: A quantitative structure activity relationships (QSAR) complexation model has been developed from a series of fifteen carbonitriles pyrimidine derivatives to establish a linear correlation between the calculated Gibbs free energies (GFE: ΔΔGcom) of pfFP2-CNP complex formation and the experimental half-maximal enzymatic inhibition concentration ( ).The predictive power of the QSAR model was then validated with the generation of a 3D-QSAR-PH4 pharmacophore (PH4) model as CNP chemical subspace (exemplified as a virtual combinatorial library of more than 83.300 CNP analogs) explorer for novel predicted more potent CNP analogs. Finally the best PH4 hits were evaluated with the initial QSAR model for predicted potency ( ) and pharmacokinetic profile. Results: The QSAR model linear correlation equation: p = -0.1025 x ∆∆Gcom + 7.2867, R2=0.94, the subsequent PH4 model linear correlation between experiment and PH4-estimated IC50: p = 0.9366 x p + 0.2849, R2=0.91 documents the high predictive power of this approach. Finally the screening of the virtual library of CNP analogs yielded 52 orally bioavailable candidates the best reaching a predicted potency ( ) of 14 pM and displaying favorable pharmacokinetic profile. Conclusion: The combined use of one descriptor complexation QSAR model and 3D-QSAR Pharmacophore model performs well in identifying novel CNP analogs against pfFP2 and the handful of top predicted analogs are worth undergoing synthesis and biological evaluation.                        Peer Review History: Received: 12 August 2023; Revised: 17 September; Accepted: 27 October, Available online: 15 November 2023 Academic Editor: Prof. Dr. Gorkem Dulger, Duzce University, Turkey, [email protected] Received file:                             Reviewer's Comments: Average Peer review marks at initial stage: 7.0/10 Average Peer review marks at publication stage: 9.0/10 Reviewers: Prof. Hassan A.H. Al-Shamahy, Sana'a University, Yemen, [email protected] Prof. Cyprian Ogbonna ONYEJI, Obafemi Awolowo University, Ile-Ife, Nigeria, [email protected] Dr. U. S. Mahadeva Rao, Universiti Sultan Zainal Abidin, Terengganu Malaysia, [email protected] Dr. Hayriye Eda Şatana Kara, Gazi University, Turkey, [email protected]

Virtual design of novel Plasmodium falciparum cysteine protease falcipain-2 hybrid lactone–chalcone and isatin–chalcone inhibitors probing the S2 active site pocket

We report computer-aided design of new lactone–chalcone and isatin–chalcone (HLCIC) inhibitors of the falcipain-2 (PfFP-2). 3D models of 15 FP-2:HLCIC1-15 complexes with known observed activity (IC50exp) were prepared to establish a quantitative structure–activity (QSAR) model and linear correlation between relative Gibbs free energy of enzyme:inhibitor complex formation (ΔΔGcom) and IC50exp: pIC50exp = −0.0236 × ΔΔGcom+5.082(#); R2 = 0.93. A 3D pharmacophore model (PH4) derived from the QSAR directed our effort to design novel HLCIC analogues. During the design, an initial virtual library of 2621440 HLCIC was focused down to 18288 drug-like compounds and finally, PH4 screened to identify 81 promising compounds. Thirty-three others were added from an intuitive substitution approach intended to fill better the enzyme S2 pocket. One hundred and fourteen theoretical IC50 (IC50pre) values were predicted by means of (#) and their pharmacokinetics (ADME) profiles. More than 30 putative HLCICs display IC50pre 100 times superior to that of the published most active training set inhibitor HLCIC1

Structure-Based Design and Pharmacophore-Based Virtual Screening of Combinatorial Library of Triclosan Analogues Active against Enoyl-Acyl Carrier Protein Reductase of <i>Plasmodium falciparum</i> with Favourable ADME Profiles

Cost-effective therapy of neglected and tropical diseases such as malaria requires everlasting drug discovery efforts due to the rapidly emerging drug resistance of the plasmodium parasite. We have carried out computational design of new inhibitors of the enoyl-acyl carrier protein reductase (ENR) of Plasmodium falciparum (PfENR) using computer-aided combinatorial and pharmacophore-based molecular design. The Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) complexation QSAR model was developed for triclosan-based inhibitors (TCL) and a significant correlation was established between the calculated relative Gibbs free energies of complex formation (∆∆Gcom) between PfENR and TCL and the observed inhibitory potencies of the enzyme (IC50exp) for a training set of 20 known TCL analogues. Validation of the predictive power of the MM-PBSA QSAR model was carried out with the generation of 3D QSAR pharmacophore (PH4). We obtained a reasonable correlation between the relative Gibbs free energy of complex formation ∆∆Gcom and IC50exp values, which explained approximately 95% of the PfENR inhibition data: pIC50exp=−0.0544×∆∆Gcom+6.9336,R2=0.95. A similar agreement was established for the PH4 pharmacophore model of the PfENR inhibition (pIC50exp=0.9754×pIC50pre+0.1596, R2=0.98). Analysis of enzyme–inhibitor binding site interactions suggested suitable building blocks to be used in a virtual combinatorial library of 33,480 TCL analogues. Structural information derived from the complexation model and the PH4 pharmacophore guided us through in silico screening of the virtual combinatorial library of TCL analogues to finally identify potential new TCL inhibitors effective at low nanomolar concentrations. Virtual screening of the library by PfENR-PH4 led to a predicted IC50pre value for the best inhibitor candidate as low as 1.9 nM. Finally, the stability of PfENR-TCLx complexes and the flexibility of the active conformation of the inhibitor for selected top-ranking TCL analogues were checked with the help of molecular dynamics. This computational study resulted in a set of proposed new potent inhibitors with predicted antimalarial effects and favourable pharmacokinetic profiles that act on a novel pharmacological target, PfENR

Computer-Aided Design of Orally Bioavailable Pyrrolidine Carboxamide Inhibitors of Enoyl-Acyl Carrier Protein Reductase of Mycobacterium tuberculosis with Favorable Pharmacokinetic Profiles

We have carried out a computational structure-based design of new potent pyrrolidine carboxamide (PCAMs) inhibitors of enoyl-acyl carrier protein reductase (InhA) of Mycobacterium tuberculosis (MTb). Three-dimensional (3D) models of InhA-PCAMx complexes were prepared by in situ modification of the crystal structure of InhA-PCAM1 (Protein Data Bank (PDB) entry code: 4U0J), the reference compound of a training set of 20 PCAMs with known experimental inhibitory potencies (IC50exp). First, we built a gas phase quantitative structure-activity relationships (QSAR) model, linearly correlating the computed enthalpy of the InhA-PCAM complex formation and the IC50exp. Further, taking into account the solvent effect and loss of inhibitor entropy upon enzyme binding led to a QSAR model with a superior linear correlation between computed Gibbs free energies (ΔΔGcom) of InhA-PCAM complex formation and IC50exp (pIC50exp = −0.1552·ΔΔGcom + 5.0448, R2 = 0.94), which was further validated with a 3D-QSAR pharmacophore model generation (PH4). Structural information from the models guided us in designing of a virtual combinatorial library (VL) of more than 17 million PCAMs. The VL was adsorption, distribution, metabolism and excretion (ADME) focused and reduced down to 1.6 million drug like orally bioavailable analogues and PH4 in silico screened to identify new potent PCAMs with predicted IC50pre reaching up to 5 nM. Combining molecular modeling and PH4 in silico screening of the VL resulted in the proposed novel potent antituberculotic agent candidates with favorable pharmacokinetic profiles

Computer-Aided Design of Peptidomimetic Inhibitors of Falcipain-3: QSAR and Pharmacophore Models

In this work, antiparasitic peptidomimetics inhibitors (PEP) of falcipain-3 (FP3) of Plasmodium falciparum (Pf) are proposed using structure-based and computer-aided molecular design. Beginning with the crystal structure of PfFP3-K11017 complex (PDB ID: 3BWK), three-dimensional (3D) models of FP3-PEPx complexes with known activities ( IC50exp) were prepared by in situ modification, based on molecular mechanics and implicit solvation to compute Gibbs free energies (GFE) of inhibitor-FP3 complex formation. This resulted in a quantitative structure–activity relationships (QSAR) model based on a linear correlation between computed GFE (ΔΔGcom) and the experimentally measured  IC50exp. Apart from the structure-based relationship, a ligand-based quantitative pharmacophore model (PH4) of novel PEP analogues where substitutions were directed by comparative analysis of the active site interactions was derived using the proposed bound conformations of the PEPx. This provided structural information useful for the design of virtual combinatorial libraries (VL), which was virtually screened based on the 3D-QSAR PH4. The end results were predictive inhibitory activities falling within the low nanomolar concentration range

Computer-Aided Design of Peptidomimetic Inhibitors of Falcipain-3: QSAR and Pharmacophore Models

In this work, antiparasitic peptidomimetics inhibitors (PEP) of falcipain-3 (FP3) of Plasmodium falciparum (Pf) are proposed using structure-based and computer-aided molecular design. Beginning with the crystal structure of PfFP3-K11017 complex (PDB ID: 3BWK), three-dimensional (3D) models of FP3-PEPx complexes with known activities (&nbsp;IC50exp) were prepared by in situ modification, based on molecular mechanics and implicit solvation to compute Gibbs free energies (GFE) of inhibitor-FP3 complex formation. This resulted in a quantitative structure–activity relationships (QSAR) model based on a linear correlation between computed GFE (ΔΔGcom) and the experimentally measured &nbsp;IC50exp. Apart from the structure-based relationship, a ligand-based quantitative pharmacophore model (PH4) of novel PEP analogues where substitutions were directed by comparative analysis of the active site interactions was derived using the proposed bound conformations of the PEPx. This provided structural information useful for the design of virtual combinatorial libraries (VL), which was virtually screened based on the 3D-QSAR PH4. The end results were predictive inhibitory activities falling within the low nanomolar concentration range