Elucidating solvent effects on lipase-catalyzed peroxyacid synthesis through activity-based kinetics and molecular dynamics.

Peroxyacid synthesis is the first step in Prilezhaev epoxidation, which is an industrial method to form epoxides. Motivated by the development of a kinetic model as a tool for solvent selection, the effect of solvent type and acid chain length on the lipase-catalyzed peroxyacid synthesis was studied. A thermodynamic activity-based ping-pong kinetic expression was successfully applied to predict the effect of the reagent loadings in hexane. The activity-based reaction quotients provided a prediction of solvent-independent equilibrium constants. However, this strategy did not achieve satisfactory estimations of initial rates in solvents of higher polarity. The lack of compliance with some assumptions of this methodology could be confirmed through molecular dynamics calculations i.e. independent solvation energies and lack of solvent interaction with the active site. A novel approach is proposed combining the activity-based kinetic expression and the free binding energy of the solvent with the active site to predict kinetics upon solvent change. Di-isopropyl ether generated a strong interaction with the enzyme's active site, which was detrimental to kinetics. On the other hand, toluene or limonene gave moderate interaction with the active site rendering improved catalytic yield compared with less polar solvents, a finding sharpened when peroctanoic acid was produced.

A Putative New Role of Tv-PSP1 Recognizes IRE and ERE Hairpin Structures from Trichomonas vaginalis.

To understand whether protein Tv-PSP1 from Trichomonas vaginalis recognizes mRNA parasite stem-loop structures, we conducted REMSA and intrinsic fluorescence assays. We found the recombinant Tv-PSP1 structure, determined with X-ray crystallography, showed unusual thermal stability of the quaternary structure, associated with a disulfide bridge CYS76-CYS104. To gain deeper insight into the Tv-PSP1 interaction with mRNA stem-loops (mRNAsl) and its relationship with thermal stability, we also used an integrated computational protocol that combined molecular dynamics simulations, docking assays, and binding energy calculations. Docking models allowed us to determine a putative contact surface interaction region between Tv-PSP1 and mRNAsl. We determined the contributions of these complexes to the binding free energy (ΔGb) in the electrostatic (ΔGelec) and nonelectrostatic (ΔGnon-elec) components using the Adaptive Poisson-Boltzmann Solver (APBS) program. We are the first, to the best of our knowledge, to show the interaction between Tv-PSP1 and the stem-loop structures of mRNA.

Computational Analysis of Triazole-Based Kojic Acid Analogs as Tyrosinase Inhibitors by Molecular Dynamics and Free Energy Calculations.

Molecular docking, molecular dynamics (MD) simulations and the linear interaction energy (LIE) method were used here to predict binding modes and free energy for a set of 1,2,3-triazole-based KA analogs as potent inhibitors of Tyrosinase (TYR), a key metalloenzyme of the melanogenesis process. Initially, molecular docking calculations satisfactorily predicted the binding mode of evaluated KA analogs, where the KA part overlays the crystal conformation of the KA inhibitor into the catalytic site of TYR. The MD simulations were followed by the LIE method, which reproduced the experimental binding free energies for KA analogs with an r2 equal to 0.97, suggesting the robustness of our theoretical model. Moreover, the van der Waals contributions performed by some residues such as Phe197, Pro201, Arg209, Met215 and Val218 are responsible for the binding recognition of 1,2,3-triazole-based KA analogs in TYR catalytic site. Finally, our calculations provide suitable validation of the combination of molecular docking, MD, and LIE approaches as a powerful tool in the structure-based drug design of new and potent TYR inhibitors.

Computational Analysis of SAM Analogs as Methyltransferase Inhibitors of nsp16/nsp10 Complex from SARS-CoV-2.

Methyltransferases (MTases) enzymes, responsible for RNA capping into severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are emerging important targets for the design of new anti-SARS-CoV-2 agents. Here, analogs of S-adenosylmethionine (SAM), obtained from the bioisosteric substitution of the sulfonium and amino acid groups, were evaluated by rigorous computational modeling techniques such as molecular dynamics (MD) simulations followed by relative binding free analysis against nsp16/nsp10 complex from SARS-CoV-2. The most potent inhibitor (2a) shows the lowest binding free energy (-58.75 Kcal/mol) and more potency than Sinefungin (SFG) (-39.8 Kcal/mol), a pan-MTase inhibitor, which agrees with experimental observations. Besides, our results suggest that the total binding free energy of each evaluated SAM analog is driven by van der Waals interactions which can explain their poor cell permeability, as observed in experimental essays. Overall, we provide a structural and energetic analysis for the inhibition of the nsp16/nsp10 complex involving the evaluated SAM analogs as potential inhibitors.

Exploring the druggability of the binding site of aurovertin, an exogenous allosteric inhibitor of FOF1-ATP synthase.

In addition to playing a central role in the mitochondria as the main producer of ATP, FOF1-ATP synthase performs diverse key regulatory functions in the cell membrane. Its malfunction has been linked to a growing number of human diseases, including hypertension, atherosclerosis, cancer, and some neurodegenerative, autoimmune, and aging diseases. Furthermore, inhibition of this enzyme jeopardizes the survival of several bacterial pathogens of public health concern. Therefore, FOF1-ATP synthase has emerged as a novel drug target both to treat human diseases and to combat antibiotic resistance. In this work, we carried out a computational characterization of the binding sites of the fungal antibiotic aurovertin in the bovine F1 subcomplex, which shares a large identity with the human enzyme. Molecular dynamics simulations showed that although the binding sites can be described as preformed, the inhibitor hinders inter-subunit communications and exerts long-range effects on the dynamics of the catalytic site residues. End-point binding free energy calculations revealed hot spot residues for aurovertin recognition. These residues were also relevant to stabilize solvent sites determined from mixed-solvent molecular dynamics, which mimic the interaction between aurovertin and the enzyme, and could be used as pharmacophore constraints in virtual screening campaigns. To explore the possibility of finding species-specific inhibitors targeting the aurovertin binding site, we performed free energy calculations for two bacterial enzymes with experimentally solved 3D structures. Finally, an analysis of bacterial sequences was carried out to determine conservation of the aurovertin binding site. Taken together, our results constitute a first step in paving the way for structure-based development of new allosteric drugs targeting FOF1-ATP synthase sites of exogenous inhibitors.

Association strength of E6 to E6AP/p53 complex correlates with HPV-mediated oncogenesis risk.

Human papillomavirus (HPV) is recognized as the causative agent of cervical cancer in women, and it is associated with other anogenital and head/neck cancers. More than 120 types of HPV have been identified and many classified as high- or low-risk according to their oncogenic potential. One of its proteins, E6, has evolved to overcome the oncosuppressor functions of p53 by targeting this protein for degradation via interaction with the human ubiquitin-ligase E6AP. This study evaluates the correlation between the association strength of 40 HPV E6 types to the E6AP/p53 complex and the HPV oncogenesis risk using molecular simulations and machine and deep learning (ML/DL). In addition, a ML/DL-driven prediction is proposed for the HPV unclassified oncogenic risk type. The results indicate that thermodynamics play a pivotal role in the establishment of HPV-associated cancer and highlight the need to include some viral types in the HPV-related cancer surveillance and prevention strategies.

Molecular Basis of Inhibitory Mechanism of Naltrexone and Its Metabolites through Structural and Energetic Analyses.

Naltrexone is a potent opioid antagonist with good blood-brain barrier permeability, targeting different endogenous opioid receptors, particularly the mu-opioid receptor (MOR). Therefore, it represents a promising candidate for drug development against drug addiction. However, the details of the molecular interactions of naltrexone and its derivatives with MOR are not fully understood, hindering ligand-based drug discovery. In the present study, taking advantage of the high-resolution X-ray crystal structure of the murine MOR (mMOR), we constructed a homology model of the human MOR (hMOR). A solvated phospholipid bilayer was built around the hMOR and submitted to microsecond (µs) molecular dynamics (MD) simulations to obtain an optimized hMOR model. Naltrexone and its derivatives were docked into the optimized hMOR model and submitted to µs MD simulations in an aqueous membrane system. The MD simulation results were submitted to the molecular mechanics-generalized Born surface area (MMGBSA) binding free energy calculations and principal component analysis. Our results revealed that naltrexone and its derivatives showed differences in protein-ligand interactions; however, they shared contacts with residues at TM2, TM3, H6, and TM7. The binding free energy and principal component analysis revealed the structural and energetic effects responsible for the higher potency of naltrexone compared to its derivatives.

Search for Novel Potent Inhibitors of the SARS-CoV-2 Papain-like Enzyme: A Computational Biochemistry Approach.

The rapid emergence and spread of new variants of coronavirus type 2, as well as the emergence of zoonotic viruses, highlights the need for methodologies that contribute to the search for new pharmacological treatments. In the present work, we searched for new SARS-CoV-2 papain-like protease inhibitors in the PubChem database, which has more than 100 million compounds. Based on the ligand efficacy index obtained by molecular docking, 500 compounds with higher affinity than another experimentally tested inhibitor were selected. Finally, the seven compounds with ADME parameters within the acceptable range for such a drug were selected. Next, molecular dynamics simulation studies at 200 ns, ΔG calculations using molecular mechanics with generalized Born and surface solvation, and quantum mechanical calculations were performed with the selected compounds. Using this in silico protocol, seven papain-like protease inhibitors are proposed: three compounds with similar free energy (D28, D04, and D59) and three compounds with higher binding free energy (D60, D99, and D06) than the experimentally tested inhibitor, plus one compound (D24) that could bind to the ubiquitin-binding region and reduce the effect on the host immune system. The proposed compounds could be used in in vitro assays, and the described protocol could be used for smart drug design.

Elucidation of the inhibitory activity of ivermectin with host nuclear importin α and several SARS-CoV-2 targets.

Ivermectin (IVM) is an FDA-approved drug that has shown antiviral activity against a wide variety of viruses in recent years. IVM inhibits the formation of the importin-α/ß1 heterodimeric complex responsible for the translocation and replication of various viral species proteins. Also, IVM hampers SARS-CoV-2 replication in vitro; however, the molecular mechanism through which IVM inhibits SARS-CoV-2 is not well understood. Previous studies have explored the molecular mechanism through which IVM inhibits importin-α and several potential targets associated with COVID-19 by using docking approaches and MD simulations to corroborate the docked complexes. This study explores the energetic and structural properties through which IVM inhibits importin-α and five targets associated with COVID-19 by using docking and MD simulations combined with the molecular mechanics generalized Born surface area (MMGBSA) approach. Energetic and structural analysis showed that the main protease 3CLpro reached the most favorable affinity, followed by importin-α and Nsp9, which shared a similar relationship. Therefore, in vitro activity of IVM can be explained by acting as an inhibitor of importin-α, dimeric 3CLpro, and Nsp9, but mainly over dimeric 3CLpro.Communicated by Ramaswamy H. Sarma.

A study of possible substitutes for the endocrine disruptor DEHP in two hormone receptors.

Bis(2-ethylhexyl) phthalate (DEHP) has been widely used for the production of plastics, and the compound has also been found to act as endocrine disruptor. Exposure to DEHP has been found to cause several hormonal problems, including decreased fertility. Due to the environmental and health risks posed by the use of DEHP, the present study employed molecular docking, molecular dynamics, and free energy analyses (MM-GBSA, MM-PBSA, and SIE) aiming at evaluating the action of DEHP and that of two other compounds (ATEC and DL9TH), tested as potential DEHP substitutes, on two hormone receptors (sex hormone-binding globulin - SHBG - and progesterone receptor - PR). The results obtained showed that ATEC may be a good substitute for DEHP in the production of plastics, such as PVC, considering that the compound recorded the greatest free energy values with respect to binding with SHBG (-31.36 kcal/mol obtained from MM-GBSA; -20.28 kcal/mol for MM-PBSA, and -7.40 for SIE) and PR (-36.40 kcal/mol for MM-GBSA; -27.00 kcal/mol for MM-PBSA, and -8.51 kcal/mol for SIE) - this shows that ATEC presented the least activity in the two hormone receptors. The findings of this study provide relevant insights on potential substitutes for DEHP and help shed light on the action of these new efficient substances, which have similar properties to DEHP (ATEC and DL9TH) yet do not act as endocrine disruptors.Communicated by Ramaswamy H. Sarma.

Binding of Folate-G4-PAMAM dendrimer conjugate with indomethacin via ligand diffusion MD simulations.

Preceding experimental findings revealed that the release of indomethacin decreased when a folate conjugate G4-PAMAM (folate-G4-PAMAM) dendrimer was used compared with its unconjugated dendrimer (G4-PAMAM). Further, better encapsulation of the conjugated dendrimer was achieved, information useful for elucidating the structural and energetic basis of indomethacin on folate-G4-PAMAM encapsulation. In this study, we employed a ligand diffusion molecular dynamic simulations (LDMDSs) strategy combined with the molecular mechanics-generalized-born surface area (MMGBSA) approach to explore the mechanism by which indomethacin conjugated to folate-G4-PAMAM dendrimer forms complexes better than G4-PAMAM dendrimer. To this, we first constructed and equilibrated the folate-G4-PAMAM dendrimer, then, this system was submitted to docking and molecular dynamics (MD) simulation to evaluate its ability to form a stable complex with the folate receptor (FR). We observed that the folate-G4-PAMAM dendrimer was able to bind FR with higher affinity than free folic acid. Based on these results, we further performed LDMDSs to assess folate-G4-PAMAM dendrimer and G4-PAMAM dendrimer contacts with indomethacin. Our results correlate with experimental data, which confirm that folate-G4-PAMAM dendrimers are capable of most rapidly binding greater numbers of indomethacin molecules than G4-PAMAM, which suggests better loading and slower release occurs when the functionalized G4-PAMAM dendrimer is used. The simulations further revealed that van der Waals interactions govern the affinity.Communicated by Ramaswamy H. Sarma.

Structural mechanism of the Tanford transition of bovine ß-lactoglobulin through microsecond molecular dynamics simulations.

X-ray analysis has provided structural data about a pH-driven conformational change in ß-lactoglobulin (BLG) known as the Tanford transition, which occurs at around pH 7 and involves the EF loop, which acts as a lid closing the internal cavity of the protein below pH 7 and opening it above pH 7. NMR studies using wild-type BLG have encountered problems trying to explain the Tanford transition, however, they have provided important insight using a dimeric BLG mutant, revealing that the opening and closure of the EF loop consists of two types of motions in the microsecond and milliseconds timescales. This provides valuable information indicating that the dimeric state is a good model to study the Tanford transition, although the understanding of this structural change is still lacking at the atomic level. We performed microsecond molecular dynamics (MD) simulations starting from different conformations of BLG in the monomeric and dimeric state, with protonated and deprotonated E89, in order to explore the Tanford transition. Our results provide structural information for the transition from the closed to the open conformation in BLG and show it occurs in the dimeric state in the microsecond timescale, in line with the fast motion observed through NMR experiments. In addition, MD simulations coupled to MMGBSA approach indicated that the most populated conformer of BLG in the open state is able to bind ligands with similar affinity to that of BLG at neutral pH obtained through crystallographic experiments.Communicated by Ramaswamy H. Sarma.

Energetic and structural basis for the differences in infectivity between the wild-type and mutant spike proteins of SARS-CoV-2 in the Mexican population.

SARS-CoV-2 is the causative agent of the ongoing viral pandemic of COVID-19. After the emergence of this virus, it became a global public health concern and quickly evolved into a pandemic. Mexico is currently in the third position in the number of deaths due to SARS-CoV-2. To date, there have been several lineages of SARS-CoV-2 worldwide; in the Mexican population, two variants of the spike protein (S-protein) are found, localized at H49Y and D614G, which have been related to increased infectivity with respect to the wild-type S-protein. To understand how these differences impact the structural behavior of the S-protein of SARS-CoV-2, as well as binding with ACE2, we performed MD simulations combined with the molecular mechanics generalized Born/Poisson-Boltzmann surface area (MMGB(PB)SA) approach starting from X-ray crystallography data. Energetic and structural analysis showed that the differences in infectivity can be explained by differences in affinity of the protein-protein interface between the wild-type and mutant S-protein with ACE2. Conformational analysis showed that molecular recognition between the S-protein and ACE2 is linked to a decrease in the conformational flexibility of wild-type and mutant S-protein; however, an increase in the conformational mobility of ACE2 could also contribute to the binding affinity observed using the MMGB(PB)SA method.

Thermodynamic and structural aspects of molecular recognition in mannose-binding protein complexes: a theoretical study over HRP-ArtinM association.

The biomolecular recognition of D-mannose-binding lectin from Artocarpus heterophyllus (ArtinM) by Horseradish Peroxidase (HRP) mediated by glycosylation allows their application in a multitude of biological systems. The present work describes the use of molecular dynamics (MD) to assess the Gibbs free energy associated with the formation of a ArtinM-HRP conjugate mediated by a glycosylation molecule. For the enthalpy term, we applied the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method and for the vibrational entropy term, we use the quasi-harmonic approximation. Our results show that, even without glycosylation, the binding free energy between ArtinM and HRP is - 196.154 kJmol- 1, an extremely high affinity with low selectivity, originated mainly through the van der Waals energy terms. The binding free energy between ArtinM and the glycosylated HRP (gHRP) was calculated at - 66.156 kJmol- 1, an absolute and considerably lower value, however, originated from electrostatic energy terms, which increases the selectivity of molecular recognition. Our work has shown that the HRP active site region has a high affinity and low selectivity for other biomolecules. The presence of glycosylation plays a role in increasing this selectivity for this region. Thus, we conclude that performing mutagenesis of amino acid residues near the entrance of the catalytic site, can improve the activity of non-glycosylated HRPs. This illustrates new insights that can be applied to carbohydrate-based immunochemistry.

In silico Studies on the Interaction Between Bioactive Ligands and DPPIV: Insights on Potential Candidates for the Treatment of type 2 Diabetes Mellitus.

INTRODUCTION: The enzyme called dipeptidyl peptidase IV (DPP-IV) is related to the glycemic control associated with the stimulation of the pancreas to produce insulin. So, its inhibition is a good strategy for the treatment of type 2 diabetes mellitus. METHODS: In this study, we have employed molecular modeling strategies such as CoMFA, molecular docking, molecular dynamics, and binding free energy calculations of a set of DPP-IV inhibitors in order to understand the main characteristics related to the biological activity of these ligands against the enzyme. RESULTS: The models obtained from CoMFA presented significant values of internal (0.768) and external (0.988) validations. Important interactions with some residues, such as Glu205, Tyr666, Arg125, Ser630, Phe357 and Tyr662, were also identified. In addition, calculations of the electronic properties allowed relating the LUMO and HOMO energies with the biological activity of the compounds studied. The results obtained from the molecular dynamics simulations and the SIE calculations (ΔG) indicated that the inhibitor 40 increases the stability of the DPP-IV target. CONCLUSIONS: Therefore, from this study, it is possible to propose molecular modifications of these DPP-IV inhibitors in order to improve their potential to treat type 2 diabetes.

Evaluating the Performance of a Non-Bonded Cu2+ Model Including Jahn-Teller Effect into the Binding of Tyrosinase Inhibitors.

Tyrosinase (TYR) is a metalloenzyme classified as a type-3 copper protein, which is involved in the synthesis of melanin through a catalytic process beginning with the conversion of the amino acid l-Tyrosine (l-Tyr) to l-3,4-dihydroxyphenylalanine (l-DOPA). It plays an important role in the mechanism of melanogenesis in various organisms including mammals, plants, and fungi. Herein, we used a combination of computational molecular modeling techniques including molecular dynamic (MD) simulations and the linear interaction energy (LIE) model to evaluate the binding free energy of a set of analogs of kojic acid (KA) in complex with TYR. For the MD simulations, we used a dummy model including the description of the Jahn-Teller effect for Cu2+ ions in the active site of this enzyme. Our results show that the LIE model predicts the TYR binding affinities of the inhibitor in close agreement to experimental results. Overall, we demonstrate that the classical model provides a suitable description of the main interactions between analogs of KA and Cu2+ ions in the active site of TYR.

In silico design of peptides as potential ligands to resistin.

Resistin is a hormone of biological interest due to its connection with several diseases of worldwide concern. This work aims to design a series of cyclic peptides as "lead compounds" to identify potential ligands to resistin. To this end, we propose an approach based on a peptide design algorithm plus a two-stage selection which accounts for selectivity, one of the most forgotten steps in the design of ligands. Following this approach, we have been able to identify several peptides as strong candidates for the design of elements of bio-recognition. Those peptides present low scoring binding energy to albumin, good water solubility, stability in water at 300 K, and high scoring binding energy to resistin. Among those peptides, two were chosen, to perform a more rigorous calculation of binding free energy based on the Alchemical Absolute Binding Free Energy method. We were able to establish a methodological route for the development of strong candidates for the design of ligands to resistin. Graphical Abstract Combined MD + MC + AABFE approach to design and screening of high-affinity binders to resistin.

Competition Between Phenothiazines and BH3 Peptide for the Binding Site of the Antiapoptotic BCL-2 Protein.

The study of proteins and mechanisms involved in the apoptosis and new knowledge about cancer's biology are essential for planning new drugs. Tumor cells develop several strategies to gain proliferative advantages, including molecular alterations to evade from apoptosis. Failures in apoptosis could contribute to cancer pathogenesis, since these defects can cause the accumulation of dividing cells and do not remove genetic variants that have malignant potential. The apoptosis mechanism is composed by proteins that are members of BCL-2 and cysteine-protease families. BH3-only peptides are the "natural" intracellular ligands of BCL-2 family proteins. On the other hand, studies have proved that phenothiazine compounds influence the induction of cellular death. To understand the characteristics of phenothiazines and their effects on tumoral cells and organelles involved in the apoptosis, as well as evaluating their pharmacologic potential, we have carried out computational simulation with the purpose of relating the structures of the phenothiazines with their biological activity. Since the tridimensional (3D) structure of the target protein is known, we have employed the molecular docking approach to study the interactions between compounds and the protein's active site. Hereafter, the molecular dynamics technique was used to verify the temporal evolution of the BCL-2 complexes with phenothiazinic compounds and the BH3 peptide, the stability and the mobility of these molecules in the BCL-2 binding site. From these results, the calculation of binding free energy between the compounds and the biological target was carried out. Thus, it was possible to verify that thioridazine and trifluoperazine tend to increase the stability of the BCL-2 protein and can compete for the binding site with the BH3 peptide.

Microbial ß-Galactosidases of industrial importance: Computational studies on the effects of point mutations on the lactose hydrolysis reaction.

Hydrolysis efficiency of ß-galactosidases is affected due to a strong inhibition by galactose, hampering the complete lactose hydrolysis. One alternative to reduce this inhibition is to perform mutations in the enzyme's active site. The aim of this study was to evaluate the effect of point mutations on the active site of different microbial ß-galactosidases, using computational techniques. The enzymes of Aspergillus niger (AnßGal), Aspergillus oryzae (AoßGal), Bacillus circulans (BcßGal), Bifidobacterium bifidum (BbßGal), and Kluyveromyces lactis (KlßGal) were used. The mutations were carried out in all residues that were up to 4.5 Å from the galactose/lactose molecules and binding energy was computed. The mutants Tyr96Ala (AnßGal), Asn140Ala and Asn199Ala (AoßGal), Arg111Ala and Glu355Ala (BcßGal), Arg122Ala and Phe358Ala (BbßGal), Tyr523Ala, Phe620Ala, and Trp582Ala (KlßGal) had the best results, with higher effect on galactose binding energy and lower effect on lactose affinity. To maximize enzyme reactions by reducing galactose affinity, double mutations were proposed for BcßGal, BbßGal, and KlßGal. The double mutations in BcßGal and BbßGal caused the highest reduction in galactose affinity, while no satisfactory results were observed to KlßGal. Using computational tools, mutants that reduced galactose affinity without significantly affecting lactose binding were proposed. The mutations proposed can be used to reduce the negative feedback process, improving the catalytic characteristics of ß-galactosidases and rendering them promising for industrial applications.

Binding Free Energy Calculation Using Quantum Mechanics Aimed for Drug Lead Optimization.

The routine use of in silico tools is already established in drug lead design. Besides the use of molecular docking methods to screen large chemical libraries and thus prioritize compounds for purchase or synthesis, more accurate calculations of protein-ligand binding free energy has shown the potential to guide lead optimization, thus saving time and resources. Theoretical developments and advances in computing power have allowed quantum mechanical-based methods applied to calculations on biomacromolecules to be increasingly explored and used, with the purpose of providing a more accurate description of protein-ligand interactions and an enhanced level of accuracy in the calculation of binding affinities. It should be noted that the quantum mechanical formulation includes, in principle, all contributions to the energy, considering terms usually neglected in molecular mechanics force fields, such as electronic polarization, metal coordination, and covalent binding; moreover, quantum mechanical approaches are systematically improvable. By treating all elements and interactions on equal footing, and avoiding the need of system-dependent parameterizations, they provide a greater degree of transferability. In this review, we illustrate the increasing relevance of quantum mechanical methods for binding free energy calculation in the context of structure-based drug lead optimization, showing representative applications of the different approaches available.