Insights into susceptibility of antiviral drugs against the E119G mutant of 2009 influenza A (H1N1) neuraminidase by molecular dynamics simulations and free energy calculations

Design of new chemical entities targeting both native and H275Y mutant influenza a virus by deep reinforcement learning

Influenza virus remains a major public health challenge due to its high morbidity and mortality and seasonal surge. Although antiviral drugs against the influenza virus are widely used as a first-line defense, the virus undergoes rapid genetic changes, resulting in the emergence of drug-resistant strains. Thus, new antiviral drugs that can outwit resistant strains are of significant importance. Herein, we used deep reinforcement learning (RL) algorithm to design new chemical entities (NCEs) that are able to bind to the native and H275Y mutant (oseltamivir-resistant) neuraminidases (NAs) of influenza A virus with better binding energy than oseltamivir. We generated more than 66211 NCEs, which were prioritized based on the filtering rules, structural alerts, and synthetic accessibility. Then, 18 NCEs with better MM/PBSA scores than oseltamivir were further analyzed in molecular dynamics (MD) simulations conducted for 100 ns. The MD experiments showed that 8 NCEs formed very stable complexes with the binding pocket of both native and H275Y mutant NAs of H1N1. Furthermore, most NCEs demonstrated much better binding affinity to group 2 (N2, N3, and N9) and influenza B virus NAs than oseltamivir. Although all 8 NCEs have non-sialic acid-like structures, they showed a similar binding mode as oseltamivir, indicating that it is possible to find new scaffolds with better binding and antiviral properties than sialic acid-like inhibitors. In conclusion, we have designed potential compounds as antiviral candidates for further synthesis and testing against wild and mutant influenza virus.Communicated by Ramaswamy H. Sarma.

Designing new drug candidates as inhibitors against wild and mutant type neuraminidases: molecular docking, molecular dynamics and binding free energy calculations

Influenza virus is the cause of the death of millions of people with about 3-4 pandemics every hundred years in history. It also turns into a seasonal disease, bringing about approximately 5-15% of the population to be infected and 290,000-650,000 people to die every year. These numbers reveal that it is necessary to be on the alert to work towards influenza in order to protect public health. There are FDA-approved antiviral drugs such as oseltamivir and zanamivir recommended by the World Center for Disease Prevention. However, after the recent outbreaks such as bird flu and swine flu, increasing studies have shown that the flu virus has gained resistance to these drugs. So, there is an urgent need to find new drugs effective against this virus. This study aims to investigate new drug candidates targeting neuraminidase (NA) for the treatment of influenza by using computer aided drug design approaches. They involve virtual scanning, de novo design, rational design, docking, MD, MMGB/PBSA. The investigation includes H1N1, H5N1, H2N2 and H3N2 neuraminidase proteins and their mutant variants possessing resistance to FDA-approved drugs. Virtual screening consists of approximately 30 thousand molecules while de novo and rational designs produced over a hundred molecules. These approaches produced three lead molecules with binding energies for both non-mutant (-34.84, -59.99 and -60.66 kcal/mol) and mutant (-40.40, -58.93, -76.19 kcal/mol) H2N2 NA calculated by MM-PBSA compared with those of oseltamivir -25.64 and -18.40 respectively. The results offer new drug candidates against influenza infection.Communicated by Ramaswamy H. Sarma.

Discovery of human coronaviruses pan-papain-like protease inhibitors using computational approaches

The papain-like protease (PLpro) is vital for the replication of coronaviruses (CoVs), as well as for escaping innate-immune responses of the host. Hence, it has emerged as an attractive antiviral drug-target. In this study, computational approaches were employed, mainly the structure-based virtual screening coupled with all-atom molecular dynamics (MD) simulations to computationally identify specific inhibitors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PLpro, which can be further developed as potential pan-PLpro based broad-spectrum antiviral drugs. The sequence, structure, and functional conserveness of most deadly human CoVs PLpro were explored, and it was revealed that functionally important catalytic triad residues are well conserved among SARS-CoV, SARS-CoV-2, and middle east respiratory syndrome coronavirus (MERS-CoV). The subsequent screening of a focused protease inhibitors database composed of ∼7,000 compounds resulted in the identification of three candidate compounds, ADM_13083841, LMG_15521745, and SYN_15517940. These three compounds established conserved interactions which were further explored through MD simulations, free energy calculations, and residual energy contribution estimated by MM-PB(GB)SA method. All these compounds showed stable conformation and interacted well with the active residues of SARS-CoV-2 PLpro, and showed consistent interaction profile with SARS-CoV PLpro and MERS-CoV PLpro as well. Conclusively, the reported SARS-CoV-2 PLpro specific compounds could serve as seeds for developing potent pan-PLpro based broad-spectrum antiviral drugs against deadly human coronaviruses. Moreover, the presented information related to binding site residual energy contribution could lead to further optimization of these compounds.

Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery

BACKGROUND

Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). Molecular dynamics, on the other hand, introduces flexibility to understand the drug binding process.

OBJECTIVE

The aim of the present study is to provide a systematic review on the usage of molecular dynamics simulations to aid the process of structure-based drug design.

METHOD

This review discussed findings from various research articles and review papers on the use of molecular dynamics in drug discovery. All efforts highlight the practical grounds for which molecular dynamics simulations are used in drug designing program. In summary, various aspects of the use of molecular dynamics simulations that underline the basis of studying drug-target complexes were thoroughly explained.

RESULTS

This review is the result of reviewing more than a hundred papers. It summarizes various problems that use molecular dynamics simulations.

CONCLUSION

The findings of this review highlight how molecular dynamics simulations have been successfully implemented to study the structure-function details of specific drug-target complexes. It also identifies the key areas such as stability of drug-target complexes, ligand binding kinetics and identification of allosteric sites which have been elucidated using molecular dynamics simulations.

Discovery of novel Hepatitis C virus inhibitor targeting multiple allosteric sites of NS5B polymerase

HCV is a viral infection posing a severe global threat when left untreated progress to end-stage liver disease, including cirrhosis and HCC. The NS5B polymerase of HCV is the most potent target that harbors four allosteric binding sites that could interfere with the HCV infection. We present the discovery of a novel synthetic compound that harbors the potential of NS5B polymerase inhibition. All eight compounds belonging to the benzothiazine family of heterocycles displayed no cellular cytotoxicity in HepG2 cells at nontoxic dose concentration (200 μM). Subsequently, among eight compounds of the series, merely compound 5b exhibited significant inhibition of the expression of the HCV NS5B gene as compared to DMSO control in semi-quantitative PCR. Based on our western blot result, 5b at the range of 50, 100 and 200 μM induced 20, 40, and 70% inhibition of NS5B protein respectively. To estimate the binding potential, 5b was docked at respective allosteric sites followed by molecular dynamics (MD) simulations for a period of 20 ns. In addition, binding free energy calculation by MM-GB/PBSA method revealed a conserved interaction profile of residues lining the allosteric sites in agreement with the reported NS5B co-crystallized inhibitors. The presented results provide important information about a novel compound 5b which may facilitate the the discovery of novel inhibitors that tends to target multiple sites on NS5B polymerase.

Novel oseltamivir-resistant mutations distant from the active site of influenza B neuraminidase

We performed a neuraminidase sequence analysis of thirty-two pediatric patients with influenza B who visited Teikyo University Hospital from January 2016 to March 2017, and found oseltamivir-resistant samples belonging to the Yamagata and Victoria lineages. Comparison with the neuraminidase sequence of oseltamivir-susceptible B/Brisbane/60/2008 revealed 5 common amino acid substitutions in many of these samples. According to the binding free energy calculation, the N340D and E358K substitutions reduced the affinity of oseltamivir to neuraminidase. Unexpectedly, these substitutions were located distant from the oseltamivir-binding site in neuraminidase. According to the molecular dynamics simulations, the N340D substitution rearranged complicated hydrogen bond networks in an extensive surface region of neuraminidase. The E358K substitution extensively altered the electrostatic potential map of the overall neuraminidase structure. Through these novel mechanisms, the N340D and E358K substitutions indirectly influenced the affinity reduction. These results may be useful for designing drugs for the treatment of oseltamivir-resistant virus infections.Communicated by Ramaswamy H. Sarma.

Perspectives towards antiviral drug discovery against Ebola virus

Ebola virus disease (EVD), caused by Ebola viruses, resulted in more than 11 500 deaths according to a recent 2018 WHO report. With mortality rates up to 90%, it is nowadays one of the most deadly infectious diseases. However, no Food and Drug Administration‐approved Ebola drugs or vaccines are available yet with the mainstay of therapy being supportive care. The high fatality rate and absence of effective treatment or vaccination make Ebola virus a category‐A biothreat pathogen. Fortunately, a series of investigational countermeasures have been developed to control and prevent this global threat. This review summarizes the recent therapeutic advances and ongoing research progress from research and development to clinical trials in the development of small‐molecule antiviral drugs, small‐interference RNA molecules, phosphorodiamidate morpholino oligomers, full‐length monoclonal antibodies, and vaccines. Moreover, difficulties are highlighted in the search for effective countermeasures against EVD with additional focus on the interplay between available in silico prediction methods and their evidenced potential in antiviral drug discovery.

Discovery of novel natural compound inhibitors targeting estrogen receptor α by an integrated virtual screening strategy

Estrogen receptor (ER) is a nuclear hormone receptor and plays an important role in mediating the cellular effects of estrogen. ER can be classified into two receptors: estrogen receptor alpha (ERα) and beta (ERβ), and the former is expressed in 50~80% of breast tumors and has been extensively investigated in breast cancer for decades. Excessive exposure to estrogen can obviously stimulate the growth of breast cancers primarily mediated by ERα, and thus anti-estrogen therapies by small molecules are of concern to clinicians and pharmaceutical industry in the treatment of ERα-positive breast cancers. Although a series of estrogen receptor modulators have been developed, these drugs can lead to resistance and side effects. Therefore, the development of small molecule inhibitors with high target specificity has been intensified. In this pursuit, an integrated computer-aided virtual screening technique, including molecular docking and pharmacophore model screening, was used to screen traditional Chinese medicine (TCM) databases. The compounds with high docking scores and fit values were subjected to ADME (adsorption, distribution, metabolism, excretion) and toxicity prediction, and ten hits were identified as potential inhibitors targeting ERα. Molecular docking was used to investigate the binding modes between ERα and three most potent hits, and molecular dynamic simulations were chosen to explore the stability of these complexes. The rank of the predicted binding free energies evaluated by MM/GBSA is consistent with the docking score. These novel scaffolds discovered in the present study can be used as critical starting point in the drug discovery process for treating ERα-positive breast cancer. Graphical abstract .

In silico structural elucidation of RNA-dependent RNA polymerase towards the identification of potential Crimean-Congo Hemorrhagic Fever Virus inhibitors

The Crimean-Congo Hemorrhagic Fever virus (CCHFV) is a segmented negative single-stranded RNA virus (-ssRNA) which causes severe hemorrhagic fever in humans with a mortality rate of ~50%. To date, no vaccine has been approved. Treatment is limited to supportive care with few investigational drugs in practice. Previous studies have identified viral RNA dependent RNA Polymerase (RdRp) as a potential drug target due to its significant role in viral replication and transcription. Since no crystal structure is available yet, we report the structural elucidation of CCHFV-RdRp by in-depth homology modeling. Even with low sequence identity, the generated model suggests a similar overall structure as previously reported RdRps. More specifically, the model suggests the presence of structural/functional conserved RdRp motifs for polymerase function, the configuration of uniform spatial arrangement of core RdRp sub-domains, and predicted positively charged entry/exit tunnels, as seen in sNSV polymerases. Extensive pharmacophore modeling based on per-residue energy contribution with investigational drugs allowed the concise mapping of pharmacophoric features and identified potential hits. The combination of pharmacophoric features with interaction energy analysis revealed functionally important residues in the conserved motifs together with in silico predicted common inhibitory binding modes with highly potent reference compounds.

Importance of Incorporating Protein Flexibility in Molecule Modeling: A Theoretical Study on Type I1/2 NIK Inhibitors

NF-κB inducing kinase (NIK), which is considered as the central component of the non-canonical NF-κB pathway, has been proved to be an important target for the regulation of the immune system. In the past few years, NIK inhibitors with various scaffolds have been successively reported, among which type I^1/2 inhibitors that can not only bind in the ATP-binding pocket at the DFG-in state but also extend into an additional back pocket, make up the largest proportion of the NIK inhibitors, and are worthy of more attention. In this study, an integration protocol that combines molecule docking, MD simulations, ensemble docking, MM/GB(PB)SA binding free energy calculations, and decomposition was employed to understand the binding mechanism of 21 tricyclic type I^1/2 NIK inhibitors. It is found that the docking accuracy is largely dependent on the selection of docking protocols as well as the crystal structures. The predictions given by the ensemble docking based on multiple receptor conformations (MRCs) and the MM/GB(PB)SA calculations based on MD simulations showed higher linear correlations with the experimental data than those given by conventional rigid receptor docking (RRD) methods (Glide, GOLD, and Autodock Vina), highlighting the importance of incorporating protein flexibility in predicting protein–ligand interactions. Further analysis based on MM/GBSA demonstrates that the hydrophobic interactions play the most essential role in the ligand binding to NIK, and the polar interactions also make an important contribution to the NIK-ligand recognition. A deeper comparison of several pairs of representative derivatives reveals that the hydrophobic interactions are vitally important in the structural optimization of analogs as well. Besides, the H-bond interactions with some key residues and the large desolvation effect in the back pocket devote to the affinity distinction. It is expected that our study could provide valuable insights into the design of novel and potent type I^1/2 NIK inhibitors.

Structural optimization on a virtual screening hit of smoothened receptor

The Hedgehog (Hh) pathway plays a critical role during embryonic development by controlling cell patterning, growth and migration. In adults, the function of Hh pathway is curtailed to tissue repair and maintenance. Aberrant reactivation of Hh signaling has been linked to tumorigenesis in various cancers, such as basal cell carcinoma (BCC) and medulloblastoma. The Smoothened (Smo) receptor, a key component of the Hh pathway which is central to the signaling transduction, has emerged as an attractive therapeutic target for the treatment of human cancers. Taking advantage of the availability of several crystal structures of Smo in complex with different antagonists, we have previously conducted a molecular docking-based virtual screening to identify several compounds which exhibited significant inhibitory activity against the Hh pathway activation (IC₅₀ < 10 μM) in a Gli-responsive element (GRE) reporter gene assay. The most potent compound (ChemDiv ID C794-1677: 47 nM) showed comparable Hh signaling inhibition to the marketed drug vismodegib (46 nM). Herein, we report our structural optimization based on the virtual screening hit C794-1677. Our efforts are aimed to improve potency, decrease cLogP, and remove potentially metabolic labile/toxic pyrrole and aniline functionalities presented in C794-1677. The optimization led to the identification of numerous potent compounds exemplified by 25 (7.1 nM), which was 7 folds more potent compared with vismodegib. In addition, 25 was much less lipophilic compared with C794-1677 and devoid of the potentially metabolic labile/toxic pyrrole and aniline functional groups. Furthermore, 25 exhibited promising efficacy in inhibiting Gli1 mRNA expression in NIH3T3 cells with either wildtype Smo or D473H Smo mutant. These results represented significant improvement over the virtual screening hit C794-1677 and suggested that compound 25 can be used as a good starting point to support lead optimization.

Insight into tetrodotoxin blockade and resistance mechanisms of Nav 1.2 sodium channel by theoretical approaches

Na_v 1.2, a member of voltage-gated sodium channels (Na_v s) that are responsible for the generation and propagation of action potentials along the cell membrane, and play a vital role in the process of information transmission within the nervous system and muscle contraction, is preferentially expressed in the central nervous system. As a potent and selective blocker of Na_v s, tetrodotoxin (TTX) has been extensively studied in biological and chemical sciences, whereas the detailed mechanism by which it blocks nine Na_v 1 channel subtypes remain elusive. Despite the high structural similarity, the TTX metabolite 4,9-anhydro-TTX is 161 times less effective toward the mammalian Na_v 1.2, which puzzled us to ask a question why such a subtle structural variation results in the largely binding affinity difference. In the current work, an integrated computational strategy, including homology modeling, induced fit docking, explicit-solvent MD simulations, and free energy calculations, was employed to investigate the binding mechanism and conformational determinants of TTX analogs. Based on the computational results, the H-bond interactions between C4-OH and C9-OH of TTX and the outer ring carboxylates of the selectivity-filter residues, and the cation-π interaction between the primary amine of guanidinium of TTX and Phe385 determine the difference of their binding affinities. Moreover, the computationally simulations were carried out for the D384N and E945K mutants of hNa_v 1.2-TTX, and the rank of the predicted binding free energies is in accordance with the experimental data. These observations provide a valuable model to design potent and selective neurotoxins of Na_v 1.2 and shed light on the blocking mechanism of TTX to sodium channels.

Importance of protein flexibility on molecular recognition: modeling binding mechanisms of aminopyrazine inhibitors to Nek2

NIMA-related kinase 2 (Nek2) plays a significant role in cell cycle regulation, and overexpression of Nek2 has been observed in several types of carcinoma, suggesting it is a potential target for cancer therapy. In this study, we attempted to gain more insight into the binding mechanisms of a series of aminopyrazine inhibitors of Nek2 through multiple molecular modeling techniques, including molecular docking, molecular dynamics (MD) simulations and free energy calculations. The simulation results showed that the induced fit docking and ensemble docking based on multiple protein structures yield better predictions than conventional rigid receptor docking, highlighting the importance of incorporating receptor flexibility into the accurate predictions of the binding poses and binding affinities of Nek2 inhibitors. Additionally, we observed that the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculations did not show better performance than the docking scoring to rank the binding affinities of the studied inhibitors, suggesting that MM/GBSA is system-dependent and may not be the best choice for the Nek2 systems. Moreover, the detailed information on protein-ligand binding was characterized by the MM/GBSA free energy decomposition, and a number of derivatives with improved docking scores were designed. It is expected that our study can provide valuable information for the future rational design of novel and potent inhibitors of Nek2.

Exploring the binding mechanisms of PDE5 with chromeno[2,3-c]pyrrol-9(2H)-one by theoretical approaches

Cyclic nucleotide phosphodiesterase type 5 (PDE5), exclusively specific for the cyclic guanosine monophosphate (cGMP), is an important drug target for the treatment of erectile dysfunction and pulmonary arterial hypertension (PAH). Although many PDE5 inhibitors have been approved, such as sildenafil, vardenafil, tadalafil and so on, extensive studies have reported some side effects, such as vision disturbance and hearing loss as a result of the amino acid sequence and the secondary structural similarity of other PDEs to the catalytic domain of PDE5. In this study, multiple docking strategies, molecular dynamics (MD) simulations, free energy calculations and decomposition were employed to explore the structural determinants of PDE5 with a series of chromeno[2,3-c]pyrrol-9(2H)-one derivatives. First, reliable docking results were obtained using quantum mechanics/molecular mechanics (QM/MM) docking. Then, MD simulations and MM/GBSA free energy calculations were used to explore the dynamic binding process and characterize the binding modes of the inhibitors with different activities. The predicted binding free energies are in good agreement with the experimental data, and the MM/GBSA free energy decomposition analysis sheds light on the importance of hydrogen bonds with Gln817, π–π stacks against Phe820 and hydrophobic residues for the PDE5 binding of the studied inhibitors. The structural and energetic insights obtained here are useful for understanding the molecular mechanism of ligand binding and designing novel potent and selective PDE5 inhibitors with new scaffolds.

Cyclic nucleotide phosphodiesterase type 5 (PDE5) is exclusively specific for the cyclic guanosine monophosphate (cGMP), and PDE5 is an important drug target for the treatment of erectile dysfunction and pulmonary arterial hypertension (PAH).

Molecular Basis for Differential Patterns of Drug Resistance in Influenza N1 and N2 Neuraminidase

Neuraminidase (NA) inhibitors are used for the prevention and treatment of influenza A virus infections. Two subtypes of NA, N1 and N2, predominate in viruses that infect humans, but differential patterns of drug resistance have emerged in each subtype despite highly homologous active sites. To understand the molecular basis for the selection of these drug resistance mutations, structural and dynamic analyses on complexes of N1 and N2 NA with substrates and inhibitors were performed. Comparison of dynamic substrate and inhibitor envelopes and interactions at the active site revealed how differential patterns of drug resistance have emerged for specific drug resistance mutations, at residues I222, S246, and H274 in N1 and E119 in N2. Our results show that the differences in intermolecular interactions, especially van der Waals contacts, of the inhibitors versus substrates at the NA active site effectively explain the selection of resistance mutations in the two subtypes. Avoiding such contacts that render inhibitors vulnerable to resistance by better mimicking the dynamics and intermolecular interactions of substrates can lead to the development of novel inhibitors that avoid drug resistance in both subtypes.

Role of R292K mutation in influenza H7N9 neuraminidase toward oseltamivir susceptibility: MD and MM/PB(GB)SA study

The H7N9 avian influenza virus is a novel re-assortment from at least four different strains of virus. Neuraminidase, which is a glycoprotein on the surface membrane, has been the target for drug treatment. However, some H7N9 strains that have been isolated from patient after drug treatment have a R292K mutation in neuraminidase. This substitution was found to facilitate drug resistance using protein- and virus- assays, in particular it gave a high resistance to the most commonly used drug, oseltamivir. The aim of this research is to understand the source of oseltamivir resistance using MD simulations and the MM/PB(GB)SA binding free energy approaches. Both methods can predict the reduced susceptibility of oseltamivir in good agreement to the IC ₅₀ binding energy, although MM/GBSA underestimates this prediction compared to the MM/PBSA calculation. Electrostatic interaction is the main contribution for oseltamivir binding in terms of both interaction and solvation. We found that the source of the drug resistance is a decrease in the binding interaction combined with the reduction of the dehydration penalty. The smaller K292 mutated residue has a larger binding pocket cavity compared to the wild-type resulting in the loss of drug carboxylate-K292 hydrogen bonding and an increased accessibility for water molecules around the K292 mutated residue. In addition, oseltamivir does not bind well to the R292K mutant complex as shown by the high degree of fluctuation in ligand RMSD during the simulation and the change in angular distribution of bulky side chain groups.

Molecular modeling studies demonstrate key mutations that could affect the ligand recognition by influenza AH1N1 neuraminidase

The goal of this study was to identify neuraminidase (NA) residue mutants from human influenza AH1N1 using sequences from 1918 to 2012. Multiple alignment studies of complete NA sequences (5732) were performed. Subsequently, the crystallographic structure of the 1918 influenza (PDB ID: 3BEQ-A) was used as a wild-type structure and three-dimensional (3-D) template for homology modeling of the mutated selected NA sequences. The 3-D mutated NAs were refined using molecular dynamics (MD) simulations (50 ns). The refined 3-D models were used to perform docking studies using oseltamivir. Multiple sequence alignment studies showed seven representative mutations (A232V, K262R, V263I, T264V, S367L, S369N, and S369K). MD simulations applied to 3-D NAs showed that each NA had different active-site shapes according to structural surface visualization and docking results. Moreover, Cartesian principal component analyses (cPCA) show structural differences among these NA structures caused by mutations. These theoretical results suggest that the selected mutations that are located outside of the active site of NA could affect oseltamivir recognition and could be associated with resistance to oseltamivir.

A 3D-RISM/RISM study of the oseltamivir binding efficiency with the wild-type and resistance-associated mutant forms of the viral influenza B neuraminidase

The binding affinity of oseltamivir to the influenza B neuraminidase and to its variants with three single substitutions, E119G, R152K, and D198N, is investigated by the MM/3D-RISM method. The binding affinity or the binding free energy of ligand to receptor was found to be determined by a subtle balance of two major contributions that largely cancel out each other: the ligand-receptor interactions and the dehydration free energy. The theoretical results of the binding affinity of the drug to the mutants reproduced the observed trend in the resistivity, measured by IC50 ; the high-level resistance of E119G and R152K, and the low-level resistance of D198N. For E119G and R152K, reduction of the direct drug-target interaction, especially at the mutated residue, is the main source of high-level oseltamivir resistance. This phenomenon, however, is not found in the D198N strain, which is located in the framework of the active-site.

Molecular dynamics, monte carlo simulations, and langevin dynamics: a computational review

Macromolecular structures, such as neuraminidases, hemagglutinins, and monoclonal antibodies, are not rigid entities. Rather, they are characterised by their flexibility, which is the result of the interaction and collective motion of their constituent atoms. This conformational diversity has a significant impact on their physicochemical and biological properties. Among these are their structural stability, the transport of ions through the M2 channel, drug resistance, macromolecular docking, binding energy, and rational epitope design. To assess these properties and to calculate the associated thermodynamical observables, the conformational space must be efficiently sampled and the dynamic of the constituent atoms must be simulated. This paper presents algorithms and techniques that address the abovementioned issues. To this end, a computational review of molecular dynamics, Monte Carlo simulations, Langevin dynamics, and free energy calculation is presented. The exposition is made from first principles to promote a better understanding of the potentialities, limitations, applications, and interrelations of these computational methods.