With ongoing earlier enrollment on and rapid scale-up of antiretroviral therapy (ART) in Cameroon, there are increasing risks of transmitted HIV drug resistance (HIVDR) at population levels. We, therefore, evaluated the threshold of HIVDR in a population initiating ART, to inform on the effectiveness of first-line regimens, considering HIV-1 diversity, plasma viral load (PVL), and CD4-based disease progression. A total of 53 adults [median (interquartile range, IQR) CD4: 162 cell/mm(3) (48-284); median (IQR) PVL: 5.34 log10 RNA (4.17-6.42) copies/ml] initiating ART in 2014 at the Yaoundé Central Hospital were enrolled for HIV-1 protease-reverse transcriptase sequencing. Drug resistance mutations (DRMs) were interpreted using the 2009 World Health Organization (WHO) list versus the Stanford HIVdb algorithm version 7.0. Level of DRMs was low (3.77%) versus moderate (7.55%), respectively, following the WHO list (T69D, K103N) versus Stanford HIVdb (T69D, A98G, K103N, K238T), respectively. Prevailing clade was CRF02_AG (71.70%). Based on Stanford HIVdb, a slightly higher proportion of patients with DRMs were found among ones infected with CRF02_AG than in those non-CRF02_AG infected (7.89% vs. 6.67%, p = 1.000), with lower PVL (7.69% <5.5 vs. 0% ≥5.5 log10 RNA copies/ml, p = .488) and with higher CD4 counts (9.52% CD4 ≥200 vs. 3.33% CD4 <200 cells/mm(3), p = .749). Thresholds of DRMs suggest that standard first-line regimens currently used in Cameroon may remain effective at population levels, despite scale-up of ART in the country, pending adherence, and closed virological monitoring. With an intent-to-diagnose approach, the discrepant levels of DRMs support using Stanford HIVdb to evaluate initial ART, while revising the WHO list for surveillance.

The rates of virological failure (VF) and HIV-1 drug resistance were evaluated in a cross-sectional study in HIV-1-infected children living in Dakar, and taking antiretroviral treatment (ART) according to WHO recommendations. The plasma HIV-1 RNA load was measured using the Abbott m2000 RealTime HIV-1 assay. The full-length protease gene and partial reverse transcriptase gene were sequenced, and resistance mutations were assessed by reference to the Stanford University HIV drug resistance database. Of 125 included children (median age, 7 years) taking first-line ART for a median duration of 20 months, 82 (66%) showed detectable HIV-1 RNA load, and 70 (56%) met the 2010 revised WHO criteria of VF (defined as plasma HIV-1 RNA load ≥3.7 log(10) copies/ml). Drug resistance results were available for 52 children with plasma HIV-1 RNA load ≥3.0 log(10) copies/ml, and viruses carrying resistance mutations were found in 48 (92%) children. Among these 48, mutations conferring resistance to nucleoside reverse transcriptase inhibitors (NRTIs) or non-NRTIs (NNRTIs) were found in 42 (88%) and 47 (99%) children, respectively. The NRTI-resistant viruses harbored the M184V/I (95%), Q151M (2%), and thymidine-analogue mutations (40%), and the NNRTI-resistant viruses harbored the K103N (34%), Y181C (32%), G190A (23%), and K101E (21%) mutations. A high rate (56%) of VF was demonstrated in Senegalese children after 20 months of first-line ART and therapeutic failure was assessed by the presence of antiretroviral drug resistance mutations in 9 out of 10 children in VF. These findings point out the difficulties of optimizing ART in children living in sub-Saharan Africa, and the crucial need of laboratory monitoring reinforcement.

Protein flexibility is essential for enzymatic function, ligand binding, and protein-protein or protein-nucleic acid interactions. Normal mode analysis has increasingly been shown to be well suited for studying such flexibility, as it can be used to identify favorable structural deformations that correspond to functional motions. However, normal modes are strictly relevant to a single structure, reflecting a particular minimum on a complex energy surface, and are thus susceptible to artifacts. We describe a new theoretical framework for determining \"consensus\" normal modes from a set of related structures, such as those issuing from a short molecular dynamics simulation. This approach is more robust than standard normal mode analysis, and provides higher collectivity and symmetry properties. In an application to HIV-1 protease, the low-frequency consensus modes describe biologically relevant motions including flap opening and closing that can be used in interpreting structural changes accompanying the binding of widely differing inhibitors.

Improving the scoring functions for small molecule-protein docking is a highly challenging task in current computational drug design. Here we present a novel consensus scoring concept for the prediction of binding modes for multiple known active ligands. Similar ligands are generally believed to bind to their receptor in a similar fashion. The presumption of our approach was that the true binding modes of similar ligands should be more similar to each other compared to false positive binding modes. The number of conserved (consensus) interactions between similar ligands was used as a docking score. Patterns of interactions were modeled using ligand receptor interaction fingerprints. Our approach was evaluated for four different data sets of known cocrystal structures (CDK-2, dihydrofolate reductase, HIV-1 protease, and thrombin). Docking poses were generated with FlexX and rescored by our approach. For comparison the CScore scoring functions from Sybyl were used, and consensus scores were calculated thereof. Our approach performed better than individual scoring functions and was comparable to consensus scoring. Analysis of the distribution of docking poses by self-organizing maps (SOM) and interaction fingerprints confirmed that clusters of docking poses composed of multiple ligands were preferentially observed near the native binding mode. Being conceptually unrelated to commonly used docking scoring functions our approach provides a powerful method to complement and improve computational docking experiments.

The ability to find novel bioactive scaffolds in compound similarity-based virtual screening experiments has been studied comparing Tanimoto-based, ranking-based, voting, and consensus scoring protocols. Ligand sets for seven well-known drug targets (CDK2, COX2, estrogen receptor, neuraminidase, HIV-1 protease, p38 MAP kinase, thrombin) have been assembled such that each ligand represents its own unique chemotype, thus ensuring that each similarity recognition event between ligands constitutes a scaffold hopping event. In a series of virtual screening studies involving 9969 MDDR compounds as negative controls it has been found that atom pair descriptors and 3D pharmacophore fingerprints combined with ranking, voting, and consensus scoring strategies perform well in finding novel bioactive scaffolds. In addition, often superior performance has been observed for similarity-based virtual screening compared to structure-based methods. This finding suggests that information about a target obtained from known bioactive ligands is as valuable as knowledge of the target structures for identifying novel bioactive scaffolds through virtual screening.

We considered several key issues regarding the development of a DNA-based human immunodeficiency virus type 1 (HIV-1) vaccine: (1) should the candidate vaccine construct be derived from incident or prevalent HIV-1 strains; and (2) should circulating plasma virus, archived HIV-1 provirus recovered from peripheral blood mononuclear cells, or both be included? To address these questions, we collected circulating HIV-1 strains from infected individuals residing in Abidjan, Côte d\'Ivoire. From a panel of 23 strains, 22 were HIV-1 subtype A in gag, 19 of which phylogenetically clustered with the recombinant HIV-1, CRF02-AG strains from West Africa. The mosaic genome of CRF02-AG was confirmed by sequencing the protease gene. A consensus gag p24 protein sequence was generated and 147 of 148 codons were identical to CRF02-AG (IbNG). Regardless of the sequence origin (RNA, provirus, incident, or prevalent), the gag p24 consensus sequences were highly representative of these distinct virologic compartments. These data suggest that the consensus sequence generated from incident and prevalent infections may provide an appropriate sequence for a DNA vaccine and is largely representative of the major circulating viral strain.

Several different functions have been put forward for evaluating the energetics of ligand binding to proteins. Those employed in the DOCK, GOLD and FlexX docking programs have been especially widely used, particularly in connection with virtual high-throughput screening (vHTS) projects. Until recently, such evaluation functions were usually considered only in conjunction with the docking programs that relied on them. In such studies, the evaluation function in question actually fills two distinct roles: it serves as the objective function being optimized (fitness function), but is also the scoring function used to compare the candidate docking configurations generated by the program. We have used descriptions available in the open literature to create free-standing scoring functions based on those used in DOCK and GOLD, and have implemented the more recently formulated PMF [J. Med. Chem. 42 (1999) 791] scoring function as well. The performance of these functions was examined individually for each of several data sets for which both crystal structures and affinities are available, as was the performance of the FlexX scoring function. Various ways of combining individual scores into a consensus score (CScore) were also considered. The individual and consensus scores were also used to try to pick out configurations most similar to those found in crystal structures from among a set of candidate configurations produced by FlexX docking runs. We find that the reliability and interpretability of results can be improved by combining results from all four functions into a CScore.

The protease and reverse transcriptase (RT) genes were studied in antiretroviral (ARV)-experienced and drug-naive HIV-1-infected individuals in Libreville, Gabon. We have shown, although on a limited number of samples that in 58% (11/19) of the patients, with a mean of 17.7 months of ARV drug experience, major mutations inevitably inducing resistances to ARV drugs were present. Resistance was mainly observed to the NRTIs (nucleoside analogue RT inhibitors). This high prevalence may reflect inappropriate ARV drug use. In order to avoid the rapid emergence of resistant viruses on a large scale in the developing world, it is important that the infrastructures necessary to monitor ARV treatment are also rapidly implemented in these countries and that clinicans are trained in the appropriate use of ARV drugs. A continuous surveillance of the circulation of ARV drug-resistant viruses must be organized to guide ARV treatment strategies and policies.

We present the results of an extensive computational study in which we show that combining scoring functions in an intersection-based consensus approach results in an enhancement in the ability to discriminate between active and inactive enzyme inhibitors. This is illustrated in the context of docking collections of three-dimensional structures into three different enzymes of pharmaceutical interest: p38 MAP kinase, inosine monophosphate dehydrogenase, and HIV protease. An analysis of two different docking methods and thirteen scoring functions provides insights into which functions perform well, both singly and in combination. Our data shows that consensus scoring further provides a dramatic reduction in the number of false positives identified by individual scoring functions, thus leading to a significant enhancement in hit-rates.